Adaptive compressive sensing and processing for radar tracking

Compressive sensing and processing of radar waveforms enables high-resolution tracking while using low sampling rates and inexpensive processing. Compressive processing, however, introduces an additional estimation error, especially when the compressive sensing process is agnostic to the received waveform characteristics. In this work, an adaptive compressive sensing and processing scheme is applied to the radar tracking problem. The adaptive scheme naturally incorporates sequentially updated information on target state that is readily available from a particle filter based tracker. The proposed method is shown to improve tracking performance compared to a non-adaptive scheme, while maintaining a low-sampling rate and a computationally inexpensive operation.