利用先验知识的空时自适应检测方法

doi:10.3969/j.issn.1001-2400.2010.03.012

Abstract

Abstract:

The heterogeneous clutter results in insufficiency of available secondary data in radar Space-Time adaptive detection. To solve the problem, this paper deals with the design and the analysis of adaptive detector by exploring the Knowledge-based (KB) processing technique. Considering the theory that the outer product of independent identical Gaussian distribution vectors is the Wishart distribution, the covariance matrix in the Wald detector is assumed to be inverse Wishart distribution. The parameter matrix can be obtained by exploring the sensed environment. The proposed Knowledge-based Wald detector makes use of information from both secondary data and prior knowledge available about the sensed environment. Results show that noticeable performance improvements can be obtained especially when only a small number of secondary data is available.

Key words: space-time adaptive processing, Wald test, prior knowledge, inverse Wishart distribution

ZHOU Yu;ZHANG Lin-rang;LIU Nan;LIU Xin. Knowledge-aided space-time adaptive detection method[J].J4, 2010, 37(3): 454-458+546.

References

[1]Reed S, Mallett J D, Brennan L E. Rapid Convergence Rate in Adaptive Arrays [J]. IEEE Trans on Aerosp Electron Syst, 1974, 10(4): 853-863.
[2]Kelly E J. An Adaptive Detection Algorithm [J]. IEEE Trans on Aerosp Electron Syst, 1986, 22(1): 115-127.
[3]Robey F C, Fuhrmann D R, Nitzberg R, et al. A CFAR Adaptive Matched Filter Detector [J]. IEEE Trans on Aerosp Electron Syst, 1992, 28(1): 208-216.
[4]Kay S M. Fundamentals of Statistical Signal Processing, Detection Theory [M]. Englewood Cliffs: Prentice-Hall, 1998.
[5]Melvin W L. Space-time Adaptive Radar Performance in Heterogeneous Clutter [J]. IEEE Trans on Aerosp Electron Syst, 2000, 36(2): 621-633.
[6]Melvin W L, Wicks M C. Improving Practical Space-time Adaptive Radar [C]//Proc of the 1997 IEEE National Radar Conf. New York: IEEE, 1997: 48-53.
[7]Guerci J R, Baranoski E J. Knowledge-aided Adaptive Radar at DARPA—an Overview [J]. IEEE Signal Process Mag, 2006, 23(1): 41-50.
[8]刘聪锋, 廖桂生. 基于Bayes准则的STAP协方差矩阵估计算法[J]. 西安电子科技大学学报, 2008, 35(2): 223-227.
Liu Congfeng, Liao Guisheng. Covariance Matrix Estimation for the STAP Based on the Bayes Criterion [J]. Journal of Xidian University, 2008, 35(2): 223-227.
[9]De Maio A, Farina A, Foglia G. Adaptive Radar Detection: A Bayesian Approach [C]//Radar Conference 2007 IEEE. New York: IEEE, 2007: 624-629.
[10]Wishart J. The Generalized Product Moment Distribution in Samples from a Normal Multivariate Population [J]. Biometrika, 1928, 20(A): 32-52.
[11]Dogandzic A, Zhang B. Bayesian Complex Amplitude Estimation and Adaptive Signal Detection in Low-rank Interference [J]. IEEE Trans on Signal Process, 2007, 55(3): 1176-1182.
[12]Besson O, Tourneret J Y, Bidon S. Knowledge-aided Bayesian Detection in Heterogeneous Environments [J]. IEEE Signal Process Lett, 2007(14): 355-358.
[13]Melvin W, Showman G A. An Approach to Knowledge-aided Covariance Estimation [J]. IEEE Trans on Aerosp Electron Syst, 2006, 42(3): 1021-1042
[14]National Land Cover Data (NLCD) [DB/OL]. [2007-08-03]. http://landcover.usgs.gov/.
[15]National Elevation Data (NED) [DB/OL]. [2007-08-03]. http://seamless.usgs.gov/.
[16]Tague J A, Caldwell C I. Expectations of Useful Complex Wishart Forms [J]. Multidimens Syst Signal Process, 1994(5): 263-279.

Knowledge-aided space-time adaptive detection method

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