Efficient multiple emitter localization for fully decentralized large-scale/low-cost multimodal sensor networks

Philip J. Haney; Paul D. Fiore

doi:10.1117/12.2023392

30 September 2013 Efficient multiple emitter localization for fully decentralized large-scale/low-cost multimodal sensor networks

Philip J. Haney, Paul D. Fiore

Author Affiliations +

Proceedings Volume 8857, Signal and Data Processing of Small Targets 2013; 88570K (2013) https://doi.org/10.1117/12.2023392
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

This paper presents a robust approach to the problem of localizing multiple emitters in cluttered environments using a network of low-cost sensors. A pseudo maximum likelihood (PML) function, whose peaks strongly indicate the number and locations of the true emitters, is generated from available sensor measurements. Localization is performed by first iteratively associating the individual sensor measurements to the PML peaks and then generating true maximum likelihood (ML) estimates of the emitter locations based on the associated measurements. These emitter location estimates are fed to an EKF-based, decentralized architecture for initiating, sustaining and sharing local track activity throughout the sensor network. The iterative PML approach is shown to be efficient with computational complexity that is linear in the number of measurements. Additionally, simulation results illustrate the ability of the proposed approach to generate accurate emitter location estimates in cluttered environments for generating and sustaining all track activity in a fully decentralized sensor network.

Citation Download Citation

Philip J. Haney and Paul D. Fiore "Efficient multiple emitter localization for fully decentralized large-scale/low-cost multimodal sensor networks", Proc. SPIE 8857, Signal and Data Processing of Small Targets 2013, 88570K (30 September 2013); https://doi.org/10.1117/12.2023392

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KEYWORDS

Sensors

Sensor networks

Environmental sensing

Position sensors

Data fusion

Monte Carlo methods

Device simulation

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