A Quadratic Optimization Algorithm Based on Multi-array Fusion Localization

In this paper, we study related algorithms for multi-node localization in acoustic detection, and propose several data fusion methods in terms of multi-array fusion algorithms. A Monte Carlo simulation of the localization error under different fusion conditions is designed to derive the error model. Under the assumption of many arrays, we propose a weighted fusion method based on density clustering, and the simulation and experiments are made. The experimental results show that the multi-node data fusion positioning can effectively improve the positioning accuracy. on this basis, the optimization algorithm described in this paper has good positioning performance.