On the use of expert reasoning to enhance GLRT performance

This paper presents the use of tailored covariance matrix estimates that may differ for the three components of the GLRT. These components are an adaptive filter and two different quadratic forms that function as a limiter and a detector. Expert reasoning is used to optimize the covariance matrix in each component.

[1]  Michael C. Wicks,et al.  Adaptive array technology for clutter rejection in airborne radar , 1993, The Record of the 1993 IEEE National Radar Conference.

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

[3]  H. Wang,et al.  Performance comparisons of modified SMI and GLR algorithms , 1991 .

[4]  Michael C. Wicks,et al.  On the use of circular SAR to improve the performance of knowledge-aided STAP , 2016, 2016 IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS).

[5]  J. S. Goldstein,et al.  Nonhomogeneity detection and the multistage Wiener filter , 2002, Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322).

[6]  Mark A. Richards,et al.  Fundamentals of Radar Signal Processing , 2005 .

[7]  Walter Gautschi,et al.  Numerical Analysis , 1978, Mathemagics: A Magical Journey Through Advanced Mathematics.

[8]  William L. Melvin,et al.  Bistatic STAP: application to airborne radar , 2002, Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322).

[9]  Hong Wang,et al.  Further results on robust CFAR processing in conjunction with adaptive clutter/jamming suppression , 1992 .

[10]  Fulvio Gini,et al.  Knowledge-Based Radar Detection, Tracking, and Classification: Gini/Radar Detection , 2008 .

[11]  W. Marsden I and J , 2012 .

[12]  Joseph R. Guerci,et al.  Space-Time Adaptive Processing for Radar , 2003 .

[13]  Tareq F. Ayoub,et al.  Modified GLRT signal detection algorithm , 2000, IEEE Trans. Aerosp. Electron. Syst..