Evaluation of the normalized parametric adaptive matched filter STAP test in airborne radar clutter

The performance of a recently proposed parametric space-time adaptive processing (STAP) detection method is considered here and compared with several candidate algorithms. Specifically, we consider signal detection in additive disturbance consisting of compound-Gaussian clutter plus Gaussian thermal white noise. Consideration is given to both detection and constant false alarm rate (CFAR) robustness with respect to clutter texture power variations. Finally, the performance of the new test is assessed using small training data support size.

[1]  O. Strand.  Multichannel complex maximum entropy (autoregressive) spectral analysis , 1977 .

[2]  S. Watts,et al.  Radar Detection Prediction in K-Distributed Sea Clutter and Thermal Noise , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Marco Lops,et al.  Asymptotically optimum radar detection in compound-Gaussian clutter , 1995 .

[4]  Giuseppe Ricci,et al.  Performance prediction in compound-Gaussian clutter , 1994 .

[5]  Ronald L. Spooner.  On the Detection of a Known Signal in a Non‐Gaussian Noise Process , 1968 .

[6]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[7]  F. Gini.  Sub-optimum coherent radar detection in a mixture of K-distributed and Gaussian clutter , 1997 .

[8]  J. Mallett.  Rapid convergence in adaptive arrays , 1976 .

[9]  J.H. Michels,et al.  Innovations based detection algorithm for correlated non-Gaussian random processes , 1992, [1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing.

[10]  F. Gini,et al.  Performance analysis of two covariance matrix estimators in compound-Gaussian clutter , 1999 .

[11]  K. Gerlach.  Spatially distributed target detection in non-Gaussian clutter , 1999 .

[12]  S. Kraut,et al.  A canonical representation for distributions of adaptive matched subspace detectors , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[13]  Kung Yao,et al.  A representation theorem and its applications to spherically-invariant random processes , 1973, IEEE Trans. Inf. Theory.

[14]  A. Farina,et al.  Radar detection of targets located in a coherent K distributed clutter background , 1992 .

[15]  Irving S. Reed,et al.  A new CFAR detection test for radar , 1991, Digit. Signal Process..

[16]  Qingwen Zhang,et al.  Parametric adaptive matched filter for airborne radar applications , 2000, IEEE Trans. Aerosp. Electron. Syst..

[17]  Muralidhar Rangaswamy,et al.  Multichannel detection for correlated non-Gaussian random processes based on innovations , 1993, Defense, Security, and Sensing.

[18]  James Henry Michels.  Multichannel detection using the discrete-time model-based innovations approach , 1991 .

[19]  Fulvio Gini,et al.  Clairvoyant and adaptive signal detection in non-Gaussian clutter: a data-dependent threshold interpretation , 1999, IEEE Trans. Signal Process..

[20]  C. K. Yuen,et al.  Digital spectral analysis , 1979 .

[21]  Scharf,et al.  11 - Geometries, invariances, and SNR interpretations of matched and adaptive subspace detectors , 1998 .

[22]  Marco Lops,et al.  Adaptive detection schemes in compound-Gaussian clutter , 1998 .

[23]  M. Rangaswamy,et al.  A parametric multichannel detection algorithm for correlated non-Gaussian random processes , 1997, Proceedings of the 1997 IEEE National Radar Conference.

[24]  Raviraj S. Adve,et al.  Space-Time Adaptive Processing , 1998 .

[25]  Georges Vezzosi,et al.  Détection d’un signal certain dans un bruit sphériquement invariant, structure et caractéristiques des récepteurs , 1972 .

[26]  Daniel R. Fuhrmann,et al.  A CFAR adaptive matched filter detector , 1992 .