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A Real-Time Time-Domain EMI Measurement System for Full-Compliance Measurements According to CISPR 16-1-1 Stephan Braun, Member, IEEE, Thomas Donauer, and Peter Russer, Fellow, IEEE
Abstract—Time-domain electromagnetic interference (EMI) measurement systems allow measurement time to be reduced by several orders of magnitude. In this paper, a novel real-time operating time-domain EMI measurement system is presented. By the use of several analog-to-digital converters, the dynamic range requested by international electromagnetic compatibility (EMC) standards is achieved. A real-time operating digital signal processing unit is presented. The frequency band that is investigated is subdivided into several subbands. The EMI signal of the complete frequency band is digitized. By a digital down converter, each subband is shifted toward its baseband and low-pass filtered. The low-pass filtered signal is down sampled. The down-sampled signal is processed by a short-time fast Fourier transform. The obtained spectrogram is processed by a parallel implementation of peak, average, and quasi-peak detectors. The dynamic range of the system has been investigated. A comparison of the digital signal processing to the analog signal processing of an EMI receiver is shown. Measurements have been performed in the frequency range 30 MHz to 1 GHz. Such a system can fulfill the international EMC standard CISPR 16-1-1. By the parallel simulation of several thousand EMI receivers, the measurement at several thousand frequency bins can be performed simultaneously. Due to this benefit, the measurement time can be reduced, and further investigations on a device under test can be performed. These investigations are full characterizations, as well as full scans in the final detector mode, which is especially of benefit for highly unstationary emitting devices. Index Terms—Electromagnetic compatibility (EMC), electromagnetic interference (EMI), fast Fourier transform (FFT), frequency domain, time domain.
I. INTRODUCTION ULL-compliance measurements are carried out by electromagnetic interference (EMI) receivers operating in the frequency domain. EMI receivers have to fulfill the requirements that are given by the international standard CISPR 16-1-1 [1]. However, measurements in the frequency domain take long times. A possibility to reduce the time for a single scan up to five orders of magnitude is to perform the measurement in the time domain and simulate several thousand EMI receivers in parallel on digital hardware. With a time-domain EMI (TDEMI) measurement system, the input signal is digitized by an analog-to-digital converter (ADC) system. Spectral estimation is performed by a fast Fourier transform (FFT). The block diagram of a multiresolution TDEMI measurement system is
F
Manuscript received September 4, 2006; revised March 2, 2007 and October 31, 2007. The authors are with the Institute for High-Frequency Engineering, Munich University of Technology, Munich D-85747, Germany (e-mail: braun@ tum.de;
[email protected];
[email protected]). Digital Object Identifier 10.1109/TEMC.2008.918980
Fig. 1.
Multiresolution time-domain EMI measurement system.
shown in Fig. 1. The EMI signal is received via a broadband antenna [2]. By a multiresolution ADC system, a floating-point analog-to-digital conversion is performed [3]. The measured and digitized EMI signal is processed via digital signal processing and the amplitude spectrum is displayed. An algorithm that allows measurements in the peak, average, and rms detector modes to be simulated has been presented in [4]. One of the first systems was based on a digital storage oscilloscope and used the FFT, as presented by Keller and Feser [5]. An algorithm for the quasi-peak detector mode has been presented in [6]. With both the algorithms, almost all requirements that are given by CISPR 16-1-1 are fulfilled [7]. The only requirement that could not be fulfilled by these algorithms is the continuous processing of the input signal. However, continuous processing is mandatory in order to provide the requested intermediate frequency (IF) signal and quasi-peakmeter signal. Such an auxiliary output signal can only be provided by a system that is operating in real time. Another benefit of the real-time operating system is processing of the EMI signal without gaps during the dwell time. The basic operation of a real-time operating multiresolution TDEMI measurement system has already been presented in [8]. In the following, an improved real-time operating TDEMI measurement system is presented. Due to the real-time operation, the system can emulate the complete behavior of an EMI receiver. A detailed comparison between the analogue signal processing and the digital signal processing of the real-time operating system is shown. The EMI signal is digitized by an ADC system. The frequency band that has to be processed during the characterization of a device under test is subdivided into several subbands. The subbands are measured sequentially. Each subband is down converted into its baseband by a digital down-conversion (DDC) unit. The down-converted signal is down sampled and processed by a short-time FFT (STFFT). The STFFT generates a spectrogram that shows a discretization in time and frequency [9]. At
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where Hqp (|sIF |) describes the behavior of the quasi-peak detector to the input signal. A detailed investigation of the response of the quasi-peak detector can be found in [10]. The output value of the average detector is described by Aavg = |sIF (t)|.
