Application of Deconvolution Processing in Passive Localization Technology for Circular Array

In the present study, a robust passive localization technology, based on a uniform circular array and combining beamforming with deconvolution processing, is developed. The goal is to be applicable in low SNR and low snapshot conditions and to be applied to cylindrical sonar systems. The study proposes two deconvolution processing methods and compares them with traditional methods: delay-and-sum beamforming (DSB) and multiple signal classification (MUSIC). The first method uses the Richardson-Lucy (RL) algorithm, a common image enhancement technique in astronomy. The second method use the deconvolution approaches for acoustic source mapping (DAMAS). Both static and dynamic scenarios are used in the simulation. In the static scenario, the array performance of each method is analyzed under different conditions of frequency, signal-to-noise ratio (SNR), and snapshot. The resolution (main lobe width), main-to-sidelobe ratio (MSR), directivity factor (DF), and localization accuracy are used as quantitative parameters for analysis. In the dynamic scenario, multi-target motion and the Doppler effect are considered to verify the feasibility of the proposed methods. The results show that, compared to the free-space array configuration, the rigid cylinder array configuration offers better MSR and DF. Additionally, the two deconvolution methods proposed in this study indeed exhibit better resolution and localization accuracy than traditional methods.