基于改进灰狼优化算法的射频识别室内定位算法

RFID indoor positioning algorithm based on improved grey wolf optimization algorithm

为了解决当前射频识别室内定位算法中存在的定位误差较大问题,把智能算法应用到室内定位算法中,提出了一种基于改进灰狼优化算法的射频识别室内定位算法。针对传统的灰狼优化算法中存在的收敛精度低、收敛速度慢和容易得到全局最优解问题,在算法中引入基于幂函数的非线性收敛因子提高算法的寻优能力;采用基于指数因子的位置更新策略提高算法的收敛精度;加入多次位置更新策略使得算法容易跳出局部最优解。实验结果表明:三边定位算法的定位误差为0.887 m,基于改进的灰狼优化算法的室内定位算法能够有效实现目标定位,定位平均误差为0.276 m,定位精度明显提高。

To solve the problems of large positioning error of Radio Frequency identification indoor positioning algorithm,an indoor positioning algorithm based on improved gray wolf optimization algorithm is proposed by applying intelligent algorithm to indoor positioning algorithm.For the traditional grey wolf optimization algorithm has the problem of low convergence accuracy and easy to get the global optimal solution,the nonlinear convergence factor based on the power function to increase the algorithm's optimization-seeking ability;the exponential factor-based position update strategy is used to heighten he convergence accuracy of the algorithm;and adds a multiple position update strategy to make the algorithm easily jump out of the local optimal solution.The experimental results show that the positioning error of the traditional trilateral localization algorithm is 0.887 m,and Indoor localization algorithm based on improved grey wolf optimization algorithm can effectively achieve the target positioning with an average positioning error of 0.276 m,which significantly improves the positioning accuracy.