空间色噪声背景下双基地多输入多输出雷达低仰角估计方法

针对多径效应的影响，该文提出一种空间色噪声背景下双基地多输入多输出(MIMO)雷达低仰角估计方法。首先对双基地MIMO雷达中低仰角目标的多径环境进行建模，同时考虑发射和接收端的镜面反射信号，并用空间色噪声模拟漫反射。然后利用协方差矩阵求差方法消除未知色噪声的影响，在发射端和接收端进行空间平滑对多径信号解相干，即进行空间差分平滑处理。最后利用酉变换旋转不变技术(ESPRIT)算法估计目标的发射角(DOD)和接收角(DOA)。该文指出特殊情况下空间差分平滑协方差矩阵缺秩的问题，并提出一种修正的空间差分平滑方法。该算法对阵元数要求不高，适用于未知噪声背景及低信噪比环境，并且解决DOD与DOA联合估计的角度兼并问题。仿真实验表明了所提算法的有效性。

Low-elevation Estimation for Bistatic MIMO Radar in Spatially Colored Noise

Concerned with the influence of multipath, this paper proposes a spatially differencing smoothing technique for the low-elevation estimation in the bistatic MIMO radar under the spatially colored noise. Firstly, the multipath environment for a low-elevation target in the bistatic MIMO radar is modeled, by considering the specular reflection of the transmitter and receiver. The diffuse reflection is assumed to be the spatially colored noise. Then, the covariance matrix differencing is used to eliminate the unknown noise component, and the transmitting array and receiving array are spatially smoothed to decorrelate the multipath signals, which does the spatially differencing smoothing operation. Finally, the Direction of Departures (DODs) and Direction of Arrivals (DOAs) are estimated by unitary Estimation of Signal Parameters using Rotational Invariance Techniques (ESPRIT) algorithm. This paper also points to the rank deficiency problem of the spatially differencing smoothed covariance matrix in a special case, and modifies the spatially differencing smoothing method correspondingly. The proposed methods require a small number of antenna elements, fit for general unknown noise fields and low SNR environment, and solve the angle-merging problem in joint DOD and DOA estimation. The simulation results demonstrate the effectiveness of the proposed method.