The basic concepts of cognitive radar and considered the Bayesian framework as an engine for its operation has been summarized in this chapter. Clearly, two critical functions of CR are a probability update function that quantifies the system's understanding and an ability to respond by adapting subsequent transmit waveforms. We applied two waveform strategies to the problem of discriminating an unknown target realization in additive Gaussian noise. The waveforms are based on the SNR and MI criteria. The potential benefits of closed-loop operation are apparent, and we have proposed a diversity-based explanation for the observed performance.

Inspec keywords: AWGN; radar detection; Bayes methods; waveform analysis; object detection

Other keywords: waveform design; unknown target realization; MI criteria; probability update function; SNR criteria; Bayesian framework; additive Gaussian noise; target class discrimination; cognitive radar; CR functions; closed-loop radar

Subjects: Signal detection; Mathematical analysis; Radar equipment, systems and applications