Sound velocity profile estimation using ray tracing and nature inspired meta‐heuristic algorithms in underwater sensor networks

Abstract

In water, the velocity of sound is a function of temperature, pressure, and salinity. The sound velocity in the ocean varies with depth and estimation of the sound velocity profile is interesting in its right for environmental monitoring. The sound velocity profile is required for sound navigation and ranging signal processing algorithms such as MUSIC. Also, the localisation of sensor nodes in an underwater sensor network requires a good estimate of the velocity profile. This study proposes an algorithm that calculates the sound velocity profile of ocean water using time of flight measurements between anchor nodes. The velocity profile is estimated in the discrete cosine transform domain to reduce the complexity of the algorithm, using two well-known meta-heuristic algorithms namely artificial bee colony and firefly algorithms. The Ray tracing method is used to improve the accuracy of the velocity profile. The Cramer–Rao lower bound of the proposed scheme is also derived. The localisation of a target node is also performed using the estimated sound velocity profile.