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Author Divband, Mohammad
Source CiteSeerX
Content type Text
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Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Particle Swarm Optimization ♦ Gradient Descent ♦ Training Wavelet Neural Network ♦ Predict Dgps Correction ♦ Dgps System ♦ Base Station ♦ Basic Gps System ♦ Gps Measurement ♦ Low Cost Gps Receiver ♦ Differential Gps ♦ Arbitrary Number ♦ Civilian Us ♦ Dgps Correction ♦ Error Real-time Prediction ♦ Wavelet Neural Network ♦ Many Part ♦ Performance Evaluation ♦ Wnn-pso Method ♦ Selective Availability ♦ Experimental Result ♦ Truth Point
Abstract Abstract—The performance of the basic GPS system has been augmented by the technique of Differential GPS (DGPS) for military as well as civilian uses. Performance evaluation of a DGPS system requires the availability of DGPS corrections as functions of time. In many parts of the world, a lack of base stations and other infrastructure makes it impossible to have the desired quality and quantity of data. Thus, it is useful to develop a system, which can generate GPS measurements for an arbitrary number of truth points. In this paper, Wavelet Neural Network (WNN) is used to online predict the corrections for Selective Availability (S/A) on and off. Gradient Descent (GD) and Particle Swarm Optimization (PSO) are used to train and optimize the weights of WNN. Experimental results for the errors real-time prediction show the feasibility and effectiveness of WNN-PSO. The results prove that the proposed WNN-PSO method has better accuracy in a low cost GPS receiver.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study