Bayesian multiple target tracking:
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This boo...
Gespeichert in:
| Beteiligte Personen: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Norwood
ARTECH HOUSE
2014
|
| Ausgabe: | Second edition |
| Schlagwörter: | |
| Zusammenfassung: | This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters. With these examples illustrating the developed concepts, algorithms, and approaches -- the book helps radar engineers develop tracking solutions when observations are non-linear functions of target state, when the target state distributions or measurement error distributions are not Gaussian, in low data rate and low signal to noise ratio situations, and when notions of contact and association are merged or unresolved among more than one target |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781608075546 9781523117017 |
Internformat
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| 520 | |a This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters. With these examples illustrating the developed concepts, algorithms, and approaches -- the book helps radar engineers develop tracking solutions when observations are non-linear functions of target state, when the target state distributions or measurement error distributions are not Gaussian, in low data rate and low signal to noise ratio situations, and when notions of contact and association are merged or unresolved among more than one target | ||
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Datensatz im Suchindex
| _version_ | 1818982761182003200 |
|---|---|
| any_adam_object | |
| author | Stone, Lawrence D. Streit, Roy L. Corwin, Thomas L. Bell, Kristine L. |
| author_facet | Stone, Lawrence D. Streit, Roy L. Corwin, Thomas L. Bell, Kristine L. |
| author_role | aut aut aut aut |
| author_sort | Stone, Lawrence D. |
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| building | Verbundindex |
| bvnumber | BV044050415 |
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| dewey-full | 621.38480151 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621.38480151 |
| dewey-search | 621.38480151 |
| dewey-sort | 3621.38480151 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| edition | Second edition |
| format | Electronic eBook |
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| id | DE-604.BV044050415 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:52:21Z |
| institution | BVB |
| isbn | 9781608075546 9781523117017 |
| language | English |
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| spelling | Stone, Lawrence D. aut Bayesian multiple target tracking Second edition Norwood ARTECH HOUSE 2014 © 2014 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters. With these examples illustrating the developed concepts, algorithms, and approaches -- the book helps radar engineers develop tracking solutions when observations are non-linear functions of target state, when the target state distributions or measurement error distributions are not Gaussian, in low data rate and low signal to noise ratio situations, and when notions of contact and association are merged or unresolved among more than one target Datenfusion (DE-588)4582612-2 gnd rswk-swf Zielerkennung (DE-588)4190792-9 gnd rswk-swf Multisensor (DE-588)4257775-5 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Radar (DE-588)4176765-2 gnd rswk-swf Radar (DE-588)4176765-2 s Mathematisches Modell (DE-588)4114528-8 s DE-604 Bayes-Entscheidungstheorie (DE-588)4144220-9 s Zielerkennung (DE-588)4190792-9 s Multisensor (DE-588)4257775-5 s Datenfusion (DE-588)4582612-2 s Streit, Roy L. aut Corwin, Thomas L. aut Bell, Kristine L. aut Erscheint auch als Druck-Ausgabe, hbk 978-1-60807-553-9 |
| spellingShingle | Stone, Lawrence D. Streit, Roy L. Corwin, Thomas L. Bell, Kristine L. Bayesian multiple target tracking Datenfusion (DE-588)4582612-2 gnd Zielerkennung (DE-588)4190792-9 gnd Multisensor (DE-588)4257775-5 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Mathematisches Modell (DE-588)4114528-8 gnd Radar (DE-588)4176765-2 gnd |
| subject_GND | (DE-588)4582612-2 (DE-588)4190792-9 (DE-588)4257775-5 (DE-588)4144220-9 (DE-588)4114528-8 (DE-588)4176765-2 |
| title | Bayesian multiple target tracking |
| title_auth | Bayesian multiple target tracking |
| title_exact_search | Bayesian multiple target tracking |
| title_full | Bayesian multiple target tracking |
| title_fullStr | Bayesian multiple target tracking |
| title_full_unstemmed | Bayesian multiple target tracking |
| title_short | Bayesian multiple target tracking |
| title_sort | bayesian multiple target tracking |
| topic | Datenfusion (DE-588)4582612-2 gnd Zielerkennung (DE-588)4190792-9 gnd Multisensor (DE-588)4257775-5 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Mathematisches Modell (DE-588)4114528-8 gnd Radar (DE-588)4176765-2 gnd |
| topic_facet | Datenfusion Zielerkennung Multisensor Bayes-Entscheidungstheorie Mathematisches Modell Radar |
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