利用不规则曲线测量数据实现雷达目标三维成像

Three-dimensional Radar Imaging with Squiggle Path Measurements

由于平台任务要求或环境影响,雷达数据采样路径可能是不规则曲线。利用通常舍弃的不规则曲线测量数据实现雷达目标三维成像,而且在稀疏测量情形下的成像分辨率甚至超过密集采样时传统成像算法的分辨率。不规则曲线测量数据的空间采样具有稀疏性和非均匀性,不能用传统成像算法得到高分辨率图像。基于压缩感知的雷达目标成像,突破了传统分辨率的瑞利准则限制,且可应用于非均匀采样数据。目标高频散射的稀疏性为压缩感知在雷达成像中的应用奠定了基础。更重要地研究证明,不规则曲线测量矩阵具有良好的互不相干性,因此基于压缩感知的三维成像能够满足重构精度和稳定性要求。考虑到三维成像中测量矩阵的高维性,用分段正交匹配追踪算法实现目标信号的稀疏重构。实验结果表明,算法不仅能够精确实现超分辨三维成像,而且成像算法具有很好的鲁棒性。

A new algorithm is proposed to achieve 3-D the instability of aircraft, the radar data collection path is a imaging with squiggle path measurements. Because of squiggle curve. The samples of squiggle path data are sparsity and uniformly, which means that the traditional algorithms are not suited for 3-D imaging. Compressive sensing theory indicates that the optimal reconstruction of an unknown sparse signal can be achieved from limited noisy measurements. For synthetic aperture radar （SAR） imagry, the scattering field of the target is usually com- posed of only limited number of strong scattering centers, representing strong spatial sparsity. The sparsity of radar target pave the way for radar 3-D imaging with squiggle path data by compressive sensing theory. The measurement matrix is mutual incoherence, which results show that the frame is capable of precise ments. means that the 3-D imaging is steady an reconstruction of 3-D SAR images with squiggle path d robust. Experimental squiggle path measure