Source localization in inhomogeneous underwater medium using sensor arrays: Received signal strength approach

• Published in: Signal processing Vol. 183; p. 108047
• Main Authors: Poursheikhali, Saleheh, Zamiri-Jafarian, Hossein
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2021
• Subjects: Acoustic; Inhomogeneous; Received signal strength (RSS); Sensor array network; Time difference of arrival (TDOA); Underwater localization; Sensor array network; Inhomogeneous; Acoustic; Received signal strength (RSS); Time difference of arrival (TDOA); Underwater localization
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2021.108047

•Combine the TDOA and the RSS methods to improve the performance of asynchronized localization method in an inhomogeneous underwater medium.•Obtain a new steering vector for each sensor array in an inhomogeneous environment by analyzing wave propagation in underwater medium. The developed steering vector can be applied to both far- and near-filed scenarios.•Develop an Array-RSS localization method based on an iterative algorithm to estimate source location in a network of asynchronous sensor arrays by measuring the RSS parameter of the beamformer output. Source localization is one of the major challenges of the underwater acoustic sensor network (UASN). The received signal strength (RSS) and the time of flight (TOF) are the main localization approaches. The requirement of the TOF method is the synchronization of sensors, however, synchronization is a challenging issue in an underwater environment and the RSS approach can be considered as an appropriate choice to overcome it. In this paper, we aim to improve the performance of the RSS localization approach by applying a network of acoustic sensor arrays in an inhomogeneous underwater medium. Considering the inhomogeneity as one of the basic challenges in underwater beamforming, at first we analyze the problem of wave propagation in inhomogeneous underwater medium and derive a new steering vector for both far- and near-field scenarios. Then, we develop an Array-RSS underwater narrowband source localization method based on an iterative algorithm. Several computer simulations are accomplished for evaluating the performance of our proposed method. Simulation results demonstrate the considerable effect of using a sensor array in the performance improvement of the RSS localization, such that under a particular signal bandwidth the performance of the Array-RSS method is comparable with that of the TOF at high SNRs.