基于稀疏解的米波雷达测高方法

Method of Height Measuring Based on Sparse Solution in Meter-Wave Radar

针对米波雷达由于波束宽和地面反射多径引起的测高难题,提出一种基于稀疏解的米波雷达低仰角测高法。该方法首先构造基于类-p范数稀疏度和2-范数约束的代价函数,通过迭代方法最小化代价函数得到稀疏解,最后由尺寸远大于阵元数的稀疏解估计目标仰角和高度。与传统的高分辨算法相比,该方法对信噪比和快拍数要求不高、无需特征值分解和多维搜索过程,具有较高的分辨率和极低的旁瓣电平。计算机仿真和实测数据的处理结果验证了该算法的有效性。

A height measuring method for meter-wave radar is proposed to overcome the problem in height measuring due to wide beam and reflection multipath. The algorithm starts with the cost function based on a p-norm-like（l（p≤1）） diversity measure with a 2-norm constraint. The sparse solution is then ob- tained by minimizing the cost function using an iteration algorithm. Finally, the elevation and height of target can be estimated using the sparse solution with much larger size than the spatial sampled series. Compared with traditional high-resolution methods, the proposed method achieves high resolution and has no multi-dimensional spectral search and eigen-decomposition. Simulations and real data processing results are presented to verify the effectiveness of the method.