Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Time Synchronization for Wireless Sensor Networks
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Sensor network-based countersniper system
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Shooter localization and weapon classification with soldier-wearable networked sensors
Proceedings of the 5th international conference on Mobile systems, applications and services
Learning sound location from a single microphone
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Acoustic shooter localization with a minimal number of single-channel wireless sensor nodes
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Weapon classification and shooter localization using distributed multichannel acoustic sensors
Journal of Systems Architecture: the EUROMICRO Journal
Acoustic shockwave-based bearing estimation
Proceedings of the 12th international conference on Information processing in sensor networks
Hi-index | 0.04 |
Shooter localization in a wireless network of microphones is studied. Both the acoustic muzzle blast (MB) from the gunfire and the ballistic shock wave (SW) from the bullet can be detected by the microphones and considered as measurements. The MB measurements give rise to a standard sensor network problem, similar to time difference of arrivals in cellular phone networks, and the localization accuracy is good, provided that the sensors are well synchronized compared to the MB detection accuracy. The detection times of the SW depend on both shooter position and aiming angle and may provide additional information beside the shooter location, but again this requires good synchronization. We analyze the approach to base the estimation on the time difference of MB and SW at each sensor, which becomes insensitive to synchronization inaccuracies. Cramér-Rao lower bound analysis indicates how a lower bound of the root mean square error depends on the synchronization error for the MB and the MB-SW difference, respectively. The estimation problem is formulated in a separable nonlinear least squares framework. Results from field trials with different types of ammunition show excellent accuracy using the MB-SW difference for both the position and the aiming angle of the shooter.