01125535

Component

https://doi.org/10.3141/2105-10

http://scholar.google.com....+Yu&publication_year=2009

Applications of an intelligent transportation system (ITS) often require wireless communication networks to support navigation and location identification, which is emerging as an important research issue in ITS. Of the various infrastructures for supporting ITS development, the wireless sensor network is the most commonly used medium to transmit data from a target source to the receiving sensors, between sensors, or both. Such data, often referred to as geolocation data, can then be used to calculate the time difference of arrival (TDOA) to the various sensors for the purpose of precise location identification. However, the limitation on the system bandwidth and energy resources motivates the use of data compression within the network when data are transmitted between sensors. This paper presents three data compression approaches specifically designed for geolocation data transmitted between sensors within a wireless communication network for the purposes of transportation target identification and location-finding. The approaches include the wavelet transform with arithmetic encoding method, the wavelet packet analysis with the Fisher-information method, and the Texas Southern University model (the monotone increase method). The effectiveness of each presented method is evaluated by calculation of the precision of TDOA from the decompressed data, which are used for determination of source location. Sensitivity analysis is conducted on all the presented methods in relation to compression ratio, signal-to-noise ratio, and computational time. A comparison of the three methods permits recommendation of the optimal compression tool for various applications.

01141653

09-0694

English

pp 71-82

2009

Transportation Research Record: Journal of the Transportation Research Board

9780309126205

Print

Figures (10) ; References (26)

Data compression; Intelligent transportation systems; Sensors; Wireless communication systems

Geolocation; Target identification

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 30 2009 4:56PM

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