Quasi-peak detector model for a time-domain measurement system

320

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 47, NO. 2, MAY 2005

Quasi-Peak Detector Model for a Time-Domain Measurement System Florian Krug, Member, IEEE, and Peter Russer, Fellow, IEEE

Abstract—In this paper, a quasi-peak detector mode for a time-domain electromagnetic interference (TDEMI) measurement system is described. Measurements were performed in the 30–1000-MHz range. The digital signal processing of EMI measurements can emulate in real time the modes of conventional analog equipment, e.g., peak, average, rms, and quasi-peak detector. With the presented time-domain measurement system, the measurement time can be reduced by a factor of ten. A novel signal recording routine for TDEMI measurements and quasi-peak detection is described. Measurement results obtained from the investigation of a drill machine, monitor, and laptop obtained with the TDEMI measurement system are discussed. The comparison of the results obtained with the described TDEMI measurement system and measurements performed with a conventional EMI receiver show an average deviation over the whole frequency range less than 3 dB. Index Terms—Digital signal processing, electromagnetic interference (EMI), fast Fourier transform (FFT), measurement, spectral analysis, time-domain measurements.

I. INTRODUCTION UE TO THE rapid development of new electronic products and due to emerging new technologies the ability to achieve and to improve electromagnetic compatibility is a major challenge in development of electronic products. Electromagnetic compatibility (EMC) and electromagnetic interference (EMI) measurement equipment which can extract comprehensive and accurate information within short measurement times will reduce the costs and improve the quality in circuit and system development. Generally, radio noise and EMI are measured and characterized by super heterodyne radio receivers. The disadvantage of this method is the quite long measurement time of typically 30 min for a frequency band from 30 MHz to 1 GHz [1]. Since such a long measurement time results in high test-costs, it is important to reduce the measurement time without loss of quality. With digital processing of time-domain EMI (TDEMI) measurements using the Fourier transform make the decomposition of a signal into its spectral components possible. In general, the digital processing of EMI measurements can emulate in real time the various modes of conventional analogous equipment and it is also possible to introduce new concepts of analysis [2].

D

Manuscript received April 16, 2003; revised October 6, 2004. This work was supported in part by Deutsche Forschungsgemeinschaft, in part by Rohde & Schwarz GmbH & Co. KG, and in part by Albatross Projects GmbH. F. Krug is with GE Global Research, Gachring 85748, Germany (e-mail: [email protected]). P. Russer is with the Institute for High-Frequency Engineering, Technical University Munich, Munich 80333, Germany (e-mail: [email protected]). Digital Object Identifier 10.1109/TEMC.2005.847410

TABLE I CHARACTER OF THE DISTURBANCE

In this paper, an advanced signal recording routine for TDEMI measurements is described. Further, the implementation and evaluation of a quasi-peak detector in time-domain is shown. The measurement routine use intelligent triggering to record the TDEMI signal. This makes it possible to reduce data enormously. A method to reconstruct an equivalent of the original signal is described. So an accurate time-domain emission measurement with rms, average, and quasi-peak detection on all signal types is possible. II. CLASSIFICATION OF INTERFERENCES The EMI originating from the equipment under test (EUT) depends on frequency, time and geometry of the test setup (position, distance and direction). The interferences may be classified on the basis of the receiver and interference bandwidth [3], [4] as shown in Table I. Furthermore, EMI signals may be classified on the basis of their statistical behavior as random or deterministic signals. The random signals can be further subdivided in stationary and nonstationary signals [5]. The statistical properties of nonstationary random signals may change considerably over the observation time. The deterministic signals may be periodic, quasi-periodic, nonperiodic, or a combination of these signal types. Periodic and quasi-periodic signals exhibit line spectra. Transients are nonperiodic signals. Nonperiodic signals exhibit continuous spectra. Finally, signals can be combinations of two or more of the above classes. III. ADVANCED TDEMI MEASUREMENT CONCEPT In Fig. 1, the advanced TDEMI measurement concept is shown. The TDEMI measurement system consists of broad-band antenna or line impedance stabilization network (LISN), amplifier, low-pass filter, analog-to-digital converter (ADC) (e.g., oscilloscope), and a PC. The antialiasing filter limits the signal bandwidth according to the requirements of the sampling process. The oscilloscope exhibits an analog bandwidth of 1.5 GHz. The sampled EMI data are transferred from the ADC via the GPIB bus to the personal computer. A detailed hardware description of the TDEMI measurement system has

0018-9375/$20.00 © 2005 IEEE

KRUG AND RUSSER: QUASI-PEAK DETECTOR MODEL FOR A TIME-DOMAIN MEASUREMENT SYSTEM

321

Fig. 1. Advanced TDEMI measurement concept.

