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Proceedings Paper

New estimation architecture for multisensor data fusion
Author(s): Joseph M. Covino; Barry E. Griffiths
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Paper Abstract

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Paper Details

Date Published: 1 July 1991
PDF: 12 pages
Proc. SPIE 1478, Sensors and Sensor Systems for Guidance and Navigation, (1 July 1991); doi: 10.1117/12.45628
Show Author Affiliations
Joseph M. Covino, Synetics Corp. (United States)
Barry E. Griffiths, Synetics Corp. (United States)


Published in SPIE Proceedings Vol. 1478:
Sensors and Sensor Systems for Guidance and Navigation
Jack F. Wade; Avi Tuchman, Editor(s)

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