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Über dieses Buch

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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Inhaltsverzeichnis

Frontmatter

Open Access

Chapter 1. Introduction

On 7 March 2014 at 16:42, Malaysian Airlines flight MH370 departed from Kuala Lumpur (KL) International Airport bound for Beijing. There was a total of 239 persons on board (227 passengers and 12 crew).
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 2. Factual Description of Accident and Available Information

The detailed chronological factual statement of known information about flight MH370 is given at [35]. A brief summary is given here sufficient to put the analysis in the rest of the book in context.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 3. The Bayesian Approach

Bayesian inference methods [9] provide a well-studied toolkit for calculating a distribution of a quantity of interest given observed evidence (measurements). As such, they are well-suited for calculating a probability distribution of the final location of the aircraft given the data available from the Inmarsat satellite communication system.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 4. Aircraft Prior Based on Primary Radar Data

The Bayesian approach described in the previous chapter is a recursive method that calculates the posterior state distribution at each measurement time from a distribution at the previous measurement time.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 5. Measurement Model, Satellite Communications

The Bayesian filter discussed in Chap. 3 relies on knowledge of three probability density functions: the state prior distribution, the state stochastic model, and the measurement conditional probability density.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 6. Aircraft Cruise Dynamics

The final piece of the Bayesian filter is the dynamics model. In object tracking, it is common to model either the velocity or the acceleration of the object as a random walk in two or three dimensions (e.g., [7]).
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 7. Aircraft Manoeuvre Dynamics

As discussed in the previous chapter, the dynamics model used for this analysis consists of a sequence of deliberate manoeuvres interspersed with periods of cruise, in which the speed and control angle are almost constant.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 8. Particle Filter Implementation

Solution of the Bayesian estimation method described in Chap. 3 requires one to recursively integrate the aircraft dynamics pdf (3.​6) and multiply it by the likelihood (3.​7).
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 9. Validation Experiments

The variable rate model developed for MH370 was validated by analysing data from a collection of flights where the true aircraft location was known; we refer to these as validation flights. A total of six validation flights were used for testing.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 10. Application to the MH370 Accident

The previous chapters have constructed a Bayesian method for estimating commercial aircraft trajectories using models of the information contained in satellite communications messages and of the aircraft dynamics. This chapter applies the estimator to the accident flight.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 11. Ongoing Refinement

The previous chapters of this book have built up models for the limited available measurement data and for aircraft motion, and then used these models to produce a pdf of the final aircraft latitude and longitude. In principle, one could use this pdf to direct a search and then the very act of searching would provide further measurement data.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Open Access

Chapter 12. Conclusions

In this book we have described our Bayesian approach to defining the MH370 search zone.
Samuel Davey, Neil Gordon, Ian Holland, Mark Rutten, Jason Williams

Backmatter

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