DEVELOPMENT OF A MAP MATCHING ALGORITHM FOR CAR NAVIGATION SYSTEM USING FUZZY Q-FACTOR ALGORITHM
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Many hybrid algorithms which estimate car's position and velocity from GPS signals and INS signals suffer from the unknown GPS noise characteristic such as S/A noise. The unknown characteristic makes it impossible to get rid of the noise perfectly. As a result, the estimated position information from the hybrid algorithms will be contaminated with undesirable position errors. Many researchers are trying to eliminate such noise. It is very desirable and effective to use a digital road map to correct the position error, as reliable road maps will be easily available. This method is known as map matching method. In this paper, a new map matching method is suggested named as Q-factor algorithm, which can exactly give the position of a car on a road. The Q-factor algorithm is very easy to calculate, and calculations will not exponentially increase with the increase in the number of junctions. It makes the Q-factor algorithm very appropriate for car navigation systems. The effectiveness of this algorithm is shown with real road experiments. For experimental testing, a car navigation system is built with a DSP chip. It uses one GPS receiver, one vehicle speed sensor and one vertical gyroscope. For the covering abstract see IRRD E102946.