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Proceedings Paper

PADF RF localization criteria for multimodel scattering environments
Author(s): Miguel Gates; Christopher Barber; Rastko Selmic; Huthaifa Al-Issa; Raul Ordonez; Atindra Mitra
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Paper Abstract

This paper provides a summary of recent results on a novel multi-platform RF emitter localization technique denoted as Position-Adaptive RF Direction Finding (PADF). This basic PADF formulation is based on the investigation of iterative path-loss based (i.e. path loss exponent) metrics estimates that are measured across multiple platforms in order to robotically/intelligently adapt (i.e. self-adjust) the location of each distributed/cooperative platform. Recent results at the AFRL indicate that this position-adaptive approach shows potential for accurate emitter localization in challenging embedded multipath environments (i.e., urban environments). As part of a general introductory discussion on PADF techniques, this paper provides a summary of our recent results on PADF and includes a discussion on the underlying and enabling concepts that provide potential enhancements in RF localization accuracy in challenging environments. Also, an outline of recent results that incorporate sample approaches to real-time multi-platform data pruning is included as part of a discussion on potential approaches to refining a basic PADF technique in order to integrate and perform distributed self-sensitivity and self-consistency analysis as part of a PADF technique with distributed robotic/intelligent features. The focus of this paper is on the experimental performance analysis of hardware-simulated PADF environments that generate multiple simultaneous mode-adaptive scattering trends. We cite approaches to addressing PADF localization performance challenges in these multi-modal complex laboratory simulated environments via providing analysis of our multimodal experiment design together with analysis of the resulting hardware-simulated PADF data.

Paper Details

Date Published: 21 June 2011
PDF: 14 pages
Proc. SPIE 8021, Radar Sensor Technology XV, 80210W (21 June 2011); doi: 10.1117/12.879760
Show Author Affiliations
Miguel Gates, Louisiana Tech Univ. (United States)
Christopher Barber, Louisiana Tech Univ. (United States)
Rastko Selmic, Louisiana Tech Univ. (United States)
Huthaifa Al-Issa, Univ. of Dayton (United States)
Raul Ordonez, Univ. of Dayton (United States)
Atindra Mitra, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 8021:
Radar Sensor Technology XV
Kenneth I. Ranney; Armin W. Doerry, Editor(s)

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