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.