矢量传感器阵列MIMO雷达高精度二维DOA与极化联合估计

发布时间：2018-09-01 08:55

【摘要】：该文采用矢量传感器配置下的十字型阵列MIMO雷达系统,提出一种新的2维高精度DOA与极化参数联合估计算法。首先根据MIMO雷达虚拟阵列导向矢量的特点,通过降维矩阵的设计及回波数据的降维变换,将高维回波数据转换至低维信号空间;然后基于传播算子获得对应信号子空间的估计,利用收、发阵列阵元间长基线对应的旋转不变性和极化矢量中电场矢量和磁场矢量的叉积进行2维高精度DOA估计和解模糊处理,同时利用与阵列结构无关的极化域旋转不变性进行极化辅角和极化相位差的联合估计。该矢量传感器MIMO雷达阵列可同时获取MIMO雷达的波形分集和矢量传感器的极化分集,无需额外增加阵元和硬件开销,能够有效扩展阵列孔径,提高参数估计性能;同时通过降维变换及传播算子,在获取信噪比增益的同时,能够实现2维高精度DOA和2维极化矢量的联合估计及参数的自动配对,有效降低数据处理维数和参数估计的运算复杂度;最后,仿真结果验证了理论分析的正确性和算法的有效性。
[Abstract]:In this paper, a new joint estimation algorithm of 2-D high precision DOA and polarization parameters is proposed by using cross-array MIMO radar system with vector sensor configuration. Firstly, according to the characteristics of MIMO radar virtual array guidance vector, the high-dimensional echo data is converted to low-dimensional signal space by the design of the reduced dimension matrix and the reduced dimension transformation of the echo data, and then the estimation of the corresponding signal subspace is obtained based on the propagation operator. Using the rotation invariance corresponding to the long baseline between the array elements and the cross product of the electric field vector and the magnetic field vector in the polarization vector, the 2-D high-precision DOA estimation and fuzzy processing are performed. At the same time, the polarization auxiliary angle and the polarization phase difference are estimated by using the rotation invariance of the polarization domain which is independent of the array structure. The vector sensor MIMO radar array can simultaneously obtain the waveform diversity of MIMO radar and the polarization diversity of vector sensor. It can effectively expand the aperture of the array and improve the performance of parameter estimation without adding additional elements and hardware overhead. At the same time, through dimension reduction transformation and propagation operator, the gain of signal-to-noise ratio can be obtained, and the joint estimation of 2-D high-precision DOA and 2-dimensional polarization vector and the automatic matching of parameters can be realized at the same time. The computational complexity of data processing dimension and parameter estimation is reduced effectively. Finally, the simulation results verify the correctness of the theoretical analysis and the validity of the algorithm.
【作者单位】：合肥电子工程学院通信对抗系;
【基金】：国家自然科学基金(60702015) 安徽省科技攻关项目(1310115188) 电子工程学院院控科研基金(KY13A197,KY13A200,KY13A206)~~
【分类号】：TN957.51

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