New estimation architecture for multisensor data fusion

Joseph M. Covino; Barry E. Griffiths

doi:10.1117/12.45628

1 July 1991 New estimation architecture for multisensor data fusion

Joseph M. Covino, Barry E. Griffiths

Proceedings Volume 1478, Sensors and Sensor Systems for Guidance and Navigation; (1991) https://doi.org/10.1117/12.45628
Event: Orlando '91, 1991, Orlando, FL, United States

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.

Citation Download Citation

Joseph M. Covino and Barry E. Griffiths "New estimation architecture for multisensor data fusion", Proc. SPIE 1478, Sensors and Sensor Systems for Guidance and Navigation, (1 July 1991); https://doi.org/10.1117/12.45628

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