联合角度-时延-多普勒的分布式MIMO雷达运动目标定位代数解算法

对三维空间中联合角度、时延和多普勒频率的分布式MIMO雷达运动目标定位问题进行了研究，提出了一种新的目标位置和速度估计代数解算法。通过借助方位角和俯仰角测量，对时延和多普勒频率方程进行线性化处理，然后通过加权最小二乘解算目标的位置和速度。与现有基于多步骤加权最小二乘思想的定位算法相比，该算法无需引入冗余参数，仅需一步加权最小二乘即可实现目标定位，避免了步间误差传递，减少了定位所需的发射/接收单元数量，并且考虑了发射/接收单元位置-速度误差的影响，提高了算法对发射/接收单元位置-速度误差的稳健性。理论分析证明，该算法的定位误差可以达到克拉美罗界。仿真结果验证了该算法的有效性，以及相比于现有算法的优越性。

An Algebraic Solution for Moving Target Localization in Distributed MIMO Radar Using Angle-Delay-Doppler Measurements

? ?This paper addresses the moving target localization jointly using angle， time delay and Doppler shift measurements in Multiple Input Multiple Output （MIMO） radar with widely separated antennas. A novel algebraic solution for target position and velocity estimation is proposed. By using azimuth and elevation angle， the nonlinear time delay and Doppler shift measurements， equations are converted to linear ones； then， the target position and velocity are obtained by using weighted least squares （WLS） minimization. Compared with existing algorithms based on multi-stage WLS ideas， the proposed solution does not introduce any nuisance parameters and it identifies the target position and velocity in only one stage， which avoids the interstage error propagation and locates target with minimum number of transmitters and receivers. Moreover， the proposed solution considers the influence of transmitter and receiver location uncertainties on the localization accuracy， and improves the robustness to these uncertainties. Theoretical analysis indicates that the proposed solution reaches the Cramér-Rao lower bound. Simulation results verify the effectiveness and superiority of the proposed solution over existing algorithms.