Abstract
The goal of this research is to add automatic target recognition (ATR) capabilities to existing passive radar systems. We do so by comparing the radar cross section (RCS) of detected targets to the precomputed RCS of known targets in the target class. The precomputed RCS of the targets comprising the target class is modeled using a multi-step process involving programs such as the fast Illinois solver code (FISC). Advanced refractive effects prediction system (AREPS) and numerical electromagnetic code (NEC2). A Rician likelihood model compares the power profile of the detected target to the precomputed power profiles of the targets in the target class; this comparison results in target identification. Thus far, the results of simulations are encouraging, indicating that the algorithm correctly identifies aircraft with high probability at the anticipated noise level. Performance can be expected to decline as the noise power surpasses the maximum signal power.
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