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remote sensing Article

Joint Time-Frequency Signal Processing Scheme in Forward Scattering Radar with a Rotational Transmitter Raja Syamsul Azmir Raja Abdullah 1, *, Azizi Mohd Ali 1 , Mohd Fadlee A. Rasid 1 , Nur Emileen Abdul Rashid 2 , Asem Ahmad Salah 1 and Aris Munawar 1 1

2

*

Wireless and Photonic Networks Research Centre, Faculty of Engineering, Universiti Putra Malaysia (UPM), 43400 Selangor, Malaysia; [email protected] (A.M.A.); [email protected] (M.F.A.R.); [email protected] (A.A.S.); [email protected] (A.M.) Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), Shah Alam, 40450 Selangor, Malaysia; [email protected] Correspondence: [email protected]; Tel.: +60-3-8946-4347

Academic Editors: Francesco Soldovieri, Raffaele Persico, Xiaofeng Li and Prasad S. Thenkabail Received: 8 September 2016; Accepted: 2 December 2016; Published: 17 December 2016

Abstract: This paper explores the concept of a Forward Scattering Radar (FSR) system with a rotational transmitter for target detection and localization. Most of the research and development in FSR used a fixed dedicated transmitter; therefore, the detection of stationary and slow moving target is very difficult. By rotating the transmitter, the received signals at the receiver contain extra information carried by the Doppler due to the relative movement of the transmitter-target-receiver. Hence, rotating the transmitter enhances the detection capability especially for a stationary and slow-moving target. In addition, it increases the flexibility of the transmitter to control the signal direction, which broadens the coverage of FSR networks. In this paper, a novel signal processing for the new mode of FSR system based on the signal’s joint time-frequency is proposed and discussed. Additionally, the concept of the FSR system with the rotational transmitter is analyzed experimentally for the detection and localization of a stationary target, at very low speed and a low profile target crossing the FSR baseline. The system acts as a virtual fencing of a remote sensor for area monitoring. The experimental results show that the proposed mode with the new signal processing scheme can detect a human intruder. The potential applications for this system could be used for security and border surveillance, debris detection on an airport runway, ground aerial monitoring, intruder detection, etc. Keywords: remote sensors; forward scattering radar; target detection and localization; security and border surveillance

1. Introduction Forward Scattering Radar (FSR) is a specific condition in bistatic radar mode and is gaining special attention from the modern radar community lately. In theory, for target detection in an FSR system to be effective, it utilizes the electromagnetic wave scattered by the target to the receiver [1]. The technical requirement in FSR, which needs the target to be in proximity to the baseline of the transmitter-receiver, restricts the operation to within narrow angles. Furthermore, the Doppler ‘dead zone’ (very low Doppler frequencies) and loss of range resolution limits the practicality of FSR. However, FSR has a number of unique qualities that make it useful for remote monitoring. One of the special characteristics is the high amplitude target’s Radar Cross-Section (RCS) at the forward scatter position. The enhancement in forward scatter RCS, which exists within the Forward Scatter Main Lobe (FSML), can be perceived within the optical region and the specific scenario in the Mie region [2,3]. Remote Sens. 2016, 8, 1028; doi:10.3390/rs8121028

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Moreover, the target’s RCS in FSR does not affected by the Radar Absorbing Material (RAM) coating, as well as the diamond shape of some targets to reduce RCS. As a result, the FSR system is not affected by “stealth” technology. One of the earliest publications of the FSR system was dedicated to air target detection and tracking [4–6]. The FSR used the fixed transmitter–receiver pair, and the target flew crossing the baseline between the FSR systems. Later, FSR was tested for ground target detection and classification, but still used a fixed transmitter-receiver pair [7–9]. Signal processing and signal modeling of FSR are explained in [10]. The FSR system has also been tested for maritime applications [10–12]. Recently, new research in FSR is to integrate with MIMO architecture [13] and operate as a passive radar [14,15]. Although the number of research works in FSR has increased, the main published manuscripts and reported work on FSR focus on the fixed transmitter and utilize the relative movement of the target for detection and tracking. In this condition, the detection is restricted to the narrow coverage of FSML, and it is highly dependent on the target speed. A low target speed will give a low Doppler frequency and make the detection difficult. Moreover, the detection is almost impossible for a stationary target. However, if the transmitter can be controlled, for example, it can be mechanically rotated with a certain rotational speed, it offers some degree of freedom. By rotating the transmitter, the received signals at the receiver contain extra information carried by the Doppler due to relative movement of the transmitter-target-receiver. Hence, rotating the transmitter enhances the detection sensitivity especially for stationary and slow moving targets. By manipulating the Doppler frequency at the receiver, the FSR system becomes more flexible and practical. Additionally, it can also increase the coverage with multiple receivers that could be arranged in such a way; the receivers reside within the transmitter antenna beam width. Though the angular movement of the transmitter creates extra Doppler effects at the receiver, consequently the signal processing is different from the conventional FSR signal processing. The aim of this paper is to explore the concept of the FSR system with a rotational transmitter. The specific objective is to develop the detection and localization technique of stationary, as well as a very slow-moving target within the FSR region. The idea is proven by deploying the system for a remote security monitoring, which must be capable of detecting and locating an intruder. The intruder is either almost stationary or slow moving with low profile attributes. The detail derivation of the theoretical signal model at the output of ADC is explained in this paper, although a simplified version was presented in [16]. A novel detection technique based on the signal’s joint Time-Frequency (T-F) is integrated with the proposed FSR system. Two methods of signal pre-processing were tested and implemented on the signal acquired from the experimentation. Both methods exploit the difference in the Doppler effect at the receiver due to the relative angular movement of the transmitter with and without the target. The adaptation of the rotational transmitter concept to the conventional FSR system provides a new emerging area of research. Thus, the new concept of the FSR system can be functional in diverse potential applications, such as: remote security and border surveillance, close range security applications intended for humans, animal and man-made object detection, foreign object debris (FOD) detection on an airport runway where most of the objects are stationary, etc. Nevertheless, with the appropriate modification, the technique is applicable to air and maritime targets. The paper is organized as follows: Section 2 presents the common FSR layout. Then, the same section explains the new FSR system with the angular movement of the transmitter. The detail derivation of the signal model and comparison to the controlled experimental result are also given in this section. Section 3 elaborates the experimental setup of the proposed system, as well as the experimentation with the practical application of intruder detection. Section 4 is divided into two parts, with each part discussing slightly different signal pre-processing schemes that can be integrated with the system. The first part explains the detection and localization for a stationary target followed by a slow moving target in the later part. The paper is concluded in Section 5.

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2. FSR FSR System System Topology Topologyand andOverview Overview 2. Thesimplified simplifiedgeometrical geometricallayout layoutofof FSR system is illustrated in Figure 1. The transmitter The thethe FSR system is illustrated in Figure 1. The transmitter can can transmit anyoftype of modulated signal due to the non-dependent forward scatter signal transmit any type modulated signal due to the non-dependent forward scatter signal processing processing types of signal transmitted at the receiver system [15,16]. In a conventional to the typesto of the signal transmitted at the receiver system [15,16]. In a conventional FSR system, FSR the system, the received signal consists of afrom direct from the and forward scattered received signal consists of a direct signal thesignal transmitter andtransmitter forward scattered signal from the signal from the target. moving target the willDoppler introduce theinDoppler shift insignal the scattered signal [1,7]. target. A moving targetAwill introduce shift the scattered [1,7]. The Doppler The Doppler is then for target detection and identification. as signal is then signal extracted andextracted analyzedand foranalyzed target detection and identification. As long as As thelong direct the direct signal than is greater than the receiver thermal any type of non-linear component (for signal is greater the receiver thermal noise, any noise, type of non-linear component (for example, s diodecan detector) can as the mixer. In thescatter forward scatter case, signal the direct signal sexample, diode detector) be used asbe theused mixer. In the forward case, the direct is used as is a used as a heterodyne to thesignal scattered form the target. heterodyne to the scattered formsignal the target. Forward Scatter Main Lobe

RT

β/2

δ

α

RR

Ssc Sdr

Tx

Rx

v Low Frequency Circuit (Low Pass Filter, Amp, DC blocker)

ADC

Non Linear Detector

Band Pass Filter

Low Noise Amplifier

Signal Processing

Figure1. 1. Simplified Simplified conventional conventional Forward Forward Scattering Scattering Radar Radar (FSR) (FSR) geometrical geometrical topology topology and and receiver receiver Figure system block diagram. system block diagram.

