一种改进遗传算法在TDOA定位中的应用

Application of Enhanced Genetic Algorithm in TDOA Location

针对TDOA定位估计中遇到的非线性最优化问题,提出了一种基于改进遗传算法的TDOA定位方法。在遗传算法中引入了排挤机制小生境,采用欧氏距离衡量个体间隔,设置小生境半径为动态变化,并且加入精英保留策略,有效的缓解了遗传算法容易陷入局部最优的问题。仿真结果表明,改进算法性能稳定,能缓解早熟收敛问题,定位精度高于其它算法。

A novel positioning algorithm based on genetic algorithm （GA） is proposed for the nonlinear optimization in TDOA - based location. The algorithm is obtained by introducing crowding niche technology to GA, individual interval is measured by Euclidean distance, the niche radius is set as dynamic function, and elitist strategy is added in the process, which effectively alleviates the problem that GA is likely to fall into local optimum. The simulation result indicates that the improved algorithm is stable and can mitigate the premature convergence, and it has higher accuracy than other algorithms.