(4)
III. TIME-DOMAIN EMI MEASUREMENT SYSTEM A. Fast Fourier Transform Fig. 2.
Conventional heterodyne receiver.
each calculated discrete frequency, the evaluation is performed by a digital detector.
Digital spectral estimation is achieved via the discrete Fourier transform (DFT). Algorithms for DFT computations that exploit symmetry and repetition properties of the DFT are defined as FFT. The DFT formulation considers periodic repetition of the signal in time domain, and is given as follows:
II. EMI RECEIVERS X[k] =
A. Overview
N −1
x[n]e
−j 2 π k n N
.
(5)
n =0
EMI receivers measure the signal of EMI in the frequency domain. The measurement for a given set of frequencies is performed sequentially. Today’s EMI receivers are heterodyne or superheterodyne receivers. The block diagram of a conventional heterodyne receiver is shown in Fig. 2. The preselective input filter suppresses signals that are outside the band of interest. In this way, the dynamic range is improved. By a controllable attenuator, the level of the signal is controlled in a way that the following mixer does not overload. A mixer and a local oscillator perform a down conversion of the signal to an IF. The signal is bandpass filtered by an IF filter. EMI receivers according to CISPR 16-1-1 exhibit several IF filters that can be selected. Each IF filter has to fulfill the critical mask given by CISPR 16-1-1. The output signal is evaluated by peak, average, CISPR-average, rms, and quasi-peak detector modes for the selected dwell time. The IF signal sIF is provided as an analogue output signal. The response of the quasi-peak detector is also provided as analogue output signal sqp . B. IF Signal The analog output signal sIF is described in the frequency domain by SIF (f ) = S(f − fsel + fIF )HIF (f )
(1)
where fsel is the selected frequency. The EMI signal is shifted to the intermediate frequency fIF and multiplied by the frequency response of the IF filter. HIF is the amplitude response of the IF filter. C. Detector Modes
(2)
The output signal of the quasi-peak detector can be described in a general way by sqp (t) = |sIF | × hqp (|sIF |)
EMI signals, however, consist of stationary and transient signals as well as noise. In order to model the exact behavior of an EMI receiver, the STFFT is used. By the use of a Gaussian window function, the IF filter is modeled according to its impulse bandwidth, noise-bandwidth, and the filter masks, as defined in CISPR 16-1-1. By the STFFT, a spectrogram is calculated. This spectrogram shows a disctretization in frequency and time. The resolution in frequency is described by the bin width f . The resolution in time is described by a time step TsBB . The inverse of the time step is called the baseband sampling frequency fsbb . The STFFT calculates as follows: X[t, k] =
N −1
x[n − t]w[n]e
−j 2 π k n N
(6)
n =0
where w[n] is a Gaussian window function that models the IF filter of an EMI receiver [6]. The relation between the samples that are processed by a single FFT and the number of samples where shifting is performed is described by the overlap factor Of . The number of FFT calculations NO that have to be performed for N samples is described by NO =
1 fsbb . = 1 − Of f
(7)
The discretization in the time domain has to be dense enough to fulfill the Nyquist criterion. An overlapping factor of about 75% is sufficient to achieve a sufficiently dense discretization for the simulation of the various detector modes. C. Comparison to an EMI Receiver
The output value of the peak detector is described by Ap eak = max(|sIF (t)|).
B. Short-Time Fast Fourier Transform
(3)
In the following, we will show mathematically the equivalence between a real-time TDEMI measurement system and a conventional EMI receiver. In the first step, we investigate the IF signal of the TDEMI measurement system and perform a comparison with EMI receivers. In order to compare both the systems, we will have to investigate the result at single frequency fsel .