Based on Figure 1, the direct signal from the transmitter, Sdr, with carrier frequency fo (assume Based on Figure 1, the direct signal from the transmitter, Sdr , with carrier frequency fo (assume phase noise free) and a signal scattered from a target, Ssc, with a Doppler shift, fsc is given by (1) and phase noise free) and a signal scattered from a target, Ssc , with a Doppler shift, fsc is given by (1) and (2), respectively [16,17]. There exists a phase change in the Doppler signal scattered by the transmitter (2), respectively [16,17]. There exists a phase change in the Doppler signal scattered by the transmitter as explained by Babinet’s principle [18,19]. In the simplified manner, the signal at the input of the as explained by Babinet’s principle [18,19]. In the simplified manner, the signal at the input of the receiver Srx is a combination between Sdr and Ssc, which can be expressed in Equation (3): receiver Srx is a combination between Sdr and Ssc , which can be expressed in Equation (3): Sdr(t) = Adr cos((ωo)t) (1) Sdr (t) = Adr cos((ωo )t) (1) Ssc(t) = Asc sin((ωo + ωsc)t) (2) +ω Srx(t) = Sdr(t) +Ssc Ssc(t) (t)==AAscdrsin((ω cos((ωoo)t) + scA)t) sc sin((ωo + ωsc)t)

(2) (3)

Sdr )t) + Asc sin((ω ωsc )t) path signal (leakage) (3) where ωo = 2πfo andSω = =2πf sc.(t) A+ dr S and denote theoamplitudes of the rxsc(t) sc (t)A=sc A o + direct dr cos((ω and the target scattered signal, respectively. The FSR circuits used a non-linear element as the where ωo = 2πfo and ωsc = 2πfsc . Adr and Asc denote the amplitudes of the direct path signal (leakage) detection mechanism with the transfer characteristics of Yout = (Yin)2; hence, at the output of the and the target scattered signal, respectively. The FSR circuits used a non-linear element as the detection non-linear element, the signal is given by: mechanism with the transfer characteristics of Yout = (Yin )2 ; hence, at the output of the non-linear 2 element, the signal is given by: (4) Yout (t) = Adr cos(ωo t) + Asc sin (ωo + ωsc )t 2 By applying low pass the signal from the non-linear element, the high Yout (filtering t) = (Adrtocos t) + Asc sin((ω (4) (ωooutput o + ωsc )t)) frequency part of the signal is filtered out, leaving only two spectral components: the DC value and the Doppler fromlow thepass target: By applying filtering to the output signal from the non-linear element, the high frequency part of the signal is filtered out, leaving only two spectral components: the DC value and the Doppler Yout_f (t) = Κ ((Adr )2 + (Asc )2 ) + (Adr Asc sin(ωsc t)) (5) from the target:  

2 where K is the conversion which depends non-linear Yout_fcoefficient, (t) = K ((A sin (5) (Asc )2 )on+the (Atype (ωsc t)) device. dr ) + dr Ascof The direct signal can be filtered out by High Pass Filter and left only Yout = AdrAsc.sin(ωsct). The where K is the conversion coefficient, which depends on the type of non-linear device. total Doppler frequency can be extracted by the derivation of the phase component of Equation (5).

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The direct signal can be filtered out by High Pass Filter and left only Yout = Adr Asc. sin(ωsc t). The total Doppler frequency can be extracted by the derivation of the phase component of Equation (5). If the target’s Doppler frequency component due to the motion relative to the transmitter and receiver is given in Equations (7) and (8), respectively, then the total target’s Doppler frequency, fd , can be calculated as follows, the detail derivation is given in Appendix A: ftx = (v/λ) cos(β/2 + δ)

(6)

frx = (v/λ) cos(β/2 − δ)

(7)

fd = (v/λ) cos(β/2 + δ) + (v/λ) cos(β/2 − δ) = (2v/λ) cos(β/2) cos(δ)

(8)

Based on Equation (8), the total target’s Doppler shift is zero, corresponding to the target on the baseline (β = 180◦ ) regardless of any values of δ and target trajectories. For β 6= 180◦ , the target’s Doppler frequency is specified by the transmitter-target-receiver relative speed. The Doppler shift depends mainly on the target velocity vector components and the carrier frequency. The Doppler shift will be zero for a stationary target. In most of the publications on FSR, this Doppler shift can be used for target detection, moving target selection, speed determination and trajectory reconstruction [5–15]. The higher the target effective target speed, the higher the Doppler shift in the received signal. Therefore, if the target is stationary, it makes the system less sensitive for detection in the conventional FSR. It can be noted that, with the identified scenario, the FSR receiver requires a very sensitive Doppler detection, and the Doppler signal is near zero for some condition. 2.1. Practical Realization of FSR with Rotational Scanning Transmitter By rotating the transmitter antenna, two Doppler shifts will exist at the receiver. First, the changing of relative velocity between the transmitter and receiver produces a direct Doppler shift in the direct received signal. The direct signal from the transmitter is always received by the receiver (regardless of the existence of an object). Second, if any object exists within the FSR region, then the relative velocity between the transmitter-target-receiver is changing, producing a scattered Doppler shift in the scattered received signal in addition to the direct signal. The proposed rotational transmitter in the FSR system with the scanning scenario setup is illustrated in Figure 2. A stationary object resides within the scanning area set by an angularly-moving transmitter and a fixed receiver. This paper concerns a stationary object, which will not be detected from the conventional FSR system because no Doppler shift exists at the receiver. The scanning can be as wide as 180◦ depending on the applications. A motor controlled by the computer is used for the antenna scanning movement and synchronization. The receiver will be triggered upon receiving a sufficient direct signal from the transmitter, and it is assumed within the transmitter antenna main lobe. Equations (1)–(8), which were dedicated to a fixed Tx-Rx pair and moving target crossing the baseline, need to be modified based on the new FSR layout. If an object exists, the two signals present at the input of the receiver are now: i. ii.

direct signal, Sdr_r , and its Doppler shift, ωdr_r signal scattered from an object, Ssc_r , with scattered Doppler shift, ωsc_r ; hence, the signal at the input of the receiver, Srx_r , will be: Sdr_r (t) = Adr_r sin((ωo + ωdr_r )t)

(9)

Ssc_r (t) = Asc_r sin((ωo + ωsc_r )t)

(10)

Srx_r (t) =Sdr_r (t) + Ssc_r (t) = Adr_r sin((ωo + ωdr_r )t) + Asc_r sin((ωo + ωsc_r )t)

(11)

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where Adr_r and Asc_r denote the amplitudes of the direct path signal (leakage) and object scattered signal, respectively. ωsc_r comprises two Doppler frequency components scattered due to the transmitter-object-receiver relative velocity. After, the non-linear element the output signal is given by: Yout_r (t) = (Adr_r sin((ωo + ωdr_r )t) + Asc_r sin((ωo + ωsc_r )t))2

(12)

Sens. 2016, 8, 1028 18 ByRemote applying low pass filtering on the output signal, the high frequency part of the5 ofsignal will be cut off, with only three spectral components remaining: DC from the direct path (leakage) signal, By applying low pass filtering on the output signal, the high frequency part of the signal will be Dopplercutdue to the movement of the transmitter and Doppler from the target: off, with only three spectral components remaining: DC from the direct path (leakage) signal,

 Doppler due to the movement of the transmitter  and Doppler from the target: Yout_r_f (t) = χ Y

_ _

(Adr_r )2 + (Asc_r )2 + (Adr_r Asc_r sin((ωdr_r + ωsc_r )t))

