A Fine Anti-Noise Algorithm Based on Matrix Block Variational Estimation in Underwater Navigation

Autonomous underwater vehicle (AUV) has been widespread to oceanography applications based on a reliable navigation. The complex underwater environment leads to more velocity measurement errors of AUV, so it is difficult to determine the accurate navigation and positioning information. To solve the problem of non-Gaussian noise in the underwater navigation, this paper proposes an anti-noises algorithm based on matrix block variational estimation (AN-MBVE) method. The matrix block method is used to divide the measurement noises into two parts: Gaussian noises, and non-Gaussian noises. Then, the accurate measurement noise is estimated by using the variational estimation method. The state vector and the error covariance matrix are derived by using the precise measurement noises. Simulation results demonstrate the superiority of the proposed AN-MBVE compared with the traditional extended Kalman filter under the condition of the complex noises.