Autonomous collection of dynamically-cued multi-sensor imagery

Brian Daniel; Michael L. Wilson; Jason Edelberg; Mark Jensen; Troy Johnson; Scott Anderson

doi:10.1117/12.882926

25 May 2011 Autonomous collection of dynamically-cued multi-sensor imagery

Brian Daniel, Michael L. Wilson, Jason Edelberg, Mark Jensen, Troy Johnson, Scott Anderson

Proceedings Volume 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII; 80200A (2011) https://doi.org/10.1117/12.882926
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

Citation Download Citation

Brian Daniel, Michael L. Wilson, Jason Edelberg, Mark Jensen, Troy Johnson, and Scott Anderson "Autonomous collection of dynamically-cued multi-sensor imagery", Proc. SPIE 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII, 80200A (25 May 2011); https://doi.org/10.1117/12.882926

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