MIMO雷达幅相误差自校正方法研究

发布时间：2018-05-25 01:05

本文选题：幅相误差自校正 + MIMO雷达　；参考：《西安电子科技大学》2015年硕士论文

【摘要】：近些年来随着研究的不断深入,MIMO雷达在目标检测、参数估计、干扰抑制以及低截获率等方面的优势逐渐显现。MIMO雷达在发射通道和接收通道采用了更多的有源器件,这些器件的幅相特性都会随加工误差、工作环境的变化和使用年限等因素发生改变。大多数MIMO雷达信号处理算法都是基于阵列流形已知的情况,但是发射接收通道的幅相误差会改变阵列流形,从而严重影响算法的性能,因此对幅相误差校正的研究具有理论意义和实用价值。根据是否需要设置校正源,可以将幅相误差校正方法分为有源校正和自校正两类。有源校正需要设置方向已知的校正源,因此应用场景受限。本文针对MIMO雷达幅相误差自校正问题进行了研究,工作的主要内容包括如下两个方面:1.传统的MIMO雷达幅相误差自校正迭代算法将幅相误差和目标参数设为代价函数的变量,为了使代价函数最小化需要在幅相误差和目标参数间交替迭代求解。但是这类算法存在收敛于局部解的缺陷的问题。同时,当幅相误差较大时,传统的迭代算法收敛缓慢甚至不收敛。另一方面传统的基于辅助阵元的幅相误差自校正方法虽然不需要迭代,没有收敛性问题,但是由于其需要对参数进行多维搜索,计算量大、估计精度低。为了克服以上问题,本文提出了一种改进的基于辅助阵元的MIMO雷达幅相误差自校正方法。该方法利用三个完全校正的辅助阵元,在MIMO雷达接收数据中形成旋转不变因子。通过对协方差矩阵的奇异值分解获得目标角度的估计,并估计出发射阵列和接收阵列的阵列流形,进而可以提取出发射阵列和接收阵列的幅相误差。仿真分析表明,本文方法不需要迭代和搜索,具有较高的幅相误差估计精度。2.上述MIMO雷达幅相误差自校正方法都是基于目标参数和幅相误差的联合求解。由于机载MIMO雷达杂波功率远远高于目标功率,当幅相误差未知时难以实现目标参数和幅相误差的联合求解。虽然基于压缩感知的机载雷达幅相误差校正方法能够利用杂波求解幅相误差,但是在幅相误差较大的情况下无法收敛。针对上述问题,本文提出了一种基于杂波子空间特性的机载MIMO雷达幅相误差自校正方法。该方法利用扁长椭球波函数构造杂波子空间,结合最大似然估计方法,获得了幅相误差的闭式解。该方法利用机载MIMO雷达的杂波特性,不需要求解目标参数,同时不要求杂波在不同距离门间独立同分布,因此具有较高的实用性。仿真与分析表明,该方法仅需要较少距离门的数据即可实现幅相误差的自校正,并且其性能优于基于压缩感知的算法。
[Abstract]:In recent years, the advantages of MIMO radar in target detection, parameter estimation, interference suppression and low interception rate gradually show that MIMO radar uses more active devices in both transmit and receive channels. The amplitude-phase characteristics of these devices vary with processing error, working environment and service life. Most MIMO radar signal processing algorithms are based on the known array manifold, but the amplitude and phase error of the transmitting and receiving channel will change the array manifold, which will seriously affect the performance of the algorithm. Therefore, the study of amplitude and phase error correction has theoretical significance and practical value. According to whether it is necessary to set up the correction source, the amplitude and phase error correction methods can be divided into two categories: active correction and self correction. The active correction needs to set the correction source with known direction, so the application scene is limited. In this paper, the amplitude and phase error self-tuning problem of MIMO radar is studied. The main contents of the work are as follows: 1. The traditional MIMO radar amplitude-phase error self-tuning iterative algorithm sets the amplitude-phase error and the target parameters as variables of the cost function. In order to minimize the cost function, the iterative solution between the amplitude-phase error and the target parameters is needed. However, this kind of algorithm has the defect of converging to the local solution. At the same time, when the amplitude and phase error is large, the convergence of the traditional iterative algorithm is slow or even non-convergence. On the other hand, the traditional amplitude-phase error self-tuning method based on auxiliary array element does not need iteration and has no convergence problem. In order to overcome the above problems, an improved MIMO radar amplitude and phase error self-tuning method based on auxiliary array elements is proposed in this paper. In this method, three fully corrected auxiliary elements are used to form a rotation invariant factor in the data received by MIMO radar. The target angle is estimated by the singular value decomposition of the covariance matrix, and the array manifolds of the transmit and receiving arrays are estimated, and the amplitude-phase errors of the transmitting and receiving arrays can be extracted. Simulation results show that the proposed method does not need iteration and search, and has a high amplitude and phase error estimation accuracy of .2. The above MIMO radar amplitude-phase error self-tuning methods are based on the joint solution of target parameters and amplitude-phase errors. Because the clutter power of airborne MIMO radar is far higher than the target power, it is difficult to solve the target parameter and the amplitude and phase error when the amplitude and phase error is unknown. Although the amplitude and phase error correction method of airborne radar based on compression sensing can use clutter to solve the amplitude and phase error, it can not converge when the amplitude and phase error is large. In order to solve the above problems, a new method of amplitude and phase error self-tuning for airborne MIMO radar based on clutter subspace characteristics is proposed in this paper. In this method, the clutter subspace is constructed by using the ellipsoidal wave function of flat length and the closed-form solution of the amplitude and phase error is obtained by combining the maximum likelihood estimation method. This method makes use of the clutter characteristics of airborne MIMO radar, and does not need to solve the target parameters, at the same time, it does not require the clutter to be distributed independently among different distance gates, so it has high practicability. Simulation and analysis show that the proposed method can self-correct the amplitude-phase error only with less range gate data, and its performance is better than that based on compression sensing.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN958

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