基于四阶累积量的MIMO雷达角度估计方法研究

发布时间：2018-05-05 15:29

本文选题：双基地MIMO雷达 + 高斯色噪声　；参考：《哈尔滨工程大学》2014年硕士论文

【摘要】：多输入多输出(MIMO)雷达在目标的高辨识能力与高测量精度、干扰抑制和反隐身等方面都有着显著的优势,已受到国内外学者的广泛关注。目标角度估计方面的研究是MIMO雷达信号处理领域中的一个重要的研究方向,然而目前关于MIMO雷达的目标角度估计算法大多是在假设噪声为高斯白噪声这一理想的情况下进行的理论推导和仿真研究,但在实际高斯色噪声的环境下,其角度估计性能会严重下降,甚至有时结果还可能与实际情况背道而驰,出现目标的错误估计。因此,本课题主要是研究在高斯色噪声的环境下,利用高阶累积量的盲高斯特性实现双基地MIMO雷达的目标角度估计问题。首先,建立了双基地MIMO雷达系统的信号模型,而后详细介绍了其角度估计算法的基本原理,通过仿真实验验证了上述算法的有效性,得到了预期结果,并且给出了每种算法的优缺点分析,最后对高阶统计量的相关基本理论知识进行介绍,为后续用其实现目标角度的正确估计做理论铺垫。其次,针对高斯色噪声的环境下,利用传统基于二阶统计量的角度估计算法的角度估计性能严重下降的问题,提出了一种基于四阶累积量的MUSIC算法,并且通过仿真实验证明该算法可对高斯色噪声的影响进行有效抑制,从而正确估计出目标的DOD和DOA。但由于其需要进行二维空间谱搜索,计算量会非常大,因此又提出了一种基于四阶累积量的PM算法,该算法避免了累积量矩阵的特征值分解计算和二维空间谱搜索,而且目标的DOD和DOA这两个参数可以自动配对,大大降低了算法的运算复杂度,通过仿真实验说明了该算法的角度估计性能。最后,对传统双基地MIMO雷达中的空间平滑类解相干算法的基本原理进行了详细介绍,然后针对在高斯色噪声环境下,传统空间平滑类解相干算法的角度估计性能严重下降的问题,提出了一种基于四阶累积量的前向空间平滑算法。该方法可有效抑制高斯色噪声的影响,实现多个相干目标的正确估计,最后通过仿真实验验证了该算法的角度估计性能。
[Abstract]:Multi-input and multiple-output MIMO-radar has many advantages in target identification, high measurement accuracy, interference suppression and anti-stealth, and has been widely concerned by scholars at home and abroad. The research of target angle estimation is an important research direction in the field of MIMO radar signal processing. However, at present, most of the target angle estimation algorithms of MIMO radar are theoretical derivation and simulation research under the ideal condition that the noise is assumed to be Gao Si white noise. The performance of angle estimation will be seriously degraded, and sometimes the result may be contrary to the actual situation, resulting in the misestimation of the target. Therefore, in the environment of Gao Si color noise, the target angle estimation problem of bistatic MIMO radar is studied by using the higher-order cumulant's blind Gao Si characteristic. Firstly, the signal model of bistatic MIMO radar system is established, and then the basic principle of the angle estimation algorithm is introduced in detail. The effectiveness of the algorithm is verified by simulation experiments, and the expected results are obtained. The advantages and disadvantages of each algorithm are analyzed. At last, the basic theoretical knowledge of high order statistics is introduced, which lays the foundation for the correct estimation of the target angle in the future. Secondly, aiming at the problem that the performance of the traditional angle estimation algorithm based on second-order statistics is seriously degraded in the environment of Gao Si color noise, a fourth-order cumulant based MUSIC algorithm is proposed. The simulation results show that the algorithm can effectively suppress the influence of Gao Si color noise and estimate the DOD and DOA of the target correctly. However, due to the need of 2-D spatial spectral search, the computational complexity will be very large. Therefore, a fourth-order cumulant based PM algorithm is proposed, which avoids the eigenvalue decomposition of the cumulant matrix and the two-dimensional spatial spectral search. Moreover, the DOD and DOA parameters of the target can be paired automatically, which greatly reduces the computational complexity of the algorithm. The simulation results show that the performance of the algorithm is estimated by angle estimation. Finally, the basic principle of spatial smoothing decoherence algorithm in traditional bistatic MIMO radar is introduced in detail. A forward spatial smoothing algorithm based on fourth-order cumulant is proposed in this paper. This method can effectively suppress the influence of Gao Si color noise and realize the correct estimation of multiple coherent targets. Finally, the performance of the algorithm is verified by simulation experiments.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN958

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