针对基于特征投影预处理的主瓣干扰抑制算法中主瓣干扰对应的特征向量难以分辨的问题,提出一种基于子空间正交性的主瓣干扰抑制算法。该方法首先利用主瓣大致区域这一先验知识求出主瓣子空间;再将采样协方差矩阵进行特征分解,得到干扰对应的特征向量并逐一在主瓣子空间中进行正交性测试,筛选出主瓣干扰对应的特征向量；然后利用特征投影矩阵预处理抑制实际接收数据中的主瓣干扰成分；最后,通过协方差重构求解自适应权矢量去除旁瓣干扰。仿真实验结果表明,子空间正交性验证能够检测出多个主瓣干扰对应的特征向量,能够有效抑制多个主瓣干扰,避免了基于特征投影矩阵预处理和协方差矩阵重构的主瓣干扰抑制算法仅能抑制单个主瓣干扰的问题。

To solve the problem that the eigenvectors corresponding to the mainlobe interference are difficult to distinguish in eigen-projection matrix preprocessing, a mainlobe interference suppression algorithm based on subspace orthogonality is proposed.Firstly, the prior information of rough mainlobe region is exploited to calculate the mainlobe subspace, and eigen decomposition is made to the sampling covariance matrix.Then, the orthogonality of the obtained eigenvectors of interference is tested one by one in the mainlobe subspace, and the eigenvectors corresponding to the mainlobe interference are extracted.Subsequently, the mainlobe component can be suppressed by eigen-projection matrix preprocessing.Finally, the adaptive weight vector can be calculated by covariance matrix reconstruction to cancel sidelobe interference.Simulation results validate that, the subspace orthogonality test can detect all the eigenvectors corresponding to the mainlobe interference, suppress multiple mainlobe interferences successfully, and solve the problem that the mainlobe interference suppression method based on eigen-projection matrix preprocessing and covariance matrix reconstruction can only suppress single mainlobe interference.