A covariance shaping filtering method for tightly-coupled MIMU/GNSS of UAV
| Autor: | Bangsheng Fu, Tianyu An, Jiangtao Xu, Yong Hao, Bin Liu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010504 meteorology & atmospheric sciences
Computer science 020209 energy Aerospace Engineering 02 engineering and technology Filter (signal processing) Kalman filter Covariance Sensor fusion 01 natural sciences Adaptive filter GNSS applications Inertial measurement unit Robustness (computer science) Control theory 0202 electrical engineering electronic engineering information engineering 0105 earth and related environmental sciences |
| Zdroj: | Aircraft Engineering and Aerospace Technology. 91:1257-1267 |
| ISSN: | 1748-8842 |
| DOI: | 10.1108/aeat-07-2018-0211 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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