Evaluation of a segmented navigation filter approach for vehicle self-localization in urban environment
- 94 Downloads
Advanced road safety automotive applications require reliable (available) and robust (e.g., GNSS outages) position, velocity and heading information. The velocity information generated by a GNSS receiver, in general, is affected by less errors then the further generated position and ranges. Determination of the measurement weighting for the range information is not in all cases appropriate. Unidentified multipath effects may reduce the quality but do not affect the signal to noise ratio.
This paper explores the concept of a segmented Kalman navigation for a vehicle navigation filter which fuses automotive onboard sensor data. A position filter providing only position information and a dynamic filter covering velocity and sensor error information are implemented in this approach. The dynamic filter is only aided by velocity information provided either by odometer or GNSS. The position filter is aided by the GNSS range information.
The evaluation covers the processing of simulated sensor data and the usage of real time automotive sensor data recorded in scenarios with reduced GNSS quality in urban area.
KeywordsRoot Mean Square GNSS Inertial Measurement Unit Clock Error Test Drive
Unable to display preview. Download preview PDF.
- 1.Lu, B. Development of a Segmented GPS/INS Kalman Filter for Vehicle Localization, Master thesis, Karlsruhe Institute of Technology, October 2012.Google Scholar
- 2.Farrell, J.L., GPS/INS-Streamlined, Bd. 49, USA, Journal of the Institute of Navigation, 2002–2003.Google Scholar
- 3.Gao, J., Development of Precise GPS/INS/Wheel Speed Sensor/Yaw Rate Sensor Integrated Vehicular Positioning System, University of Calgary, 2006.Google Scholar
- 4.Groves, P.D., Principles of GNSS, Inertial and Multisensor Integrated Navigations Systems, Artech House, 2008.Google Scholar
- 5.Wankerl, M., Popp, M., and Trommer, G.F., Robustness improvements and comparisons of automotive GPS-INS navigation filters in suburban scenarios fusing automotive on-board sensors, Proceedings of Inertial Sensors and Systems-Symposium Gyro Technology, Karlsruhe, 2012.Google Scholar
- 6.Ko-PER, 2013, [online], available: http://ko-fas.de/english/ko-per—cooperative-perception.html.
- 8.Farrell, J.L., Carrier phase processing without integers, Proceedings of the 57th Annual Meeting of the Institute of Navigation, Albuquerque, 2001.Google Scholar