The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated.A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy...The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated.A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy of the INS/GNSS integrated navigation system.The adaptive filtering algorithm aims to estimate and adapt the unknown state noise covariance Q in high dynamic conditions,when the measurement noise covariance R is assumed to be known empirically in advance.The new adaptive Kalman filter based on the innovation sequence and pseudo-measurement vector approach makes it more effective to estimate and adapt Q.The simulation results and semi-physical experiments show that the application of the proposed adaptive Kalman filter can guarantee a higher estimation accuracy of the state variables.展开更多
基金supported by the project“Component’s digital transformation methods'fundamental research for micro-and nanosystems”(No.#0705-2020-0041).
文摘The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated.A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy of the INS/GNSS integrated navigation system.The adaptive filtering algorithm aims to estimate and adapt the unknown state noise covariance Q in high dynamic conditions,when the measurement noise covariance R is assumed to be known empirically in advance.The new adaptive Kalman filter based on the innovation sequence and pseudo-measurement vector approach makes it more effective to estimate and adapt Q.The simulation results and semi-physical experiments show that the application of the proposed adaptive Kalman filter can guarantee a higher estimation accuracy of the state variables.
