基于发射波束域-三迭代的机载MIMO雷达STAP方法

针对传统机载多输入多输出(MIMO)雷达空时自适应处理(STAP)中由于发射功率分散而造成的输出信杂噪比(SCNR)下降的问题，该文提出一种基于发射波束域-三迭代的机载MIMO雷达STAP方法。首先建立了发射波束域MIMO雷达STAP的信号模型，并且给出了发射波束加权矩阵的优化设计准则，能够使发射功率聚集于感兴趣的目标空域。然后对发射波束域MIMO雷达的杂噪比(CNR)进行分析，表明其与发射总功率的关系，理论推导显示:相比于全向等功率发射的传统MIMO雷达CNR，发射波束域MIMO雷达CNR减小。同时，为进一步降低发射波束域MIMO-STAP的训练样本数需求与运算复杂度，采用三迭代算法进行权值降维求解。理论分析与仿真实验结果表明:通过相应的三迭代降维处理，发射波束域MIMO-STAP与传统全向等功率发射MIMO-STAP相比能够获取更加优越的输出SCNR性能，且运算量进一步降低。因此，本文提出的发射波束域-三迭代方法具有重要的工程应用价值。

Airborne MIMO Radar STAP Method Based on Transmit Beamspace-tri-iterative Algorithm

The output Signal-to-Clutter-plus-Noise Ratio (SCNR) of traditional airborne MIMO radar STAP decreases because of the transmit power dispersion. To solve this problem, a MIMO-STAP method based on Transmit Beamspace (TB)-TRi-Iterative Algorithm (TRIA) is proposed. Firstly, the signal model of the TB-based MIMO radar STAP is established, and the optimizing criterion for designing the TB weight matrix is proposed to focus all transmit power within the desired spatial sector. Then, the Clutter-to-Noise Ratio (CNR) of the TB-based MIMO radar is analyzed to show its relationship with the total transmit power. The theoretical derivation is further provided to illustrate that the CNR of the TB-based MIMO radar is reduced compared with that of the traditional MIMO radar with uniform omni-directional transmission. Furthermore, in order to decrease the training sample requirement and the computational complexity of the TB-based MIMO-STAP, the TRIA is utilized to resolve the reduced-dimension weight vectors. The theoretical analysis and simulation results show that, through the corresponding tri-iterative reduced-dimension processing, the TB-based MIMO-STAP can achieve the improvement of the output SCNR, compared to the traditional MIMO-STAP with uniform omni-directional transmission. Moreover, the computational burden is further decreased. Therefore, the proposed TB-TRIA method has great value for engineering application.