基于FMCW雷达的旋转目标微动参数提取方法

针对旋转目标微多普勒频率相互交叠、重合难以提取的问题, 提出了一种基于调频连续波(frequency modulated continuous wave, FMCW)雷达的微动参数提取方法。考虑到旋转目标微多普勒频率具有正弦形式的特征, 利用多普勒信号构造了矩阵并进行奇异值分解, 使得奇异值比谱在旋转频率处的比值达到最大。为了估计旋转半径和初始相位, 对多普勒信号时频分析结果进行逆Radon变换, 将正弦曲线的参数估计问题转化成了参数空间中的峰值检测问题。仿真和实验数据结果表明, 结合奇异值分解、时频分析技术和逆Radon变换的旋转目标微动参数提取方法具有在低信噪比条件下提取高精度参数值的能力, 有效解决了相互交叉的微多普勒频率参数提取问题。

Micro-motion parameters extraction for rotating targets based on FMCW radar

The micro-Doppler frequencies of rotating targets usually overlap in the time-frequency domain, it is difficult to extract them by traditional methods. To address this issue, this paper proposes a novel micro-motion parameters extraction method for rotating targets based on frequency modulated continuous wave (FMCW) radar. Given the fact that the obtained micro-Doppler frequency is featured by sinusoidal model, a matrix based on the received signal is constructed and carried out by singular value decomposition to ensure that the singular value ratio spectrum reaches the peak value at the rotating frequency. To estimate rotating radius and initial phase, a method of calculating inverse Radon transform for the result of time-frequency analysis is proposed, which transformed the parameter estimation of sine curve into the problem of peak value detection in parameter space. The simulation and experiment data show that the proposed method can achieve high accuracy for parameter estimation in the low signal-to-noise ratio and can extract overlapped micro-Doppler frequencies effectively.