A5026726859- Inertial Sensor and Navigation
- Target Tracking and Data Fusion in Sensor Networks
- GNSS positioning and interference
- Robotics and Sensor-Based Localization
- Geophysics and Gravity Measurements
- Maritime Navigation and Safety
- Satellite Image Processing and Photogrammetry
- Control and Dynamics of Mobile Robots
- Vehicle Dynamics and Control Systems
- Underwater Vehicles and Communication Systems
- Advanced Vision and Imaging
- Adaptive Control of Nonlinear Systems
- Autonomous Vehicle Technology and Safety
- Advanced Sensor and Control Systems
- Video Surveillance and Tracking Methods
- Dynamics and Control of Mechanical Systems
- Traffic Prediction and Management Techniques
- Advanced Algorithms and Applications
- Advanced Image and Video Retrieval Techniques
- Hydraulic and Pneumatic Systems
- 3D Surveying and Cultural Heritage
Tsinghua University
2024
Naval University of Engineering
2021-2022
Unmanned SystemsAccepted Papers No AccessA Robust Visual Inertial Navigation Method for Illumination Challenging ScenesJiankang Qu, Xu Lyu, Ziyang Meng, Pengfei Gu, and Jun WangJiankang Lyu Search more papers by this author , Meng Gu Wang https://doi.org/10.1142/S2301385026500068Cited by:0 (Source: Crossref) PreviousNext AboutFiguresReferencesRelatedDetailsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend Library ShareShare onFacebookTwitterLinked InRedditEmail Cite...
In this study, both adaptive and robust one is proposed, considering that the properties of a classic unscented Kalman filter (UKF) can be degraded severely by outliers measured in contamination distribution effects time-varying noise. An UKF approach on Gaussian process regression- assisted Variational Bayesian proposed. The Variable (VB) method used to statistically approximate noise due strong nonlinearity inaccuracy system model. At same time, Process Regression (GPR) has advantage...
In order to solve the problem that spherical harmonic model has a large amount of calculation, especially in background aviation navigation, it is difficult realize real-time gravity compensation, compensation method based on back-propagation neural network (BPNN) proposed. Firstly, highest order/degree EIGEN-6C4 used calculate vector information planning navigation area, which regarded as true value. The disturbance and corresponding position are training data set BPNN. Then, BPNN obtained...
In this study, the problem of measuring noise pollution distribution by intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial error modeling, a nested dual Kalman filter framework structure developed. It consists unscented (UKF) master and slave filter. This method uses UKF for state estimation. At same time, exact measurement covariance estimated dependency The algorithm based adaptive (Dual-AUKF) has high accuracy robustness, especially in case...
Autonomous driving vehicle is a kind of unmanned on the ground. Navigation and positioning technology becoming an indispensable part practical applications, especially in intelligent transportation systems military fields. In this study, multi-source information fusion plays necessary role enhancing quality reliability navigation positioning. actual complex environment, accuracy requirements case nonlinear non-Gaussian distribution are fully considered. paper, new adaptive sharing factor...
The integrated navigation system based on the Global Navigation Satellite System (GNSS) in conjunction with strapdown inertial (SINS) and Doppler Velocity Logger (DVL) is essential for accurate long-distance maritime environments. However, error of gradually diverges due to inevitable velocity measurement DVL when GNSS outages occur. To ensure high navigational accuracy stability SINS, it necessary dynamically adjust damping state SINS provided externally. In this paper, we have developed a...
The gravity gradient is the second derivative of potential. A gradiometer can measure small change at two points, which contains more abundant navigation and positioning information than gravity. In order to solve problem passive autonomous, long-voyage, high-precision submarines, an aided method based on strapdown proposed. unscented Kalman filter framework used realize fusion inertial information. performance analyzed evaluated from six aspects: long voyage, measurement update period,...
High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global satellite system (SINS/GNSS) integrated system, and its plays an important role in performance evaluation system. Traditional filter methods usually assume that measurement noise conforms to Gaussian distribution, without considering influence pollution introduced by GNSS signal, which susceptible external interference. To address this problem, a high-precision method using...
For high-precision inertial navigation system, gravity disturbance has become a key factor restricting the further improvement of positioning accuracy. How to carry out effective and real-time compensation problem worthy attention. In this paper, method based on multilayer feedforward neural network is proposed, which can realize system. Firstly, highest order spherical harmonic model EIGEN-6C4 used calculate vector information in planned area, as training data set network. Then, obtained by...
Aiming to improve the reliability of SINS/GPS integrated navigation system, considering that traditional residual chi-square detection method is not efficient in detecting small mutations and slow mutations. An information fault for system based on AR measurement modeling proposed. This establishes an model measured data under no-fault conditions, combines Kalman filter obtain predicted value calculation. It avoids introduces observation pollution data, which leads failure statistics...