Bian Hongwei
Naval University of Engineering
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Bian Hongwei.
Journal of Systems Engineering and Electronics | 2006
Bian Hongwei; Jin Zhihua; Tian Wei-feng
Abstract A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessels altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter (SKF) assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering (IAE-AKF) algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAE-AKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstrated that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.
2017 Forum on Cooperative Positioning and Service (CPGPS) | 2017
Dai Hai-fa; Ma Heng; Bian Hongwei; Wang Rongying
Based on the problem of the difficulty to set up the precise models for the information fuse method which bases on the Kalman filters, a new method based on the autoregression (AR) model is put forward in this paper. This method is one of the time series analysis methods, which uses the temporal correlation between the errors data to set up the AR model, and then the estimation results are utilized to fuse the location information; To detect and isolate the information fault timely, this paper suggests the fault detection and isolation method based on maximum solution separation; Finally, the feasibility of the algorithm is verified by the data collected from the actual sensors.
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on | 2013
Fan Songwei; Bian Hongwei
The small multi-rotors unmanned aerial vehicle (UAV) fits for complex narrow ship environment. Using it could improve the efficiency of the lots of ship task. The tasks include the carry mission and video mission could be performed by the small multi-rotors UAV. According to the mission requirements: low weight, small size, antivibration, low power consumption, and easy interfacing, the vehicle system is designed in four subsystems: flight power subsystem, long-range wireless data link subsystem, flight control subsystem and ground control subsystem. The model vehicle is constructed and the flying experiment shows that the model vehicle could realize steady flight and Airline flight, meets the design requirements.
2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC) | 2013
Gao Xin; Bian Hongwei; Fan Songwei
In order to restrain the Schuler oscillation in inertial navigation system (INS), external velocity measurement was used as a reference to design optimal damping algorithm based on the Kalman filter. The error models of INS horizontal loops were studied according to its control model and Kalman filters were adopted to estimate the platform misalignment errors, velocity errors and gyro drift. Then based on the optimal control thought, feedback correction algorithm was designed and the estimate was put forward to damp Schuler oscillation and Foucault oscillation. Compared with the traditional damping network, optimal damping algorithm developed the transient response characteristics, in addition it could be used to estimate and compensate gyro drift. Simulation results shown that this algorithm could effectively suppress the Schuler oscillation and improve accuracy of inertial navigation system.
Archive | 2013
Bian Hongwei; Liu Wenchao; Wang Rongying; Wen Chaojiang; Ma Heng; Fan Songwei; Zhang Yuxin
Zhongguo Guanxing Jishu Xuebao | 2016
Wang Rongying; Liu Wenchao; Bian Hongwei; Gao Xin
Zhongguo Guanxing Jishu Xuebao | 2016
Wang Rongying; Liu Wenchao; Bian Hongwei; Gao Xin
Archive | 2016
Chen Lei; Wang Rongying; Ma Heng; Bian Hongwei; Xiao Dou
Ship Electronic Engineering | 2013
Bian Hongwei
Archive | 2013
Bian Hongwei; Wang Rongying; Fan Songwei; Han Bo; Gao Xin