| 摘要: |
| 为了提高算法在强杂波环境中对通带约束范围选择的鲁棒性,提出了一种基于稀疏优化的MTD滤波器设计算法。该算法首先在通带约束范围内最窄通带两侧分别引入一个满足单调性、非负约束的通带松弛变量,将通带约束范围的合理选择问题转化为在事先给定通带约束范围内寻找两个满足单调性、非负约束的通带松弛变量的稀疏优化问题,然后同时考虑该稀疏优化约束、其他通带和阻带约束,将MTD滤波器的稀疏优化设计转化为一个基于迭代重加权的凸优化问题,可获得MTD滤波器系数的全局最优解。与原有算法相比,所提算法在强杂波抑制指标要求下对通带约束范围的选择更加稳健。仿真实验验证了所提算法的有效性。 |
| 关键词: MTD滤波器 杂波抑制 稀疏优化 脉冲重复频率 凸优化 |
| DOI： |
| 分类号:TN958.2 |
| 基金项目:安徽省科技重大专项(No. 202003a05020027) |
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| A design algorithm of MTD filters based on sparse optimization |
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| Abstract: |
| To enhance the robustness of the passband constraint range selection for algorithms in strong clutter environments, a MTD (Move Target Detection) filter design algorithm based on sparse optimization is proposed. The algorithm introduces a passband relaxation variable, satisfying monotonicity and non-negativity constraints, on both sides of the narrowest passband within the passband constraint range. This transforms the problem of selecting a reasonable passband constraint range into a sparse optimization problem aimed at finding two passband relaxation variables that meet these constraints. By incorporating this sparse optimization constraint and other passband and stopband constraints, the MTD filter design is converted into a convex optimization problem based on iterative reweighting. This approach yields the global optimal solution for the MTD filter coefficients. Compared to existing algorithms, the proposed method exhibits greater robustness in selecting the passband constraint range under strong clutter suppression requirements. The effectiveness of the proposed method is verified in simulation experiments. |
| Key words: MTD filter clutter rejection sparse optimization pulse repetition frequency convex optimization |