基于Hankel矩阵分解的天波超视距雷达机动目标检测算法

机动目标检测是天波超视距雷达的研究重点之一。目前已有的算法在高信噪比条件时对单个机动目标的检测效果较好，但在低信噪比时对多个机动目标的检测性能有待提高。该文提出一种基于Hankel矩阵分解的机动目标检测算法，该算法将机动目标信号构造为Hankel矩阵的形式，通过矩阵分解将信号时频估计转化为线性主成分分析的凸优化问题，从而实现匀速与机动目标的分离以及多个目标的同时估计。仿真结果证明了该算法具有估计精度高，信噪比条件低，可以同时多目标检测等优点。

Maneuvering Target Detection Algorithm Based on Hankel Matrix Decomposition in Over-The-Horizon Radar (OTHR)

Maneuvering target detection is one of the focuses in skywave Over-The-Horizon Radar (OTHR). The performance of existing algorithms is good for single maneuvering target in the condition of high SNR. However, the performance for multiple maneuvering targets in low SNR needs to be improved. In this paper, a new maneuvering target detection algorithm is proposed based on Hankel matrix decomposition. The maneuvering target signal is constructed in the form of Hankel matrix. Then the time-frequency estimation of maneuvering target signal is transformed into a convex optimization problem based on linear Principal Component Analysis (PCA) by matrix decomposition, so as to realize the separation of uniform and maneuvering targets, and the simultaneous estimation of multiple targets. The simulation results show that the proposed algorithm has the advantages of high estimation accuracy, low SNR and multiple target detection.