Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System
The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamles...
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| Veröffentlicht in: | Electronics (Basel) 2024-12, Vol.13 (23), p.4623 |
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| creator | Kim, Kyounghun Lee, Seongwoo Hwang, Byungsun Kim, Jinwook Seon, Joonho Kim, Soohyun Sun, Youngghyu Kim, Jinyoung |
| description | The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamless 6G services is achievable. However, accurate three-dimensional (3D) outdoor positioning has been challenging to achieve in NLOS environments where positioning accuracy may be severely degraded. In this paper, a novel 3D outdoor positioning method considering both LOS and NLOS environments is proposed. Considering the practical positioning systems, the data received from satellites often contain null values and outliers. Thus, a kernel density estimation (KDE)-based outlier removal method is used for effectively detecting the null values and outliers through temporal correlation analysis. A dilution of precision-based adaptive Kalman filter (DOP-AKF) is proposed to mitigate the effects of an NLOS environment. In the proposed method, the DOP-AKF can optimize the performance of the 3D positioning system that dynamically adapts to complex environments. Experimental results show that the proposed method can improve 3D positioning accuracy by up to 18.84% compared to conventional methods. Therefore, the proposed approach can be suggested as a promising solution for 3D outdoor positioning in 6G wireless systems. |
| doi_str_mv | 10.3390/electronics13234623 |
| format | Article |
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In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamless 6G services is achievable. However, accurate three-dimensional (3D) outdoor positioning has been challenging to achieve in NLOS environments where positioning accuracy may be severely degraded. In this paper, a novel 3D outdoor positioning method considering both LOS and NLOS environments is proposed. Considering the practical positioning systems, the data received from satellites often contain null values and outliers. Thus, a kernel density estimation (KDE)-based outlier removal method is used for effectively detecting the null values and outliers through temporal correlation analysis. A dilution of precision-based adaptive Kalman filter (DOP-AKF) is proposed to mitigate the effects of an NLOS environment. In the proposed method, the DOP-AKF can optimize the performance of the 3D positioning system that dynamically adapts to complex environments. Experimental results show that the proposed method can improve 3D positioning accuracy by up to 18.84% compared to conventional methods. Therefore, the proposed approach can be suggested as a promising solution for 3D outdoor positioning in 6G wireless systems.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics13234623</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>6G mobile communication ; Accuracy ; Adaptive systems ; Altitude ; Analysis ; Approximation ; Calibration ; Communications equipment ; Correlation analysis ; Data analysis ; Density ; Dilution ; Kalman filters ; Line of sight ; Localization ; Methods ; Outliers (statistics) ; Performance evaluation ; Satellite tracking ; Satellites ; Telecommunication systems</subject><ispartof>Electronics (Basel), 2024-12, Vol.13 (23), p.4623</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c241t-7adcd34e78526b338cd57fa42651f50f9235dc15daefa772ad4ed890acf84ae63</cites><orcidid>0000-0001-7279-5090 ; 0000-0002-1456-7097 ; 0009-0008-5462-1108 ; 0000-0002-0850-871X ; 0009-0003-2515-2529 ; 0000-0001-9146-2144 ; 0000-0003-3712-0009 ; 0009-0009-6143-915X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Kim, Kyounghun</creatorcontrib><creatorcontrib>Lee, Seongwoo</creatorcontrib><creatorcontrib>Hwang, Byungsun</creatorcontrib><creatorcontrib>Kim, Jinwook</creatorcontrib><creatorcontrib>Seon, Joonho</creatorcontrib><creatorcontrib>Kim, Soohyun</creatorcontrib><creatorcontrib>Sun, Youngghyu</creatorcontrib><creatorcontrib>Kim, Jinyoung</creatorcontrib><title>Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System</title><title>Electronics (Basel)</title><description>The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamless 6G services is achievable. However, accurate three-dimensional (3D) outdoor positioning has been challenging to achieve in NLOS environments where positioning accuracy may be severely degraded. In this paper, a novel 3D outdoor positioning method considering both LOS and NLOS environments is proposed. Considering the practical positioning systems, the data received from satellites often contain null values and outliers. Thus, a kernel density estimation (KDE)-based outlier removal method is used for effectively detecting the null values and outliers through temporal correlation analysis. A dilution of precision-based adaptive Kalman filter (DOP-AKF) is proposed to mitigate the effects of an NLOS environment. In the proposed method, the DOP-AKF can optimize the performance of the 3D positioning system that dynamically adapts to complex environments. Experimental results show that the proposed method can improve 3D positioning accuracy by up to 18.84% compared to conventional methods. Therefore, the proposed approach can be suggested as a promising solution for 3D outdoor positioning in 6G wireless systems.