To solve the problem of deviation of mainlobe and high sidelobe in the adaptive beamformer in the situation of limited snapshots, this paper presents a robust beamforming algorithm in the situation of limited snapshots. The proposed algorithm amends the exponent of covariance matrix of input signal in the Linearly Constrained Minimum Variance ( LCMV) adaptive beamformer which is computed by Sample Matrix Inversion ( SMI) algorithm to make the small eigenvalues of the covariance matrix close to each other in the situation of limited snapshots. This algorithm can diminish the deviation of mainlobe and suppress the high sidelobe. By analyzing the signal to interference plus noise ratio of the proposed algorithm, this paper gives the range of the exponent of covariance matrix. Simulation results demonstrate the validity and superiority of the proposed algorithm.%针对低快拍情况下自适应波束形成器输出方向图存在主峰偏移,副瓣电平较高的问题,该文提出一种低快拍情况下稳健的波束形成算法.算法通过对线性约束最小方差(LCMV)波束形成器的输入信号协方差矩阵进行指数修正,改善了采用协方差矩阵求逆(SMI)算法的LCMV波束形成器输入信号协方差矩阵小特征值在低快拍情况下的发散程度,从而可在减小主峰偏移的同时,有效地解决副瓣电平较高的问题；最后通过分析波束形成器输出信干噪比(SINR)随修正指数变化的情况,给出算法修正指数的取值范围.计算机仿真结果验证了该算法的有效性和优越性.
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