(t) = χ

A

_

+ A

_

+ A

_

A

_

sin

ω

_

+ω

_

t



(13) (13)

(a)

(b) Figure 2. FSR geometrical layout with the rotational transmitter for (a) the direct signal and (b) the

Figure signal 2. FSRscattered geometrical layout with the rotational transmitter for (a) the direct signal and (b) the from the object. signal scattered from the object. Direct Doppler frequency fdr_r and scattered Doppler frequency fsc_r can be calculated by adopting the concept as illustrated Figure 2. scattered The direct Doppler signal pathfrequency is shown by thecan boldbe line connectingby the Direct Doppler frequencyinfdr_r and fsc_r calculated adopting transmitter and receiver. The transmitter antenna moves with angular velocity Txω attached to an the concept as illustrated in Figure 2. The direct signal path is shown by the bold line connecting the arm with length r, producing tangential velocity Txv. The movement center of the transmitter antenna transmitter receiver. transmitter antennathe moves with angular velocity Txω attached to an arm is at and origin Ox,y. TheThe relative velocity between transmitter and receiver is changing due to the with length r, producing tangential The movement scanning mechanism; thus, directvelocity DopplerTx shift given by [14]: center of the transmitter antenna is at v . is

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origin Ox,y . The relative velocity between the transmitter and receiver is changing due to the scanning mechanism; thus, direct Doppler shift is given by [14]: fdr_r =

TxRV Txv cos σ = λ λ

(14)

where Txv is the tangential velocity of the transmitter antenna and λ is the wavelength. The fdr_r can be expressed as a function of time.     Rxx − Txx 1   − ϕ fd_r (t) = rTxω coscos−1  q
2 λ (Txx − Rxx )2 + Txy − Rxy

(15)

where r denotes the length of the transmitter antenna arm, φ is the direction angle of the transmitter tangential velocity, Txω is the transmitter angular velocity, (Txx , Txy ) and (Rxx , Rxy ) are the transmitter and receiver position in the XY-coordinate, respectively. Txx , Txy and φ are given by the following equations:  π Txx =Ox + r cos(θ) = Ox + r cos (θo + Txω t) − 2  π Txy =Oy + r sin(θ) = Oy + r sin (θo + Txω t) − 2

(16) (17)

θ1 = θo + Txω t

(18)

ϕ = (π/2) − θ1

(19)

σ = Ω−ϕ   −1 Rxx − Txx Ω = cos R q
2 R = (Rxx − Txx )2 + Rxy − Txy

(20) (21) (22)

where: θ1 is the angular position of the transmitter antenna (antenna look angle); θo indicates position of start angle; φ is the angle between the transmitter tangential velocity and reference X-axis origin coordinate; σ is the angle between the direct signal path and transmitter tangential velocity Txv ; Ω and Ω1 are the angles between the direct signal path and the reference X-axis transmitter antenna coordinate for the cases of the direct Doppler and the target’s scattered Doppler, respectively. The scattered signal path from a stationary point object is shown by the bold line connecting the transmitter, object and receiver, as shown in Figure 2b, which contribute the scattered Doppler shift, ωsc_r . Instantaneously-scattered Doppler frequency fsc_r is given by: fscr =

  1 d(R1 + R2 ) 1 d(R1 ) d(R2 ) 1 = + = [ Txv cos(σ1 ) + Txv cos(σ1 ) cos(φ)] λ dt λ dt dt λ

(23)

= Tx_v/λ [cos(σ_1) + cos(σ_1) cos(φ)] where σ1 is the angle formed between transmitter tangential velocity Txv and transmitter-object direction TxObjvr and φ is the angle from TxObjvr to the receiver. Equation (23) shows that the system can literally increase the Doppler frequency by adjusting the radial velocity of the transmitter. Therefore, it has some flexibility even for a very low speed (almost stationary) target. The fsc_r can be represented as a factor of time by:            rTxω −1 objx − Txx −1 objx − Txx fsc_r (t) = cos cos − ϕ + cos cos − ϕ cos(φ) λ R2 R2

(24)

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where Objx and Objy are the target position in the X and Y axis, respectively. σ1 , Ω1 and R1 are defined as below: R2 σ1 = Ω1 − ϕ (25)   Objx − Txx Ω1 = cos−1 (26) Remote Sens. 2016, 8, 1028 7 of 18 R2 r  Tx 2 Obj − (26) (27) R1 = (Ω Txx=−cos Objx )2 +R2Txy − Objy Obj)x − (Tx−1− Obj R == sin + Tx Txx − Obj φ − Ω1 





(27)

R2

Obj − Tx

The amplitude of the direct received ϕ = signal sin Adr_r follows − the Ω general form of bistatic radar, which R2 is given by Equation (22) below. The amplitude of the direct received signal P Adr_r the general form of bistatic radar, λ2 t Gt Grfollows (28) Adr_r = 2 which is given by Equation (22) below. (4πR) PG G λ where Pt is the transmitter power and Gt andA G_r are antenna, (28) = the gain of the transmitting and receiving (4πR) respectively. The amplitude of scattered received signal Asc_r is given by: where Pt is the transmitter power and Gt and Gr are the gain of the transmitting and receiving antenna, 2 respectively. The amplitude of scattered receivedPsignal sc_r is given by: σλ t Gt GrA

Asc_r = A

_

=

3 2 (4π P G) G(Rσλ 1 R2 )

(29)

(29)

(4π) (R R )

where σ denotes the forward scatter RCS of the target. Simulation on rotational forward scattering where σ denotes the forward scatter RCS of the target. Simulation on rotational forward scattering radar for static target detection has been done using MATLAB. All parameters are set to be as close radar for static target detection has been done using MATLAB. All parameters are set to be as close to the experimental as possible, which transmit the continuous wave signal with carrier frequency to the experimental as possible, which transmit the continuous wave signal with carrier frequency fc fc = 2.4 GHz W. The Thetransmitting transmittingand and receiving antenna radiation patterns are illustrated = 2.4 GHzatatPPt t== 10 10 dBm dBm W. receiving antenna radiation patterns are illustrated in Figure 3. in Figure 3.

(a)

(b)

Figure 3. Antenna radiation pattern used for theoretical analysis and experimentayion (a) transmitter

Figure 3. Antenna radiation pattern used for theoretical analysis and experimentayion (a) transmitter antenna and (b) receiver antenna antenna and (b) receiver antenna.

An experiment to proof the signal model in Equation (14) has been implemented inside the semi-anechoic chamber withthe thesignal parameters listed in Table 1.(14) Figure shows the simulatedinside and the An experiment to proof model in Equation has 4been implemented experimental received with signalthe (no parameters target). Both signals show some However, the and semi-anechoic chamber listed in Table 1. degree Figureof4similarity. shows the simulated simulated signal can be further improved by taking into account other propagation models, such as the experimental received signal (no target). Both signals show some degree of similarity. However, two-ray path propagation due to the lower height of the antenna. The full ground clutter is also not simulated signal can be further improved by taking into account other propagation models, such as integrated into the equation. Nevertheless, these signals can be used as reference signals for target two-ray path propagation due to the lower height of the antenna. The full ground clutter is also not detection in the new FSR system with the rotational transmitter. integrated into the equation. Nevertheless, these signals can be used as reference signals for target Figure 5 illustrates the simulated (point target on the baseline) and experimental received signal detection in the new FSR system the metal rotational after Doppler processing for with a small objecttransmitter. with size L = W = H = 2 cm at position Objx,y = (10, 10) m. For the simulated signal (Figures 4a and 5a), the envelope shows some similarity, but it possesses an amplitude difference especially when the transmitter is parallel to the baseline. The experimental signal indicates some distortion in the received signal as compared to Figure 4b.

