TY - GEN
T1 - Long-term testing of acoustic system for tracking low-flying aircraft
AU - Sedunov, Alexander
AU - Salloum, Hady
AU - Sutin, Alexander
AU - Sedunov, Nikolay
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/11
Y1 - 2018/12/11
N2 - Stevens Institute of Technology conducted a longterm test of an acoustic system designed to track low-flying small aircraft in remote locations. The system consists of 4 nodes located between 1 and 4 km apart in a mountainous terrain. Each node is comprised of a pyramid-shaped volumetric cluster of 5 microphones, an embedded computer, and a pan-tilt-zoom camera steered to detected targets in real time. A communication device was used to transfer data to a centralized location. Each node estimates the direction of arrival toward the sound sources and sends it along to a central processing computer. The central computer combines the data from all nodes to generate tracks and classify targets. The duration and the scale of the deployment allowed to identify and solve many problems, including the effects of propagation delays between nodes on cooperative localization and tracking, the seasonal changes in environmental noise, persistent and transient noise sources, and the diversity of targets of opportunity and their signatures. The propagation delay effects led to the development of separate trackers for review of target trajectories and for immediate action such as automatically steering the camera.
AB - Stevens Institute of Technology conducted a longterm test of an acoustic system designed to track low-flying small aircraft in remote locations. The system consists of 4 nodes located between 1 and 4 km apart in a mountainous terrain. Each node is comprised of a pyramid-shaped volumetric cluster of 5 microphones, an embedded computer, and a pan-tilt-zoom camera steered to detected targets in real time. A communication device was used to transfer data to a centralized location. Each node estimates the direction of arrival toward the sound sources and sends it along to a central processing computer. The central computer combines the data from all nodes to generate tracks and classify targets. The duration and the scale of the deployment allowed to identify and solve many problems, including the effects of propagation delays between nodes on cooperative localization and tracking, the seasonal changes in environmental noise, persistent and transient noise sources, and the diversity of targets of opportunity and their signatures. The propagation delay effects led to the development of separate trackers for review of target trajectories and for immediate action such as automatically steering the camera.
KW - low-flying aircraft
KW - passive acoustics
KW - signal processing
UR - http://www.scopus.com/inward/record.url?scp=85060398549&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060398549&partnerID=8YFLogxK
U2 - 10.1109/KSE.2018.8573366
DO - 10.1109/KSE.2018.8573366
M3 - Conference contribution
AN - SCOPUS:85060398549
T3 - Proceedings of 2018 10th International Conference on Knowledge and Systems Engineering, KSE 2018
BT - Proceedings of 2018 10th International Conference on Knowledge and Systems Engineering, KSE 2018
A2 - Phuong, Tu Minh
A2 - Nguyen, Minh Le
T2 - 10th International Conference on Knowledge and Systems Engineering, KSE 2018
Y2 - 1 November 2018 through 3 November 2018
ER -