Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

Jerry Burman; Joao Hespanha; Upamanyu Madhow; Tien Pham

doi:10.1117/12.882802

23 May 2011 Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Tien Pham

Author Affiliations +

Proceedings Volume 8047, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR II; 80470Y (2011) https://doi.org/10.1117/12.882802
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Citation Download Citation

Jerry Burman, Joao Hespanha, Upamanyu Madhow, and Tien Pham "Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance", Proc. SPIE 8047, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR II, 80470Y (23 May 2011); https://doi.org/10.1117/12.882802

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