Jammer mitigation with adaptive waveforms and use of EM-simulated targets in cognitive radar for target classification

Approved for public release; distribution is unlimited.Cognitive radar (CRr) is a knowledge-aided dynamic radar architecture where the operation of the receiver and transmitter is controlled adaptively through provision for feedback about the electromagnetic (EM) environment. Consequently, transmit waveform design using feedback from the CRr interactions with the environment is crucial to a closed-loop system’s performance. This work is divided into three sections. First, we investigate the classification performance of adaptive waveforms in CRr for deterministic and stochastic land or ground vehicle target response recognition. High-fidelity EM-simulated target responses are generated and utilized in our simulations. Second, we consider an aircraft target recognition problem in the presence of noise jammers and apply the CRr framework in an electronic warfare scenario. Jammer nulling transmit-adaptive waveforms are introduced as countermeasures to various types of noise jammers. Lastly, we propose a dual matched-filter discriminator (DMFD) scheme for coherent jammer suppression in an aircraft target detection scenario. The DMFD is also incorporated into a closed-loop CRr framework for integrated extended moving target detection and identification in an environment where false targets are produced by coherent jammers.RE239CivilianApproved for public release; distribution is unlimited