Nonparametric belief propagation for self-localization of sensor networks

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Nonparametric belief propagation for self-localization of sensor networks (2005)

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by Alexander T. Ihler , John W. Fisher III , Randolph L. Moses , Alan S. Willsky

Venue:	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Citations:	98 - 3 self

BibTeX

@ARTICLE{Ihler05nonparametricbelief,
    author = {Alexander T. Ihler and John W. Fisher III and Randolph L. Moses and Alan S. Willsky},
    title = {Nonparametric belief propagation for self-localization of sensor networks},
    journal = {IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS},
    year = {2005},
    volume = {23},
    pages = {809--819}
}

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Abstract

Automatic self-localization is a critical need for the effective use of ad-hoc sensor networks in military or civilian applications. In general, self-localization involves the combination of absolute location information (e.g. GPS) with relative calibration information (e.g. distance measurements between sensors) over regions of the network. Furthermore, it is generally desirable to distribute the computational burden across the network and minimize the amount of inter-sensor communication. We demonstrate that the information used for sensor localization is fundamentally local with regard to the network topology and use this observation to reformulate the problem within a graphical model framework. We then present and demonstrate the utility of nonparametric belief propagation (NBP), a recent generalization of particle filtering, for both estimating sensor locations and representing location uncertainties. NBP has the advantage that it is easily implemented in a distributed fashion, admits a wide variety of statistical models, and can represent multi-modal uncertainty. Using simulations of small- to moderately-sized sensor networks, we show that NBP may be made robust to outlier measurement errors by a simple model augmentation, and that judicious message construction can result in better estimates. Furthermore, we provide an analysis of NBP’s communications requirements, showing that typically only a few messages per sensor are required, and that even low bit-rate approximations of these messages can have little or no performance impact.

Keyphrases

nonparametric belief propagation sensor network judicious message construction effective use automatic self-localization measurement error location uncertainty sensor localization multi-modal uncertainty relative calibration information sensor location low bit-rate approximation nbp communication requirement recent generalization ad-hoc sensor network graphical model framework performance impact statistical model civilian application distributed fashion moderately-sized sensor network network topology inter-sensor communication critical need wide variety particle filtering simple model augmentation distance measurement computational burden absolute location information

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