Muutke küpsiste eelistusi

E-raamat: Bayesian Methods in the Search for MH370

  • Formaat - EPUB+DRM
  • Hind: 4,08 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

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.

Arvustused

I enjoyed every moment of reading this book, which is pedagogical, informative, and full of suspense. The writing is crisp and to the point, illustrating the depth and complexity of current aviation accident investigation techniques and the skills of the experts in this field. I advise both statisticians and aviation enthusiasts to have a look at this book . (P. Jouvelot, Computing Reviews, April, 2017)

Muu info

This is an open access book, the electronic versions are freely accessible online.
1 Introduction
1(6)
1.1 Summary of Results
3(4)
2 Factual Description of Accident and Available Information
7(4)
3 The Bayesian Approach
11(8)
3.1 The Problem and its Conceptual Solution
13(2)
3.1.1 Prediction
13(1)
3.1.2 Update
14(1)
3.2 The Particle Filter
15(1)
3.3 Rao--Blackwellised Particle Filter
16(3)
4 Aircraft Prior Based on Primary Radar Data
19(4)
5 Measurement Model, Satellite Communications
23(12)
5.1 Satellite Communications System
24(1)
5.2 Burst Timing Offset
25(3)
5.3 Burst Frequency Offset
28(3)
5.4 C-Channel Telephone Calls
31(2)
5.5 Information Content of Measurements
33(2)
6 Aircraft Cruise Dynamics
35(12)
6.1 Ornstein--Uhlenbeck Process
36(2)
6.1.1 Determining Process Parameters
37(1)
6.2 Mach Number
38(1)
6.2.1 Cost Index
39(1)
6.3 Control Angle
39(4)
6.3.1 Constant Magnetic Heading
41(1)
6.3.2 Constant True Heading
42(1)
6.3.3 Constant Magnetic Track
42(1)
6.3.4 Constant True Track
42(1)
6.3.5 Lateral Navigation
43(1)
6.4 Wind
43(1)
6.5 Altitude
44(1)
6.6 Putting It Together
45(2)
7 Aircraft Manoeuvre Dynamics
47(8)
7.1 Manoeuvre Frequency
47(2)
7.2 Manoeuvre Extent
49(3)
7.2.1 Parameter Selection
50(1)
7.2.2 Manoeuvre Model Summary
51(1)
7.3 Example Realisations
52(3)
8 Particle Filter Implementation
55(8)
8.1 BFO Bias
57(1)
8.2 Algorithm
57(3)
8.3 Assumptions
60(3)
9 Validation Experiments
63(24)
9.1 9M-MRO 26 February 2014 Kuala Lumpur to Amsterdam
65(1)
9.2 9M-MRO 2 March 2014 Mumbai to Kuala Lumpur
65(4)
9.3 9M-MRO 6 March 2014 Kuala Lumpur to Beijing
69(1)
9.4 9M-MRO 7 March 2014 Beijing to Kuala Lumpur
69(6)
9.5 7 March 2014 Kuala Lumpur to Amsterdam
75(1)
9.6 7 March 2014 Kuala Lumpur to Frankfurt
75(1)
9.7 Quantitative Analysis
75(12)
9.7.1 Measurement Selection
80(1)
9.7.2 Performance Measure
81(2)
9.7.3 Results
83(4)
10 Application to the MH370 Accident
87(14)
10.1 The Filter Applied to the Accident Flight
87(3)
10.2 Manoeuvre Statistics
90(3)
10.3 Residual Measurement Errors
93(1)
10.4 Posterior Distribution of Manoeuvre Time Constant
94(1)
10.5 End of Flight
94(2)
10.6 Earlier Initialisation
96(3)
10.7 Cost Index
99(1)
10.8 Other Variations
100(1)
11 Ongoing Refinement
101(10)
11.1 Updating the Distribution Using Search Results
101(1)
11.2 Reunion Island Debris
102(9)
11.2.1 Update of Final Location Distribution
103(1)
11.2.2 Data from Global Drifter Program
104(2)
11.2.3 Posterior Distribution Using Debris Data
106(5)
12 Conclusions
111
References
113
Samuel Davey received the Bachelor of Engineering, Master of Mathematical Science and PhD degrees from the University of Adelaide, Australia, in 1996, 1999, and 2003, respectively. Since 1995 he has worked for the Defence Science and Technology Group, Australia, in the areas of target tracking, tracker performance assessment, and multi-sensor fusion. He is a Visiting Research Fellow at the University of Adelaide and a Senior Member of the IEEE. Neil Gordon received a PhD in Statistics from Imperial College London in 1993. He was with the Defence Evaluation and Research Agency in the UK until 2002 working on missile guidance and statistical data processing. He is best known for initiating the particle filter approach to nonlinear, non-Gaussian dynamic estimation which is now in widespread use throughout the world in many diverse disciplines. He is the co-author/co-editor of two books on particle filtering. In 2002 he moved to the Defence Science and Technology Group in Adelaide, Australia where he is currently head of Data and Information Fusion. In 2014 he became an Honorary Professor with the School of Information Technology and Electrical Engineering at the University of Queensland. He is a Senior Member of the IEEE. Ian Holland received the Bachelor of Electronic and Communication Engineering in 2000 and a PhD in wireless telecommunications in 2005, both from Curtin University of Technology, Western Australia. Since then he has held positions in the University of Western Australia, the Institute for Telecommunications Research at the University of South Australia, EMS Satcom Pacific and Lockheed Martin Australia. Since January 2011, Ian has been working as a Research Scientist in Protected Satellite Communications at the Defence Science and Technology Group. Mark Rutten received theBachelor of Science, Bachelor of Engineering and Master of Mathematical Science from the University of Adelaide in 1995, 1996 and 1999, respectively and a PhD from the University of Melbourne in 2005 on Multipath Tracking for Over the Horizon Radars. He has worked on data and information fusion for the Defence Science and Technology Group since 1996. His research interests include nonlinear state estimation, target tracking and multi-sensor fusion. Jason Williams received degrees of Bachelor of Engineering in Electronics andBachelor of Information Technology from Queensland University of Technology in 1999, Master of Science in Electrical Engineering from the United States Air Force Institute of Technology in 2003, and PhD in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 2007. He worked for several years as an engineering officer in the Royal Australian Air Force, before joining Australias Defence Science and Technology Group in 2007. He is also an Adjunct Senior Lecturer at the University of Adelaide. His research interests include target tracking, sensor resource management, Markov random fields and convex optimisation.