Localization of Multi-source UHF Signals Based on Random Matrix Theory

For a power source to be dependable, power equipment must operate safely and steadily. The insulation state of power equipment can be evaluated by the partial discharge (PD) measurement through the widely used ultra-high frequency (UHF) technology. In practical applications, because of the requirements in real-time performance, small snapshot systems are used which may cause the failure of traditional UHF positioning methods in effectively resolving multiple sources with similar angles. Therefore, in this paper, following the Stieltjes correction of the sample covariance matrix’s eigenvalues and eigenvectors, a multi-source PD UHF localization approach based on random matrix theory was presented. From then, the PD source could be located by looking for its spectral peak in a spatial spectrum. According to the simulation findings, the suggested approach can resolve nearby UHF PD sources with fewer snapshots, and the resolution success rate was highly improved.