Paper
20 June 2014 Fusing airborne video with RF location estimates to locate moving emitters in dense mover environments
Robert Cole, Geoffrey Guisewite, Guy Swope
Author Affiliations +
Abstract
Moving emitters in dense environments present challenges for conventional, single-INT, SIGINT-based location estimation. The emergence of wide field of view, high resolution, persistent EO imaging from airborne sensors introduces the possibility of a multi-INT approach via video-SIGINT data fusion. Video-based object extraction techniques can identify moving objects with very high spatial precision, precision that can be leveraged to locate moving emitters if a means of associating extracted movers to SIGINT observations can be demonstrated. To examine the feasibility of improving SIGINT location estimates in this manner, we conducted a simulation study in which we correlated simulated video tracks and SIGINT observations. In this study, we generated simulated vehicle movement over a road network under varying levels of mover density. Simulated SIGINT was generated via a conventional multicollector location estimation approach under varying levels of SIGINT processing noise level. Association of the simulated SIGINT to the video tracks was performed via a fusion algorithm that used a physical model to re-process the SIGINT observables under constraints derived from the video tracks. Our results suggest that with only a few SIGINT observations from a given moving emitter, the associated mover can be identified at a low error rate, even under levels of processing noise that would result in extremely high levels of location estimate uncertainty, suggesting the potential utility of our approach.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Cole, Geoffrey Guisewite, and Guy Swope "Fusing airborne video with RF location estimates to locate moving emitters in dense mover environments", Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 909105 (20 June 2014); https://doi.org/10.1117/12.2050359
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KEYWORDS
Signals intelligence

Video

Roads

Error analysis

Video surveillance

Statistical analysis

Computer simulations

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