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Figure 5 illustrates the simulated (point target on the baseline) and experimental received signal after Doppler processing for a small metal object with size L = W = H = 2 cm at position Objx,y = (10, 10) m. For the simulated signal (Figures 4a and 5a), the envelope shows some similarity, but it possesses an amplitude difference especially when the transmitter is parallel to the baseline. The experimental signal indicates some distortion in the received signal as compared to Figure 4b. Hence, the target Sens. 2016, 8,in 1028 8 of 18for the detectionRemote is possible the proposed FSR system and will be explained in the next section Sens.processing 2016, 8, 1028 algorithm. 8 of 18 detectionRemote signal Hence, the target detection is possible in the proposed FSR system and will be explained in the next section detection signal processing algorithm. Hence, for the the target detection is possible in the proposed FSR system and will be explained in the next

Table 1. Experiment parameters.

section for the detection signal processing algorithm.

Table 1. Experiment parameters.

Parameter Value Table 1. Experiment parameters. Parameter

Antenna angular (Tr ω) Antennavelocity angular velocity (Tr ) Parameter Antenna Antenna arm length (r)length (r) arm Antenna angular velocity (Tr ) Rx antenna position (Rxx,y ) RxAntenna antennaarm position (Rx(r), ) length Rx antenna position (Rx , )

(a)

Value

0.378π rad/s 0.378π rad/s Value 0.25 m 0.25 m 0.378π rad/s (10 m,15 m) (100.25 m,15mm) (10 m,15 m)

(b)

(a) analysis of the no-target Doppler signal and (b) the (b)received direct signal Figure 4. (a) Theoretical Figure 4. (a) Theoretical analysis of the no-target Doppler signal and (b) the received direct signal from from the4.FSR system withanalysis the rotational Figure (a) Theoretical of the transmitter. no-target Doppler signal and (b) the received direct signal

the FSR system with the rotational transmitter.

from the FSR system with the rotational transmitter.

(a)

(b)

(a)signal with a point target and (b) the received signal (b)during the experiment Figure 5. (a) Theoretical from the5.direct and scattered signal thetarget object.and (b) the received signal during the experiment Figure (a) Theoretical signal withfrom a point

Figure 5. (a) Theoretical signal with a point target and (b) the received signal during the experiment from the direct and scattered signal from the object. from3.the direct Application and scattered from the object. Transmitter: Intruder Detection Practical ofsignal FSR with the Rotational 3. Practical Application FSR with theFSR Rotational Transmitter: Intruder Detectionis tested on the The performance ofofthe proposed system with the rotational transmitter 3. Practical Application of FSR with the Rotational Intruder Detection detection of stationary and slow-moving targets. It Transmitter: resembles a human intruding a specific In The performance of the proposed FSR system with the rotational transmitter is testedarea. on the this case, the radar system as an electronic fence in securityasurveillance and protecting critical detection of stationary andacts slow-moving targets. It resembles human intruding a specificaarea. Thearea. performance of the proposed FSR system with the rotational transmitter is testedInon the Intrusion detection very in fence today’s Typical detection uses an ainfrared this case, the radar systemisacts as important an electronic in scenario. security surveillance and protecting critical detectionfencing, of stationary and slow-moving targets. Itcannot resembles ahigh human intruding a specific cameradetection and manual observation. Infrared provide accuracy location and is area. area. Intrusion is very important in today’s scenario. Typical detectioninuses an infrared In this case, the radar system acts as an electronic fence in security surveillance and protecting aiscritical poor during badand weather conditions, whileInfrared the camera hasprovide limitedhigh accuracy during the nightand [20]. fencing, camera manual observation. cannot accuracy in location Manual observation by the human eye is not efficient for 24 h and remote monitoring. In contrast, the area. Intrusion detection is very important inthe today’s infrared poor during bad weather conditions, while camerascenario. has limitedTypical accuracydetection during theuses nightan [20]. system provide accurate location, in 24 and bad weather In conditions. By and is Manual observation by the human eye isInfrared notworking efficient for 24hhprovide and during remote monitoring. contrast, the fencing, radar camera andcan manual observation. cannot high accuracy in location using FSR, some can belocation, obtained, especially the recognition capability and target radar radarbad system can advantages provide accurate working in 24 h and duringaccuracy bad weather conditions. By [20]. poor during weather conditions, while the camera has limited during the night cross-section enhancement. However, the detection area inthe therecognition conventional FSR system limited to using FSR, some advantages can be obtained, especially capability and is target radar Manual the observation by theofhuman eyescatter is notmain efficient forbaseline. 24 h and remote monitoring. In contrast, narrow coverage the forward lobe and Hence, the proposed FSR system cross-section enhancement. However, the detection area in the conventional FSR system is limited to the radarwith system can provide accurate location, working 24 hinand during bad weather conditions. the rotational transmitter can overcome this drawback, and a Hence, practical application, it cansystem work the narrow coverage of the forward scatter main lobe andin baseline. the proposed FSR By usingin FSR, some advantages cancan be obtained, especially the capability and hybrid mode with the existing system to increase the effectiveness for area application, remote monitoring. with the rotational transmitter overcome this drawback, andrecognition in a practical it cantarget work radar in hybrid mode with the existing system to increase the effectiveness for area remote monitoring.

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Remote Sens. 2016, 8, 1028 9 of 18 cross-section enhancement. However, the detection area in the conventional FSR system is limited to the narrow coverage of the forward scatter main lobe and baseline. Hence, the proposed FSR system This section presents the possible application of the proposed FSR system by practical with the rotational transmitter can overcome this drawback, andconsideration in a practical it can experimentation. Three main aspects that the paper takes into in application, the experiment andwork in hybrid mode with the existing system to increase the effectiveness for area remote monitoring. requirement are: (i) a very slow-moving intruder with start and go movement; (ii) detection of a very This section the possible application of theofproposed FSRtransmitter system rotation. by practical low profile (lowpresents altitude) ground target; and (iii) wide coverage detection with The experiment was conducted onthe a flat terrain covered with asphalt in within an area of and experimentation. Three main aspects that paper takes into consideration the experiment 200 m × are: 100 m. FSRslow-moving system transmits 2.4 GHz to and havego a higher Doppler requirement (i) aThe very intruder withCW start movement; (ii)frequency, detection thus of a very increasing the detection rate. The transmitting antenna is attached to a rotational motorized control, low profile (low altitude) ground target; and (iii) wide coverage of detection with transmitter rotation. whichexperiment can be controlled by computer on via aanflat ADC. In thiscovered experiment, theasphalt transmitter was rotated The was conducted terrain with within an area of 180° in the clockwise direction within, Trot = 4 s duration for one complete rotation. The FSR system 200 m × 100 m. The FSR system transmits 2.4 GHz CW to have a higher Doppler frequency, thus uses the receiver setup as explained in Section 2 and illustrated in Figure 6. The direct and scattered increasing the detection rate. The transmitting antenna is attached to a rotational motorized control, signals were recorded at the receiver side and stored in the computer. Figure 6 also shows the whichexperimental can be controlled by computer viaintruder an ADC. In this experiment, transmitter was distance rotated 180◦ setup and scenario for detection. Rtgt in Figurethe 6 shows the target in thefrom clockwise direction within, duration for one complete rotation. The FSR system uses rot = 4 the baseline in X-axis with T origin ons the transmitter receiver baseline. the receiver setup as explained in Sectionwhich 2 andare: illustrated in Figure 6. The direct and scattered signals Three scenarios were conducted, were recorded at the receiver side and stored in the computer. Figure 6 also shows the experimental i. Target sitting and stationary (without any movement), setupii.andTarget scenario forwith intruder detection. Rtgt in Figure 6 shows the target distance from the baseline sitting slightly shaking mode and in X-axis with origin on the transmitter receiver baseline. iii. Target moving (crawling), slowly crossing the FSR baseline.

(a)

(b)

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Figure 6. (a) FSR experimental setup and geometrical scenario showing the motorized controlled

Figure 6. (a) FSR experimental setup and geometrical scenario showing the motorized controlled rotational transmitter and fixed receiver; (b) target sitting in stationary and (c) target crawling rotational transmitter and fixed receiver; (b) target sitting in stationary and (c) target crawling crossing crossing the FSR baseline. the FSR baseline.

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Three scenarios were conducted, which are: i. Target sitting and stationary (without any movement), ii. Target sitting with slightly shaking mode and Remote Sens. 2016, 8, 1028 iii. Target moving (crawling), slowly crossing the FSR baseline.

