GLRT-based detection in SIRV clutter with steering vector mismatches

This paper mainly deals with the problem of detecting a target in SIRV clutter with steering vector mismatches. Assuming that the mismatch of the steering vector is satisfied the conic constraint, the generalized likelihood ratio test (GLRT) is devised, and the geometry explain is presented for the derived solution. Meanwhile, fixed point estimate (FPE) of the covariance structure is adopted using the secondary data. Finally, we assess the performance of the derived test by Monte Carlo techniques, and several numerical results show that the derived test is consistent with the famous normalized matched filter (NMF), and has the ability to reject high mismatched signals.