基于压缩感知的低空风切变风速估计方法

在机载气象雷达的低空风切变检测流程中，风速估计精度是影响风切变检测效果的重要因素。针对脉冲数较少且信噪比较低时风速估计精度变差的问题，该文提出一种基于压缩感知的低空风切变风速估计方法。该方法根据雷达回波信号的稀疏性，利用多普勒矢量构建一个冗余字典以实现信号的稀疏表示，采用观测矩阵对信号进行压缩处理，并通过信号重构算法恢复该稀疏信号，实现风速的精确估计。仿真实验表明：当脉冲数较少且信噪比较低时，该方法能够在获得精确风速估计的同时使得频谱分辨率大大提高，即能够很好地区分在频域间隔很近的风切变与地杂波信号。

Wind Speed Estimation for Low-attitude Wind Shear via Compressive Sensing

Among the basic steps of low-altitude wind shear detection for airborne weather radar, the wind speed estimate accuracy is the most important affecting factors. In this paper, a novel method of wind speed estimation based on compressive sensing is proposed to solve the problem of performance degradation in low signal-to-noise ratio and few pulses. According to the sparsity of radar echoes, the Doppler vector is used to design a redundant dictionary for the sparse representation of the signal. The signal compression processing is achieved by using the observation matrix, and then the reconstruction algorithm is used to recover the sparse signal and acquire the accurate estimate of the wind speed. Experimental results show that the proposed method can achieve the accurate wind speed estimation and improve the spectral resolution in low signal-to-noise ratio and few pulses, which means it can identify the wind shear and clutter spectrum even in the adjacent areas.