Robust Target Identification Using a Modified Generalized Likelihood Ratio Test

In order to correctly identify a remote target, an efficient and robust target signature identification technique is required. Radar target identification based on complex natural resonances (CNRs) has drawn the interest of many researchers following the development of the singularity expansion method (SEM). As evident from the literature, statistical techniques such as the generalized likelihood ratio test (GLRT) have produced a better identification result, in the presence of noise, compared to some other SEM-based identification methods such as the extinction pulse (E-pulse) technique. However, one of the issues related to a resonance based target classifier is that it requires the commencement of the late time period for the unknown target response to be determined accurately in order to avoid false alarms during target classification process. For automatic target recognition (ATR) applications, usually such information is not known a priori. In view of this problem, a modified GLRT technique that utilizes time-frequency analysis is presented in this paper. The improved GLRT method does not require prior knowledge of the beginning of the late time period for the transient response of the unknown target. Simulation results using various targets show that our method is comparable to the original GLRT technique when the commencement of the late time period for the unknown target response is correctly determined and outperforming the original GLRT technique when the commencement of the late time period for the unknown target response is incorrectly determined.