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These scenarios scenarioswere were chosen to replicate typical security surveillance scenarios, like These chosen to replicate somesome typical security surveillance scenarios, like intruder intruder behavior and on anrunway. airport Conventional runway. Conventional Doppler radarandetects via behavior and debris ondebris an airport Doppler radar detects object an viaobject Doppler Doppler shift produced by the rate of change of the total path length travelled signal between the shift produced by the rate of change of the total path length travelled signal between the transmitter transmitter receiver. the case of a static or slow-moving the rate of path length changes and receiver.and In the case ofIn a static or slow-moving target, the ratetarget, of path length changes is almost zero, is almost zero, thus making it very difficult for the radar to detect a target. Moreover, since FSR thus making it very difficult for the radar to detect a target. Moreover, since FSR uses CW signal, ifuses the CW signal, if thenear target located (FSR near dead the baseline dead impossible zone), it is almost impossible to extract target is located theisbaseline zone), it(FSR is almost to extract range information rangethe information from the signal. this reason, the transmitter is rotated to induce an from received signal. Forreceived this reason, the For transmitter is rotated to induce an object Doppler shift object Doppler shift signal. The second reason is to have a wide area of detection coverage. Within signal. The second reason is to have a wide area of detection coverage. Within the integration time, the the integration time,acquire the received willfrom acquire a direct Doppler from the transmitter, the main received signal will a directsignal Doppler the transmitter, the main Doppler from the body and Doppler the from the Doppler body and possibly from other parts theDue body, like aelbow, possibly micro from other the partsmicro of theDoppler body, like elbow, head, leg,ofetc. to this, wide head, leg,range etc. Due to this, afrequency wide dynamic range of Doppler analysis is accurate required intruder in order dynamic of Doppler analysis is required in frequency order to ensure that to ensure that accurate intruder detection could be achieved. detection could be achieved. Figure 77 shows shows the the signal signal recorded, recorded, using using aa 50-kSps 50-kSps ADC, ADC, for for ground ground clutter clutter (no (no target) target) after after Figure scanning the interested area. This procedure will be repeated many times, and the signal collected scanning the interested area. This procedure will be repeated many times, and the signal collected will willaveraged be averaged out and selected as the reference signal proposed detection algorithm. There be out and selected as the reference signal for for the the proposed detection algorithm. There is is a phase change in the received signal with the change point when the transmitter is directly facing a phase change in the received signal with the change point when the transmitter is directly facing the receiver. receiver. Moreover, Moreover, the the signal signal exhibits exhibits aa symmetrical symmetrical characteristic, characteristic, and and there there exists exists some some Doppler the Doppler modulation at at both both sides sides of of the the signal. signal. Figure Figure 7b 7b illustrates illustrates the the time-frequency time-frequency characteristics characteristics of of the the modulation reference signal. It shows the intensity of different frequency versus time ranging between DC up to reference signal. It shows the intensity of different frequency versus time ranging between DC up to 10 Hz. The dead zone area can be clearly seen in the figure as the transmitter approaching the 10 Hz. The dead zone area can be clearly seen in the figure as the transmitter approaching the baseline. baseline. signal shows symmetrical an almost symmetrical frequency andon amplitude onofboth sides of Then, the Then, signal the shows an almost frequency and amplitude both sides the Doppler the Doppler dead zone. The strong amplitude of low Doppler frequency can be seen at both sides dead zone. The strong amplitude of low Doppler frequency can be seen at both sides due to the relative ◦ ◦ due to the relative velocity maximum at an90angle = 45° and 90°. The represents the velocity being maximum at being an angle θ = 45 and . Theθsignal represents thesignal ground clutter, and ground clutter, and mainly, it is scattered from the ground surface. Figure 7a also shows that the mainly, it is scattered from the ground surface. Figure 7a also shows that the target’s forward scattered target’s forward scattered signal overlaps with the reference signal (direct signal). The difference in signal overlaps with the reference signal (direct signal). The difference in amplitude and frequency can amplitude and frequency canatbethe seen between the signals the forward Thisfor property be seen between the signals forward scatter region.atThis propertyscatter can beregion. exploited target can be exploited for target detection. However, the inherent amplitude dynamic range gives some detection. However, the inherent amplitude dynamic range gives some ambiguity, and the target’s ambiguity, and the target’s position may not be available. position may not be available.

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Figure 7. (a) Received signal comprised of the direct signal (Doppler from the transmitter and clutter) Figure 7. (a) Received signal comprised of the direct signal (Doppler from the transmitter and clutter) and received signal with target scattering; (b) spectrogram of the direct signal. and received signal with target scattering; (b) spectrogram of the direct signal.

4. Joint T-F-Based Target Detection and Localization This section describes the target detection and localization processing scheme in the FSR system with the rotational transmitter. Target detection based on the time domain signal is difficult, and the position information is not available (Figure 7a). Thus, an extended detection technique based on the

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4. Joint T-F-Based Target Detection and Localization This section describes the target detection and localization processing scheme in the FSR system with the rotational transmitter. Target detection based on the time domain signal is difficult, and the position information is not available (Figure 7a). Thus, an extended detection technique based on the joint time-frequency representation of the signal is proposed as depicted in Figure 8. The first step is Remote Sens. 2016, 8, 1028 of 18 converting the received signal for each complete scan cell into the T-F domain. Then, the11normalized amplitude for each frequency is plotted against scanning time. The amplitude difference for each amplitude for each frequency is plotted against scanning time. The amplitude difference for each Remote Sens. 2016,the 8, 1028 11 of procedure. 18 frequency between Doppler Doppler is calculated this frequency betweenscanned the scanned Dopplerand andthe the reference reference Doppler is calculated in thisinprocedure. The lastThe step is step summing the amplitude differences andtime. plotting them respect time. Then, last is summing up the differences and plotting withwith respect to time. Then, amplitude for each up frequency isamplitude plotted against scanning Thethem amplitude difference forto each the detection threshold can be derived from this final plot. Doppler is calculated in this procedure. the detection threshold can derived from this final plot. frequency between thebe scanned Doppler and the reference The last step is summing up the amplitude differences and plotting them with respect to time. Then, the detection threshold can be derived from this final plot. Time Domain Testing

Reference Scanned signal in time domain without any object

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8. Detection processing schemeonbased on the time-frequency (T-F) for the signal. Figure 8.Figure Detection processing scheme based the time-frequency (T-F) signal for signal the stationary stationary signal. Figure 8. Detection processing scheme based on the time-frequency (T-F) signal for the stationary signal.

Figure 9Figure shows the normalized amplitude received frequency extracted from the 9 shows the normalized amplitudeof of each each received frequency extracted from the joint T-Fjoint T-F representation of the signal. It is clearly shown that each frequency has a different amplitude along representation of the signal. is clearlyamplitude shown that each frequency hasextracted a different along the Figure 9 shows theItnormalized of each received frequency fromamplitude the joint T-Fthe scanning time. The peak of the normalized amplitude that happened at around 3.2 s shows that of theof signal. is clearly shown that each frequency has a different amplitude theall that all scanningrepresentation time. The peak the Itnormalized amplitude that happened at around 3.2along s shows Doppler possess a high amplitude for this time The graph also that scanningfrequencies time.possess The peak the normalized that duration. happened at The around 3.2 s shows showsshows that there allthat there Doppler frequencies aofhigh amplitudeamplitude for this time duration. graph also are 10 significant Doppler frequencies in the received signal. It is important treat eachthat frequency Doppler frequencies possess a high amplitude for this time duration. The graphtoalso shows there are 10 significant Doppler frequencies in the as received signal. It istoimportant treat each independently for detection and localization explained earlier due the effect ofto Doppler shift. frequency are 10 significant Doppler frequencies in the received signal. It is important to treat each frequency independently for detection and localization as explained earlier due to the effect of Doppler shift. independently for detection and localization as explained earlier due to the effect of Doppler shift. Amplitude for all frequency in the reference signal

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Practically, for target detection in the proposed system, two considerations should be taken into account: (i) the receiver received a 3D forward scatter RCS lobe from the target and (ii) each time cell comprises many scattered points within the same vertical resolution cell. The different scattered points produce different shifted frequencies (f1 , f2 , . . . fi ) as shown in Figure 6a. Many scattered points are within the same time cell, T. This effect is crucial even for a small movement. Hence, the equation of the received Doppler signal (Equation (24)) is modified as follows:  rTxω fsc_ri (t) = λ





  −1    cos cos  r



  Objxi − Txx −1    2  − ϕ cos π − tan 2 (Txx − Objxi ) + Txy − Objyi

Objyi − Rxy Objxi − Rxx

!

