A robust signal subspace estimator

An original estimator of the orthogonal projector onto the signal subspace is proposed. This estimator is derived as the maximum likelihood estimator for a model of sources plus orthogonal outliers, both with varying power (modeled by Compound Gaussians process), embedded in a white Gaussian noise. Validity and interest - in terms of performance and robustness - of this estimator is illustrated through simulation results on a low rank STAP filtering application.

[1]  H. Vincent Poor,et al.  Complex Elliptically Symmetric Distributions: Survey, New Results and Applications , 2012, IEEE Transactions on Signal Processing.

[2]  Philippe Forster,et al.  Clutter Subspace Estimation in Low Rank Heterogeneous Noise Context , 2015, IEEE Transactions on Signal Processing.

[3]  A. Swindlehurst,et al.  Subspace-based signal analysis using singular value decomposition , 1993, Proc. IEEE.

[4]  R. S. Raghavan.  Statistical Interpretation of a Data Adaptive Clutter Subspace Estimation Algorithm , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[5]  James Ward,et al.  Space-time adaptive processing for airborne radar , 1994, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[6]  Stéphanie Bidon,et al.  Adaptive Processing With Signal Contaminated Training Samples , 2013, IEEE Transactions on Signal Processing.

[7]  Muralidhar Rangaswamy,et al.  Robust adaptive signal processing methods for heterogeneous radar clutter scenarios , 2004, Signal Process..

[8]  D. Tufts,et al.  Adaptive detection using low rank approximation to a data matrix , 1994 .

[9]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[10]  Philippe Forster,et al.  Maximum likelihood estimation of clutter subspace in non homogeneous noise context , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

[11]  Peter Bajorski,et al.  Wiley Series in Probability and Statistics , 2010 .

[12]  Jean-Yves Tourneret,et al.  Minimum Mean Square Distance Estimation of a Subspace , 2011, IEEE Transactions on Signal Processing.

[13]  Andrzej Cichocki,et al.  Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications , 2002 .

[14]  Prabhu Babu,et al.  Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems , 2016, IEEE Transactions on Signal Processing.

[15]  Louis L. Scharf,et al.  The SVD and reduced rank signal processing , 1991, Signal Process..

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

[17]  John K. Thomas,et al.  The probability of a subspace swap in the SVD , 1995, IEEE Trans. Signal Process..

[18]  K. Gerlach,et al.  Robust adaptive matched filtering using the FRACTA algorithm , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[19]  Y. Selen,et al.  Model-order selection: a review of information criterion rules , 2004, IEEE Signal Processing Magazine.