Fig. 2.

Principle of fast frame mode.

already been presented in [6]. The data acquisition process for the time-domain measurement starts with the sample process of the oscilloscope. Then the spectra via the short-time Fourier transform (STFT) are digitally computed. After the STFT, the errors due to the frequency characteristics of antenna, transmission line, amplifier, and antialiasing filter are corrected by signal processing. After this, the analysis of peak, rms, average, and quasi-peak values of the EMI signal is performed. IV. AUTOMATED TDEMI MEASUREMENT ALGORITHM The automated TDEMI measurement algorithm consists of a trigger time measurement of the transient signal, the ordinary measurement of the signal, and a merger of both to a signal representation. When measuring signals with transient envelope, the pulses can record separately. The pulses can be sampled with different amplitudes with an optimum vertical resolution of the ADC. In case the signal shows no pulsar envelope, or if the delay between the pulses are shorter than the fast frame mode is able to follow updating trigger times (e.g., the limit of the Tektronix TDS 7154 oscilloscope is 6 s), doing statistical analysis brings no merit. For such a class A signal, a continuous measurement mode is needed. A detailed measurement description of class A signals have already been presented in [7]. First the measurement routine with one vertical resolution is described. A. Trigger Time Measurement For an accurate time-domain measurement, the oscilloscope needs to offer a fast frame mode. In this mode, the oscilloscope captures the absolute time between the trigger events that occur in sequence. In the case that the oscilloscope triggers on pulses, the times between the pulses can be calculated. The principle of the fast frame mode is shown in Fig. 2.

Fig. 3. Discrete probability density estimation for the emission of a drill machine.

A measurement of a certain amount of trigger times, a calculation of the reliable statistics about which times between pulses occur mostly. Fig. 3 shows an example for a discrete probability density estimate calculated over times between pulses radiated by a hand-held drill machine. The time that correlate to the local maximum value of the graph will be used for signal reconstruction. They are randomly but according to their relative frequency of occurrence distributed on the timescale. An example for a reconstructed timescale is shown in Fig. 4. B. Signal Measurement The sampling rate must meet the Nyquist requirements. Recording occurs in a manner of several single-shot measurements. Time per division on the oscilloscope must be set that single pulses fit in single records. The recorded pulse is used for signal reconstruction only if it meets the following requirements. First, the pulse does not clip; and second, it is unique, which means the amplitude spectrum of the pulse is in comparison to already saved pulses. In the algorithm, the signal energy ratio of the actual measured pulse and already saved pulses can be defined and so the user has the possibility to influence the accuracy of the time-domain measurement. This detection criteria leads to an enormous data reduction. If the pulse has a similar amplitude spectrum as an already saved pulse but the pulse sequence is not strictly periodical, then the disregarding of pulses will change the spectral composition of the composed

322

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 47, NO. 2, MAY 2005

Fig. 4.

Reconstructed timescale from the probability density estimation.

Fig. 5.

Pulse distribution on the reconstructed timescale.

signal. This important effect leads to the next step of the advanced TDEMI measurement concept. From the record of a high amount of pulses, a reliable estimation is calculated. The estimation gives information in what relation the frequency of occurrence of the pulses stand to each other. Weighed with that estimation, the pulses are randomly distributed on the marks of the timescale as shown in Fig. 4. The result of the pulses distribution on the reconstructed timescale is shown in Fig. 5. With the measured pulse distribution used for the signal reconstruction process and the following spectral estimation all effects of disregarding for strictly repetitive, semirepetitive, and nonrepetitive pulses is taken into account. As the signal contains pulses of varying amplitudes, the routine which is described above needs to be done for different oscilloscope vertical resolutions. The oscilloscope trigger-level must be adapted to each vertical oscilloscope setting (e.g., fix trigger level on the oscilloscope screen). This ensures improvement of the measurement dynamic range. For each vertical oscilloscope result, one timescale will be saved. The last step is to merge these timescales together to one signal representation. C. Merger to One Signal Representation That procedure of merge to one signal representation is shown for the example of two timescales in Fig. 6. In the fast frame mode, the oscilloscope also triggers on pulses that clip. That means the times between trigger events measured consider the clipping pulses. So randomly distributed pulses of the measurement at lower oscilloscope resolution replace the timescale of the measurement with higher resolution. This needs to be done at places where they overlap. In case there exist measurements for further oscilloscope vertical settings, the procedure described above would be done iteratively. V. SPECTRAL ESTIMATION TECHNIQUE Spectral estimation is done with use of the discrete Fourier transform (DFT). The window function is equivalent to the bandwidth of the intermediate-frequency filter (IF filter) of the conventional EMI receiver. The window function needs

