فیلتر کالمن دو اصلاح شده بدون بو و شتاب اطلاعات در برآورد سطحی خودروی بدون سرنشین

The stability problem is one of the existing problems of unscented Kalman filter (UKF), which due to the nonlinearity and complexity of system. The precision will be decreased or even UKF will be halted when the algorithm can't ensure the state covariance to be positive semidefinite. Based on decomposition of state covariance, the paper first reviews two modified UKFs which can enhance the state covariance to be positive semidefinite, then describes a method which combines the modified UKFs with acceleration measurement together to unmanned surface vehicle (USV) state estimation which main advantage lies in binding UKF with acceleration to simplify the system estimation model, so that it becomes an online estimation algorithm with higher precision and lower calculation complexity.