Information-Theoretic Approach to Joint Design of Waveform and Receiver Filter with Desired Cross-Correlation Properties for Imaging Radar

An imaging radar is expected to provide high-quality images for interesting targets. To this end, an information-theoretic approach is used in this article to jointly optimize waveform and receive filter with desired cross-correlation properties. First, the problem formulation is achieved by maximizing the mutual information (MI), subject to constant modulus, high resolution, and low peak sidelobe ratio (PSLR) constraints. Second, to solve the resultant problem with a fractional quadratic objective function and various nonconvex constraints, four customized iterative loops are performed to transform the problem into a series of solvable subproblems, via minorization-maximization (MM), alternate direction penalty method (ADPM), and feasible point pursuit successive convex (FPP-SCA) approximation. Convergence of every iterative loop is proved, resulting in guaranteed convergence of the whole procedure with polynomial-time complexity. Finally, numerical examples are presented to demonstrate that the proposed method can construct a unimodular waveform and filter with better information acquisition ability and more desirable cross-correlation function.