Multi-Sensor Data Fusion for Future Telematics Application

Kim, Seong-Baek; Lee, Seung Yong; Choi, Jihoon; Choi, Kyoung-Ho; Jang, Byungtae

doi:10.5140/jass.2003.20.4.359

Cited by 1 publication

(2 citation statements)

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“…But the measurement error of INS will accumulate if it is not calibrated on-line. Several IMU error models have been derived (Kim, Lee, Choi & al., 2003), which are all (Jekeli, 2001). In this model, the errors modulated by the Earth's spin rate are neglected because of short-range nature of our present application.…”

Section: Hardware Malfunctionmentioning

confidence: 99%

“…Apart from safety issues, the next generation of vehicles will allow the driver and passengers to have access to a broad range of services, such as path planning, navigation, guidance and tracking, which are based on information technologies, telecommunications and telematics. Future vehicles are likely to be as well mobile offices, information centers on wheel, or e-nodes connected to the web and other networks (Kim, Lee, Choi & al., 2003). To supply those services and to provide the adequate information contents to the driver and passengers, it is required to determine in real-time the vehicle's position as accurately and efficiently as possible.…”

Section: Introductionmentioning

confidence: 99%

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An Overview of Positioning and Data Fusion Techniques Applied to Land Vehicle Navigation Systems

Gingras

2009

Automotive Informatics and Communicative Systems

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In this chapter, the authors will review the problem of estimating in real-time the position of a vehicle for use in land navigation systems. After describing the application context and giving a definition of the problem, they will look at the mathematical framework and technologies involved to design positioning systems. The authors will compare the performance of some of the most popular data fusion approaches and provide some insights on their limitations and capabilities. They will then look at the case of robustness of the positioning system when one or some of the sensors are faulty and will describe how the positioning system can be made more robust and adaptive in order to take into account the occurrence of faulty or degraded sensors. Finally, they will go one step further and explore possible architectures for collaborative positioning systems, whereas many vehicles are interacting and exchanging data to improve their own position estimate. The chapter is concluded with some remarks on the future evolution of the field.

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Section: Hardware Malfunctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%