【摘要】 针对无线传感器网络中的(TDOA)节点无源定位中的非线性优化问题，提出一种基于双种群粒子群(DIR-WOA)的鲸鱼优化的TDOA定位算法；在标准鲸鱼算法的基础上，引入混沌模型，改进粒子种群生成方式，利用主辅粒子群进行相互制约，有效解决粒子易陷入局部最优的问题，迅速得到全局最优解；仿真结果表明，改进算法相较于标准鲸鱼算法，增强了粒子搜索范围，算法收敛时间减少了0.568 8 s,定位误差减小到0.029 m。更多还原

【Abstract】 To solve nonlinear optimization of time difference of arrival(TDOA) node passive location in wireless sensor networks, a whale optimization TDOA location algorithm based on dual population particle swarm(DIR-WOA) is proposed. On the basis of the standard whale algorithm, the chaotic model is introduced to improve the particle population generation mode, and constrains the main and auxiliary particle swarm to each other, effectively solving the problems of particles easily falling into local optima and quickly obtaining global optima. Simulation results show that compared with the standard whale algorithm, the improved algorithm greatly enhances the search range of particle swarm, and reduces the convergence time by 0.568 8 s and the positioning error to 0.029 m.更多还原