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1) If-Signal: At a single frequency, we may take (6) and replace kn/N fs by fsel . We obtain the signal of the spectrogram at a single frequency in sbb,f s e l [t] =
N −1
x[n − t]w[n]e−j 2π f s e l = x[t]w[t]e−j 2π f s e l t .
n =0
(8) We transform (8) to the frequency domain. The convolution between x[t] and w[t] is a multiplication in the frequency domain. The factor e−j 2π f s e l describes a frequency shift by the selected frequency. The signal sbb,f s e l [t] shows a discretization in time, which is the inverse of the baseband sampling frequency fsbb . The base band signal is described in frequency domain by Sbb,fse [f ] = W [f ]X[f − fsel ]
(9)
where W [f ] is the Fourier transform of the window function w[n]. In order to generate the IF signal by the TDEMI measurement system, we need to shift the baseband signal Sbb to an intermediate frequency. A typical intermediate frequency used in EMI receivers is fIF = 10.7 MHz. This operation is described by SIF,fsel [f ] = Sbb,fse [f + fIF ].
(10)
Comparing (1) and (10), we see that in order to get the same IF signal, the frequency response of the IF filter and W [f ] has to be the same. Additionally, the sampling rate of the IF signal has to fulfill the Nyquist criterion. D. Detector Modes The base-band signal is processed at each discrete frequency by a detector. The peak detector is described by Ap = MAX{|sbb,fsel [n]| n ∈ {1, . . . , M }}.
(11)
Aavg
Real-time digital signal processing.
tifacts of the ADCs by a multisampling algorithm have been discussed. A detailed description of the SNR of the TDEMI measurement system has been discussed in [11]. The real-time operating TDEMI measurement system is based on field-programmable gate arrays (FPGAs). The implemented digital signal processing is performed with integer values. Thus, the effects of the discretization of the spectrum in frequency domain also have to be investigated. The relation between the maximum measurement error Xer,dB and the quantization error is given by = 10(
X er,dB 20
)
− 1.
(14)
Consequently, the number of bits that are necessary to obtain a maximum error of in a truncation implementation is described by X ( e2r 0, d B ) −1 . (15) ba = −log2 10 For an implementation that uses rounding instead of truncation, 1 bit less is needed. For our example, we consider that we need an accuracy of 1 dB and used truncation. Thus, we would need 3 bit for quantization. The requirement for achieving a sufficient dynamic range is given by XSFDR . (16) 6 dB The total number of bits bt needed by the system is given by bd =
The formulation of the average detector is given by M −1 1 = |sbb,fsel [n]|. M n =0
Fig. 3.
(12)
b t = bd + ba .
(17)
In order to obtain the same results in comparison to an EMI receiver, the detectors have to evaluate the input signal for the same dwell time. Thus, M has to be
Thus, an ideal system using 16-bit resolution in the frequency domain, and a required accuracy of 1 dB shows a dynamic range of 78 dB.
M = fsbb tdwell .
IV. REAL-TIME OPERATION
(13)
E. Dynamic Range The dynamic range of a TDEMI measurement system, considering the analog-to-digital conversion, has been investigated in [11]. The investigation of the intermodulation effects for transient signals has been performed in [3]. The intermodulation effects of a multiresolution EMI measurement system mainly depend on the parasitic effects of the implemented limiters. It has been shown that at least 36 dB as requested by CISPR 16-1-1 have been achieved. The intermodulation effects of a single ADC and a comparison with the EMI receiver have been discussed in [12]. Strategies to remove spurious signals and ar-
An overview of the digital signal processing blocks is presented in Fig. 3. In order to perform measurements in the frequency range 30 MHz to 1 GHz, the sampling rate fS has to be at least 2 GS/s to fulfill the Nyquist criteria. Because of the limited clock speed of the hardware used the input of the DDC is subdivided into eight parallel inputs with at least 250 MS/s per channel. As a consequence, the maximum frequency has to be reduced by a factor of 8. Thus, the frequency range 0–1 GHz is subdivided into eight bands. Each band exhibits a bandwidth of 125 MHz. The eight frequency bands are shown in Fig. 4. The spectrum of each band is processed separately by DDC, STFFT, and the digital detectors. After having selected and measured
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Fig. 4.
