Waveform-agile track-before-detect for low observable targets

Abstract

We investigate waveform agile selection for dynamic target tracking under low signal-to-noise ratio (SNR) conditions. Our approach combines two techniques aimed at increasing tracking performance. It uses track-before-detect (TBD) that employs unthresholded delay-Doppler measurements and is implemented using particle filtering. Integrated into the TBD is an adaptive waveform configuration algorithm that selects the transmit waveform parameters at each time step by minimizing the predicted mean-squared estimation error of the target's state. Using simulations to track a low SNR target, we demonstrate the increased performance of waveform-agile sensing (WAS)-TBD over TBD with fixed transmit waveforms.