基于压缩感知的雷达目标散射中心提取

发布时间：2019-06-03 22:05

【摘要】：雷达散射中心提取是雷达自动目标识别领域的重要基础性问题。散射中心提取的精度和效率直接影响着目标识别的精度和效率。因此,研究雷达目标散射中心提取技术成为目标识别等领域的重要问题之一。为了得到可靠的散射数据,本文采用了基于积分方程的数值方法求解电磁散射问题。同时,将信息论中的压缩感知技术应用于单站散射快速计算,为雷达散射中心提取提供高效,准确的散射数据。论文深入研究了组合激励方法,通过有限个组合激励入射的方法,有效地压缩了单站的入射角度个数,加速单站计算速度。多层快速多极子方法加速了迭代求解中的矩矢相乘,将复杂度从O(N2)降低到O(NlogN),而压缩感知技术可以通过有限个组合激励入射,通过得到的解重构出原始电磁散射问题的解。所以,采用多层快速多极子方法与压缩感知结合,使得电大目标多角度入射的单站问题得到了有效地解决。组合激励的方法可以降低单站的入射角度个数,为进一步降低压缩感知的复杂度,本文采用了特征基函数技术,减少了基函数数目,提升了计算效率。组合激励方法也成功用于特征基函数的构造,用以加速特征基函数的构造。论文还提出了将压缩感知与高阶矩量法相结合,来解决电大目标单站散射的快速计算。采用传统的RWG基函数,或是CRWG基函数,一般选取1/10波长至1/8波长,高阶矩量法是在大的剖分贴片上通过高阶矢量基函数模拟实际电流,最大的剖分尺寸可以达到RWG基函数剖分尺寸的3倍,从而大大降低未知量数目,再通过压缩感知技术降低单站的入射平面波的数目。这样,本文将压缩感知技术与高阶矩量法相结合,用以降低单站散射求解时间,提高电磁计算效率。最后,基于压缩感知技术与多层快速多极子方法相结合的方法,通过FFT成像算法实现了对典型雷达目标散射中心的快速提取。研究结果表明,本文方法在保证散射中心提取精度不下降的条件下,提升了提取效率。针对单频点加速问题,计算效率最高可以提高28%,有效地降低了计算时间。
[Abstract]:Radar scattering center extraction is an important basic problem in the field of radar automatic target recognition. The accuracy and efficiency of scattering center extraction directly affect the accuracy and efficiency of target recognition. Therefore, the research on radar target scattering center extraction technology has become one of the important problems in the field of target recognition. In order to obtain reliable scattering data, a numerical method based on integral equation is used to solve the electromagnetic scattering problem. At the same time, the compressed sensing technology in information theory is applied to the fast calculation of unistatic scattering, which provides efficient and accurate scattering data for radar scattering center extraction. In this paper, the combined excitation method is deeply studied. Through the finite combined excitation incident method, the number of incident angles of a single station is effectively compressed and the calculation speed of a single station is accelerated. The multi-layer fast multipole method accelerates the moment vector multiplication in the iterative solution, reduces the complexity from O (N2) to O (NlogN), and the compression sensing technique can excite the incident through a limited number of combinations. The solution of the original electromagnetic scattering problem is reconstructed by the obtained solution. Therefore, the multi-layer fast multipole method and compressed sensing are used to solve the single-station problem of multi-angle incidence of large targets. The method of combined excitation can reduce the number of incident angles of a single station. in order to further reduce the complexity of compression perception, the eigenbasis function technique is used in this paper, which reduces the number of basis functions and improves the computational efficiency. The combined excitation method is also successfully applied to the construction of feature basis functions to accelerate the construction of feature basis functions. The paper also proposes a combination of compressed sensing and high-order moment method to solve the fast calculation of unistatic scattering of electrically large targets. Using the traditional RWG basis function or CRWG basis function, the 1 鈮，

本文编号：2492254