to be adapted to the IF filter regarding impulse bandwidth and equivalent noise bandwidth. Appropriately, the IF filter is modeled with a Gaussian window. In order to receive the filter response in form of a time-dependent amplitude spectrum, a DFT calculation using record samples less than the length of the time record is necessary. The process of iteratively shifting the window along the time record followed by computing a DFT is the STFT [7]. The window shift is done with an appropriate increment. The of the calculated amplitude time-domain resolution corspectra is important for an accurate filter response. responds with the increment used in the STFT as follows [8]: (1) is the base-band sampling frequency. The signal representation in Fig. 6 and time response for each pulse calculated via STFT is given to the model of the average, peak, rms, and quasi-peak detector. VI. DETECTOR MODEL A. Analog Quasi-Peak Detector In Fig. 7, the circuit of an analog quasi-peak detector is of the conventional EMI shown. The demodulated signal as long as receiver charges the capacitor by the resistor is above . This is a typical RC charging with the time is lower than , the constant . If the input signal is discharged by resistor . A critically damped voltage is used to display the amplimeter with the time constant tude. The maximum of the shown value is taken as quasi-peak value. In Table II, the CISPR 16-1 [9] values of time constants and IF bandwidths are shown. For proper quasi-peak detection, the input signal must be provided up to 2 s, to have a ready steady state. Conventional quasi-peak detectors can evaluate the measured EMI signal for a single frequency within 2 s. For about 15 000 frequency points, in a normal CISPR Band C/D measurement about 9 h measurement time is necessary.

KRUG AND RUSSER: QUASI-PEAK DETECTOR MODEL FOR A TIME-DOMAIN MEASUREMENT SYSTEM

323

Fig. 6. Example of a signal reconstruction.

the signal flow of a IIR1 filter. For calculating the filter coefficients, the following transfer function is used: (2) Fig. 7.

Analog quasi-peak detector. TABLE II CHARACTER OF THE DISTURBANCE

Also, the bilinear transformation for characterizing the RC system is used. The bilinear transformation is defined as follows: (3) is the frequency-domain variable, is the discrete time-domain variable, and is the time-domain discretization. In order to get better numeric precision, not the normal topology of an IIR2 system, but a cascading of two identical IIR1 filters for modeling the critically damped meter, were used. The maximum of the output signal is taken as quasi-peak value. A comparator decides charging and discharging, while in discharging mode the coefficient is set to zero. The model of the digital quasi-peak detector was written for a conventional Intel Pentium III 1-GHz processor. Therefore, the simulation time of a single quasi-peak value at a single frequency is about 0.04 s. With today’s processors, a quasi-parallel computation of the quasi-peak values is possible. C. Signal Representation for Quasi-Peak Detection

Fig. 8.

Signal flow of an IIR1 filter.

B. Digital Quasi-Peak Detector Model With a digital quasi-peak detector mode for a TDEMI system the measurement time can be reduced at least one order of magis provided by intelligent recording technique and nitude. a spectral estimation via STFT. For modeling the charging and discharging process digital IIR1 filters are used. Fig. 8 shows

A main problem is providing a suitable signal for the quasipeak detector. By recording up to 2 s (requirement of CISPR 16-1 [9]) with a TDEMI system with 5-GS/s sample rate (e.g., Tektronix TDS 7154), to reach a necessary signal-to-noise ratio of 50 dB, at least 10-GB RAM is necessary. Therefore, the signal is reconstructed from representative time-domain signal parts and their corresponding time stamps. The reconstruction is done after the STFT and the demodulation. A time-domain

324

Fig. 9.

