Adaptive Kalman filtering methods for tracking GPS signals in high noise/high dynamic environments

2007 ◽  
Author(s):  
Qiyao Zuo ◽  
Hong Yuan ◽  
Baojun Lin
Keyword(s):  
Kalman Filtering ◽  
Dynamic Environments ◽  
High Noise ◽  
High Dynamic

A covariance shaping filtering method for tightly-coupled MIMU/GNSS of UAV

2019 ◽  
Vol 91 (10) ◽  
pp. 1257-1267 ◽  
Author(s):  
Bin Liu ◽  
Jiangtao Xu ◽  
Bangsheng Fu ◽  
Yong Hao ◽  
Tianyu An
Keyword(s):  
Real Time ◽  
Kalman Filtering ◽  
Adaptive Filter ◽  
Dynamic Environments ◽  
Content Type ◽  
Filtering Method ◽  
Time Performance ◽  
Dual Channel ◽  
Tightly Coupled ◽  
Parallel Filter

Purpose Regarding the important roles of accuracy and robustness of tightly-coupled micro inertial measurement unit (MIMU)/global navigation satellite system (GNSS) for unmanned aerial vehicle (UAV). This study aims to explore the efficient method to improve the real-time performance of the sensors. Design/methodology/approach A covariance shaping adaptive Kalman filtering method is developed. For optimal performance of multiple gyros and accelerometers, a distribution coefficient of precision is defined and the data fusion least square method is applied with fault detection and identification using the singular value decomposition. A dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed. Findings Hardware-in-the-loop numerical simulation was adopted, the results indicate that the gain of the covariance shaping adaptive filter is self-tuning by changing covariance weighting factor, which is calculated by minimizing the cost function of Frobenius norm. With the improved method, the positioning accuracy with tightly-coupled MIMU/GNSS of the adaptive Kalman filter is increased obviously. Practical implications The method of covariance shaping adaptive Kalman filtering is efficient to improve the accuracy and robustness of tightly-coupled MIMU/GNSS for UAV in complex and dynamic environments and has great value for engineering applications. Originality/value A covariance shaping adaptive Kalman filtering method is presented and a novel dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed, to improve the real-time performance in complex and dynamic environments.

scholarly journals Evaluation of a Cubature Kalman Filtering-Based Phase Unwrapping Method for Differential Interferograms with High Noise in Coal Mining Areas

Sensors ◽  
2015 ◽  
Vol 15 (7) ◽  
pp. 16336-16357 ◽  
Author(s):  
Wanli Liu ◽  
Zhengfu Bian ◽  
Zhenguo Liu ◽  
Qiuzhao Zhang
Keyword(s):  
Coal Mining ◽  
Kalman Filtering ◽  
Phase Unwrapping ◽  
High Noise ◽  
Mining Areas
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