A new adaptive high-order unscented Kalman filter was developed to improve the accuracy and robustness of target tracking. This algorithm helps track moving targets more accurately by adjusting to errors in the model used for tracking. By introducing a free parameter, the algorithm can better handle changes in target behavior and reduce the impact of model errors. The results of simulations show that this new algorithm is more precise and reliable compared to other existing tracking methods.