CAJ | 학술논문

为有效克服期望信号方向存在指向误差而导致的阵列流形向量失配的问题，提出了一种基于支持向量回归机的波束形成方法。该方法在分析线性约束最小方差波束形成器的基础上，将支持向量机的损失函数引入到线性约束最小方差波束形成器的最优化问题中，从而使基于结构风险最小化原理的支持向量回归机算法与波束形成算法相结合。通过MATLAB仿真实验，在没有失配的理想情况和期望信号存在方向向量失配的情况下，选取不同的支持向量机参数以及信噪比，分析对2种损失函数的基于支持向量机的波束形成算法。仿真实验结果表明，该算法在期望信号方向存在指向误差时，依然能够保持较好的系统输出信噪比，具有一定的稳健性。
위유효극복기망신호방향존재지향오차이도치적진렬류형향량실배적문제，제출료일충기우지지향량회귀궤적파속형성방법。해방법재분석선성약속최소방차파속형성기적기출상，장지지향량궤적손실함수인입도선성약속최소방차파속형성기적최우화문제중，종이사기우결구풍험최소화원리적지지향량회귀궤산법여파속형성산법상결합。통과MATLAB방진실험，재몰유실배적이상정황화기망신호존재방향향량실배적정황하，선취불동적지지향량궤삼수이급신조비，분석대2충손실함수적기우지지향량궤적파속형성산법。방진실험결과표명，해산법재기망신호방향존재지향오차시，의연능구보지교호적계통수출신조비，구유일정적은건성。
A robust beamforming method is proposed ,w hich can effectively overcome the influence of DOA (direction of arrival ) mismatch .Based on the analysis of linearly constrained minimum variance beamformer ,loss function is introduced in optimization problem of linearly constrained minimum variance beamformer .Then the support vector regression (SVR) algorithm is applied to the robust beamform‐ing ,which is based on the principle of structural risk minimization .Under an ideal scenario of no‐mis‐match and an actual scenario of mismatch respectively ,the SVR‐based beamforming method of two loss function are researched via Matlab simulation through choosing the different parameters and signal to noise ratio (SNR) .Simulation results show that the SVR‐based beamforming method enhances the ro‐bustness in terms of desired signal array manifold vector errors .