Abstract
Conventionally, all of the sensors, except the IMUs, function as aiding sensors in the multisensor integrated kinematic positioning and navigation. In this way, the IMU measurements are only used in free inertial navigation calculation, not through measurement update in Kalman filter (KF) between two adjacent aiding measurement epochs. This paper strives for a novel structure of IMU/GNSS integration KF, which deploys a kinematic trajectory model as the core of the KF system model and utilizes all of the measurements, inclusive of the ones from IMUs, through measurement updates. This novel multisensor integration strategy takes advantage of modern computing technology and well advances the realization of Kaman filter for a better utilization of the IMU measurements, especially either with low-cost IMUs or in poor GNSS and/or GNSS denied environment. Moreover, one no longer needs to distinguish between the core sensors and the aiding sensors. The conceptual comparison with the conventional error-state and error measurement based inertial navigation integration shows its advantages. The results from real road tests along with discussions are also presented.
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The authors sincerely acknowledge the financial support through research grant provided by Natural Sciences and Engineering Council (NSERC) of Canada.
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Wang, JG., Qian, K., Hu, B. (2015). An Unconventional Full Tightly-Coupled Multi-Sensor Integration for Kinematic Positioning and Navigation. In: Sun, J., Liu, J., Fan, S., Lu, X. (eds) China Satellite Navigation Conference (CSNC) 2015 Proceedings: Volume III. Lecture Notes in Electrical Engineering, vol 342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46632-2_65
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DOI: https://doi.org/10.1007/978-3-662-46632-2_65
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