diffusion networks for localization in satellite target tracking applications. It provides a comprehensive convergence analysis for the Mobile DQA-RLS (MDQA-RLS) algorithm, considering various quantization levels and the corresponding convergence conditions. The simulation results confirm the potential for convergence in the MDQA-RLS network and demonstrate that the power consumption of this method is highly suitable for satellite localization tasks. Additionally, the observed convergence degradation remains within reasonable limits when compared to the mobile DRLS (MDRLS) algorithm, which does not account for quantization. Comprehensive convergence analyses are conducted across various quantization levels, and the specific conditions under which the Mobile MDQA-RLS algorithm converges are thoroughly outlined. Simulation experiments confirm the convergence capability of the MDQA-RLS-based network and indicate that its power efficiency is well-suited for satellite target tracking scenarios. Additionally, the observed degradation in convergence performance is within acceptable limits when compared to the Mobile DRLS (MDRLS) algorithm, which lacks quantization awareness. The findings further illustrate that as signal quantization resolution decreases, the advantages of MDQA-RLS over MDRLS become significantly more pronounced.