localization plays a significant role in many underwater applications. Underwater communications encounter critical challenges different from terrestrial wireless sensor networks. In this study, we focus on the challenges of the variable sound speed underwater and synchronization. Among localization approaches, the received signal strength (RSS) is cost-effective and, unlike time-based approaches is synchronization-free. In some applications, the source transmitted power is unknown or hard to obtain. While this parameter is required to be known in RSS-based approaches, it is not a requirement in differential RSS (DRSS) based approaches. Regarding these issues, in this paper, we propose a DRSS-based localization algorithm considering an iso-gradient sound speed profile in an underwater medium when the source transmitted power is unknown. To improve the received signals’ SNR, we use a network of sensor arrays where beamforming is conducted within each array. Then, DRSS values are calculated and the iterative DRSS-based localization algorithm is presented. We show the effectiveness of the proposed algorithm compared with the Array-RSS and the Array-TDOA algorithms via computer simulations. Results indicate that the Array-DRSS performs accurately when the source transmitted power is unknown. Moreover, it outperforms the Array-TDOA algorithm when low bandwidth is available.

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