Bayesian Methods in the Search for MH370
This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how the probabilistic models of aircraft flight dynamics, satellite communication system measurements, env...
I tiakina i:
Ngā kaituhi matua: | , , , , |
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Kaituhi rangatōpū: | |
Hōputu: | Tāhiko īPukapuka |
Reo: | Ingarihi |
I whakaputaina: |
Singapore :
Springer Singapore : Imprint: Springer,
2016.
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Rangatū: | SpringerBriefs in Electrical and Computer Engineering,
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Ngā marau: | |
Urunga tuihono: | http://dx.doi.org/10.1007/978-981-10-0379-0 |
Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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Whakarāpopototanga: | This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how the probabilistic models of aircraft flight dynamics, satellite communication system measurements, environmental effects and radar data were constructed and calibrated. The probability distribution was used to define the search zone in the southern Indian Ocean. The book describes particle-filter based numerical calculation of the aircraft flight-path probability distribution and validates the method using data from several of the involved aircraft’s previous flights. Finally it is shown how the Reunion Island flaperon debris find affects the search probability distribution. |
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Whakaahuatanga ōkiko: | XVI, 114 p. 51 illus., 2 illus. in color. online resource. |
ISBN: | 9789811003790 |
ISSN: | 2191-8112 |
DOI: | 10.1007/978-981-10-0379-0 |
Urunga: | Open Access |