Tech twist lets soldiers identify sniper positions in half a second
Radical revamp of WW1 research uses mobile phone to detect shooter distance and direction. Richard A Lovett reports.
Military researchers are closing in on using cell phones to detect the location of snipers from a single shot.
The technique is a sophisticated version of one developed as far back as World War I by Australian-born Nobel laureate William Lawrence Bragg, who developed a technique known as “sound ranging”, based on the difference in the arrival times of sound waves at two different microphones.
Bragg, who had won the 1915 Nobel Prize in Physics for his work in X-ray diffraction, was able to use this method to pinpoint the location of enemy artillery to within 10 metres, Dan Costley, a researcher in sound ranging with the US Army Engineer Research and Development Centre in Vicksburg, Mississippi, reported recently at a meeting of the Acoustical Society of America, in Louisville, Kentucky.
Bragg’s method, developed generations before the dawn of modern electronics, used microphones separated by as much as two kilometres, and required several minutes to process results.
The new method, presented at the same conference by Sébastien Hengy, a combat acoustics researcher at the French-German Research Institute of Saint-Louis, Saint-Louis, France, dispenses with the need for long-distance baselines or slow, laborious computations.
Instead, it uses microphones built into the soldiers’ own tactical headsets, then harnesses the computing power of their smartphones to determine the range and direction of a sniper attack. It’s all done within half a second, based on a single shot.
“At the beginning of an ambush, the most important thing for soldiers is to know where the shooting is coming form, so that they can hide on the right side of a vehicle, or at least aim in the right direction,” Hengy says. “And they need this information very fast.”
The soldiers’ headsets, called Tactical Communication and Protective Systems (TCAPS), are designed to simultaneously keep soldiers in communication with each other and in acoustical touch with their environment, while protecting their hearing from the sound of their own gunfire or other loud nearby noises. To do this, they include microphones, positioned near each ear.
When a sniper shot passes nearby, Hengy says, it produces two types of sound waves.
The first, generated by the supersonic projectile, is a shockwave that fans out from the bullet as it passes. The second is the muzzle wave, generated by the explosion of powder in the barrel of the gun.
The difference in arrival time between the two sounds is a measure of the distance from which the shot was fired.
The difference in time between when the supersonic shockwave is detected by the right-ear microphone and the left-ear microphone is a clue to the direction of the shooter.
The existence of the soldier’s head between the two microphones is a complicating factor affecting the acoustics, Hengy says, but his team has figured out how to take it into account by using a 3D model of an artificial one.
“This helps us estimate the time delay between the right ear and the left ear,” he says.
Another complicating factor is the orientation of the soldier’s head at the time the shot is heard by the microphones, but that can be accounted for with tiny compasses mounted in the TCPAS headset.
All of the necessary computations, Hengy adds, can be done by sending the information to the smartphone, which has a processor more than sophisticated enough to handle the calculations and display the answer nearly as fast as the soldier can react.
“This allows us to estimate the position of the shooter on one shot,” he says. “We can show the direction of the threat and how to react.”
It’s even possible to combine data from several soldiers’ TCPAS headsets to produce an even more accurate calculation, he adds.
Currently, Hengy says, the technology is in the proof-of-concept stage. But barring glitches, the first field tests (using artificial heads, so nobody actually gets shot at) will be made in September, with a final demonstration set for June 2020. If all goes well, the technology will be deployed as early as 2021.