Tightly Coupled GNSS/INS Integration with Robust Sequential Kalman Filter for Accurate Vehicular Navigation
Open Access
- 20 January 2020
- Vol. 20 (2), 561
- https://doi.org/10.3390/s20020561
Abstract
With the development of multi-constellation multi-frequency Global Navigation Satellite Systems (GNSS), more and more observations are available for tightly coupled GNSS/Inertial Navigation System (INS) integration. Concerning the accuracy, robustness, and computational burden issues in the integration, we proposed a robust and computationally efficient implementation. The new tight integration model uses pseudorange, Doppler and carrier phase simultaneously, to achieve the maximum possible navigation accuracy for a single receiver. The resultant high-dimensional observation vector is then processed by a sequential Kalman Filter (KF) to improve the computational efficiency in the measurement update step. Based on the innovation of the sequential KF, a robust estimation method with Gaussian test is further devised to detect and adapt the faults in individual GNSS channels. Two field vehicular tests are conducted to evaluate the performance improvements of the proposed method, compared with loose coupling and conventional tight coupling. Test results in favorable environments indicate that the proposed method can significantly improve the velocity and attitude accuracy by 69.42% and 47.16% over loose coupling and by 64.75% and 30.88% over conventional tight coupling, respectively. Moreover, the computational efficiency is also improved by about 53.09% for the proposed method, compared with batch KF processing. In GNSS challenging environments, the proposed method also shows superiority in terms of velocity and attitude accuracy, and better bridging capability during the GNSS partial or complete outages. These results demonstrate that the proposed method is able to provide a more robust and accurate solution in real-time vehicular navigation.Keywords
This publication has 26 references indexed in Scilit:
- Multiantenna GNSS and Inertial Sensors/Odometer Coupling for Robust Vehicular NavigationIEEE Internet of Things Journal, 2018
- Tightly-Coupled Integration of Multi-GNSS Single-Frequency RTK and MEMS-IMU for Enhanced Positioning PerformanceSensors, 2017
- Evaluation on the impact of IMU grades on BDS + GPS PPP/INS tightly coupled integrationAdvances in Space Research, 2017
- Robust GPS/BDS/INS tightly coupled integration with atmospheric constraints for long-range kinematic positioningGPS Solutions, 2017
- Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban ScenariosSensors, 2017
- Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman FilterSensors, 2016
- High-Precision Vehicle Navigation in Urban Environments Using an MEM's IMU and Single-Frequency GPS ReceiverIEEE Transactions on Intelligent Transportation Systems, 2016
- PPP/INS tightly coupled navigation using adaptive federated filterGPS Solutions, 2016
- Tight integration of ambiguity-fixed PPP and INS: model description and initial resultsGPS Solutions, 2015
- Tightly coupled GPS/INS integration for missile applicationsAerospace Science and Technology, 2004