New Kalman Filtering Algorithm for Passive-BD/SINS Integrated Navigation System Based on UKF

2009 ◽  
Vol 4 (2) ◽  
Author(s):  
Wang
Keyword(s):  
Kalman Filtering ◽  
Navigation System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Filtering Algorithm ◽  
Kalman Filtering Algorithm

A Measurement-Based Robust Adaptive Kalman Filtering Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 3773-3779 ◽  
Author(s):  
Yan Hong Chang ◽  
Hai Zhang ◽  
Qi Fan Zhou
Keyword(s):  
Kalman Filtering ◽  
Measurement Noise ◽  
Statistical Characteristics ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Measurement Systems ◽  
Filtering Algorithm ◽  
Gps Measurement ◽  
Kalman Filtering Algorithm ◽  
Robust Adaptive

In the case that the accuracy of standard kalman filter (SKF) declines when the noise statistical characteristics are unknown or changing, a measurement-based adaptive kalman filtering algorithm (MAKF) is presented. Based on the contrastive analysis of measurement characteristics of different measurement systems, MAKF is put forward to estimate adaptively the measurement noise variance R by co-difference measurement sequences. Simulation is performed by applying this algorithm to the GPS/INS integrated navigation system, the results show that MAKF can track the GPS measurement noise in real time on condition that the GPS measurement noise is unknown or changing, and the filtering accuracy and robustness are superior to those of SKF and an improved Sage-Husa adaptive kalman filtering algorithm.

Application of Federated Filter to AUV Based on Terrain-Aided SINS

2014 ◽  
Vol 711 ◽  
pp. 338-341 ◽  
Author(s):  
Qi Wang ◽  
Cheng Shan Qian ◽  
Zi Jia Zhang ◽  
Chang Song Yang
Keyword(s):  
Kalman Filtering ◽  
Navigation System ◽  
Autonomous Underwater Vehicles ◽  
Inertial Navigation ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Filtering Method ◽  
Long Time ◽  
Federated Filtering ◽  
Strapdown Inertial Navigation

To improve the navigation precision and reliability of autonomous underwater vehicles, a terrain-aided strapdown inertial navigation based on Federated Filter (FF) is proposed in this paper. The characteristics of strapdown inertial navigation system and terrain-aided navigation system are described in this paper, and Federated Filtering method is applied to the information fusion. Simulation experiments of novel integrated navigation system proposed in the paper were carried out comparing to the traditional Kalman filtering methods. The experiment results suggest that the Federated Filtering method is able to improve the long-time navigation precision and reliability, relative to the traditional Kalman Filtering method.

Application of Interval Kalman Filtering Algorithm in Integrated Navigation Data Fusion

2012 ◽  
Vol 433-440 ◽  
pp. 4059-4064
Author(s):  
Yun Feng Ma
Keyword(s):  
Kalman Filter ◽  
Kalman Filtering ◽  
Interval Matrix ◽  
Uncertain Parameters ◽  
Integrated Navigation ◽  
System Matrix ◽  
Inversion Algorithm ◽  
Filtering Algorithm ◽  
Kalman Filtering Algorithm ◽  
Time Accuracy

The traditional Kalman filter cannot be used directly when some system parameters such as certain elements of the system matrix are not precisely known or gradually change with time. Some uncertain parameters can be described as an interval model. An interval Kalman filtering algorithm is studied in this paper, which can be used to process a system with uncertain parameters. A simple inversion algorithm of interval matrix has been applied and its statistic performances and iterative form are similar to those of traditional Kalman filter. Simulation results show that such filtering algorithm can provide the real time accuracy error estimation and can be applied to such kind of low-cost integrated navigation system.

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