A University of Liverpool researcher features in a new BBC documentary 'Why Planes Vanish: The Hunt for MH370' which airs tonight.
Simon Maskell, Professor of Autonomous Systems with the University of Liverpool's School of Electrical Engineering, Electronics and Computer Science, is providing statistical expertise and insight to the search to find Malaysia Airlines flight MH370 which disappeared on March 8, 2014, during a flight from Kuala Lumpur to Beijing.
MH370 left radar coverage less than two hours after take-off from Kuala Lumpur crashing somewhere in the Indian Ocean around two hours after it was due to have arrived in Beijing.
Novel statistical techniques for analysing data from an Inmarsat satellite were developed by the Australian government and then used to constrain where MH370 might be located to an area approximately the size of the UK. This area was searched however, ten years later, Malaysia Airlines flight MH370 has still not been found.
Professor Maskell features in a new BBC documentary 'Why Planes Vanish: The Hunt for MH370' which airs tonight (Wednesday 6 March) .
During the one-hour programme, Professor Maskell discusses the work he and his team are undertaking that could provide a breakthrough in the search to locate missing flight MH370.
Professor Maskell and his team are analysing data relating to an amateur radio technology called Weak Signal Propagation Reporter (WSPR) to see if it could be used to track the final flightpath of the aircraft.
WSPR involves amateur radio operators recording when a transmitter successfully sends a low frequency signal lasting 110 seconds to a receiver that might be as far as 10,000 km away. These signals have been recorded since 2008 and are stored in a huge database, the WSPRnet database.
An aerospace engineer who has been working independently to try to help find MH370 for the last 10 years, Richard Godfrey, believes that MH370 generated anomalies in the WSPR data after it went missing: Richard's hypothesis is that an aircraft passing between the transmitter and receiver causes an increase in the rate at which anomalies are detected.
He believes it is possible to detect such anomalies in the WSPR data over the timeframe of MH370's disappearance and that these anomalies can be used to refine the search area for the missing plane.
This analysis is seen as compelling by some, whilst others are sceptical that WSPR could provide useful information pertinent to finding MH370.
In response, Professor Maskell and his team (Alberto Acuto, Paul Horridge, and Shashi Lakra) are analysing other Boeing 777's flights, for which the trajectories are known, and the associated WSPR data.
The scale being considered far exceeds the analysis that Richard has done to date. The hope is that this analysis will provide conclusive and compelling evidence to substantiate the claim that WSPR can provide useful information. Ultimately, the hope is that this analysis could help define a new search area and so inform a new search for the missing plane.
Professor Maskell said: "I strongly believe that a synergistic mix of statistics, data science and High Performance Computing (HPC) can be used to help find MH370. My team are using their expertise and know how in statistical modelling and Bayesian techniques to analyse vast quantities of WPSR data. We hope that our analysis helps in the quest to provide new evidence to support a new search and help locate MH370."
Professor Maskell heads up the Signal Processing Research Group which specialises in Bayesian statistics, computational methodology, autonomy, machine learning, behavioural analytics and simulation.
He is also Director of the EPSRC Centre for Doctoral Training in Distributed Algorithms which, in partnership with industrial partners, provides PhD students with the skills, theory and technical experiences to meet the world's pressing need for highly-trained data scientists who understand about HPC and can apply that combination of skills to help solve challenging real-world problems.
'Why Planes Vanish: The Hunt for MH370' will be broadcast on BBC 1 at 8pm on Wednesday, 6 March and will also be available to watch on BBC iPlayer.
