Application of Updated Sage–Husa Adaptive Kalman Filter in the Navigation of a Translational Sprinkler Irrigation Machine
Autonomous navigation for agricultural machinery has broad and promising development prospects. Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much research performed into navigation for sprinkle...
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| Veröffentlicht in: | Water (Basel) 2019-06, Vol.11 (6), p.1269 |
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| creator | Liu, Kenan Zhao, Wuyun Sun, Bugong Wu, Pute Zhu, Delan Zhang, Peng |
| description | Autonomous navigation for agricultural machinery has broad and promising development prospects. Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much research performed into navigation for sprinkler irrigation machines (SIMs). In this paper, firstly, a self-developed SIM is introduced. Secondly, the kinematics model is established on the platform of the self-developed SIM, and the updated Sage–Husa adaptive Kalman filter, which is an accurate and real-time self-adaptive filtering algorithm, is applied in the navigation of the SIM with the aim of improving the positioning accuracy. Finally, experiment verifications were carried out, and the results show that the self-developed SIM has good navigation performance. Besides this, the influence of abnormal observations on the positioning accuracy of the system can be restrained by using the updated Sage–Husa adaptive Kalman filter. After using the updated Sage–Husa adaptive Kalman filter for the SIM, the maximum deviation between the SIM and the predetermined path is 0.18 m, and the average deviation is 0.08 m; these deviations are within a reasonable range. This proves that the updated Sage–Husa adaptive Kalman filter is applicable for the navigation of sprinkler irrigation machines. |
| doi_str_mv | 10.3390/w11061269 |
| format | Article |
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Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much research performed into navigation for sprinkler irrigation machines (SIMs). In this paper, firstly, a self-developed SIM is introduced. Secondly, the kinematics model is established on the platform of the self-developed SIM, and the updated Sage–Husa adaptive Kalman filter, which is an accurate and real-time self-adaptive filtering algorithm, is applied in the navigation of the SIM with the aim of improving the positioning accuracy. Finally, experiment verifications were carried out, and the results show that the self-developed SIM has good navigation performance. Besides this, the influence of abnormal observations on the positioning accuracy of the system can be restrained by using the updated Sage–Husa adaptive Kalman filter. After using the updated Sage–Husa adaptive Kalman filter for the SIM, the maximum deviation between the SIM and the predetermined path is 0.18 m, and the average deviation is 0.08 m; these deviations are within a reasonable range. This proves that the updated Sage–Husa adaptive Kalman filter is applicable for the navigation of sprinkler irrigation machines.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w11061269</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; Adaptive algorithms ; Adaptive filters ; Agricultural equipment ; Agricultural production ; Agricultural technology ; Algorithms ; Autonomous navigation ; Deviation ; Electronics in navigation ; Energy ; Farm machinery ; Fiber optics ; Global positioning systems ; GPS ; Irrigation ; Kalman filters ; Kinematics ; Machinery ; Magneto-electric machines ; Navigation systems ; Noise ; Sensors ; Sprinkler irrigation ; Vehicles ; Vision systems ; Wheels</subject><ispartof>Water (Basel), 2019-06, Vol.11 (6), p.1269</ispartof><rights>COPYRIGHT 2019 MDPI AG</rights><rights>2019 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 (http://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><citedby>FETCH-LOGICAL-c331t-98251b98f7df4ae0c91301db23a99ef6ebf1e4a8aad54d60f7137c3892fc1fd53</citedby><cites>FETCH-LOGICAL-c331t-98251b98f7df4ae0c91301db23a99ef6ebf1e4a8aad54d60f7137c3892fc1fd53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Liu, Kenan</creatorcontrib><creatorcontrib>Zhao, Wuyun</creatorcontrib><creatorcontrib>Sun, Bugong</creatorcontrib><creatorcontrib>Wu, Pute</creatorcontrib><creatorcontrib>Zhu, Delan</creatorcontrib><creatorcontrib>Zhang, Peng</creatorcontrib><title>Application of Updated Sage–Husa Adaptive Kalman Filter in the Navigation of a Translational Sprinkler Irrigation Machine</title><title>Water (Basel)</title><description>Autonomous navigation for agricultural machinery has broad and promising development prospects. Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much research performed into navigation for sprinkler irrigation machines (SIMs). In this paper, firstly, a self-developed SIM is introduced. Secondly, the kinematics model is established on the platform of the self-developed SIM, and the updated Sage–Husa adaptive Kalman filter, which is an accurate and real-time self-adaptive filtering algorithm, is applied in the navigation of the SIM with the aim of improving the positioning accuracy. Finally, experiment verifications were carried out, and the results show that the self-developed SIM has good navigation performance. Besides this, the influence of abnormal observations on the positioning accuracy of the system can be restrained by using the updated Sage–Husa adaptive Kalman filter. After using the updated Sage–Husa adaptive Kalman filter for the SIM, the maximum deviation between the SIM and the predetermined path is 0.18 m, and the average deviation is 0.08 m; these deviations are within a reasonable range. This proves that the updated Sage–Husa adaptive Kalman filter is applicable for the navigation of sprinkler irrigation machines.