PERFORMANCE ENHANCED HIGH SPEED UWB GPR SYSTEM ...

PERFORMANCE ENHANCED HIGH SPEED UWB GPR SYSTEM FOR BURIED REBAR DETECTION Tian Xia*, Anbu Venkatachalam, Yu Zhang, Dylan Burns, Dryver Huston School of Engineering, University of Vermont Burlington, VT, USA

Abstract This paper describes an air-coupled, ultra-wide-band (UWB) ground penetrating radar (GPR) system that is designed for assessing the condition of reinforced concrete bridge decks from a vehicle traveling at highway speeds. The hardware design combines digital signal processing techniques to create a shaped ultrawideband source with a full waveform digitizing high-speed data acquisition system. The UWB pulse generator uses a novel, yet simple, step recovery diode (SRD) based impedance matching and differentiator circuit technique, which produces a high pulse amplitude (18 Vpp) and low level ringing. By employing the 8 Gsps real time data acquisition unit to sample the reflection signals without sub-sampling, the GPR survey speed is significantly improved. This makes it applicable for highway and bridge inspection at regular driving speed. Moreover, multithreaded parallel operations are implemented to speed up the large volume data pipeline from the digitizer. Customized signal processing methods, including data pre-processing, target area detection and hyperbola fitting, have been developed to reduce systematic noise and RF interference, and to leverage subject detection accuracy. Design validations include rebar detection experiments under different test setup conditions. Keywords: GPR system; high speed real time sampling; air-coupled; rebar detection; imaging processing.

Introduction As an important structural component, the buried rebar plays a vital role supporting highway or bridge deck reinforced concrete. Hence it is of great importance to indentify rebar location and condition. A variety of GPRs are currently available for rebar detection (Uddin, W. 2006, Che, W.C. 2009 and Olhoeft, G.R. 2000). However, various factors, such as the relatively low signal sampling rate, bulky mechanical structure, and ground coupling antennas installed at close proximity to the detection surface, limit the scanning speed of these GPRs to speeds that are too slow to move with traffic, and instead require lane closures and other traffic disruptions. Many of these limitations arise from speed processing restrictions and the need to comply with radiated EM restrictions. To overcome these drawbacks, our research (Xia, T., Venkatachalam, A.S. 2012 and Xia, T., Xu, X. 2012)

has been focusing on developing a high speed UWB GPR equipping with a high speed real-time sampling unit to accomplish the full reflected GPR waveforms in a single shot, which bypasses the slower sub-sampling methods used by most presently-available impulse radar systems. Moreover, the multithread operating mode is configured to leverage radar data throughput and processing speed. These improvements enable UWB radar to operate in a vehicle running at normal driving speed. In this paper, we continue our effort to improve UWB GPR system performance from two other aspects: 1. Designing a new pulse generator circuit that can leverage radar transceiver pulse amplitude from 9 volts (Xia, T. and Xu, X., 2012) to about 18 volts, which results in additional 6dB dynamic range improvement; 2. Implementing new signal processing methods to leverage radar data feature extraction effectiveness and radar image quality. Specifically, Short Time Fourier Transform (STFT) and digital filtering are implemented to reduce signal noise and to enhance radar signal time and frequency characterizations. For validation, experiments are conducted by means of different test setups.

UWB GPR hardware Development The UWB GPR is impulse radar. Its hardware consists of radio frequency front end and digital control and data processing backend, including data acquisition module. In the front end, the UWB pulse generator plays a critical role in determining GPR system bandwidth, the detection depth and range resolution. While in the backend, the data acquisition unit is crucial. Its sampling speed directly determines whether GPR can operate at regular highway driving speed while to achieve high spatial resolution. In most GPRs, equivalent-time sampling is utilized due to its low development cost. The equivalent-time sampling is based on the assumption that the object under test is static or moves slowly relative to GPR transceiver. However for highway speed GPR, such assumption may lose validity. In this design, we exploit high speed real time sampling techniques to realize single shot data collection, where the reflection signal in a complete cycle can be obtained in a single trigger event with great fidelity. High Amplitude UWB Pulse Generator In the GPR radar design presented in this paper, one of the critical components of the RF front end is the UWB pulse generator. A high quality pulse with low ringing noise is important to detect targets in the subsurface of the material under investigation. In this research, referring (Protiva, P. 2009 and Zhang, C. 2006), we developed a pulse generator that produces 18 V peak-to-peak pulses with ringing amplitude less than 10% for a wider range of pulse repetition frequency (PRF). The circuit diagram of the UWB pulse generator is presented in Figure 1. It comprises of four elements: a) Op-amp to amplify the digital clock from a FPGA; b) Edge triggered timing circuit to maintain constant driving pulse irrespective of the input PRF; c) BJT driver circuit to generate a sharp negative driving pulse; d) Gaussian pulse generator using a step-recovery diode (SRD) for sharpening the transition edge and microstrip delay line.

