Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (2): 15-26.doi: 10.19665/j.issn1001-2400.2021.02.003

• Special Issue: Advances in Radar Technology • Previous Articles     Next Articles

Knowledge-based adaptive detection of radar targets in sea clutter background

XU Shuwen(),WANG Zhexiang(),SHUI Penglang()   

  1. National Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China
  • Received:2020-10-14 Revised:2020-12-14 Online:2021-04-20 Published:2021-04-28

Abstract:

This paper focuses on the problem of radar targets detection in the compound-Gaussian sea clutter on the condition with the limited secondary data.The texture is modeled by the generalized inverse Gaussian distribution.Two adaptive detectors based on a priori knowledge of the speckle covariance matrix are proposed.First,the inverse complex Wishart distribution is exploited to model the speckle covariance matrix,and then an adaptive detector without using the secondary data is designed according to the generalized likelihood ratio.According to the maximum posterior test criterion,the secondary data are used to design an adaptive detector with secondary data and prior knowledge.Experimental results show that when the number of secondary cells is small,the two detectors proposed in this paper have a better detection performance than the GLRT-GIG detector.With different numbers of secondary cells,the proposed adaptive detector depending on the secondary data and a prior knowledge has the best performance.

Key words: generalized inverse Gaussian distribution, complex inverse Wishart distribution, compound Gaussian model, adaptive detection

CLC Number: 

  • TN957.51