RCS特性辅助的CMIMO雷达功率资源分配方法

针对集中式多输入多输出(collocated multiple-input multiple-output, CMIMO)雷达在实际探测过程中,未有效结合目标雷达散射截面(radar cross section, RCS)高动态变化特性导致雷达跟踪精度不高甚至失跟的问题,提出一种基于目标RCS高动态特性的CMIMO雷达功率资源自适应分配方法。考虑到目标RCS特征的角度敏感性,利用目标运动状态的可预测性动态获取实际观测角度,从而完成跟踪帧的极化方式优选；在此基础上构建包含功率与RCS的多目标跟踪误差后验克拉美罗下界,将其作为目标函数进行优化,利用内点惩罚法求解该凸优化问题即可实现RCS高动态情况下的功率优化分配。实验结果表明:该方法可结合目标不同方向RCS动态分集特性实现功率的有效分配,相比于传统RCS模型分配方案,有效解决了分配方案与实际跟踪场景之间的失配问题,从而提升了CMIMO雷达的多目标跟踪性能。

Power resource allocation method for CMIMO radar based on characteristics of RCS

In the actual tracking scenarios of the CMIMO (collocated multiple-input multiple-output) radar, the high dynamic RCS(radar cross section) fluctuation characteristic is not utilized effectively and thus it will lead to low tracking accuracy or even missing tracking. To solve this problem, a CMIMO radar power resource adaptive allocation method based on the high dynamic RCS fluctuation characteristic was proposed. Note that the target RCS was sensitive to the observing angle and the actual observing angle could be obtained dynamically via the prediction of target kinetic state, thus the polarization mode could be optimized during different tracking frames. Thereafter, the tracking posterior Cramer-Rao bound which included radar transmitting power and RCS was derived and it could see as the object function to be optimized. Finally, the internal penalty function method was implemented to tackle the aforementioned optimization problem and it achieved the optimized power allocation with high dynamic RCS. Simulation results validate that compared with the traditional RCS model allocation method, the proposed method fully utilizes the dynamic RCS fluctuation characteristics to achieve the effective allocation and it solves the mismatched problem between the allocation scheme and the actual tracking scenarios, which improves the multi-target tracking performance of the CMIMO radar.