Frequency bands.
Fig. 5.
Digital down-converter.
each band one by another, the complete spectrum is composed of those eight parts.
Fig. 6.
Transfer function of the polyphase decimator.
Fig. 7.
Processing of frequency band 5 by the digital down-conversion.
A. Digital Down Conversion Fig. 5 shows the block diagram of the DDC unit. fD i is the center frequency of band i. The selected band is shifted into baseband. This is done in order to process the output signal by the STFFT. Mathematically, the shifting operation in the frequency domain corresponds to a phase rotation in the time domain x[n]ej ω n ←→ X(ej (ω −ω 0 ) ).
(18)
For the shifting application, we obtain x[n]e
−j 2 π f D n N
←→ X[(k − fD ) mod N ].
(19)
written as
Using the Euler formula jx
e
= cos (x) + j sin (x)
(20)
u[n] = x[n] × h[n] =
N
h[k]x[n − k].
(22)
k =0
the shifting coefficients can be described as −j 2 π n f D j2πnfD j2πnfD N e = cos − j sin . N N
(21)
The real part is obtained by a multiplication with a cosine signal. The imaginary part is calculated by multiplication with a sinusoidal signal. By this way, the complete spectrum is shifted by fD . In order to get the signal of a single frequency band, two identical polyphase decimators [9] are used. In order to achieve high measurement accuracy and avoid aliasing effects, the following specifications have been chosen: 1) passband ripple of 0.1 dB; 2) stopband attenuation of 100 dB; 3) decimation by a factor of 8. In Fig. 6, the obtained transfer function of a finite impulse response (FIR) filter with an order of 95 is shown. A polyphase decimator with M input channels consists of a structure of M parallel FIR subfilters. The outputs of the subfilters are added. Each subfilter runs at the clock rate of the output signal. A filtering with a low-pass FIR filter can be
Regarding the functionality of a regular decimation by a factor of M y[m] = u[nM ]
(23)
we obtain for a polyphase decimator y[m] =
N
h[k]x[n × M − k].
(24)
k =0
The L coefficients for each subflter can be derived from a model using one single-input FIR filter with K = L × M coefficients followed by a regular M-to-1 decimator by distributing the K coefficients to the subfilters in rotation. The polyphase decimator used for the TDEMI measurement system contains K = 96 filter coefficients and shows a symmetrical impulse response. Taking advantage of this symmetry, the hardware resources can almost be cut to half by summarizing the operations of two identical coefficients, as described in [13]. Fig. 7 demonstrates the operation of the DDC if frequency band 5 is selected.
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Fig. 10.
Fig. 8.
Short-time FFT.
Block diagram of ADC system.
a 16-bit integer value. The processing is performed in real time. Thus, the FPGA has to process a data rate of 69 Gb/s. The signal can be processed by the first FPGA or forwarded to the second FPGA. Four SRAMs are integrated on the board to store the signal in the time domain. Real-time processing can be performed by implementing the decimation filter into the first FPGA, and the STFFT as well as the detector modes on the second FPGA. The calculated spectra as well as the time-domain signal can be transferred to external personal computer (PC) and visualized. A. Analog-to-Digital Converters
Fig. 9.
STFFT with a reduced number of discrete frequencies.
The ADCs used exhibit a sampling rate of 2.3 GS/s and 10-bit resolution. The ADCs feature 51 dBc SNR, 7.8 effective number of bits (ENOB), and −55 dBc spurious free dynamic range (SFDR) at sampling rate(Fs ) of 2 GS/s and input tone (Fin ) of 1000 MHz. The dual-tone third-order intermodulation distortion (IMD3 ) is −60 dBFs at Fs = 2 Gsps and Fin1 = 945 MHz and Fin2 = 955 Hhz (−7 dBFs each tone).