Figure 1:

UWB monocycle pulse generator

The first part of the circuit comprises of a current feedback wide band operational amplifier THS3091 to amplify the clock signal generated from a Spartan-3E FPGA. The PRF of the transmitted pulse is determined by the frequency of the digital clock controlled directly from the FPGA. The 3.3 V high impedance digital clock is amplified by the operational amplifier to 10 V square wave signal capable of driving 50 Ohm low impedance load. The second part of the pulse generator is the timing control circuit. The timing control circuit ensures that irrespective of the PRF of the input clock signal, a pulse with defined width is provided to the driver stage of the circuit. At the rising edge of the square wave from the op-amp, transistor T2 (MM3904) is turned on and voltage builds up across the emitter resistor, Re. The coupling capacitor, Cc accelerates the biasing of the transistor T2. When fully on, the bias current of the transistor T2 is maintained by the bias resistor, Rc. The output pulse width of this stage is controlled by the timing circuit elements Ri, Ci and a wide band transistor T1 (BFG410W). Switching on of T1 is delayed by the Ri and Ci, integrator combination. When T1 is turned on, its collector output is grounded which turns off the transistor T2 and effectively controlled the driver pulse duration. A high voltage transistor T3 (BFG135), a resistor Rc1 and a capacitor Cc1 form the third part of the pulse generator and produces the negative pulse driving the SRD. In steady state, transistor T3 is off and the capacitor Cc1 is charged with a steady current controlled by the charging resistor Rc1. When transistor T2 is turned on, voltage across the resistor Re raises to +V instantaneously which turns on the driver transistor T3 and immediately puts it in saturation region. The capacitor Cc1 is discharged rapidly by the transistor T3, thus creating a negative voltage (-Vneg) at its output terminal with a sharp transition edge in the order of ~100s of picoseconds. When the transistor T2 is turned off after the controlled delay, determined by the timing circuit, voltage across the resistor Re decreases slowly depending on the size of the resistor itself. This slow decrease in the voltage turns off the transistor T3 gently at a much slower pace, thereby without creating any significant overshoot in the rising edge of the output negative pulse, as shown in Figure 2. The width of the pulse can be reduced to as small as few nanoseconds to reduce the power drawn from the supply voltage.

Figure 2:

Negative pulse with sharp edge to drive the SRD

The UWB Gaussian pulse is generated using the combination of a step-recovery diode, a Schottky diode, delay line and a filter capacitor. In steady state, the Schottky diode is reverse biased and the SRD is forward biased by a small bias voltage Vbias (~1.25 V). The bias voltage provides a steady current (~30 mA) for the operation of the diodes. When the negative pulse is applied from the driver circuit, the effective voltage (Vbias-Vneg) reverse biases the SRD and forward biases the Schottky diode there by grounding one end of the delay line and resulting in a short-circuited stub connected to the SRD. When the SRD is reverse biased, due to the inherent device nature of the diode, it still conducts in the forward direction due to the charges accumulated in the intrinsic layer of the SRD. When all the charges are depleted, the SRD turns off instantaneously and generates a very sharp transition edge in the order of 10s of picoseconds. Also, the SRD offers very high impedance which reflects the sharp negative edge away from the SRD node in both the directions, one towards to the output and second back towards the source. Since the Schottky is forward biased and effectively grounded, the signal that travelled via the delay line to the Schottky diode is reflected back to the output with opposite polarity. The two signals combine and produce a UWB negative Gaussian pulse. Figure 3 is the snapshot of the UWB pulse captured using a wide bandwidth oscilloscope after 12 dB attenuation. The width of the UWB pulse is determined by signal propagation delay across the length of the delay line. By reducing the length of the delay line, pulse as narrow as 100 ns can be generated but reduction in the amplitude. The filter capacitor, Cf, acts as a high pass filter, eliminates the low frequency noise and passes only the UWB pulse.