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 47, NO. 2, MAY 2005

CISPR 16-1 and TDEMI system pulse response curve.

signal is created for 2 s and is estimated by the quasi-peak detector. The sampling frequency of the time-domain signal must be chosen properly to minimize the error between the digital and the analog implementation. For Band C/D [9], about 500 kHz is sufficient. The reconstruction is equivalent to reconstructing the signal in the time domain and applying the STFT and quasi-peak detection, as long as the pulse response of the IF filter does not overlap. Selecting the appropriate mode of the intelligent recording algorithm minimizes the error.

Fig. 10. Drill machine: comparison between TDEMI system and conventional EMI receiver.

VII. MEASUREMENT RESULTS A. Simulation CISPR 16-1 Pulse For approving the quasi-peak detection in the time domain, the CISPR 16-1 pulse response curves simulated at a single frequency is shown in Fig. 9 [9]. The CISPR 16-1 curve and the TDEMI system pulse response curve show an agreement for all pulse repetition frequencies. B. Emission Measurement The emission measurement is done in an anechoic chamber, with a distance between antenna and EUT of 5 m and a fully maximized E field (turntable, polarization, and antenna height). Fig. 10 shows the result of a measurement with the TDEMI system on a drill machine in band C/D for quasi-peak detection. Pulses of the drill machine vary greatly in amplitude and spectrum. The automated TDEMI measurement algorithm for class C signals was used. Fig. 11 shows the result of a measurement with the TDEMI system on a Pentium 200-MHz laptop in band C/D. The average deviation over the whole frequency ranges less than 3 dB. A laptop emits pulses with a high, not regular repetition frequency. The automated TDEMI measurement algorithm for class A signals was used. In Fig. 12, a measurement with the TDEMI system of an SVGA monitor in band C is shown. A good match of the emission measured with the conventional EMI receiver and the TDEMI system is shown. Even the low spectral lines of the monitor power supply show a maximum difference less than 1.5 dB. The monitor emits pulses with a high but constant

Fig. 11. Laptop: comparison between TDEMI system and conventional EMI receiver.

repetition frequency. The automated TDEMI measurement algorithm for class A signals was used. Precompliance measurement results obtained with the TDEMI system are already published in [11]. VIII. PERFORMANCE OF THE TDEMI SYSTEM A. The TDEMI System Is a Full-Compliance System With a Precompliance Measurement Time Performance There are many time-optimized precompliance strategies that are used to obtain an idea on the performance of the EUT and to derive a reduced list of frequencies at which a full quasi-peak detection measurement and additional shielding optimization needs to be done [12]. Often peak detection and peak-hold mode is applied while turning the turntable and moving the antenna. This frequency list reduction works well on narrow-band signals. For broad-band signals, it either leads a large set of frequencies of further decisions on which frequency to quasi-peak and to maximize within the broad-band range need to be taken. Here, additional risks are taken, as the peak detection might mask a narrow-band signal underneath a

KRUG AND RUSSER: QUASI-PEAK DETECTOR MODEL FOR A TIME-DOMAIN MEASUREMENT SYSTEM

Fig. 12.

325

SVGA monitor: comparison between TDEMI system and conventional EMI receiver.

broad-band signal, while a quasi-peak detection would reduce the level of the broad-band signal, but not reduce the level of the narrow-band signal. Many test houses use a spectrum analyzer in peak-hold mode at, e.g., 1-MHz resolution bandwidth and spin the turntable, change the antenna height in a few coarse steps, and measure in both antenna polarizations to obtain a quick idea on the emissions. The used peak-hold mode delivers an overestimated emission spectrum. The TDEMI measurement system does not have the disadvantages of the time-optimized precompliance strategies described above. The TDEMI system measures the emission information of the EUT at all frequencies in parallel with the well-known principle of time-domain measurement and a spectral estimation with the fast Fourier transform (FFT), so from the principle no signal information is lost. The TDEMI system is a full-compliance system with a precompliance measurement time performance, so it can be used for precompliance measurements to obtain an idea on the emission performance of the EUT. On the other hand, the use of the TDEMI system for full-compliance measurements give also a lot of advantages in comparison to conventional EMI receivers. While using the quasi-peak detector for full-compliance measurements, an E-field maximization caused by the turntable, the antenna height, the polarization, and possibly the cable routing needs to be done. The mechanical movement, not by the measurement time, might determine the test time. In this case, the time-domain method is able to keep track of the quasi-peaked values at multiple frequencies in parallel while mechanical changes are done. In addition, relative to the peak-holding prescan, fewer frequencies would need to be fully quasi-peaked, as the peak-hold method often overestimated the emissions, relative to the measurement with the quasi-peak detector. B. Measurement Time Comparison to a Conventional Full-Compliance Measurement Systems in Quasi-Peak Detection Mode The faster measurement time is one of the main advantages of a time-domain measurement system. In Table III, the contributions to the measurement time are listed for the TDEMI system and for the conventional EMI receiver. According to the CISPR 16 standards [9], [13] the EMI receiver operates in the

