Ranging in an Underwater Medium with Multiple Isogradient Sound Speed Profile Layers

Abstract

In this paper, we analyze the problem of acoustic ranging between sensor nodes in an underwater environment. The underwater medium is assumed to be composed of multiple isogradient sound speed profile (SSP) layers where in each layer the sound speed is linearly related to the depth. Furthermore, each sensor node is able to measure its depth and can exchange this information with other nodes. Under these assumptions, we first show how the problem of underwater localization can be converted to the traditional range-based terrestrial localization problem when the depth information of the nodes is known a priori. Second, we relate the pair-wise time of flight (ToF) measurements between the nodes to their positions. Next, based on this relation, we propose a novel ranging algorithm for an underwater medium. The proposed ranging algorithm considers reflections from the seabed and sea surface. We will show that even without any reflections, the transmitted signal may travel through more than one path between two given nodes. The proposed algorithm analyzes them and selects the fastest one (first arrival path) based on the measured ToF and the nodes’ depth measurements. Finally, in order to evaluate the performance of the proposed algorithm we run several simulations and compare the results with other existing algorithms.

A hydroacoustic positioning system for the experimental cluster of the cubic-kilometer-scale neutrino telescope at Lake Baikal

“…As was shown in [13,21], the simplifying assump tion on the rectilinear signal propagation fails to ensure a high positioning accuracy. In turn, assess ment of the path shape at a known ASP guarantees a higher accuracy.…”

Localization Packet Scheduling for Underwater Acoustic Sensor Networks

“…If each sensor node is equipped with a pressure sensor, then it can measure its depth, and with this information, it only requires three ToF measurements to find its location. Three-dimensional localization based on the surface-located anchors and the depth information of the sensor nodes has been analyzed in [30] and [33]. Although the more ToFs a node acquires, the better the localization accuracy, one may say that for the localization task, each point in the operational area has to be covered by at least four (without pressure sensor) or three (with pressure sensor) anchors.…”

“…The underwater sensor nodes receive the transmitted packets, and use them for self-localization. In a 3D environment, each node requires at least 4 (3 if the depth is known [30]) localization packets for self-localization. The localization accuracy and localization coverage depends on the density of the anchors per squared meter.…”

Packet scheduling for underwater acoustic sensor network localization

“…In general, the value of K is usually 3 for a 2D operating environment and 4 for a 3D if synchronous localization algorithms are employed. In a situation where the underwater nodes are equipped with pressure sensors, three different successful packets would be enough in a 3D synchronous localization algorithm [12]. The time it takes for an underwater node to gather at least K correct packets from K different anchors is called the localization time, t. A shorter localization time allows for a more dynamic network and reduced energy consumption.…”