Figure 3:

Measured Gaussian monocycle pulse upon 12 dB attenuation

High Speed Digitizer Configuration The digitizer utilized in this system is the Agilent Acronis real-time AD converter, whose sampling rate is 8 Gsps and the resolution is 10-bit. To handle the large volume and high rate sampling data stream, we opt to configure the digitizer into the simultaneous multi-buffer acquisition and readout (SAR) mode, where the digitizer’s internal memory is divided into three banks to form a circular structure. The SAR mode supports dual-port data access to allow simultaneous data writing and reading. The data acquisition bank is further configured to operate in sequence acquisition (SC) mode, in which the bank is divided into 333 segments. Each segment has the capacity to store 320 sampling data sequentially. For digitizer operation, it takes about 13 ns to transfer each sampling data from digitizer’s internal memory to the backend computer hard disk. However, acquiring each sampling data only takes 125 ps corresponding to 8 Gsps sampling rate. The data transfer speed is about 100 times slower than sampling data acquisition. Such large speed discrepancy could cause digitizer operation jam and data loss. Fortunately, for impulse GPR, its signal duty is extremely low, and for reflection signal, the meaningful time interval is only a small portion of the whole signal period. In our test development, the radar signal pulse repetition frequency is 30 KHz (33.3 us period). While for reflection signal acquisition, the sampling window is only 40 ns wide, which leads to 320 sampling data points collected within every 33.3 us signal period. To fill up one memory bank, it takes about 1 ms (33.3 us/segment * 333 segments = 1 ms), while the effective sampling time is only 13.32 us (40 ns/segment * 333 segments = 13.32 us). In SAR mode, the memory writing and reading are parallel operations, which thus give 1 ms time margin for transferring sampling data collected within 13.32 us. As a result, it compensates speed mismatch between back end data transferring and front end signal sampling by 76 times (= 1 ms/ 13.32 us). To further alleviate speed mismatch, a quad-core computer is adopted to realize multi-thread data reading and writing. In the configuration, each processor implements one thread, named a lab.

Using a quad-core computer, the data reading and writing are accomplished in parallel with 4 labs. Such parallel operating mode effectively speeds up the backend data storage from two perspectives: First, the data is not directly transferred into the slow speed hard disk, instead it is relayed through processor’s fast dynamic memory. Second, using one-to-three lab configuration to implement the multi-thread data buffering, the backend data transferring speed is accelerated by about three times. Utilizing the above techniques, the speed mismatch between radar signal sampling and data transferring is resolved.

Rebar Test Development Our GPR system is designed for rebar detection and its feature characterizations. In this paper, our focus is on locating the precise position of buried rebar. To illustrate design effectiveness, an outdoor experimental study has been conducted. The outdoor rebar test configurations are: (1) One 1.5 cm diameter rebar is buried 1 foot deep underground; (2) The underground materials contain soil and stone pebbles; (3) The antennas of our GPR system are installed 14 inches above the soil ground surface. The test setups are illustrated in Figure 4.

Figure 4: Photos of rebar setup: (a) Our GPR system; (b) The outdoor test environment; (c) 1 foot underground; (d) Scan test setup.

Radar Data Processing Radar data processing for increasing rebar detection accuracy is an active research subject (Halabe U.B. 1993, Roqueta, G. 2012, Huston, D. 2000 and Borgioli, G. 2008). Reflection signals acquired from the receiver antennas contain various noise interferences, such as systematic noise, radio frequency interference and strong ground surface reflections etc. These signals blur the features of the rebar in the B-scan image and sometimes even mask the rebar reflection signal when the amplitudes of noise signals are very high. Therefore to develop effective radar signal characterization method is both important and indispensible. In this project, besides the regular background removal and trace averaging operations to alleviate systematic noise, one other characterization algorithm explored for radar time and frequency characterization is Short Time Fourier Transform (STFT).

