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Journal of Aerospace Science and Technology، جلد ۱۲، شماره ۲، صفحات ۱۱-۱۸
عنوان فارسی Improving the Reliability of GPS and GLONASS Navigation Solution in Urban Canyons using a Tuned Kalman Filter
چکیده فارسی مقاله Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
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Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Improving the Reliability of GPS and GLONASS Navigation Solution in Urban Canyons using a Tuned Kalman Filter
چکیده انگلیسی مقاله Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
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Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
کلیدواژه‌های انگلیسی مقاله GPS,GLONASS,Urban canyon positioning,Kalman Filter,Weighted least square
نویسندگان مقاله Ali Khavari |
Department of Electrical Engineering, Iran University of Science and Technology

S. Mohammad Reza Moosavi |
Department of Electrical Engineering, Iran University of Science and Technology

Amir Tabatabaee |
Samara National Research University, 34, Moskovskoye shosse, Samara, 443086, Russia

Hadi Shahriyar Shahhosseini |
Department of Electrical Engineering, Iran University of Science and Technology

نشانی اینترنتی https://jast.ias.ir/article_113995_3124a4bfdd57fc29400b71b6b2b2736e.pdf
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