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An integrated land vehicle navigation system based on context awareness

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Abstract

In the complex urban environments, land vehicle navigation purely relying on GNSS cannot satisfy user needs due to the loss of satellite signals caused by obstructions such as buildings, tunnels, and trees. To solve this problem, we introduce a GPS-/MSINS-/magnetometer-integrated urban navigation system based on context awareness. In this system, the data from the Micro Strapdown Inertial Navigation System (MSINS) are used to analyze and detect the context knowledge of vehicles, whose sensor errors can be compensated by the heuristic drift reduction algorithm for different motion situations. When GPS is available, the vehicle position can be estimated by unscented Kalman Filter, whereas in the case of GPS outages, the vehicle attitude is provided by an attitude and heading reference system and the motion constraints-aided algorithm is used to complete the positioning. In the experiment validation, the integrated navigation system is set up by low-cost inertial sensors. The result shows that the proposed system can achieve high accuracy when GPS is available. For most of the time without GPS, the system can guarantee the positioning precision of 10 m and compensate the errors of MSINS effectively, which fully satisfies positioning needs in complex urban environments.

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Acknowledgments

This project is supported by the key program of the National Natural Science Foundation of China (Grant No. 61039003), the National Natural Science Foundation of China (Grant No. 41274038), the Aeronautical Science Foundation of China (Grant No. 2013ZC51027), the Aerospace Innovation Foundation of China(CASC201102), and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Nan Gao & Long Zhao

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  1. Nan Gao
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  2. Long Zhao
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Correspondence to Long Zhao.

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Gao, N., Zhao, L. An integrated land vehicle navigation system based on context awareness. GPS Solut 20, 509–524 (2016). https://doi.org/10.1007/s10291-015-0460-6

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  • DOI: https://doi.org/10.1007/s10291-015-0460-6

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