!

− Ω1

(30)

where i shows the number of scattered point. The novel detection technique in this paper utilizes the sum of differences in amplitude for each frequency content, As (T), in the signal along the sweep time. The target is detected if the sum of the difference between signal from a target and reference signal is greater than the threshold. The sum of the difference in amplitude for each frequency content is given by: As ( T ) =

i=n

i=n

i=1

i=1

∑ ∆fi (T) = ∑ fsc_ri (T)

− fdr_ri (T)

(31)

where T = 1, 2 . . . J, and J is determined by the number of signals and the length of the window. ∆fi is the difference in the amplitude for frequency I, and fdr_ri is the amplitude of reference signal at frequency i. Good statistics are required to decide the threshold level for the reference signal. The threshold is defined by the sum of the difference in amplitude for each frequency content for all signals during the mapping clutter from the ground, as shown in Figure 10. From the analysis, the detection threshold level (difference) of 3 dB is chosen. It has to be clarified here that the detection threshold level might be different for different areas, and it has to be adaptive. Hence, many background clutter signals need to be collected to be an optimum reference signal. The adaptive Constant False Alarm Rate (CFAR) processing is an important procedure for producing precise target images separated from the existing clutter. Then, the extracted target signatures that are free of clutter can be used to estimate different target parameters for their classifications. Therefore, a modified CFAR technique has to be made by using the information of As (T). In CFAR, the term ‘Cell Under Test’ (CUT) is commonly used for the cell to be detected, and in this paper, CUT will be assumed as the signal at frequency i. The threshold, Th, is determined after estimating the average As (T) from the neighboring cells and is given by: Th = ε Pn (32) where ε is the scaling factor (threshold factor) and Pn is the estimated amplitude difference, ∆fi . The cell-averaging CFAR detector is used, where the noise samples are extracted from the training cells (leading and lagging cells) around the CUT (the signal with frequency i). The estimated noise can be calculated by the following [21]. 1 I Pn = ∑ xi (33) I i=1 where xi is the sample in each training cell (i.e., each frequency content) and I is the number of training cells (i.e., number of frequencies). The number of leading cells is generally the same as the lagging ones. To avoid having a leaked signal component in the training cell, which may have a harmful effect on the noise estimation, guard cells leading and lagging the CUT are used.

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4.1. Stationary Target Detection and Localization 4.1. Stationary Target Detection and Localization Two conditions as explained in Section 3 for detecting (i) target sitting and (ii) slight shaking Two conditions as explained in Section 3 for detecting (i) target sitting and (ii) slight shaking were were tested. The sum of the differences in amplitude for each frequency, As, was calculated for each tested. The sum of the differences in amplitude for each frequency, As , was calculated for each set for set for target detection and localization. Figure 11a,b shows the plot of the final output of As, for a target detection and localization. Figure 11a,b shows the plot of the final output of As , for a target target sitting in a static position at Rtgt = +2 m, −2 m and Rtgt = +4 m, 4 m, respectively, with Rb = 10 m. sitting in a static position at Rtgt = +2 m, −2 m and Rtgt = +4 m, 4 m, respectively, with Rb = 10 m. Note that the experiment was done separately; the figures combine the results for illustrative Note that the experiment was done separately; the figures combine the results for illustrative purposes. purposes. The peak of summation differences is obvious even for a target sitting in completely The peak of summation differences is obvious even for a target sitting in completely stationary mode. stationary mode. The target is clearly detected by the peak of the amplitude, which is way above the The target is clearly detected by the peak of the amplitude, which is way above the 3-dB threshold. 3-dB threshold. The highest peak of As is used for target detection, although some peaks at different The highest peak of As is used for target detection, although some peaks at different times appeared times appeared to be more than the threshold. Target location, Rtgt, can be estimated by calculating to be more than the threshold. Target location, Rtgt , can be estimated by calculating the transmitter the transmitter antenna looking angle, θ1 (Figure 2), for each scan. The angle θ1 can be determined antenna looking angle, θ1 (Figure 2), for each scan. The angle θ1 can be determined from the time from the time position of the peak As; for example, Figure 11a shows peak As at ts = 1.65 s; thus, position of the peak As; for example, Figure 11a shows peak As at ts = 1.65 s; thus, θ1 = 15.75◦ . θ1 = 15.75°. The target localization result is tabulated in Table 2, the negative and positive signs The target localization result is tabulated in Table 2, the negative and positive signs indicating the indicating the target to the left and right of the FSR baseline, respectively. The results in Table 2 target to the left and right of the FSR baseline, respectively. The results in Table 2 highlight some offset highlight some offset in location, especially for a target that is supposed to be at −4 m from the FSR in location, especially for a target that is supposed to be at −4 m from the FSR baseline. This could baseline. This could be explained due to the wide antenna beam width used during the experiment. be explained due to the wide antenna beam width used during the experiment. Another factor is Another factor is the precision of the motor that holds the transmitting antenna. The antenna rotates the precision of the motor that holds the transmitting antenna. The antenna rotates in the clockwise in the clockwise direction and produced a small vibration on the rotating arm (that holds the antenna) direction and produced a small vibration on the rotating arm (that holds the antenna) at the beginning. at the beginning. The vibration form the rotating arm effects the received Doppler frequency, and it The vibration form the rotating arm effects the received Doppler frequency, and it became severe for became severe for a high vibration rate. Thus, the target located within the starting area of the antenna a high vibration rate. Thus, the target located within the starting area of the antenna was detected was detected with poor precision, in this case the target at −4 m (Figure 11b). The target location, Rtgt, with poor precision, in this case the target at −4 m (Figure 11b). The target location, Rtgt , precision is precision is high when the target is near to the baseline and towards the end of the scanning area. high when the target is near to the baseline and towards the end of the scanning area. Although the Although the system’s resolution is not dealt with in this paper, it can be improved by employing a system’s resolution is not dealt with in this paper, it can be improved by employing a small antenna small antenna beam width, like a pencil beam shape, and using a rotating system with high stability. beam width, like a pencil beam shape, and using a rotating system with high stability. Table 2. Target detection result from the proposed FSR system compared to the actual position. Table 2. Target detection result from the proposed FSR system compared to the actual position. Antenna Look Angle, Actual Position, Rtgt from Estimated Rtgt from As (m) Actual FSR Position, Rtgt from Antenna Look Angle, Estimated Baseline, (m) θ1 = (ts/T R rot)×180° tgt = Rb × R tan(90° − θAs 1) (m) tgt from ◦ ◦ −θ ) FSR Baseline, (m) θ = (ts/T ) × 180 R = R × tan(90 rot tgt 1 1 15.75° −2 b−2.82 ◦ 20.81° +3.8 −2 +2 15.75 −2.82 ◦ 45.28° −10.1 +2 −4 20.81 +3.8 ◦ −4 +4 45.28 −10.1 25.17° +4.7 +4 25.17◦ +4.7

