Physics-Based Cognitive Radar Modeling and Parameter Estimation

We consider the problem of channel response estimation in cognitive fully adaptive radar (CoFAR). We show that this problem can be expressed as a constrained channel estimation problem exploiting the similarity between the channel impulse responses (CIRs) of the adjacent channels. We develop a constrained CIR estimation (CCIRE) algorithm enhancing estimation performance compared to the unconstrained CIR estimation where the similarity between the CIRs of the adjacent channels is not employed. Further, we we derive the Cramér-Ran bound (CRB) for the CCIRE and show the optimality of the proposed CCIRE through comparing its performance with the derived CRB.