Abstract
Joint tracking and ATR with HRR radar is an important field of research in recent years. This paper addresses the issue of end-to-end performance modeling for HRR radar based joint tracking and ATR system under various operating conditions. To this end, an ATR system with peak location and amplitude as features is considered. A complete set of models are developed to capture the statistics in all stages of processing, including HRR signal, extracted features, Baysian classifier and tracker. In particular, we demonstrate that the effect of operating conditions on feature can be represented through a random variable with Log-normal distribution. Then, the result is extended to predicting the system performance under specified operating conditions. Although this paper is developed based on a type of ATR and tracking system, the result indicates the trend of the performance for general joint ATR and tracking system over operating conditions. It also provides guidance to how the empirical performance model of a general joint tracking and ATR system shall be constructed.
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