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Recursive Asymptotic GLRT Detector of Range-spread Target in Compound Gaussian Clutter
Received date: 2012-06-26
Revised date: 2012-10-11
Online published: 2012-10-18
Supported by
National Natural Science Foundation of China (61032001, 61102166); Program for New Century Excellent Talents in University(NCET-11-0872)
This paper addresses the adaptive detection of range-spread targets in a structured compound-Gaussian clutter (CGC). In view of the fact that the asymptotic generalized likelihood ratio test in a heterogeneous environment (AGLRT-HTG) suffers a signal to clutter ratio loss in a CGC environment, the structured CGC is modeled as an autoregressive process and a recursive AGLRT in the compound-Gaussian clutter (RAGLRT-CGC) environment is proposed by using the method of asymptotic generalized likelihood ratio test (AGLRT) and the idea of recursive estimation. The analytical formula relating false alarm probability to detection threshold for limit cases is deduced. The simulation results show that the RAGLRT-CGC is robust to different multiple dominant scattered targets and the detection performance of RAGLRT-CGC is obviously better than the AGLRT-HTG.
GU Xinfeng , JIAN Tao , HE You , HAO Xiaolin . Recursive Asymptotic GLRT Detector of Range-spread Target in Compound Gaussian Clutter[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(5) : 1140 -1150 . DOI: 10.7527/S1000-6893.2013.0203
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