TABLE III MEASUREMENT AND PROCESSING TIME

quasi-peak detection mode and has a dwell time of 2 s/step. The measured frequency range is 30 MHz up to 1000 MHz. For the measurement with the conventional EMI receiver, no time-reduced strategy is used, because for a full-compliance measurement time-optimized operation modes are not allowed. C. A/D Conversion Artifacts Many oscilloscopes uses a set of A/D converts in parallel. This arrangement often leads to artifacts at the A/D converter frequencies (and other frequencies) due to misalignment between the A/D converters. Such frequencies will show up in the amplitude spectrum after the FFT. Before starting an EMI measurement with the TDEMI system, a reference measurement is necessary. For this the input of the oscilloscope is connected to ground and with the measured signal the amplitude spectrum is calculated. All significant frequencies caused by the A/D conversion artifacts are used for a later amplitude comparison of the emission spectrum at these frequencies. If the measured emission amplitude value is equal to the amplitude of the conversion artifact than the frequency is deleted and substituted by an arithmetic average value of the neighborhood frequencies. On the other hand, if the measured emission amplitude value is higher or lower than the amplitude of the conversion artifact than a correct emission measurement is given. D. Clipping of A/D Converters The automated TDEMI measurement algorithm allows the A/D converter and the amplifier to go into saturation. Later the algorithm removes the saturated measurements. The finite recovery time involved in the amplifier and the A/D converter after clipping is not relevant for the EMI measurement because the recording time up to 2 s (requirement of CISPR 16-1 [9]) for

326

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 47, NO. 2, MAY 2005

quasi-peak detection is much longer than the minimum trigger time of the oscilloscope (e.g., Tektronix TDS 7154, 6 s). E. Measurement Limits of Time-Domain Methods The dynamic range of the TDEMI measurement system depends on the dynamic range of the used ADC. Because the dynamic range of the system is improved by the intelligent recording method that changes the volts per division (V/div) of the A/D conversion, the recording specification of the ADC is also important. Characteristic examples for the limits of the TDEMI measurement system: if a narrow-band pulse, e.g., from a comp-generator-like noise source having a repetition rate in the millisecond range the recording might never be able to reduce the V/div a lot due to saturation. The antenna factor will vary across the spectrum by as much as 20 dB. This will bite into the dynamic range at lower frequencies. IX. CONCLUSION The presented broad-band TDEMI measurement system can emulate in real time the various modes of conventional detector modes. With the presented time-domain measurement system, the measurement time can be reduced by a factor of ten. A novel signal recording routine for TDEMI measurements and quasipeak detection is described. Measurement results obtained from the investigation of a drill machine, monitor, and laptop obtained with the TDEMI measurement system are discussed. The results obtained with the described system have been compared with measurements performed with a conventional EMI receiver. ACKNOWLEDGMENT The authors would like to thank the Deutsche Forschungsgemeinschaft, Rohde & Schwarz GmbH & Co. KG, and the Albatross Projects GmbH. REFERENCES [1] C. Keller and K. Feser, “A new method of emission measurement,” in Proc. 2002 IEEE Int. Symp. Electromagnetic Compatibility Dig., pp. 599–604. [2] F. Krug and P. Russer, “The time-domain electromagnetic interference measurement system,” IEEE Trans. Electromagn. Compat., vol. 45, no. 2, pp. 330–338, May 2003. [3] W. P. Kodali, “Engineering electromagnetic compatibility,” in Principles, Measurements, Technologies, and Computer Models. New York: Wiley, 2001. [4] D. Middleton, “Statistical-physical models of electromagnetic interference,” IEEE Trans. Electromagn. Compat., vol. 19, no. 3, pp. 106–127, Aug. 1977. [5] W. B. Davenport and W. L. Root, An Introduction to the Theory of Random Signals and Noise. New York: Wiley, 1987. [6] F. Krug and P. Russer, “Ultra-fast broad-band EMI measurement in time domain using classical spectral estimation,” in Proc. 2002 IEEE MTT-S Int. Microwave Symp. Dig., pp. 2237–2240. [7] F. Krug and P. Russer, “Ultra-fast broad-band EMI time-domain measurement system,” in Proc. 2002 Int. Symp. Electromagnetic Compatibility Dig., pp. 379–384. [8] L. Cohen, “Time-frequency distributions—A review,” Proc. IEEE, vol. 77, no. 7, pp. 941–981, Jul. 1989.

