IEEE Sensors Journal · 2019 · 32 citations · 9 references
EngineeringMechatronics EngineeringRobotics EngineeringGlobal Navigation Satellite SystemsSensor FusionSensorsKalman FilteringMultisensor Data IntegrationRedundancy ResolutionAccuracyData FusionGyroscopesKalman Filter FusionMulti-sensor FusionRedundant ControlSensor Fusion For NavigationSystems Navigation
Sensor-level redundancy technology has gradually become the development direction of the new generation of navigation systems, so the data fusion method for redundant sensor systems has become a key factor affecting the output accuracy of redundant system. Usually, the least square method is used for data fusion of redundant sensor system, but the fusion accuracy is low, so this paper explores the application of virtual gyroscope technology in redundant oblique sensor system. The redundant 3 gyroscope system, 5 gyroscope system, and 8 gyroscope system are designed. The least square method and virtual gyroscope technology are used for data fusion. And, the Kalman filter optimization scheme is designed for Multi-gyroscope system. The experimental results show that the fusion accuracy of virtual gyroscope technology is higher than that of least square method, and the running time of optimized Kalman filter algorithm is greatly shortened. When the filter is stable, the X axis’s <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1{\sigma }$ </tex-math></inline-formula> standard deviation of the proposed method is 2.5 times lower than that of the least square method, and 4.3 times in Y axis, and 3.3 times in Z axis.
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Björn Wittenmark · Automatica · 1993 · 3.1K citations
Honglong Chang, Liang Xue, Chengyu Jiang et al. · IEEE Transactions on Instrumentation and Measurement · 2012 · 74 citations · Full text
Engineering, Electrical Engineering, Mechanical Engineering +15