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Figure 11. Illustration of the experiment and plot of As for the target sitting in the static condition at (b) in the static condition at Figure 11. Illustration of(a) the experiment and plot of As for the target sitting the actual range from the baseline of (a) Rtgt = −2 m, +2 m and (b) Rtgt = −4 m, +4 m. the actual range from the baseline of (a) R = − 2 m, +2 m and (b) R = − m, static +4 m.condition at tgt tgt Figure 11. Illustration of the experiment and plot of As for the target sitting in4the tgt = −2 shaking, m, +2 m and Rtgt = of −4 the m, +4 m. the actual range fromtarget the baseline (a) Rslight In the case of the sittingofwith the(b) ripple Doppler shift frequency is

detected as of depicted in Figure 12.with This slight is due shaking, to Doppler from shaking like In the case the target sitting thescattered ripple of theother Doppler shiftparts, frequency is In the case of the target sitting with slight shaking, the ripple of the Doppler shift frequency is arms, knees, etc. Multiple peaks of amplitude can be seen clearly at the area of the target’s shaking. detected as depicted in Figure 12. This is due to Doppler scattered from other shaking parts, like arms, detected as depicted in Figure 12.the This is due toofDoppler scattered from other shaking parts, like peaks occurred due to rapid change at ofthe thearea total knees,Multiple etc. Multiple peaks of amplitude can berate seen clearly ofpath the length target’stravelled shaking.signal Multiple arms, knees, etc. Multipleand peaks of amplitude canbody be seen clearly at rest the area ofsignal, the target’s shaking. between the transmitter receiver induced by shaking. The of the which is below the peaks occurred due to the rapid rate of change of the total path length travelled signal between Multiple peaks occurred tothe theclutter. rapid rate of change of the total path length travelled signal the 3-dB threshold, comesdue from transmitter and transmitter receiver induced by body shaking. rest of signal, whichwhich is below the 3-dB between and receiver induced by bodyThe shaking. Thethe rest of the signal, is below Thethe difference between the target for Conditions i and ii can be summarized as the target with threshold, comes from the clutter. the 3-dB threshold, comesmultiple from theripples clutter. slight movement creates of As. Those peaks appeared above the 3-dB threshold level, The difference for and can be summarized as target themultiple target The thetarget target for Conditions Conditions i iand ii iican beeffect summarized asearlier, the with with which is difference the signbetween ofbetween target the existence. Apart from the micro Doppler explained movement creates multiple ripples of As. Those peaks appeared above thereceived 3-dB3-dB threshold level, slightslight movement creates multiple ripples As. Those peaks appeared above the threshold peaks of amplitude occur with the slightof movement due to the variation of the amplitude atlevel, which is sign the sign of target existence. Apart from from effect earlier, multiple which is the of target existence. themicro microDoppler Doppler effect explained earlier, multiple different frequencies. The system Apart manages to the differentiate between theexplained target sitting completely of amplitude occur withthe the slight movement due to the variation of theofreceived amplitude at stationary and the target sitting with slight movement. peakspeaks of amplitude occur with slight movement due to the variation the received amplitude different frequencies. The system manages to differentiate between the target sitting completely at different frequencies. The system manages to differentiate between the target sitting completely stationary and the target sitting with slight movement. stationary and the target sitting with slight movement. 10

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Figure 12. Plot of As for a target sitting with slight shaking condition at the range from the baseline, (a) (b) Rtgt, of (a) −2 m and (b) +2 m. Figure 12. Plot of As for a target sitting with slight shaking condition at the range from the baseline, Figure 12. Plot of As for a target sitting with slight shaking condition at the range from the baseline, −2 m and (b) +2 m. Rtgt, of (a)Target 4.2. Moving Detection and Localization

Rtgt , of (a) −2 m and (b) +2 m. This section detection scheme for the moving target crossing the middle 4.2. Moving Targetdiscusses Detection the and proposed Localization of the FSR baseline (Rcrossand = 10Localization m). The target moved in the crawling condition, which resembles the 4.2. Moving Target Detection section discusses the If proposed detection scheme for the movingintarget crossing the middle low This profile intruder scenario. the signal processing scheme described Figure 8 is applied to this This section discusses proposed detection scheme for the moving target crossing middle of the FSR baseline (R crossthe = 10 m). The target moved in the crawling condition, which resembles the scenario, it may produces multiple spikes scattered from many moving points. Confusion thatthe might profile intruder scenario. If the signal processing describedcondition, in Figure 8 which is applied to this the of thelow FSR baseline (Rcross = 10 m). The target moved scheme in the crawling resembles scenario, it may produces multiple spikes processing scattered from many moving points. Confusion mightto this low profile intruder scenario. If the signal scheme described in Figure 8 is that applied

scenario, it may produces multiple spikes scattered from many moving points. Confusion that might lead to misinformation, such as the number of targets and the direction of the target, may arise. An

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lead to misinformation, suchbased as theonnumber of targets andspectral the direction the target, of may An improved detection scheme the different power densityofmagnitude thearise. signal’s improved scheme based on the different joint T-F is detection recommended, and it is discussed below.power spectral density magnitude of the signal’s jointAs T-Fstated is recommended, and it is discussed below. earlier, the aim of this stage was to scrutinize the feasibility of the proposed FSR with the As stated earlier, the aim of this stage was to scrutinize the feasibility the proposed FSR with rotational transmitter for security surveillance; hence, the complexity in signalofprocessing is minimized. the task rotational transmitter for security hence, complexity in signalonprocessing is The is to monitor the change in thesurveillance; received signal due the to the target movement the ground minimized. The task is to monitor the change in the received signal due to the target movement on surface. An established method, such as Coherent Change Detection (CCD), was proposed for surface the ground surface. An as established suchThe as CCD Coherent Change Detection (CCD), SAR was displacement monitoring applied in method, SAR [22–24]. technique correlates consecutive proposed for phase surface displacement monitoring as applied SAR surface [22–24].change. The CCD technique images at the level and relates the phase changes to theinactual However, the correlates consecutive SAR images at the phase level and relates the phase changes to the actual integration of the CCD concept with FSR is a new idea, and therefore, appropriate consideration has to surface thesignal integration the CCD concept is a new idea, be made.change. Firstly,However, the received in FSRofdoes not carry any with phaseFSR information; thus,and the therefore, coherent appropriate consideration hasMoreover, to be made. in FSR does not carryinany phase detection scheme is not used. theFirstly, image the thatreceived needs tosignal be processed is the signal joint T-F information; thus, the coherent detection scheme is not used. Moreover, the image that needs to be representation, which is opposed to the SAR image in CCD. processed is the signal in jointversion T-F representation, which is opposed to the detection SAR image in CCD. Consequently, a modified of CCD, which is based on the change of the amplitude Consequently, a modified version of CCD, which is based on the change detection of the of the Doppler power spectrum density (D-psd), is suggested. Figure 13 shows the detection signal amplitude of the Doppler power spectrum density (D-psd), is suggested. Figure 13 shows the processing scheme for the moving target. Again, the background signal is taken as a reference. After detection signal processing scheme for representation, the moving target. the background signal is taken converting the signal into the joint T-F the Again, amplitude of D-psd is calculated. Let as thea reference. After converting the signal into the joint T-F representation, the amplitude of D-psd D-psd amplitude of the reference signal be Prf,t and the D-psd for the newly-scanned signal be Pzf,tis. calculated. Let the difference D-psd amplitude the by: reference signal be Prf,t and the D-psd for the Then, the amplitude of D-psd isofgiven newly-scanned signal be Pzf,t. Then, the amplitude difference of D-psd is given by: ∆P∆P (34) f,t f,t==Pr f,tf,t− Pr − Pz Pzf,t f,t (34) whereffand andttindicate indicatethe thefrequency frequencyand andtime, time,respectively. respectively.Figure Figure14 14shows showsthe theplot plotofof∆P ∆Pf,tf,t for for low low where profile target targetcrawling crawling crossing crossing the theFSR FSRbaseline baselinefor forfour fourconsecutive consecutivescanned scanneddurations. durations. Once Once the the profile target slowly enters the FSR baseline, there is a significant change in amplitude D-psd as produced target slowly enters the FSR baseline, there is a significant change in amplitude D-psd as produced by ∆P ∆Pf,t f,t. The determined and and used used as as the the reference reference by The distribution distribution center center mass, mass, M∆P, for each scan is determined point. The The target target trajectory trajectory can can be be predicted predicted by by analyzing analyzing the the change change in inM∆P M∆P (Figure (Figure 14a–d; 14a–d; in in this this point. case, the target crawls from left to right). M∆P can be determined by using the best fit curved to get case, the target crawls from left to right). M∆P can be determined by using the best fit curved to get the the envelope for f,t. Then, the middle point of the mass distribution is as selected as Moreover, the M∆P. envelope for ∆P Then, the middle point of the mass distribution is selected the M∆P. f,t . ∆P Moreover, the target speed can also bebyestimated the time of M∆P for every the target speed can also be estimated utilizing by theutilizing time difference ofdifference M∆P for every revisit time. revisitthe time. the of time position of M∆Plooking and antenna looking angle, (Figure each thus scan Since timeSince position M∆P and antenna angle, θ1 (Figure 2), forθ1 each scan 2), arefor known, are target known, thuscan thebe target speed and can is begiven calculated and giventarget in Table 3. Actual moving the speed calculated in Table 3. is Actual moving speedtarget was 0.5 m/s, speed is was 0.5 m/s, which is slightly higher than and from the target moves left which slightly higher than the estimated one,the andestimated the targetone, moves the left side from to thethe right side of to the the transmitter, right side ofasthe transmitter, asproposed captured scheme. by the proposed scheme. side captured by the Time Domain Testing

