Cooperative Localization of Ground Targets Based on Improved Adaptive Grid Interactive Multiple Model Algorithm

Aiming at the problem of strong maneuverability of ground targets, unpredictable motion patterns, and difficulty in accurate positioning, the application of adaptive grids, interactive multiple models, and iterative extended Kalman filtering in collaborative positioning of ground targets was studied. In order to cover the motion form of the ground target, an interactive multi-model is used to design a multi-model framework. At the same time, the grid jump of the adaptive grid algorithm is used to complete the adaptive adjustment of the model set. To improve the accuracy of nonlinear approximation, iteratively extended Kalman filtering algorithm is designed to filter and improve the adaptive grid interactive multi-model algorithm. The simulation results show that compared with the adaptive grid interactive multi-model algorithm, this method can further improve the accuracy of the coordinated localization of ground targets, and the calculation amount is still better than the interactive multi-model algorithm with increasing models.