论文部分内容阅读
基于模糊遗传算法发展了一种新的数据关联算法。数据关联的静态部分靠一个模糊遗传算法来得出量测组合序列和 S-D分配的 m个最优解。在数据关联的动态部分 ,将得到的 S-D分配的 m个最优解在一个基于多种群模糊遗传算法的动态 2 D分配算法中依靠一个卡尔曼滤波估计器估计出移动目标各个时刻的状态。这一基于分配的数据关联算法的仿真试验内容为被动式传感器的航迹形成和维持的问题。仿真试验的结果表明该算法在多传感器多目标跟踪中应用的可行性。另外 ,对算法发展和实时性问题进行了简单讨论。
A New Data Association Algorithm Based on Fuzzy Genetic Algorithm. The static part of the data association relies on a fuzzy genetic algorithm to derive the m optimal solutions to the combined sequence and S-D assignment. In the dynamic part of data association, the obtained m optimal solutions of S-D distribution are relied on a Kalman filter estimator in a dynamic 2 D allocation algorithm based on multi-population fuzzy genetic algorithm to estimate the states of moving objects at each moment. The simulation experiment based on the distributed data association algorithm is a problem of track formation and maintenance of passive sensors. Simulation results show that the algorithm is feasible in multi-sensor multi-target tracking. In addition, the algorithm development and real-time issues are briefly discussed.