Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter

We consider the problem of knowledge-aided (possibly cognitive) transmit signal and receive filter design for point-like targets in signal-dependent clutter. We suppose that the radar system has access to a (potentially dynamic) database containing a geographical information system (GIS), which characterizes the terrain to be illuminated, and some a priori electromagnetic reflectivity and spectral clutter models, which allow the raw prediction of the actual scattering environment. Hence, we devise an optimization procedure for the transmit signal and the receive filter which sequentially improves the signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm, whose convergence is analytically proved, requires the solution of both a convex and a hidden convex optimization problem. The resulting computational complexity is linear with the number of iterations and polynomial with the receive filter length. At the analysis stage we assess the performance of the proposed technique in the presence of either a homogeneous ground clutter scenario or a heterogeneous mixed land and sea clutter environment.