Intelligently Tuned Wavelet Parameters for GPS/INS Error Estimation

查看全文 作　　者：Ahmed Mudheher [1]Hasan;Khairulmizam [1]Samsudin;Abd Rahman [1]Ramli

机构地区：[1]Computer Systems Research Group, Department of Computer and Communication Systems, University Putra Malaysia, 43400 UPM-Serdang, Malaysia

出　　处：《International Journal of Automation and computing》索引2011年第8卷第4期,共10页

基　　金：supported in part by Graduate School of Studies through the Graduate Research Fellowship (GRF) sponsored by University Putra Malaysia 摘　　要：This paper presents a new algorithm for de-noising global positioning system (GPS) and inertial navigation system (INS) data and estimates the INS error using wavelet multi-resolution analysis algorithm (WMRA)-based genetic algorithm (GA) with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of the most exploited techniques that have been recently used to increase the precision and reliability of the integrated GPS/INS navigation system. To ameliorate the WMRA algorithm, GA was exploited to optimize the wavelet parameters so as to determine the best wavelet filter, thresholding selection rule (TSR), and the optimum level of decomposition (LOD). This results in increasing the robustness of the WMRA algorithm to estimate the INS error. The proposed intelligent technique has overcome the drawbacks of the tedious selection for WMRA algorithm parameters. Finally, the proposed method improved the stability and reliability of the estimated INS error using real field test data. 关键词：误差估计智能技术 INS GPS 波参数小波多分辨率分析遗传算法调整

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Intelligently Tuned Wavelet Parameters for GPS/INS Error Estimation

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