Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation
The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemen...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 1980-07, Vol.AES-16 (4), p.481-491 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 491 |
|---|---|
| container_issue | 4 |
| container_start_page | 481 |
| container_title | IEEE transactions on aerospace and electronic systems |
| container_volume | AES-16 |
| creator | Upadhyay, Triveni N. Damoulakis, John N. |
| description | The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented covariance and filter gains at a slower rate than the state measurement update, and it uses U-D factor formulation to perform covariance computations. The SPWR algorithm saves real-time processing requirements without appreciable degradation of filter performance. Another important feature of the SPWR algorithm is that it incorporates pseudorange and delta-range data from each GPS satellite sequentially for navigation solution. The SPWR algorithm, for this application, was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented. |
| doi_str_mv | 10.1109/TAES.1980.308978 |
| format | Article |
| fullrecord | <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_ieee_primary_4102354</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4102354</ieee_id><sourcerecordid>10_1109_TAES_1980_308978</sourcerecordid><originalsourceid>FETCH-LOGICAL-c261t-166cc01c78dfc6678fb1c318bd82d54ed5cbb208fecd3f4aeee37836cd5543c93</originalsourceid><addsrcrecordid>eNo9kFFLwzAUhYMoOKfvgi_5A625TZOmj2NuUxg63Hwu6e2NRLZVk25j_96OiU-HA-d8Dx9j9yBSAFE-rkaTZQqlEakUpizMBRuAUkVSaiEv2UAIMEmZKbhmNzF-9TU3uRywyZJ-drTtvF3zhSekg4_E3wl3Ifo98alfdxS4awOfLZZ83h6Sp-PWbjxG_mr3_tN2vt3esitn15Hu_nLIPqaT1fg5mb_NXsajeYKZhi4BrREFYGEah1oXxtWAEkzdmKxROTUK6zoTxhE20uWWiGRhpMZGqVxiKYdMnLkY2hgDueo7-I0NxwpEddJQnTRUJw3VWUN_eThffE_7n-cgMtkzfwEgKloA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation</title><source>IEEE Electronic Library (IEL)</source><creator>Upadhyay, Triveni N. ; Damoulakis, John N.</creator><creatorcontrib>Upadhyay, Triveni N. ; Damoulakis, John N.</creatorcontrib><description>The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented covariance and filter gains at a slower rate than the state measurement update, and it uses U-D factor formulation to perform covariance computations. The SPWR algorithm saves real-time processing requirements without appreciable degradation of filter performance. Another important feature of the SPWR algorithm is that it incorporates pseudorange and delta-range data from each GPS satellite sequentially for navigation solution. The SPWR algorithm, for this application, was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.1980.308978</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Filters ; Floating-point arithmetic ; Gain measurement ; Global Positioning System ; Navigation ; Performance evaluation ; Performance gain ; Real time systems ; Recursive estimation</subject><ispartof>IEEE transactions on aerospace and electronic systems, 1980-07, Vol.AES-16 (4), p.481-491</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c261t-166cc01c78dfc6678fb1c318bd82d54ed5cbb208fecd3f4aeee37836cd5543c93</citedby><cites>FETCH-LOGICAL-c261t-166cc01c78dfc6678fb1c318bd82d54ed5cbb208fecd3f4aeee37836cd5543c93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4102354$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4102354$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Upadhyay, Triveni N.</creatorcontrib><creatorcontrib>Damoulakis, John N.</creatorcontrib><title>Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented covariance and filter gains at a slower rate than the state measurement update, and it uses U-D factor formulation to perform covariance computations. The SPWR algorithm saves real-time processing requirements without appreciable degradation of filter performance. Another important feature of the SPWR algorithm is that it incorporates pseudorange and delta-range data from each GPS satellite sequentially for navigation solution. The SPWR algorithm, for this application, was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented.</description><subject>Algorithm design and analysis</subject><subject>Filters</subject><subject>Floating-point arithmetic</subject><subject>Gain measurement</subject><subject>Global Positioning System</subject><subject>Navigation</subject><subject>Performance evaluation</subject><subject>Performance gain</subject><subject>Real time systems</subject><subject>Recursive estimation</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1980</creationdate><recordtype>article</recordtype><recordid>eNo9kFFLwzAUhYMoOKfvgi_5A625TZOmj2NuUxg63Hwu6e2NRLZVk25j_96OiU-HA-d8Dx9j9yBSAFE-rkaTZQqlEakUpizMBRuAUkVSaiEv2UAIMEmZKbhmNzF-9TU3uRywyZJ-drTtvF3zhSekg4_E3wl3Ifo98alfdxS4awOfLZZ83h6Sp-PWbjxG_mr3_tN2vt3esitn15Hu_nLIPqaT1fg5mb_NXsajeYKZhi4BrREFYGEah1oXxtWAEkzdmKxROTUK6zoTxhE20uWWiGRhpMZGqVxiKYdMnLkY2hgDueo7-I0NxwpEddJQnTRUJw3VWUN_eThffE_7n-cgMtkzfwEgKloA</recordid><startdate>198007</startdate><enddate>198007</enddate><creator>Upadhyay, Triveni N.</creator><creator>Damoulakis, John N.</creator><general>IEEE</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>198007</creationdate><title>Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation</title><author>Upadhyay, Triveni N. ; Damoulakis, John N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-166cc01c78dfc6678fb1c318bd82d54ed5cbb208fecd3f4aeee37836cd5543c93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1980</creationdate><topic>Algorithm design and analysis</topic><topic>Filters</topic><topic>Floating-point arithmetic</topic><topic>Gain measurement</topic><topic>Global Positioning System</topic><topic>Navigation</topic><topic>Performance evaluation</topic><topic>Performance gain</topic><topic>Real time systems</topic><topic>Recursive estimation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Upadhyay, Triveni N.</creatorcontrib><creatorcontrib>Damoulakis, John N.</creatorcontrib><collection>CrossRef</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Upadhyay, Triveni N.</au><au>Damoulakis, John N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>1980-07</date><risdate>1980</risdate><volume>AES-16</volume><issue>4</issue><spage>481</spage><epage>491</epage><pages>481-491</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented covariance and filter gains at a slower rate than the state measurement update, and it uses U-D factor formulation to perform covariance computations. The SPWR algorithm saves real-time processing requirements without appreciable degradation of filter performance. Another important feature of the SPWR algorithm is that it incorporates pseudorange and delta-range data from each GPS satellite sequentially for navigation solution. The SPWR algorithm, for this application, was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented.</abstract><pub>IEEE</pub><doi>10.1109/TAES.1980.308978</doi><tpages>11</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0018-9251 |
| ispartof | IEEE transactions on aerospace and electronic systems, 1980-07, Vol.AES-16 (4), p.481-491 |
| issn | 0018-9251 1557-9603 |
| language | eng |
| recordid | cdi_ieee_primary_4102354 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithm design and analysis Filters Floating-point arithmetic Gain measurement Global Positioning System Navigation Performance evaluation Performance gain Real time systems Recursive estimation |
| title | Sequential Piecewise Recursive Filter for GPS Low-Dynamics Navigation |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T19%3A48%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sequential%20Piecewise%20Recursive%20Filter%20for%20GPS%20Low-Dynamics%20Navigation&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Upadhyay,%20Triveni%20N.&rft.date=1980-07&rft.volume=AES-16&rft.issue=4&rft.spage=481&rft.epage=491&rft.pages=481-491&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/TAES.1980.308978&rft_dat=%3Ccrossref_RIE%3E10_1109_TAES_1980_308978%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4102354&rfr_iscdi=true |