In the strapdown inertial navigation system,the attitude information is obtained through an inertial measurement unit(IMU)device,which mainly includes a triaxial gyroscope,a triaxial accelerometer and a triaxial magne...In the strapdown inertial navigation system,the attitude information is obtained through an inertial measurement unit(IMU)device,which mainly includes a triaxial gyroscope,a triaxial accelerometer and a triaxial magnetometer.However,IMU sensors have system noise and drift errors,and these errors can accumulate over time,which makes it difficult to control the attitude accuracy.In order to solve the problems of gyro drift over time and random errors generated by the surrounding environment,this paper presents an attitude calculation algorithm based on wavelet neural network-extended Kalman filter(WNN-EKF).The wavelet neural network(WNN)is used to optimize the model and compensate the extended Kalman filter’s own model error.Through the semi-physical simulation experiment,the results show that the algorithm improves the accuracy of attitude calculation and enhances the self-adaptability to the environment.展开更多
基金National Natural Science Foundation of China(No.61863024)Basic Research Innovation Group Program of Gansu Province(No.1606RJIA327)+2 种基金Higher Education Research Project Funding of Gansu Province(No.2018C-11)Natural Foundation of Gansu Province(No.18JR3RA107)Science and Technology Program Funding of Gansu Province(No.18CX3ZA004)。
文摘In the strapdown inertial navigation system,the attitude information is obtained through an inertial measurement unit(IMU)device,which mainly includes a triaxial gyroscope,a triaxial accelerometer and a triaxial magnetometer.However,IMU sensors have system noise and drift errors,and these errors can accumulate over time,which makes it difficult to control the attitude accuracy.In order to solve the problems of gyro drift over time and random errors generated by the surrounding environment,this paper presents an attitude calculation algorithm based on wavelet neural network-extended Kalman filter(WNN-EKF).The wavelet neural network(WNN)is used to optimize the model and compensate the extended Kalman filter’s own model error.Through the semi-physical simulation experiment,the results show that the algorithm improves the accuracy of attitude calculation and enhances the self-adaptability to the environment.