Short Time Fourier Transform Fourier transform has been widely used for signal spectrum characterization. However its one major limitation is that the signal time information is lost in transforming the analysis into the frequency domain. For stationary signals analysis, where the processed signals do not change with time, this limitation is not obvious. However the premise of stationary signal does not hold in most GPRs. In GPR operation, the scanning antennas move continuously, thus the subsurface features under inspection change with time, which leads to non-stationary reflection signals being collected. For GPR signal analysis, to obtain both the time and spectrum information, the traditional Fourier Transform is ineffective. In this study, we propose to apply Short Time Fourier Transform (Allen, J.B. 1977) for GPR data characterization, which is capable of tracking frequency response change with time. In essence, STFT implements local Fourier transform algorithm on data that have been divided into smaller data windows. Mathematically, STFT algorithm is expressed as follow: −𝑗𝜔𝑛 𝑋𝑚 (𝜔) = ∑∞ = 𝐷𝑇𝐹𝑇𝜔 (𝑥 ∙ 𝑆𝐻𝐼𝐹𝑇𝑚𝑅 (𝑤)) 𝑛=−∞ 𝑥(𝑛)𝑤(𝑛 − 𝑚𝑅)𝑒 where 𝑥(𝑛) is the input signal at time 𝑛, 𝑤(𝑛) is the length M window function (e.g., Hamming, Hann or Gaussian window), 𝑋𝑚 (𝜔) is the DTFT of windowed data centered around time 𝑚𝑅, and 𝑅 is the hop size in samples between successive DTFTs. For STFT, there is a trade-off between time and frequency resolution that is controlled by the length M of the sampling window 𝑤(𝑛). Large window produces fine frequency spectrum resolution while decreases GPR inspection time or depth resolution. Narrow window width increases time or depth resolution but sacrifices its frequency resolution. In this project, the Hann window is adopted for GPR data characterizations. As shown in Figure 5, three different window width values are adopted, which are 0.625 ns, 1.25 ns and 2.5 ns respectively. In these figures, the horizontal axis represents signal traveling time (unit: nanoseconds) while the vertical axis specifies signal's frequency (unit: GHz). The signal spectrum ranging from low to high values are illustrated by cold to hot colors correspondingly. The 1.25 ns window length is chosen for it producing a balanced time resolution and frequency resolution. Figure 6 depicts the magnified view of STFT image. As illustrated, the spectrum of effective rebar reflection signal is located around 20 ns, whose spectrum is mainly below 2 GHz; while the spectrum of major noise signals exists above 2 GHz or below 0.5 GHz, and span across the whole timeline. Therefore by applying a band pass filter (BPF) with 0.5 GHz and 2 GHz cut-off frequencies, the noise signals can be attenuated, while the effective rebar reflection signals become more pronounced. Figure 7 and Figure 8 compare the B-scan images before and after BPF filtering processing. Clearly, the reflection signal traces are smoothed out upon noise filtering.

Figure 5:

STFT result using various window lengths

Figure 6:

STFT analysis GPR signal: (a) STFT result; (b) zoom in to 0-2GHz

Figure 7:

Original B-scan image and reflection signal: (a) B-scan image; (b) Reflection signal

Figure 8: signal

B-scan image and reflection signal after band pass filter: (a) B-scan image; (b) Reflection

To further improve B-scan images quality, the averaging and subtraction operations (Olhoeft, G.R. 2000) are applied to the BPF filtered radar data, which effectively remove systematic background interference signal, and improves rebar hyperbola feature visibility, as shown in Figure 9.

Figure 9: B-scan images after averaging and subtraction: (a) original image; (b) a trace signal; (c) the image upon BPF filtering; (d) the trace signal upon BPF filtering

Conclusions This paper is to improve UWB GPR system performance for buried rebar detections. Our research efforts concentrate on two aspects: 1). The development of a new high voltage pulse generator circuit that leverages radar pulse amplitude to about 18 volts; 2). Developing short time Fourier transform algorithm for radar signal time and frequency characterizations. With STFT analysis, the appropriate filter and cut-off frequency can be appropriately identified for noise alleviation, which effectively enhances the rebar feature detection.

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