000 | 05195nam a22007095i 4500 | ||
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001 | 978-3-319-90716-1 | ||
003 | DE-He213 | ||
005 | 20210201191418.0 | ||
007 | cr nn 008mamaa | ||
008 | 180625s2018 gw | s |||| 0|eng d | ||
020 |
_a9783319907161 _9978-3-319-90716-1 |
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050 | 4 | _aTA1630-1650 | |
072 | 7 |
_aUYT _2bicssc |
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_aCOM012000 _2bisacsh |
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_aUYQV _2thema |
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082 | 0 | 4 |
_a006.6 _223 |
082 | 0 | 4 |
_a006.37 _223 |
100 | 1 |
_aJing, Zhongliang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aNon-Cooperative Target Tracking, Fusion and Control _h[electronic resource] : _bAlgorithms and Advances / _cby Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
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300 |
_aXIX, 340 p. 142 illus., 80 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aInformation Fusion and Data Science, _x2510-1528 |
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500 | _aAcceso multiusuario | ||
505 | 0 | _aIntroduction -- Part I Multi-Target Tracking -- Gaussian mixture CPHD filter with gating technique -- Detection-guided multi-target Bayesian filter -- On the sensor order in sequential integrated probability data association filter -- New method for dynamic bias estimation: Gaussian mean shift registration -- Part II Visual Target Tracking -- Learning-based appearance model for probabilistic visual tracking -- Incremental visual tracking with L1 norm approximation and Grassmann update -- A dual-kernel-based tracking approach for visual target -- Kernel joint visual tracking and recognition based on structured sparse representation -- Part III Image Fusion and Deblurring -- A simple method to build oversampled filter banks and tight frames -- Multi-focus image fusion using pulse coupled neural network -- Evaluation of focus measures in multi-focus image fusion -- Multi-modality image fusion via generalized Riesz-wavelet transformation -- A sparse proximal Newton splitting method for constrained image deblurring -- Part IV Control of Spacecraft Maneuvers -- Maneuver-aided active satellite tracking using six-DOF optimal dynamic inversion control -- Dynamic optimal sliding-mode control for six-DOF follow-up robust tracking of active satellite -- Redundant adaptive robust tracking of active satellite and error evaluation. | |
520 | _aThis book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing. | ||
541 |
_fUABC ; _cTemporal ; _d01/01/2021-12/31/2023. |
||
650 | 0 | _aOptical data processing. | |
650 | 0 | _aSignal processing. | |
650 | 0 | _aImage processing. | |
650 | 0 | _aSpeech processing systems. | |
650 | 0 | _aRemote sensing. | |
650 | 0 | _aAerospace engineering. | |
650 | 0 | _aAstronautics. | |
650 | 0 | _aControl engineering. | |
650 | 1 | 4 |
_aImage Processing and Computer Vision. _0https://scigraph.springernature.com/ontologies/product-market-codes/I22021 |
650 | 2 | 4 |
_aSignal, Image and Speech Processing. _0https://scigraph.springernature.com/ontologies/product-market-codes/T24051 |
650 | 2 | 4 |
_aRemote Sensing/Photogrammetry. _0https://scigraph.springernature.com/ontologies/product-market-codes/J13010 |
650 | 2 | 4 |
_aAerospace Technology and Astronautics. _0https://scigraph.springernature.com/ontologies/product-market-codes/T17050 |
650 | 2 | 4 |
_aControl and Systems Theory. _0https://scigraph.springernature.com/ontologies/product-market-codes/T19010 |
700 | 1 |
_aPan, Han. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
700 | 1 |
_aLi, Yuankai. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
700 | 1 |
_aDong, Peng. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319907154 |
776 | 0 | 8 |
_iPrinted edition: _z9783319907178 |
776 | 0 | 8 |
_iPrinted edition: _z9783030080815 |
830 | 0 |
_aInformation Fusion and Data Science, _x2510-1528 |
|
856 | 4 | 0 |
_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-90716-1 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cLIBRO_ELEC | ||
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