Pseudo space smoothing decorrelation method based on manifold separation

The classical spatially smooth decorrelation method is not directly applicable to arbitrary arrays, and the existing arbitrary array decorrelation algorithms require better prior parameters. To address both issues simultaneously, this paper employs classical manifold separation technology to construct pseudo guide vectors in the same form as the directional vector representation of a uniform linear array (ULA), and applies the SS-MUSIC algorithm, originally limited to uniform or partially uniform linear arrays, to achieve decorrelation processing. This approach is referred to as the Manifold-Separation-based Pseudo Spatial Smoothing (MSPSS) algorithm. An unbiasedness and effectiveness analysis of the algorithm is conducted, demonstrating its asymptotic unbiasedness and variance approaching the Cramér-Rao bound. Simulation results indicate outstanding performance with high angle resolution (−3 dB main lobe width of 0.8°) and low absolute error (10⁻¹⁵ order of magnitude) at negative Signal-to-Noise Ratio (SNR). The algorithm achieves true arbitrary array manifold decorrelation processing and surpasses the "Rayleigh limit" of real matrices without limitation, laying a foundation for subsequent integration with other algorithms.