JOURNAL ARTICLE

Using spectral correlation for non-cooperative RSS-based positioning

Abstract

Typically, methods for received signal strength (RSS) based source localization assume that the signal can be separated from the noise and interference. However, in non-cooperative applications where the details of the modulation format are not known a priori, this is not possible. In a high SNR environment, the RSS of the signal can be estimated from the power spectral density (PSD) via energy detection, but the PSD becomes dominated by noise at low SNR, leading to a loss of positioning information. This paper proposes the use of the spectral correlation function (SCF) for RSS-based localization, as the SCF has been shown to outperform simple energy detection for detecting the presence of a signal.

Keywords:
RSS Spectral density Energy (signal processing) Computer science Interference (communication) SIGNAL (programming language) Noise (video) Noise power Signal-to-noise ratio (imaging) Correlation Electronic engineering Correlation function (quantum field theory) Power (physics) Algorithm Telecommunications Artificial intelligence Physics Mathematics Engineering Statistics

Metrics

4
Cited By
0.24
FWCI (Field Weighted Citation Impact)
17
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications

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