</description><subject>Accuracy</subject><subject>Adaptive algorithms</subject><subject>Adaptive filters</subject><subject>Agricultural equipment</subject><subject>Agricultural production</subject><subject>Agricultural technology</subject><subject>Algorithms</subject><subject>Autonomous navigation</subject><subject>Deviation</subject><subject>Electronics in navigation</subject><subject>Energy</subject><subject>Farm machinery</subject><subject>Fiber optics</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Irrigation</subject><subject>Kalman filters</subject><subject>Kinematics</subject><subject>Machinery</subject><subject>Magneto-electric machines</subject><subject>Navigation systems</subject><subject>Noise</subject><subject>Sensors</subject><subject>Sprinkler irrigation</subject><subject>Vehicles</subject><subject>Vision systems</subject><subject>Wheels</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNkUtOAkEQhidGE4my8AaduHIB9msevZwQESLqAlhPin5A4zAzdg8Y48Y7eENPYitKrFpU5c_3V6pSUXRBcJ8xga9fCMEJoYk4ijoUp6zHOSfH__rTqOv9GofgIsti3Ine8qYprYTW1hWqDZo3Clqt0BSW-vP9Y7T1gHIFTWt3Gt1BuYEKDW3ZaodshdqVRg-ws8uDH9DMQeXLHwFKNG2crZ7KgI-d--PuQa5spc-jEwOl193fehbNhzezwag3ebwdD_JJTzJG2p7IaEwWIjOpMhw0loIwTNSCMhBCm0QvDNEcMgAVc5VgkxKWSpYJaiQxKmZn0eV-buPq5632bbGuty5s5wsax5gRQWMWqP6eWkKpC1uZunUgQyq9sbKutLFBz1NBaCY4o8FwtTdIV3vvtCnCrRtwrwXBxfc_isM_2BdORX5L</recordid><startdate>20190601</startdate><enddate>20190601</enddate><creator>Liu, Kenan</creator><creator>Zhao, Wuyun</creator><creator>Sun, Bugong</creator><creator>Wu, Pute</creator><creator>Zhu, Delan</creator><creator>Zhang, Peng</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20190601</creationdate><title>Application of Updated Sage–Husa Adaptive Kalman Filter in the Navigation of a Translational Sprinkler Irrigation Machine</title><author>Liu, Kenan ; Zhao, Wuyun ; Sun, Bugong ; Wu, Pute ; Zhu, Delan ; Zhang, Peng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-98251b98f7df4ae0c91301db23a99ef6ebf1e4a8aad54d60f7137c3892fc1fd53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Accuracy</topic><topic>Adaptive algorithms</topic><topic>Adaptive filters</topic><topic>Agricultural equipment</topic><topic>Agricultural production</topic><topic>Agricultural technology</topic><topic>Algorithms</topic><topic>Autonomous navigation</topic><topic>Deviation</topic><topic>Electronics in navigation</topic><topic>Energy</topic><topic>Farm machinery</topic><topic>Fiber optics</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Irrigation</topic><topic>Kalman filters</topic><topic>Kinematics</topic><topic>Machinery</topic><topic>Magneto-electric machines</topic><topic>Navigation systems</topic><topic>Noise</topic><topic>Sensors</topic><topic>Sprinkler irrigation</topic><topic>Vehicles</topic><topic>Vision systems</topic><topic>Wheels</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Kenan</creatorcontrib><creatorcontrib>Zhao, Wuyun</creatorcontrib><creatorcontrib>Sun, Bugong</creatorcontrib><creatorcontrib>Wu, Pute</creatorcontrib><creatorcontrib>Zhu, Delan</creatorcontrib><creatorcontrib>Zhang, Peng</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Kenan</au><au>Zhao, Wuyun</au><au>Sun, Bugong</au><au>Wu, Pute</au><au>Zhu, Delan</au><au>Zhang, Peng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of Updated Sage–Husa Adaptive Kalman Filter in the Navigation of a Translational Sprinkler Irrigation Machine</atitle><jtitle>Water (Basel)</jtitle><date>2019-06-01</date><risdate>2019</risdate><volume>11</volume><issue>6</issue><spage>1269</spage><pages>1269-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>Autonomous navigation for agricultural machinery has broad and promising development prospects. Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much research performed into navigation for sprinkler irrigation machines (SIMs). In this paper, firstly, a self-developed SIM is introduced. Secondly, the kinematics model is established on the platform of the self-developed SIM, and the updated Sage–Husa adaptive Kalman filter, which is an accurate and real-time self-adaptive filtering algorithm, is applied in the navigation of the SIM with the aim of improving the positioning accuracy. Finally, experiment verifications were carried out, and the results show that the self-developed SIM has good navigation performance. Besides this, the influence of abnormal observations on the positioning accuracy of the system can be restrained by using the updated Sage–Husa adaptive Kalman filter. After using the updated Sage–Husa adaptive Kalman filter for the SIM, the maximum deviation between the SIM and the predetermined path is 0.18 m, and the average deviation is 0.08 m; these deviations are within a reasonable range. This proves that the updated Sage–Husa adaptive Kalman filter is applicable for the navigation of sprinkler irrigation machines.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w11061269</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Accuracy Adaptive algorithms Adaptive filters Agricultural equipment Agricultural production Agricultural technology Algorithms Autonomous navigation Deviation Electronics in navigation Energy Farm machinery Fiber optics Global positioning systems GPS Irrigation Kalman filters Kinematics Machinery Magneto-electric machines Navigation systems Noise Sensors Sprinkler irrigation Vehicles Vision systems Wheels |
| title | Application of Updated Sage–Husa Adaptive Kalman Filter in the Navigation of a Translational Sprinkler Irrigation Machine |
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