Share Email Print

Proceedings Paper

Fusing airborne video with RF location estimates to locate moving emitters in dense mover environments
Author(s): Robert Cole; Geoffrey Guisewite; Guy Swope
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 20 June 2014
PDF: 8 pages
Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 909105 (20 June 2014); doi: 10.1117/12.2050359
Show Author Affiliations
Robert Cole, Raytheon Intelligence and Information Services (United States)
Geoffrey Guisewite, Raytheon Intelligence and Information Services (United States)
Guy Swope, Consultant (United States)

Published in SPIE Proceedings Vol. 9091:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
Ivan Kadar, Editor(s)

© SPIE. Terms of Use
Back to Top