Reference Scanned signal in time domain without any object

Scanned signal in time domain

Spectrogram Doppler psd Amplitude difference, ΔPf,t Estimate distribution center mass, ΜΔP for each scan Determine direction and speed

Figure 13. Detection and localization signal processing scheme for the moving target. Figure 13. Detection and localization signal processing scheme for the moving target.

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(a)

(b)

(c)

(d)

Figure 14. Spectrogram of a target crawling and crossing the FSR baseline with the rotational transmitter

Figure 14. Spectrogram of a target crawling and crossing the FSR baseline with the rotational transmitter at four different consecutive scanning times: (a) for Scan I; (b) for Scan ii; (c) for Scan iii; (d) for Scan iv. at four different consecutive scanning times: (a) for Scan I; (b) for Scan ii; (c) for Scan iii; (d) for Scan iv. Table 3. Result for the target detection and the target’s speed by using ∆M∆P.

Table 3. Result for the target detection and the target’s speed by using ∆M∆P. M∆P (s) Antenna look angle, θ1 ∆ M∆P (s) 180° , (Trot = 4 s) θ = Antenna θ  look angle,  Distance from baseline Rtgt (m)1 ◦ M∆P ×1)180 (Trot R2tgts (m) (s) ◦ –θ1 ) for M∆P < 2 s Rtgt = Rcross∆M∆P × tan(90 ◦ ) for M∆P > 2 s R × tan(θ –90 n − M∆Pscan n−1) (M∆Pscan cross 1 Speed∆M∆P (m/s) (s) Averagenspeed (M∆Pscan − M∆Pscann−1 ) Speed (m/s)

5. Conclusions

Average speed

Scan i 1.96 Scan i

Scan ii 6.31 Scan ii

Scan iii 10.47 Scan iii

Scan iv 14.6 Scan iv

88.2° 1.96

103.95° 6.31

111.15° 10.47

14.6117°

88.2◦

103.95◦ +2.484

111.15◦ +3.869

−0.314 4.35

+2.484

−0.314

4.16

117◦ +5.095

+3.869

+5.095 4.13

0.63 0.34 0.30 4.35 4.16 4.13 0.42 m/s (misclassified by 0.8 m/s)

n, number of0.63 scans.

0.34

0.30

0.42 m/s (misclassified by 0.8 m/s) n, number of scans.

Forward scattering radar has been discussed for target detection, tracking and classification with applications to air, ground and maritime environments. Although research and development in FSR 5. Conclusions has gained interest for almost a decade, mostly fixed transmitters are used to send the signal. Thus, Forward been discussed targetthe detection, tracking and system classification the work scattering presented radar in thishas paper explored and for showed capability of the FSR with a with rotational to scan area of interest and detect a stationary or slow-moving target, which applications totransmitter air, ground and the maritime environments. Although research and development in FSR is veryinterest difficultfor foralmost the conventional system to transmitters detect. Practical forthe detecting low the has gained a decade,FSR mostly fixed areapplications used to send signal.aThus, almost stationary andand intruder crawling have beenof tested. A novel signal processing workprofile, presented in this paperintruder explored showed the capability the FSR system with a rotational detection scheme based on the joint T-F domain of the received signal is integrated with the proposed transmitter to scan the area of interest and detect a stationary or slow-moving target, which is very FSR system. As a result, a stationary target and a slow-moving target crossing the FRS baseline were difficult for the conventional FSR system to detect. Practical applications for detecting a low profile, detected for different locations and modes. The main advantage of using the FSR system with the

almost stationary intruder and intruder crawling have been tested. A novel signal processing detection scheme based on the joint T-F domain of the received signal is integrated with the proposed FSR system. As a result, a stationary target and a slow-moving target crossing the FRS baseline were

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detected for different locations and modes. The main advantage of using the FSR system with the rotational transmitter is the degree of freedom it possesses in controlling the Doppler frequency at the receiver, consequently allowing low profile target detection. Hence, the paper has shown the system’s potential for remote security and border surveillance. Based on the previous work, fixed FSR had shown that target detection and classification are affected by the target’s speed. However, this paper suggests that the transmitter is rotating, and the rotational speed can be controlled and optimized. Thus, the effect of rotational speed on the system sensitivity is interesting, and it will be analyzed in the future. The resolution is not discussed in this paper; however, the resolution can be further increased by using a narrow antenna beam width and pulse signal, which is also a subject for future work. In addition, the FSR coverage can be increased by using a network of distributed receivers. Interestingly, the concept of the rotational transmitter in FSR can be further explored for moving target detection, tracking and classification with a multisite receiver system. Acknowledgments: The authors of this paper would like to thank Professor Mike Cherniakov from The University of Birmingham, United Kingdom, for his direct and indirect technical input and critical view during the manuscript preparation. Author Contributions: Raja Syamsul Azmir Raja Abdullah and Azizi Mohd Ali designed the FSR prototype and signal processing scheme and analyzed the results. Aris Munawar and Asem Ahmad Salah performed the theoretical analysis and simulation. Mohd Fadlee A Rasid and Nur Emileen Abdul Rashid analyzed the results and supported the manuscript preparation. Conflicts of Interest: The authors declare no conflict of interest.

Appendix A By referring to Figure 1 in the text, the Doppler shift can be defined as the rate of change of the total path length travelled by the signal, i.e., the transmitter-target-receiver. The total Doppler frequency at the receiver can be written as [1]: fd =

1 d(RT + RR ) λ dt

(A1)

where RT and RR are the range between the transmitter-target and target-receiver, respectively. The target Doppler frequency (only target is moving) due to the motion relative to the transmitter can be written as:   1 d(RT ) v β ftx = = cos +δ (A2) λ dt λ 2 where δ and β are shown in Figure 1, and the target Doppler frequency due to the motion relative to the receiver is:   1 d(RR ) v β = cos −δ (A3) frx = λ dt λ 2 hence, by inserting (A2) and (A3) into Equation (A1), the total target Doppler frequency at the receiver becomes, as shown in Equation (9): fd = ftx + frx =

β v β v β β v cos ( + δ) + cos ( − δ) = [cos ( + δ) + cos ( − δ)] λ 2 λ 2 λ 2 2 " " ! !##   β β β β + δ + − δ + δ − + δ v 2v β 2 2 = 2 cos 2 cos 2 = cos cos(δ) λ 2 2 λ 2

References 1. 2. 3.

Cherniakov, M. Bistatic Radar: Principles and Practice, 1st ed.; John Wiley & Sons: Chichester, UK, 2007. Glaser, J. Forward Scatter Radar for Future Systems. WSTIAC Q. 2011, 10, 3–8. Skolnik, M.I. Radar Handbook, 2nd ed.; McGraw-Hill Professional: New York, NY, USA, 1989.

(A4)

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