Optical plankton: an optical oceanic probing scheme

Debbie Kedar; Shlomi Arnon

doi:10.1117/1.2803234

1 October 2007 Optical plankton: an optical oceanic probing scheme

Debbie Kedar, Shlomi Arnon

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 1, Issue 1, 013541 (October 2007). https://doi.org/10.1117/1.2803234

Abstract

In this paper, we evaluate the possibility of a wireless sensor network concept operating in the oceanic environment. A population of underwater sensor nodes, termed "optical plankton," form a distributed sensor network characterized by the deployment of many miniature and low-cost sensors capable of profiling the particulate composition in the immediate marine environs. The stimulation of backscatter signals from the surrounding medium is one principle of operation studied, but the potential for additional probing methods is discussed. The optically probed signal is communicated to a base station, where the large number of received signals is fused to obtain an accurate estimate of the nature of the local aqueous medium. The many similarities and differences between the atmospheric and oceanic sensing and wireless communication environments are discussed and the distinctive features of an oceanic probing system are underlined. Specific scientific applications are briefly reviewed. The challenges to be met are addressed in general and a focused analysis of the specific issue of multi-access interference (MAI), common to all optical wireless-based sensor networks, is presented. Novel analytical approaches have been employed to evaluate and quantify the MAI. It is the object of this paper to assess the feasibility of a novel miniaturized oceanic probing system and explore some of the challenges. It would appear that the proposed scheme could be the basis of an innovative oceanic probing method and fill a niche not as yet catered for with existing technologies.

Citation Download Citation

Debbie Kedar and Shlomi Arnon "Optical plankton: an optical oceanic probing scheme," Journal of Applied Remote Sensing 1(1), 013541 (1 October 2007). https://doi.org/10.1117/1.2803234

Published: 1 October 2007

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