A Novel Method of Ambient Interferences Suppressing for In Situ Electromagnetic Radiated Emission Test

A measurement method for adaptive interference suppression in in situ radiated emission test is proposed. First, the method obtained multichannel data to achieve the signal directions of arrival from equipment under test (EUT) and interference sources by the spatial spectrum estimation technique based on the multiple signal classification algorithm. Second, broadband minimum variance distortionless response (MVDR) beamforming algorithm combined with short time Fourier transform (STFT) was taken to form the beam pattern null traps in the directions of interferences, thus realizing the suppression on interferences. The factors affecting the accuracy of spatial spectrum estimation and the angular resolution of beamforming were discussed, and the suppression effects on different kinds of interferences were simulated. The simulation results show that the method can suppress multiple interferences, which are either narrowband or broadband, continuous or transient, and avoid little distortion to the time-frequency characteristics of EUT signal simultaneously. The method performance was evaluated by experiments. The results show that sine wave and pulse modulation interferences can both be suppressed remarkably, which proves the effectiveness and advantage of this new method for electromagnetic compatibility in situ test.

[1]  R. Schmidt,et al.  Multiple source DF signal processing: An experimental system , 1986 .

[2]  J. Capon.  High-resolution frequency-wavenumber spectrum analysis , 1969 .

[3]  Frederick E. Petry,et al.  Principles and Applications , 1997 .

[4]  Peter Russer,et al.  Time-domain EMI measurements in the presence of ambient noise , 2009, 2009 IEEE International Symposium on Electromagnetic Compatibility.

[5]  T. Kailath,et al.  Estimation of Signal Parameters via Rotational Invariance Techniques - ESPRIT , 1986, MILCOM 1986 - IEEE Military Communications Conference: Communications-Computers: Teamed for the 90's.

[6]  M. Marino,et al.  EMI ambient cancellation and source localization technology , 1999, 1999 International Symposium on Electromagnetic Compatibility (IEEE Cat. No.99EX147).

[7]  J. A. Cadzow.  Multiple source location: The signal subspace approach , 1989, Twenty-Third Asilomar Conference on Signals, Systems and Computers, 1989..

[8]  Thomas Kailath,et al.  On spatial smoothing for direction-of-arrival estimation of coherent signals , 1985, IEEE Trans. Acoust. Speech Signal Process..

[9]  김형순,et al.  새로운 적응잡음제거구조 ( A New Adaptive Noise Cancellation Scheme ) , 1993 .

[10]  B. G. Agee,et al.  Cyclic MUSIC algorithms for signal-selective direction estimation , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[11]  M. Marino,et al.  Innovative pre-compliance test methodology using ambient cancellation and coherence detection techniques , 1999, 1999 IEEE International Symposium on Electromagnetic Compatability. Symposium Record (Cat. No.99CH36261).

[12]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[13]  Jacob Benesty,et al.  A Study of the LCMV and MVDR Noise Reduction Filters , 2010, IEEE Transactions on Signal Processing.

[14]  Jacek Dmochowski,et al.  Decoupled Beamforming and Noise Cancellation , 2007, IEEE Transactions on Instrumentation and Measurement.

[15]  P. Russer,et al.  A Real-Time Time-Domain EMI Measurement System for Full-Compliance Measurements According to CISPR 16-1-1 , 2008, IEEE Transactions on Electromagnetic Compatibility.

[16]  J. Svacina,et al.  Virtual Anechoic Room An Useful Tool for EMI Pre-Compliance Testing , 2007, 2007 17th International Conference Radioelektronika.

[17]  O. L. Frost,et al.  An algorithm for linearly constrained adaptive array processing , 1972 .

[18]  P. Russer,et al.  Signal processing for wideband smart antenna array applications , 2004, IEEE Microwave Magazine.

[19]  Dennis Gabor,et al.  Theory of communication , 1946 .

[20]  K. Abend,et al.  Interference suppression via orthogonal projections: a performance analysis , 1993 .

[21]  T. Kailath,et al.  Estimation Of Signal Parameters Via Rotational Invariance Techniques- Esprit , 1986, Nineteeth Asilomar Conference on Circuits, Systems and Computers, 1985..

[22]  B.D. Van Veen,et al.  Beamforming: a versatile approach to spatial filtering , 1988, IEEE ASSP Magazine.

[23]  Arthur Jay Barabell,et al.  Improving the resolution performance of eigenstructure-based direction-finding algorithms , 1983, ICASSP.

[24]  R.T. Compton,et al.  A numerical pattern synthesis algorithm for arrays , 1990, International Symposium on Antennas and Propagation Society, Merging Technologies for the 90's.

[25]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[26]  P. Russer,et al.  Ambient noise cancelation with a time-domain EMI measurement system using adaptive filtering , 2008, 2008 Asia-Pacific Symposium on Electromagnetic Compatibility and 19th International Zurich Symposium on Electromagnetic Compatibility.

[27]  Lloyd J. Griffiths,et al.  A projection approach for robust adaptive beamforming , 1994, IEEE Trans. Signal Process..