01817nam a2200205   4500001000700000100004100007101000800048200014100056210006300197215002000260225003400280300004000314330107100354606001501425606003301440606001301473606002101486606001901507710008501526384486  a20071008d2007       y0pory50      ba  aeng  aShooter localization and weapon classification with soldier wearable networked sensorsbRecurso eletrónicofPeter Volgyesi... [et al.]  aNashvillecInstitute for Software Integrated Systemsd2007  a1 CD-ROMd12 cm  aTechnical ReportvISIS-07-802  aResumo inserto no próprio artigo.  aThe paper presents a sensor network-based mobile countersniper system. A sensor node consists of a helmet-mounted microphone array, a COTS MICAz mote for inter-node communication and a custom sensorboard that implements the acoustic detection and Time of Arrival (ToA) estimationalgorithms on an FPGA. A 3-axis compass provides self orientation and Bluetooth is used for communication with the soldier’s PDA running the data fusion and the user interface. The heterogeneous sensor fusion algorithm can work with data from a single sensor or it can fuse ToA or Angle of Arrival (AoA) observations of muzzleblasts and ballistic shockwaves from multiple sensors. The system estimates the trajectory, the range, the caliber and the weapon type. The paper presents the system design and the results from an independent evaluation at the US Army Aberdeen Test Center. The system performance is characterized by 1- degree trajectory precision and over 95% caliber estimation accuracy for all shots, and close to 100% weapon estimation accuracy for 4 out of 6 guns tested.  aTECNOLOGIA  aDETECÇÃO DE ARMA DE FOGO  aATIRADOR  aFORÇAS ARMADAS  aESTADOS UNIDOS  aESTADOS UNIDOSbVanderbilt University. Institute for Software Integrated Systems