基于改进ESPRIT算法的雷达多目标识别

Haitao Jia, Jian Li, Taoliu Yang, Wei Zhang
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引用次数: 1

摘要

目前,应用密集目标是重要的突防手段之一。在许多观测条件下,来自密集目标的回波中混合了许多混叠信号,而传统的雷达信号处理算法没有考虑混叠信号。因此,传统算法难以识别多目标。本文提出了一种改进的ESPRIT算法,可以在不改变算法精度的情况下从混叠回波中识别出多目标,大大降低了计算量,特别是在低信噪比环境下可以获得更好的估计。该算法首先可以快速实现对目标回波散射中心参数的估计,然后在此基础上对混叠目标进行识别。仿真还验证了改进的ESPRIT算法在低信噪比条件下对混叠目标具有更好的识别能力。此外,由于降低了计算复杂度,该算法的性能比传统方法更快,特别是在多个混叠散射中心的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Based on Improved ESPRIT Algorithm Radar Multi-target Recognition
At present, application of dense targets is one of the important means of penetration. In many observation conditions, the echoes from the dense targets mixed with many aliasing signals, and conventional radar signal processing algorithms do not take the aliasing signals into account. Therefore it is difficult for conventional algorithms to recognize multi-targets. In this paper, an improved ESPRIT algorithm is proposed which can recognize the multi-targets from the aliasing echoes and greatly reduce the computational complexity without changing the algorithm accuracy, especially can obtain a better estimation in the case of low SNR environment. The proposed algorithm can firstly quickly realize the estimate of scattering center parameters of target echoes, and then based on the estimation, the aliasing targets can be recognized. The Simulation also verifies the improved ESPRIT algorithm has a better identification and recognition capability of aliasing targets in low SNR condition. Moreover because of reduction of the computational complexity, the performance of proposed algorithm is faster than conventional methods, especially in the case of multiple aliasing scattering centers.
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