Precise outdoor localization with a GPS–INS integration system
This paper proposes a precise outdoor localization algorithm with the integration of Global Positioning System (GPS) and Inertial Navigation System (INS). To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and IN...
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Veröffentlicht in: | Robotica 2013-05, Vol.31 (3), p.371-379 |
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description | This paper proposes a precise outdoor localization algorithm with the integration of Global Positioning System (GPS) and Inertial Navigation System (INS). To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and INS data. To reduce the noise from the internal INS sensors, the discrete wavelet transform and variable threshold method are utilized, and to fuse the GPS and INS data while filtering out the noise caused by the acceleration, deceleration, and unexpected slips, the Unscented Particle Filter (UPF) is adopted. Conventional de-noising methods mainly employ a combination of low-pass and high-pass filters, which results in signal distortion. This newly proposed system also utilizes the vibration information of the actuator according to the fluctuations of the velocity to minimize the signal distortion. The UPF resolves the nonlinearities of the actuator and non-normal distributions of the noise more effectively than the conventional particle filter (PF) or Extended Kalman Filter–PF. The superiority of the proposed algorithm was verified through experiments, and the results are reported. |
doi_str_mv | 10.1017/S0263574712000379 |
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To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and INS data. To reduce the noise from the internal INS sensors, the discrete wavelet transform and variable threshold method are utilized, and to fuse the GPS and INS data while filtering out the noise caused by the acceleration, deceleration, and unexpected slips, the Unscented Particle Filter (UPF) is adopted. Conventional de-noising methods mainly employ a combination of low-pass and high-pass filters, which results in signal distortion. This newly proposed system also utilizes the vibration information of the actuator according to the fluctuations of the velocity to minimize the signal distortion. The UPF resolves the nonlinearities of the actuator and non-normal distributions of the noise more effectively than the conventional particle filter (PF) or Extended Kalman Filter–PF. 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The superiority of the proposed algorithm was verified through experiments, and the results are reported.</description><subject>Actuators</subject><subject>Algorithms</subject><subject>Global Positioning System</subject><subject>Localization</subject><subject>Noise</subject><subject>Outdoor</subject><subject>Position (location)</subject><subject>Signal distortion</subject><issn>0263-5747</issn><issn>1469-8668</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kEFLwzAYhoMoOKc_wFvBi5dqviRN2psydA6GDqbnkibpzGibmbSMefI_-A_9JXZsB1E8fYf3eV4-XoTOAV8BBnE9x4TTRDABBGNMRXaABsB4Fqecp4dosI3jbX6MTkJYYgwUmBigm5k3ygYTua7VzvmockpW9l221jXR2ravkYzGs_nXx-fkcR7ZpjULvwvDJrSmPkVHpayCOdvfIXq5v3sePcTTp_FkdDuNFU1wG6eKgcY8UcSUgDWGssAszRQBxnShC-CiJACSZoQzJbQuuBRccs2ZyQTDdIgud70r7946E9q8tkGZqpKNcV3IgQrCE85E2qMXv9Cl63zTf9dTkKZEUJH0FOwo5V0I3pT5ytta-k0OON9umv_ZtHfo3pF14a1emB_V_1rfaPJ3sg</recordid><startdate>201305</startdate><enddate>201305</enddate><creator>Seo, Wonkyo</creator><creator>Hwang, Seoyoung</creator><creator>Park, Jaehyun</creator><creator>Lee, Jang-Myung</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>201305</creationdate><title>Precise outdoor localization with a GPS–INS integration system</title><author>Seo, Wonkyo ; 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To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and INS data. To reduce the noise from the internal INS sensors, the discrete wavelet transform and variable threshold method are utilized, and to fuse the GPS and INS data while filtering out the noise caused by the acceleration, deceleration, and unexpected slips, the Unscented Particle Filter (UPF) is adopted. Conventional de-noising methods mainly employ a combination of low-pass and high-pass filters, which results in signal distortion. This newly proposed system also utilizes the vibration information of the actuator according to the fluctuations of the velocity to minimize the signal distortion. The UPF resolves the nonlinearities of the actuator and non-normal distributions of the noise more effectively than the conventional particle filter (PF) or Extended Kalman Filter–PF. The superiority of the proposed algorithm was verified through experiments, and the results are reported.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/S0263574712000379</doi><tpages>9</tpages></addata></record> |
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subjects | Actuators Algorithms Global Positioning System Localization Noise Outdoor Position (location) Signal distortion |
title | Precise outdoor localization with a GPS–INS integration system |
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