A Novel Iterative Method for Improving Radar Angular Super-Resolution

Xin Zhang, Xiaoming Liu
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Abstract

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).
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一种改进雷达角超分辨率的迭代方法
基于约束优化理论,提出了一种提高雷达角度超分辨率的新方法。提出了一种准bfgs算法来更新天线方向图矩阵,使天线方向图矩阵及其转置矩阵逼近一个正半定矩阵,从而使雷达扫描系统模型满足凸二次规划的要求。利用牛顿算法得到该模型的最优解,从而恢复目标的角度信息。仿真结果表明,该方法获得了理想的分辨率结果,并且在信噪比(SNR)方面优于其他方法。
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