Conjugate gradient parametric adaptive matched filter

The parametric adaptive matched filter (PAMF) detector for space-time adaptive processing (STAP) detection is re-examined in this paper. Originally, the PAMF detector was introduced by using a multichannel autoregressive (AR) parametric model for the disturbance signal in STAP detection. While the parametric approach brings in benefits such as significantly reduced training and computational requirements as compared with fully adaptive STAP detectors, the PAMF detector as a reduced-dimensional solution remains unclear. This paper employs the conjugate-gradient (CG) algorithm to solve the linear prediction problem arising in the PAMF detector. It is shown that CG yields not only a new computationally efficient implementation of the PAMF detector, but it also offers new perspectives of PAMF as a reduced-rank subspace detector. The CG algorithm is first introduced to provide alternative implementations for the matched filter (MF) and parametric matched filter (PMF) when the covariance matrix of the disturbance signal is known. It is then extended to the adaptive case where the covariance matrix is estimated from training data. Important issues such as unknown model order and convergence rate are discussed. Performance of the proposed CG-PAMF detector is examined by using the KASSPER and other computer generated data.

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

[2]  Gene H. Golub,et al.  Matrix computations , 1983 .

[3]  B. Himed,et al.  Parametric Rao Test for Multichannel Adaptive Signal Detection , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[5]  Biao Huang,et al.  System Identification , 2000, Control Theory for Physicists.

[6]  Jian Li,et al.  Efficient mixed-spectrum estimation with applications to target feature extraction , 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

[7]  E. J. Kelly.  An Adaptive Detection Algorithm , 1986, IEEE Transactions on Aerospace and Electronic Systems.

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

[9]  James Ward,et al.  Space-time adaptive processing for airborne radar , 1998 .

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

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

[12]  L.E. Brennan,et al.  Theory of Adaptive Radar , 1973, IEEE Transactions on Aerospace and Electronic Systems.