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Proceedings Paper

Electric-field sensors for bullet detection systems
Author(s): Stephen Vinci; David Hull; Simon Ghionea; William Ludwig; Socrates Deligeorges; Thorkell Gudmundsson; Maciej Noras
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Paper Abstract

Research and experimental trials have shown that electric-field (E-field) sensors are effective at detecting charged projectiles. E-field sensors can likely complement traditional acoustic sensors, and help provide a more robust and effective solution for bullet detection and tracking. By far, the acoustic sensor is the most prevalent technology in use today for hostile fire defeat systems due to compact size and low cost, yet they come with a number of challenges that include multipath, reverberant environments, false positives and low signal-to-noise. Studies have shown that these systems can benefit from additional sensor modalities such as E-field sensors. However, E-field sensors are a newer technology that is relatively untested beyond basic experimental trials; this technology has not been deployed in any fielded systems. The U.S. Army Research Laboratory (ARL) has conducted live-fire experiments at Aberdeen Proving Grounds (APG) to collect data from E-field sensors. Three types of E-field sensors were included in these experiments: (a) an electric potential gradiometer manufactured by Quasar Federal Systems (QFS), (b) electric charge induction, or "D-dot" sensors designed and built by the Army Research Lab (ARL), and (c) a varactor based E-field sensor prototype designed by University of North Carolina-Charlotte (UNCC). Sensors were placed in strategic locations near the bullet trajectories, and their data were recorded. We analyzed the performance of each E-field sensor type in regard to small-arms bullet detection capability. The most recent experiment in October 2013 allowed demonstration of improved versions of the varactor and D-dot sensor types. Results of new real-time analysis hardware employing detection algorithms were also tested. The algorithms were used to process the raw data streams to determine when bullet detections occurred. Performance among the sensor types and algorithm effectiveness were compared to estimates from acoustics signatures and known ground truth. Results, techniques and configurations that might work best for a given sensor platform are discussed.

Paper Details

Date Published: 4 June 2014
PDF: 13 pages
Proc. SPIE 9082, Active and Passive Signatures V, 908205 (4 June 2014); doi: 10.1117/12.2053901
Show Author Affiliations
Stephen Vinci, U.S. Army Research Lab. (United States)
David Hull, U.S. Army Research Lab. (United States)
Simon Ghionea, U.S. Army Research Lab. (United States)
William Ludwig, U.S. Army Research Lab. (United States)
Socrates Deligeorges, BioMimetic Systems, Inc. (United States)
Thorkell Gudmundsson, Optimal Ranging, Inc. (United States)
Maciej Noras, The Univ. of North Carolina at Charlotte (United States)

Published in SPIE Proceedings Vol. 9082:
Active and Passive Signatures V
G. Charmaine Gilbreath; Chadwick Todd Hawley, Editor(s)

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