NDLI: A compensated sliding-window DFT algorithm for fine-grained underwater acoustic ranging

Content Provider	IEEE Xplore Digital Library
Author	Shatara, S. Xiaobo Tan
Copyright Year	2009
Description	Author affiliation: Motorola, 1301 E. Algonquin Rd, Schaumburg, IL 60196, USA (Shatara, S.) \|\| Smart Microsystems Laboratory, Department of Electrical and Computer Engineering, Michigan State University, East Lansing, 48824, USA (Xiaobo Tan)
Abstract	Fine-grained (sub-meter) ranging and localization is critical to the deployment of dense, mobile sensor networks in aquatic environments. However, such a task is faced with a number of challenges, including noisy underwater environments, limitation on size and complexity of localization hardware, and constraints on computing capabilities of sensor platforms. In this paper we present a sliding-window discrete Fourier transform (DFT)-based algorithm for precise detection of the arrival of a monotone acoustic signal, as a key enabling step in measuring the time of flight (TOF) of the acoustic signal for localization of the sensor node. The algorithm accommodates the rise dynamics of the signal and compensates for the latency in detection given the signal model, detection threshold, and steady-state signal amplitude. The algorithm is implemented onboard a small biomimetic robotic fish, and experiments in an indoor pool have shown that the proposed method results in an underwater ranging error of 1.4 wavelengths (74.3 cm), and is thus promising for localization of dense aquatic networks. The proposed method has also shown robustness in comparison with other tested methods including a matched filter-type method.
Starting Page	4054
Ending Page	4059
File Size	362929
Page Count	6
File Format	PDF
ISBN	9781424438037
DOI	10.1109/IROS.2009.5354794
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Underwater acoustics Acoustic sensors Acoustic signal detection Discrete Fourier transforms Face detection Acoustic noise Working environment noise Hardware Acoustic measurements Time measurement
Content Type	Text
Resource Type	Article

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