Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery
A sensor fusion approach to terrain relative navigation is proposed in this paper. Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter....
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| Veröffentlicht in: | Journal of guidance, control, and dynamics control, and dynamics, 2023-09, Vol.46 (9), p.1689-1707 |
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| container_issue | 9 |
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| container_title | Journal of guidance, control, and dynamics |
| container_volume | 46 |
| creator | Weaver Adams, Davis Peck, Caleb Majji, Manoranjan |
| description | A sensor fusion approach to terrain relative navigation is proposed in this paper. Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter. The measurement model of the Doppler LIDAR is derived from first principals and employed by the filter to update the estimates propagated by the GPS/INS data stream. The line-of-sight Doppler velocity measurement provides direct feedback to the velocity states and improves sensitivity to these state estimates. A novel Rauch–Tung–Striebel smoother framework is derived that is compatible with states exhibiting multiplicative error that enables seamless postprocessing of state estimates filtered with a multiplicative extended Kalman filter. This new filter and smoother framework is tested with suborbital flight data from Blue Origin’s New Sheppard ascent and landing missions. |
| doi_str_mv | 10.2514/1.G007318 |
| format | Article |
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Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter. The measurement model of the Doppler LIDAR is derived from first principals and employed by the filter to update the estimates propagated by the GPS/INS data stream. The line-of-sight Doppler velocity measurement provides direct feedback to the velocity states and improves sensitivity to these state estimates. A novel Rauch–Tung–Striebel smoother framework is derived that is compatible with states exhibiting multiplicative error that enables seamless postprocessing of state estimates filtered with a multiplicative extended Kalman filter. This new filter and smoother framework is tested with suborbital flight data from Blue Origin’s New Sheppard ascent and landing missions.</description><identifier>ISSN: 0731-5090</identifier><identifier>EISSN: 1533-3884</identifier><identifier>DOI: 10.2514/1.G007318</identifier><language>eng</language><publisher>Reston: American Institute of Aeronautics and Astronautics</publisher><subject>Accuracy ; Aerospace engineering ; Attitudes ; Data transmission ; Doppler effect ; Estimates ; Extended Kalman filter ; Field programmable gate arrays ; Global positioning systems ; GPS ; Inertial coordinates ; Inertial navigation ; Kinematics ; Lidar ; Localization ; Moon ; Navigation systems ; Satellite navigation systems ; Sensors ; Suborbital flight ; Velocity ; Velocity measurement</subject><ispartof>Journal of guidance, control, and dynamics, 2023-09, Vol.46 (9), p.1689-1707</ispartof><rights>Copyright © 2023 by Davis Adams, Caleb Peck, and Manoranjan Majji. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-3884 to initiate your request. 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Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter. The measurement model of the Doppler LIDAR is derived from first principals and employed by the filter to update the estimates propagated by the GPS/INS data stream. The line-of-sight Doppler velocity measurement provides direct feedback to the velocity states and improves sensitivity to these state estimates. A novel Rauch–Tung–Striebel smoother framework is derived that is compatible with states exhibiting multiplicative error that enables seamless postprocessing of state estimates filtered with a multiplicative extended Kalman filter. This new filter and smoother framework is tested with suborbital flight data from Blue Origin’s New Sheppard ascent and landing missions.</description><subject>Accuracy</subject><subject>Aerospace engineering</subject><subject>Attitudes</subject><subject>Data transmission</subject><subject>Doppler effect</subject><subject>Estimates</subject><subject>Extended Kalman filter</subject><subject>Field programmable gate arrays</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Inertial coordinates</subject><subject>Inertial navigation</subject><subject>Kinematics</subject><subject>Lidar</subject><subject>Localization</subject><subject>Moon</subject><subject>Navigation systems</subject><subject>Satellite navigation systems</subject><subject>Sensors</subject><subject>Suborbital flight</subject><subject>Velocity</subject><subject>Velocity measurement</subject><issn>0731-5090</issn><issn>1533-3884</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNo9kEFLAzEUhIMoWKsH_0HAk4etL3nZJnssrdZCUSjtOWSzyZpSN2t2W-i_t9LiaWD4ZgaGkEcGI54z8cJGcwCJTF2RAcsRM1RKXJPBn5flUMAtueu6LQDDMZMDspnFtt25RJeh_urpzPXO9iE21DQVXZmmDk2dTULlKrpoXOqD2dEPcwi1-afWyWxPoZiOdOVsPLh0vCc33uw693DRIdm8va6n79nyc76YTpaZ5Uz2meKqqKCwWEgoxxIAvcAxLz2XXpSMgQKUFVphK--Q-1JwV3rljfHMGhQ4JE_n3jbFn73rer2N-9ScJjVXOXBEEPxEPZ8pm2LXJed1m8K3SUfNQP-9ppm-vIa_kwpeUQ</recordid><startdate>202309</startdate><enddate>202309</enddate><creator>Weaver Adams, Davis</creator><creator>Peck, Caleb</creator><creator>Majji, Manoranjan</creator><general>American Institute of Aeronautics and Astronautics</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-8800-5647</orcidid></search><sort><creationdate>202309</creationdate><title>Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery</title><author>Weaver Adams, Davis ; Peck, Caleb ; Majji, Manoranjan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c217t-8289d09c3970b67003f4362bf27f4b1108037d3c4cdfe32fb42ebf8faaf1ca343</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accuracy</topic><topic>Aerospace engineering</topic><topic>Attitudes</topic><topic>Data transmission</topic><topic>Doppler effect</topic><topic>Estimates</topic><topic>Extended Kalman filter</topic><topic>Field programmable gate arrays</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Inertial coordinates</topic><topic>Inertial navigation</topic><topic>Kinematics</topic><topic>Lidar</topic><topic>Localization</topic><topic>Moon</topic><topic>Navigation systems</topic><topic>Satellite navigation systems</topic><topic>Sensors</topic><topic>Suborbital flight</topic><topic>Velocity</topic><topic>Velocity measurement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Weaver Adams, Davis</creatorcontrib><creatorcontrib>Peck, Caleb</creatorcontrib><creatorcontrib>Majji, Manoranjan</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of guidance, control, and dynamics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Weaver Adams, Davis</au><au>Peck, Caleb</au><au>Majji, Manoranjan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery</atitle><jtitle>Journal of guidance, control, and dynamics</jtitle><date>2023-09</date><risdate>2023</risdate><volume>46</volume><issue>9</issue><spage>1689</spage><epage>1707</epage><pages>1689-1707</pages><issn>0731-5090</issn><eissn>1533-3884</eissn><abstract>A sensor fusion approach to terrain relative navigation is proposed in this paper. 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| ispartof | Journal of guidance, control, and dynamics, 2023-09, Vol.46 (9), p.1689-1707 |
| issn | 0731-5090 1533-3884 |
| language | eng |
| recordid | cdi_proquest_journals_2850233042 |
| source | Alma/SFX Local Collection |
| subjects | Accuracy Aerospace engineering Attitudes Data transmission Doppler effect Estimates Extended Kalman filter Field programmable gate arrays Global positioning systems GPS Inertial coordinates Inertial navigation Kinematics Lidar Localization Moon Navigation systems Satellite navigation systems Sensors Suborbital flight Velocity Velocity measurement |
| title | Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery |
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