Knowledge-aided Adaptive Detection with Multipath Exploitation Radar
Hayvacı, Harun Taha
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The adaptive detection of point-like targets in the presence of multipath is considered in this article. Target return signal is modeled as the sum of direct path return and reflected path return signals under the assumption of a zero-mean complex circular Gaussian noise with an unknown covariance matrix. A new approach to exploit multipath returns in target detection with an adaptive regime is studied. The novelty of this approach is that the multipath returns are exploited with a priori knowledge of the reflecting environment, so that we have the knowledge of the reflected steering vector for a known actual direct path steering vector. As a case study, we analyze a radar-target scenario over a flat conducting surface.