Anti-Jamming Algorithm of Polarization-Sensitive Array Based on Improved Constraint Matrix and Orthogonal Subspace Projection

The vulnerability of satellite navigation signals to suppressive interference is a major concern owing to the extremely low power. The polarization-sensitive array adds polarization diversity capability, providing outstanding anti-jamming properties. Null depth is a crucial indicator of interference mitigation capability. This article proposes a new weight vector calculation method for space-polarization-domain adaptive processing (SPAP) by focusing on interference null depth, which can improve the anti-interference performance of polarization-sensitive arrays. First, the realistic received signal model of the polarization-sensitive array is built. Second, the realistic radiation pattern of the crossed dipole antenna and the polarization characteristics of the signal are considered in the constraint matrix of the minimum variance distortionless response (MVDR) to obtain a new anti-jamming weight matrix. Finally, the orthogonal projection subspace method is introduced to effectively deepen the interference null, and its orthogonality with the interference subspace is improved by projecting the new anti-interference weight matrix into the noise subspace of the received signal, and the rationality and effectiveness of the method are verified by theoretical derivation. Through simulation experiments on a uniform linear array (ULA) and a uniform circular array (UCA), the results indicate that the proposed method can effectively increase the null depth in the space and polarization domains by 12–28 dB, which significantly improves the array’s anti-interference capability.