Waveform Design for Cognitive Radar with Deterministic Extended Targets in the Presence of Clutter

Abstract

Adjusting radar transmitted waveform to its environment is one of the most important roles in cognitive radar; having the capability of updating transmitted waveforms in different applications is a key point. It has been shown in many studies that if the waveform is designed according to the target and clutter characteristics, the detection performance will improve significantly. The uncertainty of the target radar signatures decreases via maximizing MI and the probability of extended target detection is increases via maximizing SNR. In this paper, a waveform design approach based on maximizing both SNR and MI and with regard to target and clutter shape is presented. The detection performance for proposed waveform is compared with previous proposed waveforms. The present paper compares different scenarios of target and clutter and using the probability of detection as a cost function to investigate the advantages and disadvantages of each waveform in different scenarios which are mainly discussed in this text. The desired waveform for cognitive radar is selected based on simultaneously making compromises between SNR and MI, which plays an important role in cognitive radar systems and based on the assumption addressed in the text, the best waveform transmitted into the environment.