中文摘要：

提出了一种基于启发式搜索的主动定位算法．首先利用自适应粒子聚类算法对粒子进行聚类；然后分别构造路径规划树和解空间树，并根据优先级评估函数计算解空间树中所有节点的优先级，利用优先队列式分支限界法解决路径搜索问题；最后针对单个粒子簇分散问题提出了一种定位精度主动提升方法．仿真实验验证了所提出方法的有效性．

英文摘要：

A heuristic search assisted active localization method is proposed. The algorithm clusters the particles by using adaptive particle clustering algorithm. Then, path planning trees and solution space trees are constructed respectively. Priories of all the nodes in the solution space trees are calculated according to the priority evaluation function, and the problem of path search is solved by the priority queue-type branch-and-bound method. Finally, a localizing accuracy active enhancing method is presented to solve the particle divergence problem in a single particle cluster. Simulation experiments validate the feasibility of the methods.