Sensor Network Based Countersniper System Gyula Simon Gy rgy Balogh G bor Pap Mikl s Mar ti Branislav Kusy J nos Sallai kos L deczi Andr s N das Ken Frampton Institute for Software Integrated Systems Vanderbilt University 2015 Terrace Place Nashville TN 37203 USA Phone 1 615 343 7472 e mail gyula simon miklos maroti akos ledeczi vanderbilt edu as urban terrain The main problems degrading the performance of these systems are the poor coverage due to the shading effect of the buildings and the presence of multipath effects ABSTRACT An ad hoc wireless sensor network based system is presented that detects and accurately locates shooters even in urban environments The system consists of a large number of cheap sensors communicating through an ad hoc wireless network thus it is capable of tolerating multiple sensor failures provides good coverage and high accuracy and is capable of overcoming multipath effects The performance of the proposed system is superior to that of centralized countersniper systems in such challenging environment as dense urban terrain In this paper in addition to the overall system architecture the acoustic signal detection the most important middleware services and the unique sensor fusion algorithm are also presented The system performance is analyzed using real measurement data obtained at a US Army MOUT Military Operations in Urban Terrain facility Several physical phenomena can be used for sniper detection purposes The Viper system built by Maryland Advanced Development Lab utilizes an infrared camera to detect the muzzle flash of the weapon 17 It is augmented with a microphone to detect the muzzle blast for range estimation Both sensors require direct line of sight Other limitations include the possibility of flash suppression by the shooter and a relatively high false alarm rate that is reduced by employing two disparate sensors 21 Another approach measures the thermal signature of the bullet in flight 21 Illuminating the sniper s scope with a laser and measuring the reflections can also provide accurate bearing estimates 21 None of these approaches however provide a comprehensive solution to the problem Despite the efforts of using different information sources for sniper detection so far acoustic signals such as muzzle blasts and shock waves provide the easiest and most accurate way to detect shots and the majority of the existing countersniper systems use them as the primary information source 20 The most obvious acoustic event generated by the firing of a conventional nonsilenced weapon is the blast The muzzle blast is a loud characteristic noise originating from the end of the muzzle and propagating spherically away at the speed of sound Typical rifles fire projectiles at supersonic velocities thereby producing acoustic shocks along their trajectory 20 Shockwaves can be used to accurately determine projectile trajectories because the shock waveform is distinctive and cannot be produced by any other natural phenomenon The simplified geometry of the bullet trajectory and the associated muzzle blast and shockwave fronts are shown in Figure 1 Categories and Subject Descriptors B 7 1 Integrated Circuits Types and Design Styles Algorithms implemented in hardware C 2 2 Computer Communication Networks Network Protocols Routing protocols G 1 0 Mathematics of Computing Numerical Analysis Numerical algorithms J 7 Computer Applications Computers in Other Systems Military General Terms Algorithms Design Measurement Performance Keywords Sensor Networks Middleware Services Time Synchronization Message Routing Data Fusion Acoustic Source Localization 1 INTRODUCTION Detecting and accurately locating shooters has been an elusive goal of armed forces and law enforcement agencies for a long time now Among the several systems developed in the past decade only a few can be used in such challenging environments Commercial acoustic sniper detection systems use these phenomena They measure the time of arrival TOA and some other characteristics of shockwaves and or the TOA of muzzle blasts BBN s Bullet Ears system utilizes one or two small arrays of microphones providing estimates of the caliber speed and trajectory of the projectile and also a range estimate for the shooter The average accuracy of the azimuth and elevation estimators is approximately 1 2 and 3 degrees respectively while the distance estimator s accuracy is approx 1 6 4 The similar French Pilar system uses two microphone arrays achieving bearing and range accuracy of 2 and 10 respectively 11 Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page To copy otherwise or republish to post on servers or to redistribute to lists requires prior specific permission and or a fee SenSys 04 November 3 5 2004 Baltimore Maryland USA Copyright 2004 ACM 1 58113 879 2 04 0011 5 00 1 S Shock wave front vS vB X A sin v 1 S M vB Muzzle wave Figure 2 System architecture Figure 1 Acoustic events generated by a shot The muzzle blast produces a spherical wave front traveling at the speed of sound vs from the muzzle A to the sensor S The shock wave is generated in every point of the trajectory of the supersonic projectile producing a cone shaped wave front assuming the speed of the projectile is constant vB In reality the wave front is not a cone rather it resembles the surface of a half football since the bullet is continuously decelerating The shockwave reaching sensor S was generated in point X The angle of the shockwave cone is determined by the Mach number M of the projectile software and the overall system architecture Next the middleware services utilized in the application are presented Then we briefly summarize the signal detection algorithm performed on the sensor nodes The sensor fusion algorithm is also presented followed by a comprehensive analysis of the experimental results gathered during field trials in an urban environment Finally we present our future plans and conclusions 2 SYSTEM ARCHITECTURE The countersniper application utilizes the traditional layered architecture as shown in Figure 2 The hardware layer is built upon the widely used Mica mote platform developed by UC Berkeley 10 The second generation Mica2 features a 7 3 MHz 8 bit Atmel ATmega 128L low power microcontroller a 433 MHz