B. Short-Time Fast Fourier Transform
B. Field-Programable Gate Arrays
In Fig. 8, the block diagram of an STFFT implementation with four parallel FFT calculating units is shown. The overlapping is achieved by three cascaded shift registers. Alternately, decimation in frequency (DIF) [9] can be used to calculate only a fraction of the discrete spectral values. This will increase the measurement time by a factor of 4, but will reduce the hardware resources by about a factor of 10. An example of such an implementation is shown in Fig. 9. Each channel is multiplied by a twiddle factor W n i [9]. In this way, only every fourth discrete frequency is calculated. By changing the twiddle factors, all discrete frequencies can be calculated sequentially.
Two FPGAs are used in order to process the digital signals available from the ADCs and for performing the FFT. Each of the FPGA consists of 15 360 logic cells that provide logic, arithmetic, and ROM functions and can perform 76.8 billion multiplications and accumulations per second.
V. HARDWARE IMPLEMENTATION The block diagram of the multiresolution ADC system is depicted in Fig. 10. Each amplitude scale is processed by 2.3 GS/s 10-bit ADC. The signal of each ADC is demultiplexed by a factor of 4 to reduce the data rate. By this way, the datawidth is increased by a factor of 4. The first FPGA receives the signal of all three ADCs and creates a floating-point value from the signals of the three ADCs. Afterward, the signal is converted to
C. Hardware Implementation The ADC unit has been developed on a multilayer printed circuit board (PCB). Each ADC is mounted into a separate gasket to reduce interference between the digital part and the analog input signal. EMI filters have been used for the power supply to avoid coupling between the analog and digital part of the ADCs. Differential signaling was used between the ADCs and the FPGAs to avoid noise that is caused by common mode signals. In Fig. 11, a picture of the ADC unit is shown. On the left side of the board are the three ADCs, which are placed equidistant and routed to the first FPGA that is centered between them. Each ADC is encased by a ground ring with ground vias in order to mount the gasket. On the right-hand side of the board
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B. Radiated Emission Measurements
Fig. 11.
ADC unit.
TABLE I COMPARISON FOR A SINGLE SCAN
are the second FPGA and the SRAMs. Through a connection to an universal serial bus (USB) controller, the data are transferred to a conventional PC. VI. TEST TIME The test time of a device under test is determined by the measurement speed of the measurement system and the minimum dwell time that is required by the detector mode and the dwell time that is required by the device under test as well as the measurement strategy. A. Single Scan In the following, the measurement time for a single scan in a single-detector mode is compared for the range 30 MHz to 1 GHz. Such single scans are described in the product standards for automotive testing. For example, the signal of each receiving antenna of a car is investigated. The test has to be repeated entirely for each antenna. Due to the unstationary emission of various electric and electronic components in a car, a typical selected dwell time is 2 s. The frequency step is 50 kHz. The result is shown in Table I. A TDEMI system that uses four STFFT blocks allows 2500 discrete spectral values to be processed simultaneously. In order to reduce the hardware resources, a single STFFT block that calculates 625 discrete spectral values, as described in Section IV-B, may be used. In both cases, the measurement time is below 2 min. The same measurement performed with an EMI receiver takes 9 h.
Due to such long measurement, time measurement strategies in the frequency domain are used that are based on a strategy of a prescan with the peak detector mode and final scan [14]. The benefit of such a strategy is the reduced measurement time up to a factor of 100. For angular scan, the reduction of the number of measured frequency bins reduces the measurement time drastically. Such strategies show large benefits under the condition that the dwell time required by the detector mode is higher than the dwell time required by the device under test. This may be the case during the emission measurement of a PC in the quasipeak detector mode. In this case, the prescan may be performed with a dwell time of about 1 ms and the final scan at around 10 frequency bins in the quasi-peak detector mode with a dwell time about 2 s. Typically, with a pre- and final-scan strategy, the emission measurement at the peaks of the spectrum takes about 40 min for a single polarization. For such a measurement, dwell time of about 1 ms is selected. In the time domain, a strategy of an enhanced pre- and final scan yields to a measurement time of about 40 min for a single polarization. The enhanced pre- and final scan uses a prescan at every angular position with a dwell time of 100 ms. The final scan is performed at positions where the maximum emission has been detected. Typically, about 20 positions are investigated in the final detector mode. At each position, a full scan is performed. The scan time including data transfer to an external controlling PC is about 2 s; however, the movement of the turntable takes about 4 s to move to the next position. This yields to a limitation of the measurement speed; however, another benefit is here that a larger dwell time can be selected in comparison to traditional prescans. By this way, the measurement uncertainty can be improved. For unstable emitting devices, e.g., combustion engines, the measurement time for the prescan in the peak detector mode may already take several hours. In this case, a dwell time of several seconds has to be selected. In such cases, the benefit of the ultrafast measurements for a single scan in time domain override the limitation of the measurement speed by the mechanical movements.
