Penalty Function Based Anchor-Free Positioning

Typically, anchor-free localization is considered as a nonlinear programming problem in the existing literatures. However, the nonlinear programming algorithms can only achieve constrained optimization and the localization accuracy of such algorithms depends on the precision of initial coordinators, which are the inputs of the algorithm and usually obtained based on GPS. Due to this defect, the algorithm is invalid in GPS-denied area, such as indoor area, dense urban area and forest. In our research, we combined nonlinear programming algorithm with penalty function to solve this problem. Our simulation results show that the localization accuracy of proposed algorithm is not affected by the precision of the initial coordinators, even when the initial coordinators is set randomly. Performance comparisons are also presented to show the improvement of this algorithm.