How Data Science Powered the Search for MH370 (hpe.com)

"In the absence of physical evidence, scientists are employing powerful computational tools to attempt to solve the greatest aviation mystery of our time: the disappearance of flight MH370." Slashdot reader Esther Schindler shared this article from HPE Insights: Satellite communications provider Inmarsat announced it had found recorded signals in its archives that MH370 had sent for another six hours after it disappeared. The plane had been aloft and flying for that whole time -- but where had it gone? As Inmarsat scientists examined the signals, they saw that what they had was not data such as text messages or location information. Rather, the signals contained metadata: information about the signal itself. This was recorded as the satellite automatically contacted the plane's communications system every hour to see if it was still logged on. Bafflingly, whoever had taken the plane hadn't used the satcom system to communicate with the outside world, but had switched it off and then on again, leaving it able to exchange hourly "pings" with the satellite. Some of the metadata related to extremely subtle variations in the frequency of the signal. "We're talking about changes as big as one part in a billion," says Inmarsat scientist Chris Ashton.

Nobody had tried to use this kind of data to try to locate an airplane before. At first, Ashton's team didn't know if the attempt would work. But painstakingly, over the course of weeks, the team figured out how the movement of the plane, the orbital wobble of the satellite, and the electronics within the satcom system all interacted to create the data values that had been received. "We had to create the model from scratch," Ashton says. Their work revealed that the plane had flown into the remote southern Indian Ocean. They didn't know where exactly. But since there are no islands in that part of the world, it was impossible that anyone could have survived. For the first time in history, hundreds of people were declared legally dead based on mathematics alone.
Then mathematician Dr. Neil Gordon led a team from the Defense Science and Technology Group "to extract a path from a subset of the Inmarsat data called the Burst Timing Offset. This measured how quickly the aircraft responded each time the satellite pinged it, and was used to determine the distance between the satellite and the plane." They ultimately generate "a probabilistic 'heat map' of the plane's most likely resting places using a technique called Bayesian analysis. These calculations allowed the DSTG team to draw a box 400 miles long and 70 miles across, which contained about 90 percent of the total probability distribution.

Comments

Very userful

[110010001000]

"Their work revealed that the plane had flown into the remote southern Indian Ocean. They didn't know where exactly."

Amazing stuff.

Re:Very userful

[Solandri]

Drift analysis relies on the average value of year's worth of estimated currents and winds. The satellite data analysis relied on precisely known satellite positions and the speed of light (which is also precisely known). My money is on the satellite analysis being more accurate.

But until the plane is actually found, there's no point arguing which is correct. We can't draw any conclusions until the plane is found. And it probably will never be found. Even if the search area indicated by the satellite signals is accurate, finding it there was always going to be a long shot (after the pingers stopped after 30 days). Given the relative sizes of the plane and the search area, finding a needle in a haystack is child's play by comparison. This is like trying to find a needle in field of haystacks.

If they wanted to test the accuracy of their satellite analysis, they should be running it on planes on regular flights. They can calculate a plane's position at certain times based on similar satellite ping times, then check it against the plane's actual flight path. Do it enough times and you can figure out just how accurate the methodology is.

Re: Very userful

[ls671]

Last time I tried, I couldn't grab aluminum with a magnet.

Let's not forget what brought us here

[eclectro]

Everybody would not be needing to comb over minute pieces of data and vast esoteric computations if service providers had behaved better.

The satellite service was capable of gathering the gps data from the plane instantaneously and throughout its flight path. But the satellite company was charging for it, and Malaysian authorities did not want to pay for it presumably because it cost too much.

If the gps location service had been available for this flight, one can't help but wonder if there was a possible intervention that could have been undertaken when the plane would have been discovered wildly off course, and even though it appears the crash was not survivable, the quick crash site discovery and possible apprehension of possible criminals involved (if there are any).

As it is, everybody was chintzy all the way around at the expense of the safety of the flying public.

Re:MH370, aka the moment CNN stopped being real ne

[Anonymous Coward]

CNN has been shit for a lot longer than that.

Re:Just Use Logic

[thegreatbob]

While I generally disagree with your original post, CNN is inherently an absolutely awful citation.

MH370 is STILL missing....

[kenwd0elq]

I'd be a whole lot more impressed about the performance of "Big Data" if the submarine ROVs had found any trace of the aircraft. Right now, what they have is a big fat NOTHING. Some control surfaces washed up on islands a thousand miles away are not indicative of the performance of any sort of data analysis.

Too early

[mseeger]

This post comes too early. First find the damn thing, then boast about how this or that method helped finding it.

That is not "Data Science"

[gweihir]

That is merely a bit more special RF signal analysis engineering and not so much different from other radio-location tasks, although you usually have more data. Calling this "Data Science" is nonsense.