Performance comparison of localization techniques for sequential WSN discovery
Performance comparison of localization techniques for sequential WSN discovery
- Author(s): Xue Zhang ; M.K. Banavar ; M. Willerton ; A. Manikas ; C. Tepedelenlioglu ; A. Spanias ; T. Thornton ; E. Yeatman ; A.G. Constantinides
- DOI: 10.1049/ic.2012.0120
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- Author(s): Xue Zhang ; M.K. Banavar ; M. Willerton ; A. Manikas ; C. Tepedelenlioglu ; A. Spanias ; T. Thornton ; E. Yeatman ; A.G. Constantinides Source: Sensor Signal Processing for Defence (SSPD 2012), 2012 page ()
- Conference: Sensor Signal Processing for Defence (SSPD 2012)
- DOI: 10.1049/ic.2012.0120
- ISBN: 978-1-84919-712-0
- Location: London, UK
- Conference date: 25-27 Sept. 2012
- Format: PDF
In this paper, the performance of different localization algorithms are compared in the context of the sequential Wireless Sensor Network (WSN) discovery problem. Here, all sensor nodes are at unknown locations except for a very small number of so called anchor nodes at known locations. The locations of nodes are sequentially estimated such that when the location of a given node is found, it may be used to localize others. The underlying performance of such an approach is largely dependent upon the localization technique employed. In this paper, several well-known localization techniques are presented using a united notation. These methods are time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS), direction of arrival (DOA) and large aperture array (LAA) localization. The performance of a sequential network discovery process is then compared when using each of these localization algorithms. These algorithms are implemented in the Java-DSP software package as part of a localization toolbox. (5 pages)
Inspec keywords: telecommunication computing; wireless sensor networks; direction-of-arrival estimation; Java; time-of-arrival estimation; digital signal processing chips; software packages
Subjects: Communications computing; Wireless sensor networks; Signal processing and detection
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