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2.1.1
Sensor Network-Based Countersniper System PinPtr
The Institute for Software Integrated Systems at the Vanderbilt University developed a sensor
network based system to detect and locate shooters in urban environments named PinPtr [1].
This application is in demand of armed forces and law enforcement agencies.
Several sniper detection systems have been developed in the past. Most of these systems
work best in open, flat environments. They struggle to achieve good results in urban terrain
where several complicating factors such as multipath effects or shading effects of the buildings
may occur. Some of the physical phenomena used for sniper detection are:
• Muzzle flash of the weapon, can be detected through an infrared camera and the range
can be estimated through a microphone. It requires direct line of sight, the flash might be
suppressed by the shooter.
• Thermal signature of the bullet in flight.
• Acoustic shock-wave of the bullet travelling at supersonic speed. It is distinctive and
cannot be produced by natural phenomena.
The best results in existing systems have been achieved by employing the time of arrival (TOA)
of muzzle blasts, shock waves or a combination of both. These existing systems are centralized,
using only one or two arrays of microphones. The drawback of this approach is that the localization eventually becomes inaccurate already with a few sensors not detecting the signal; be it
because they are not in the line of sight to the muzzle blast or because the shock wave is shaded
through buildings.
With PinPtr, a system based on a sensor network is introduced as the solution for these
problems. Many sensor nodes distributed over the area of interest increase the chance that several
sensor nodes detect the direct signal and increase the robustness of the system.
The team at the Vanderbilt University implemented and tested a system based on Mica2
Motes sending their TOA information back to a base station, a laptop computer, where a fusion
algorithm calculates the shooters position based on the collected data.
One important prerequisite for successful localization is time synchronization between the
sensor nodes. TOA information of several nodes is used for the fusion algorithm, the more
accurate they are aligned in time, the more accurate the resulting localization can be. For this
implementation the Flooding Time Synchronization Protocol [3] was applied.
Another prerequisite is localization of the sensor nodes themselves. The team experimented
with acoustic localization using the internal sound generator and microphones to localize the
nodes relative to a few anchor nodes. This approach had some limitations such as the range of
the sounder, so the real live tests were done with hand-placed nodes. For this kind of application
it is important to note that the localization periodically has to be repeated, as the enemy might
displace nodes on purpose.
Routing services are very specific to the application, as there is a requirement for a maximum
latency of 2 seconds for the overall system. The TOA information originates from nodes in an
area around the shooter and are generated almost at the same time. PinPtr uses a best-effort,
converge-cast protocol, meaning that the messages are routed to a selected node of the network,
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