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GIS@development


November 2002
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Methods for improving the accuracy and reliability of vehicle-borne GPS Intelligence Navigation System

Fenglin Guo
Fenglin Guo
School of Civil & Environmental Engineering,
College of Engineering, Nanyang Technological University, Singapore
Block N1-B2a-06, 50 Nanyang Avenue, Singapore 639798
Tel: +65-67904105(O)
Email: cflguo@ntu.edu.sg

Yuesheng Ji
School of Civil Engineering,
Northern Jiaotong University, Beijing, China

Guorong Hu
Guorong Hu
GPS Centre, College of Engineering,
Nanyang Technological University, Singapore


With the development of GPS-based navigation, computer and communication, intelligent vehicle navigation system will play a more important role in future transportation systems. Vehicle-borne GPS can provide positioning and navigation information quickly and accurately at relatively low cost. GPS has made a significant impact on almost all positioning and navigation applications including vehicle-borne GPS intelligence navigation system (VINS) (Allison, et al., 1999; Haddad, et al., 1999; He et al., 1998; Hu et al., 2000). However, GPS alone is insufficient to maintain continuous positioning because of inevitable obstructions caused by buildings and other natural features. When GPS signals are blocked or lost, the precision of positioning will be reduced to unacceptable level. Therefore, it is necessary to improve the accuracy and reliability of VINS. This paper presents three methods to improve the accuracy and reliability of VINS, viz., dead reckoning (DR), differential GPS (DGPS) and map matching. The advantages and disadvantages of these augmentation methods are analyzed. The results of a real application and simulation experiments are also provided. Further suggestions to assure the accuracy and reliability of VINS are also proposed.

Dead Reckoning (DR) Method
Dead reckoning method determine a vehicle’s position relative to an initial location by integrating measured distance increments and directions of travel (Hong, 1997). The distance increments are measured using a distance sensor. The directions can be derived through a course sensor. When the GPS signals are degraded, the position of a vehicle at ti epoch can be determined from the direction angle (a)and distance (D) components:




where
(X0 the initial position at t0;
(Xi,Yi) the position at ti;
Dk, ak distance and direction from (X0,Y0) at t0 to (Xk, at tk each respectively.

The course sensor could be derived from geomagnetism, gyroscope or using information from the difference between the velocity of the left tyre and right tyre. The distance sensor may be tapped from the vehicle’s odometer or from a velocity sensor. The navigation accuracy of DR is a function of the distance traveled. Longer distances tend to incur greater accumulated errors. Errors of DR are mainly caused by characteristics of the sensors and from environmental factors such as terrain and uneven tyre pressures. Hence, DR per sec cannot be used over a long period. Navigation system which combines measurements from both DR and GPS system can mitigate the errors by continuously calibrating DR sensors by acquired GPS positions Another mode of DR system is INS (Inertial Navigation System) which can continuously provide direction and acceleration (Yuan, et al., 1993). Starting from a known position, INS uses the variations in positions to determine the trail of a vehicle. Errors of INS increase with the square of time. Hence, INS alone has its limitations. A combined GPS and INS solution could overcome shortcomings of each other and is an effective method for providing continuous and precise navigation for vehicles. Examples can be seen from literature of Allison, et al., (1999).

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