VII. MEASUREMENTS In order to evaluate the accuracy of the implemented measurement system, an emission measurement of a Intel Celeron 600-MHz desktop computer has been performed. The desktop computer uses a spread spectrum-controlled clock at 300 MHz to clock the internal CPU. The measurements have been carried out for the frequency range 296–302 MHz with the TDEMI measurement and a conventional EMI receiver ESCS30 from Rohde & Schwarz. The first emission measurement has been performed under the peak detector mode. The result is shown in Fig. 12. The dwell time has been 100 ms, and the frequency step is 30 kHz. The maximum difference between both measurements is 0.8 dB.
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Fig. 12.
Emission of a desktop PC, peak detector mode.
Fig. 14.
Emission of a desktop PC, average detector mode.
Fig. 13.
Emission of a desktop PC, quasi-peak detector mode.
Fig. 15.
Emission of a desktop computer, peak detector.
The measurement was repeated in the quasi-peak detector mode. The frequency step is also 30 kHz and the dwell time has been 2 s. The result is shown in Fig. 13. The maximum deviation is 0.4 dB. An emission measurement has been carried out in average detector mode. The dwell time has been 4 s. The bin width is 30 kHz. The result is shown in Fig. 14. The maximum difference between the measurement performed with the TDEMI
measurement system and the results obtained by the EMI receiver ESCS30 is below 0.2 dB. An emission measurement has been performed in the frequency range 30 MHz to 1 GHz of a PC. The dwell time has been 100 ms. The measurement in the time domain took 11 s. In the frequency domain, the measurement took about 50 min. The result is shown in Fig. 15. It is shown that the maximum deviations are about 1 dB.
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Fig. 18.
Fig. 16.
Emission of an electrical handheld mixer.
Angular characterization of a handheld mixer.
the emission of a Celeron PC with a closed case has been performed. The result is shown in Fig. 17. It is shown that the PC radiates especially at higher frequencies through the slots at the back of the case. This characterization has been taken in about 2 min with the TDEMI measurement system. Such a complete characterization in the final detector mode would take about 36 h. With a pre- and final-scan method, the measurement can be reduced to about 1 h; however, the characterization would only be performed at several frequency bins. A complete angular characterization of the emission of a handheld mixer has been performed. The result is shown in Fig. 18. It is shown that the radiated emission strongly depends an the angular position. VIII. CONCLUSION
Fig. 17.
Angular characterization of a Celeron computer.
An emission measurement has been performed in the frequency range 30 MHz to 1 GHz of an electrical handheld mixer. The frequency step with the TDEMI measurement system has been 30 kHz. The frequency step with the EMI receiver has been 1 MHz. The frequency step of 1 MHz has been used to speed up the measurement in the frequency domain. Otherwise, the measurement time in the frequency domain would have been about 1 h. During this time, the device under test would have changed its radiation characteristic due to thermal warmup. The result of the measurement is shown in Fig. 16. An excellent agreement between both measurements is shown. In the following, further investigation methods that can be performed by a measurement system operating in the timedomain are presented. A complete angular characterization of
A time-domain system for emission measurements of EMI has been developed. By digital signal processing on FPGAs a reliable real-time operating measurement system has been implemented that can be used for full-compliance measurements. The time for a single scan is reduced up to a factor of 2000 in comparison to EMI receivers. Emission measurement in the time domain reduces the test time especially for conducted emission measurements and unstationary emissions, which require dwell times of several seconds. During radiated emission measurements in the time domain for stationary devices during an emission measurement in the time domain, a longer dwell time can be selected to reduce the measurement uncertainty. Due to the extremely short scan times, full characterization of devices can be performed. The emissions of a device depending on running software and operation mode can be investigated in a feasible time. Real-time EMI debugging is becoming by such methods feasible. For the measurement of a conventional PC, the maximum difference between the measurement in the time domain and the measurement performed with an EMI receiver was below 1 dB in the peak detector mode. For the comparison in the
BRAUN et al.: REAL-TIME TDEMI MEASUREMENT SYSTEM
average detector mode, the difference was below 0.2 dB. In the quasi-peak detector mode, the difference has been 0.4 dB. IX. OUTLOOK Optimized measurement procedures for emission measurement in the time domain will have to be implemented and investigated. This will include antenna positioners and turntables that can be driven faster than today’s systems as well as optimized strategies for emission testing. By the additional information that can be captured by emission measurements in the time domain, a further step will be possible toward fully automated EMI testing.
