一种稀疏重构的相关干涉仪测向算法

针对基于凸优化模型的相关干涉仪测向算法计算量过大的问题,提出了一种基于稀疏度自适应匹配追踪算法的相关干涉仪测向算法。该算法首先根据压缩感知原理利用传统相关干涉仪算法的测向数据库作为基底将入射信号稀疏表示;接着,根据贪婪算法对信号进行重构,估计入射信号的方位。该算法的优点在于在迭代过程中引入回溯思想,自动调整估计步长,实现计算复杂度和估计精度的平衡。仿真结果表明,相比基于凸优化模型的相关算法,该算法的计算量大大降低,测向速度提升24.6%,特别在多入射信号情况下具有明显优势。

A Sparse Reconstruction Direction Finding Algorithm for Coherent Interferometers

To reduce the calculation of coherent interferometer direction finding(DF) algorithm based on convex optimization model,a coherent interferometer DF algorithm based on sparse adaptive matching pursuit algorithm is proposed.Firstly,the sample library of the classical coherent interferometer algorithm is used as the basis to realize sparse presentation of the incident signal according to compressive sensing theory.Secondly,the signal is reconstructed according to the greedy algorithm and the orientation of the incident signal is estimated.The advantage of this algorithm is that it introduces retrospective ideal in the iterative process and achieves a balance between complexity and precision by automatic adjustment step.The simulation results verify that the calculation of the proposed algorithm is greatly reduced compared with that of the algorithm based on convex optimization model.The DF speed is increased by 24.6% and the algorithm has obvious superiority especially in the condition of multi-signal.