8 Papers
31 Citations
Chen Jiang is an academic researcher from China University of Mining and Technology. The author has contributed to research in topics: Kalman filter & GPS/INS. The author has an hindex of 4, co-authored 5 publications.
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Papers
A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.
TL;DR: A novel adaptive H-infinity filtering algorithm is presented, which integrates the adaptive Kalman filter and the H-Infinity filter in order to perform a comprehensive filtering algorithm and has multiple advantages compared to the other filtering algorithms.
38
Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems.
TL;DR: A new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter.
31
A Novel Adaptively-Robust Strategy Based on the Mahalanobis Distance for GPS/INS Integrated Navigation Systems.
Chen Jiang,Shu-Bi Zhang +1 more
TL;DR: Results show that both the influences of model deviations and outliers are weakened effectively by using the proposed adaptive robust filtering scheme, and the proposed scheme is easy to implement with a reasonable calculation burden.
17
A Novel Robust Interval Kalman Filter Algorithm for GPS/INS Integrated Navigation
TL;DR: The noise data reduction and the robust estimation methods are both introduced into the proposed interval Kalman filter algorithm and the new algorithm is equal to the standard Kalman Filter in terms of computation, but superior for managing with outliers.
A Multi-GNSS/IMU Data Fusion Algorithm Based on the Mixed Norms for Land Vehicle Applications
Chen Jiang,Dongbao Zhao,Qiuzhao Zhang,Wenkai Liu +3 more
TL;DR: In this paper , a mixed norm-based data fusion algorithm is proposed, and the hypothesis test statistics are constructed and adopted based on the chi-square distribution for the land vehicle data collected through the multi-GNSS and the IMU (Inertial Measurement Unit).