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Stephan Braun (S’03–M’07) was born in ¨ Uberlingen, Germany, in 1978. He received the Dipl.Ing. degree in electrical engineering in 2003 from the Technische Universit¨at M¨nchen (TUM), Munich, Germany, where he is currently working toward the Dr.-Ing. degree at the Institute of High-Frequency Engineering. His current research interests include highfrequency circuit design, digital signal processing, digital circuits, and electromagnetic compatibility in the time domain. He is the author or coauthor of more than 30 papers and several patents. Mr. Braun is a Member of the German Verband der Elektrotechnik und Informationstechnik (VDE) and VDE/VDI-Gesellschaft Mikroelektronik, Mikro- und Feinwerktechnik (GMM). He was the recipient of the 2006 Best Student Paper Prize at the 17th International Zurich Symposium in Singapore and the 2007 E.ON Future Award for his Ph.D. (Dr.-Ing.) thesis.
ACKNOWLEDGMENT The authors would like to thank S. Iliev who designed the ADC board. They also thank R. Schneider for the implementation of the digital detectors on the FPGAs, Dr. G. Olbrich and T. Hermann for the support in developing the low-phase noisephase looked loop synthesizer that is used to clock the ADCs, and M. Agerer and J. Franzisi for the fabrication of various mechanical parts for the measurement system.
Thomas Donauer was born in Kelheim, Germany, in 1980. He received the Bachelor’s and Dipl.Ing. degrees in electrical engineering, in 2005 and 2006, respectively, from the Technische Universit¨at M¨unchen, Munich, Germany, where he is currently working toward the MBA degree. His current research interests include electronic systems and field-programmable gate array based signal processing.
REFERENCES [1] CISPR16-1-1, Specification for Radio Disturbance and Immunity Measuring Apparatus and Methods Part 1-1: Radio Disturbance and Immunity Measuring Apparatus—Measuring Apparatus. Switzerland: Int. Electrotech. Commiss., 2003. [2] Rohde & Schwarz, Ultra Broadband Antenna HL562 ULTRALOG, Data sheet, 2001. [3] S. Braun and P. Russer, “A low-noise multiresolution high-dynamic ultrabroad-band time-domain EMI measurement system,” IEEE Trans. Microw. Theory Techn., vol. 53, no. 11, pp. 3354–3363, Nov. 2005. [4] F. Krug, T. Hermann, and P. Russer, “Signal processing strategies with the TDEMI measurement system,” in Proc. 2003 IEEE Instrum. Meas. Technol. Conf., Vail, CO, May 20–22, pp. 832–837. [5] C. Keller and K. Feser, “Fast emission measurement in time domain,” presented at the 14th Int. Zurich Symp. Electromagn. Compat., Zurich, Switzerland, Feb. 20–22, 2001, Paper no. 70K7. [6] S. Braun, F. Krug, and P. Russer, “A novel automatic digital quasi-peak detector for a time domain measurement system,” in Proc. 2004 IEEE Int. Symp. Electromagn. Compat. Digest, Santa Clara, CA, Aug. 9–14, vol. 3, pp. 919–924. [7] S. Braun, M. Aidam, and P. Russer, “Development of a multiresolution time-domain EMI measurement system that fulfils CISPR 16-1,” in Proc. 2005 IEEE Int. Symp. Electromagn. Compat., Chicago, IL, pp. 388–393. [8] S. Braun, M. Al-Qedra, and P. Russer, “A novel realtime time-domain emi measurement system based on field programmable gate arrays,” in Proc. 17th Int. Zurich Symp. Electromagn. Compat., Digest, Singapore, Feb. 2006, pp. 501–504. [9] A. V. Oppenheim and R. W. Schafer, Discrete—Time Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1999. [10] D. Ristau and D. Hansen, “Modulation impact on quasi-peak detector response,” in Proc. IEEE Int. Symp. Electromagn. Compat., Austin, TX, Aug. 1997, pp. 