[9] Specification for Radio Disturbance and Immunity Measuring Apparatus and Methods Part 1: Radio Disturbance and Immunity Measuring Apparatus, AS/NZS CISPR16-1, 1999. [10] D. Ristau and D. Hansen, “Modulation impact on quasi-peak detector response,” in Proc. 1997 IEEE Int. Symp. Electromagnetic Compatibility Dig., pp. 90–95. [11] F. Krug, T. Hermann, D. Mueller, J. Waldmann, M. Aidam, and P. Russer, “Strategies for precompliance measurements using the TDEMI measurement system,” in Proc. 2003 IEEE Int. Symp. Electromagnetic Compatibility Dig., pp. 511–516. [12] K.-O. Mueller, “Speeding up quasi-peak weighting EMI tests,” in Proc. 1991 IEEE Int. Symp. Electromagnetic Compatibility Dig., pp. 169–172. [13] Specification for Radio Disturbance and Immunity Measuring Apparatus and Methods Part 2: Methods of Measurement of Disturbances and Immunity, AS/NZS CISPR16-2, 1999.

Florian Krug (M’03) received the Dipl.-Ing. and Dr.-Ing. degrees in electrical engineering and information technology from the Technical University Munich, Munich, Germany, in 2001 and 2003, respectively. Since 2003, he has been working in the General Electric Global Research Center Europe, Munich. He is author of more than 40 scientific papers and holds two patents. His current research is focused on the analysis of electromagnetic compatibility problems using modern spectral estimation methods, lightning strike protection strategies for alternative energy systems, and sensor technologies for automotive applications. Dr. Krug is a Member of the Association of German Electrotechnical Engineers (VDE). He received the Best Student Paper Award from the IEEE Electromagnetic Compatibility Society in 2002.

Peter Russer (SM’81–F’94) received the Dipl.-Ing. and Dr.Tech. degrees in electrical engineering from the Technical University Vienna, Vienna, Austria, in 1967 and 1971, respectively. He was Assistant Professor at the Technical University Vienna from 1968 to 1971. In 1971, he joined the Research Institute of AEG-Telefunken, Ulm, Germany, where he worked on fiber-optic communication, broad-band solid-state electronic circuits, statistical noise analysis of microwave circuits, laser modulation, and fiber-optic gyroscopes. Since 1981, he has been Professor and Head of the Institute of High Frequency Engineering at the Technical University Munich, Munich, Germany. In 1990, he was Visiting Professor at the University of Ottawa, and in 1993, he was Visiting Professor at the University of Victoria. From 1992 to 1995, he was director of the Ferdinand Braun Institute for High Frequencies, Berlin, Germany. He has served as a Member of the Editorial Board of several international journals (Electromagnetics, International Journal of Numerical Modeling). His current research interests are electromagnetic fields, integrated microwave and millimeter-wave circuits, statistical noise analysis of microwave circuits, and methods for computer-aided design of microwave circuits. He is author of more than 300 scientific papers in these areas. Dr. Russer is a Member of the German Informationstechnische Gesellschaft (ITG), the German Physical Society, and the Austrian Physical Society. In 1979 he was corecipient of the NTG Award for the publication “Electronic circuits for high bit rate digital fiber optic communication systems.” He is Cochairman of the International Union of Radio Science (URSI) Commission D. He has served as a Member of the technical program committees and steering committees of various international conferences (IEEE Microwave Theory and Techniques Society (MTT-S), European Microwave Conference).