A Novel Iterative Method for Improving Radar Angular Super-Resolution
In this paper a new method is proposed to improve radar angular super-resolution on the basis of the constrained optimization theory. We provide a quasi-BFGS algorithm for updating antenna pattern matrix so that the antenna pattern matrix and its transpose matrix could approximate a positive semi-definite matrix, then the model of radar scanning system meets the requirement of convex quadratic programming. By using Newton algorithm, the optimal solution of that model could be gained and then the target angular information is accordingly restored. Simulations manifest that a desirable resolution result is gained and it provides an amazing result that our method is superior to other methods at signal to noise ratio (SNR).