90–95. [11] S. Braun and P. Russer, “The dynamic range of a time-domain EMI measurement system using several parallel analog to digital converters,” presented at the 16th Int. Zurich Symp. Electromagn. Compat., Z¨urich, Switzerland, Feb. 13–18, 2005. [12] S. Braun and P. Russer, “Measurements of spurious emission with a timedomain EMI measurement system using multi-sampling techniques,” in Proc. IEEE EMC Symp. 2006, Portland, Oregon, Aug., vol. 3, pp. 792–795. [13] Z. J. Mou, “Symmetry exploitation in digital interpolators/decimators,” in IEEE Trans. Signal Process., vol. 44, no. 10, pp. 2611–2615, Oct. 1996. [14] M. Stecher, “Automated measurement of emissions from equipment and systems,” in Proc. 2002 IEEE Int. Symp. Electromagn. Compat. Digest, Minneapolis, MN, Aug. 19–23, 2002, pp. 593–598.
Peter Russer (SM’81–F’94) received the Dipl.Ing. and Dr. Tech. degrees in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 1967 and 1971, respectively. During 1968–1971, he was an Assistant Professor at the Vienna University of Technology, where he was engaged in research on ac Josephson effect. During 1971, he was with the Research Institute, General Electricity Company (AEG)–Telefunken, Ulm, Germany, where he was involved in research on fiber optic communication, broadband solid-state electronic circuits, statistical noise analysis of microwave circuits, laser modulation, and fiber optic gyroscopes. During 1990, he was a Visiting Professor at the University of Ottawa, Ottawa, ON, Canada. During 1993, he was a Visiting Professor at the University of Victoria, Victoria, BC, Canada. From 1992 to 1995, he was the Director of the Ferdinand-Braun-Institut f¨ur H¨ochstfrequenztechnik, Berlin, Germany. From 1999 to 2002, he was the Co-Chair, and from 2002 to 2005, he was the Chair of the Union Radio Scientifique Internationale (URSI) Commission D. Since 1981, he has been with the Technische Universit¨at M¨unchen (TUM), Munich, Germany, earlier as a Professor of the Institute for HighFrequency Engineering, where he is currently the Head, and later, as the Dean of the Department of Electrical Engineering and Information Technology. He is also the Program Director of the International Graduate Program “Master of Science in Microwave Engineering” at the TUM. He is the author or coauthor of more than 590 papers published in refereed journals and conference proceedings. His current research interests include electromagnetic fields, numerical electromagnetics, metamaterials, integrated microwave and millimeter-wave circuits, statistical noise analysis of microwave circuits, time-domain measurement methods in electromagnetic compatibility, and methods for computer-aided design of microwave circuits. Prof. Russer has been a member of the Board of Directors of the European Microwave Association. During 1999, he was the General Chairman of the European Microwave Week held in Munich. He was a member of technical program committees and steering committees of several international conferences (IEEE Microwave Theory and Techniques Society (MTT-S), European Microwave Conference), and on the editorial board of several international journals (Electromagnetics, International Journal of Numerical Modeling). He was the recipient of the 1979 National Technology Group Award for the publication “Electronic Circuits for High Bit Rate Digital Fiber Optic Communication Systems” and the Distinguished Educator Award of the IEEE MTT Society in 2006. He is a member of the German Informationstechnische Gesellschaft (ITG) and the German as well as the Austrian Physical Societies.