</description><subject>6G mobile communication</subject><subject>Accuracy</subject><subject>Adaptive systems</subject><subject>Altitude</subject><subject>Analysis</subject><subject>Approximation</subject><subject>Calibration</subject><subject>Communications equipment</subject><subject>Correlation analysis</subject><subject>Data analysis</subject><subject>Density</subject><subject>Dilution</subject><subject>Kalman filters</subject><subject>Line of sight</subject><subject>Localization</subject><subject>Methods</subject><subject>Outliers (statistics)</subject><subject>Performance evaluation</subject><subject>Satellite tracking</subject><subject>Satellites</subject><subject>Telecommunication systems</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptUctKQzEQvYiCRf0CNwHX1bzuI8va1gdWFFRcXsZkopHbpCapUPx5I3XhwpnFDMM5Z2Y4VXXM6KkQip7hgDrH4J1OTHAhGy52qhGnrRorrvjun36_OkrpnZZQTHSCjqqvuX8Dr9EQMSN362xCiOQ-JJddUfSv5BbzWzDkHFLBBE8mBlbZfSK5gWEJnly4IWMk4A25wehxIDP0hb4h85TdEn50iC2izSV5drEcmxJ52KSMy8Nqz8KQ8Oi3HlRPF_PH6dV4cXd5PZ0sxppLlsctGG2ExLarefMiRKdN3VqQvKmZralVXNRGs9oAWmhbDkai6RQFbTsJ2IiD6mSru4rhY40p9-9hHX1Z2QsmJe0aztqCOt2iXmHA3nkbcgRd0uDS6eDRujKfdEx1sq0VLQSxJegYUopo-1UsD8dNz2j_40z_jzPiG2s3hSY</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Kim, Kyounghun</creator><creator>Lee, Seongwoo</creator><creator>Hwang, Byungsun</creator><creator>Kim, Jinwook</creator><creator>Seon, Joonho</creator><creator>Kim, Soohyun</creator><creator>Sun, Youngghyu</creator><creator>Kim, Jinyoung</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</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>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-7279-5090</orcidid><orcidid>https://orcid.org/0000-0002-1456-7097</orcidid><orcidid>https://orcid.org/0009-0008-5462-1108</orcidid><orcidid>https://orcid.org/0000-0002-0850-871X</orcidid><orcidid>https://orcid.org/0009-0003-2515-2529</orcidid><orcidid>https://orcid.org/0000-0001-9146-2144</orcidid><orcidid>https://orcid.org/0000-0003-3712-0009</orcidid><orcidid>https://orcid.org/0009-0009-6143-915X</orcidid></search><sort><creationdate>20241201</creationdate><title>Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System</title><author>Kim, Kyounghun ; Lee, Seongwoo ; Hwang, Byungsun ; Kim, Jinwook ; Seon, Joonho ; Kim, Soohyun ; Sun, Youngghyu ; Kim, Jinyoung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c241t-7adcd34e78526b338cd57fa42651f50f9235dc15daefa772ad4ed890acf84ae63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>6G mobile communication</topic><topic>Accuracy</topic><topic>Adaptive systems</topic><topic>Altitude</topic><topic>Analysis</topic><topic>Approximation</topic><topic>Calibration</topic><topic>Communications equipment</topic><topic>Correlation analysis</topic><topic>Data analysis</topic><topic>Density</topic><topic>Dilution</topic><topic>Kalman filters</topic><topic>Line of sight</topic><topic>Localization</topic><topic>Methods</topic><topic>Outliers (statistics)</topic><topic>Performance evaluation</topic><topic>Satellite tracking</topic><topic>Satellites</topic><topic>Telecommunication systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Kyounghun</creatorcontrib><creatorcontrib>Lee, Seongwoo</creatorcontrib><creatorcontrib>Hwang, Byungsun</creatorcontrib><creatorcontrib>Kim, Jinwook</creatorcontrib><creatorcontrib>Seon, Joonho</creatorcontrib><creatorcontrib>Kim, Soohyun</creatorcontrib><creatorcontrib>Sun, Youngghyu</creatorcontrib><creatorcontrib>Kim, Jinyoung</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Electronics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Kyounghun</au><au>Lee, Seongwoo</au><au>Hwang, Byungsun</au><au>Kim, Jinwook</au><au>Seon, Joonho</au><au>Kim, Soohyun</au><au>Sun, Youngghyu</au><au>Kim, Jinyoung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System</atitle><jtitle>Electronics (Basel)</jtitle><date>2024-12-01</date><risdate>2024</risdate><volume>13</volume><issue>23</issue><spage>4623</spage><pages>4623-</pages><issn>2079-9292</issn><eissn>2079-9292</eissn><abstract>The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. 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| source | MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | 6G mobile communication Accuracy Adaptive systems Altitude Analysis Approximation Calibration Communications equipment Correlation analysis Data analysis Density Dilution Kalman filters Line of sight Localization Methods Outliers (statistics) Performance evaluation Satellite tracking Satellites Telecommunication systems |
| title | Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System |
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