【摘要】 在单站直接定位环境中，利用元启发式蛇优化算法(SO)进行直接定位代价函数的快速求解，在保持定位精度的条件下，丰富了直接定位算法的设计思路。利用非圆信号构建直接定位代价函数并利用蛇优化进行目标位置的求解。为了验证所提算法的性能，通过对比基于子空间数据融合直接定位算法与传统两步交叉定位法，结果表明所提方法可以提升分辨目标个数，并且可以达到更高定位精度。更多还原

【Abstract】 In a single-station direct positioning environment, the metaheuristic snake optimization(SO) algorithm is used to quickly solve the cost function of direct positioning, which enriches the design ideas of the direct positioning algorithm while maintaining positioning accuracy.This paper uses non-circular signals to construct a cost function of direct positioning and uses snake optimization to solve the target position.In order to verify the performance of the proposed algorithm, this paper compares the direct positioning algorithm based on subspace data fusion with the traditional two-step cross positioning method, and the results show that the method proposed can increase the number of resolved targets and achieve higher positioning accuracy.更多还原