Closed-Loop Radar with Adaptively Matched Waveforms

Adaptive and knowledge-based radar focus on improving the performance of the radar receiver through signal processing However, rather than develop transmission waveforms and signal-processing techniques independently, it is useful to consider a closed-loop system complete with an adaptive radar transmitter. In this paper, we summarize and demonstrate a framework being developed at the University of Arizona for implementation of closed-loop radar with adaptive waveforms. This framework integrates a Bayesian channel representation, matched illumination techniques, and sequential hypothesis testing. The result is a closed-loop system that modifies its understanding of the channel based on measured data, customizes waveforms to hasten understanding of the channel, and draws conclusions (such as target classification) when sufficient understanding of the propagation channel is achieved.