摘要
为了降低MIMO雷达自适应矩阵算法(Adaptive Matrix Approach,AMA)的计算复杂度和样本需求,该文提出一种双边AMA(Two-Sided AMA,TS-AMA)算法。TS-AMA算法将AMA算法的权矩阵分解成两个低维权矩阵的Kronecker积,从而将AMA算法的代价函数转化为一个双二次的代价函数。新的代价函数可以通过结合半正定规划(Semi-Definite Programming,SDP)和双迭代算法(Bi-Iterative Algorithm,BIA)有效地求解。相比AMA算法,TS-AMA算法的收敛速度更快,样本需求更低,运算量更小。仿真结果说明了该算法的有效性。
To reduce the computational complexity and training samples required of Adaptive Matrix Approach (AMA),a Two-Sided AMA(TS-AMA) for MIMO radar is proposed.The proposed algorithm converts the cost function of AMA into a bi-quadratic one by decomposing the weight matrix of AMA into a Kronecker of two small dimensional weight matrices.The new cost function can be efficiently solved by combining Semi-Definite Programming(SDP) with Bi-Iterative Algorithm(BIA).The proposed algorithm has faster convergence rate, smaller training samples required and lower computational complexity comparable with that of AMA.The numerical examples are provided to demonstrate the effectiveness of the proposed algorithm.
出处
《电子与信息学报》
EI
CSCD
北大核心
2012年第4期898-903,共6页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60901067
61001212)
新世纪优秀人才支持计划(NCET-09-0630)
长江学者和创新团队发展计划(IRT0954)
中央高校基本科研业务费专项资金联合资助课题
关键词
MIMO雷达
方向图综合
双边自适应矩阵算法
半正定规划
双迭代算法
MIMO radar
Beampattern synthesis
Two-Sided Adaptive Matrix Approach(TS-AMA)
SemiDefinite Programming(SDP)
Bi-Iteration Algorithm(BIA)