Adaptive PRF selection technique for multiple targets in track-before-detect

Abstract

We present an adaptive pulse repetition frequency (PRF) selection technique to mitigate ambiguity, blind-zone, and clutter-zone issues in a particle-based track-before-detect (TkBD) method. A feedback loop provides information about TkBD states to the transmitter in the form of possible target locations and probabilities. The adaptive PRF selection technique is then based on a predicted entropy computation derived from the TkBD target existence probabilities. For each potential PRF, the possible target states fall on different locations in the range-Doppler map, including clutter ridges and blind zones. Thus, the information that can be expected in the next dwell varies with PRF, and the PRF that minimizes the total expected posterior entropy is selected for the next processing interval. While the TkBD enables detection of low-SNR targets that traditional radar will might miss, the adaptive PRF selection helps to minimize track loss before detections are declared. In this context, we compare the performance of adaptive PRF selection to fixed, cyclical PRF selection.