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Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system's costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.

Underwater localization is one of the main problems that must be addressed in subsea exploration, where no global positioning system (GPS) is available. In addition to the traditional underwater localization systems, such as long base line (LBL), new methods have been developed to increase the navigation performance and flexibility and to reduce the deployment costs. For example, range-only and single-beacon (ROSB) is based on an autonomous vehicle that localizes and tracks different underwater targets using slant range measurements carried out with acoustic modems. This paper presents different strategies to improve ROSB tracking methods. The ROSB target tracking method can be seen as a hidden Markov model (HMM) problem. Using Bayes' rule, the probability distribution function of the HMM states can be solved by using different filtering methods. Here, we present and compare different methods under different scenarios, both evaluated in simulations and field tests. The main mathematical notation and performance of each algorithm are presented, where best practice has been derived. From a methodological point of view, this paper advanced the understanding of accuracy that can be achieved by using the ROSB target tracking methods with autonomous underwater vehicles. INDEX TERMS Particle filter, range-only target tracking, single-beacon, autonomous underwater vehicles, acoustic modems, slant range.

Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral information of deep-sea fished ecosystems is necessary to establish the sizes of marine protected areas within the framework of large international societal programs (e.g., European Community H2020, as part of the Blue Growth economic strategy). However, such information is currently scarce, and high-frequency and prolonged data collection is rarely available. Here, we report the implementation of autonomous underwater vehicles and remotely operated vehicles as an aid for acoustic long-baseline localization systems for autonomous tracking of Norway lobster (Nephrops norvegicus), one of the key living resources exploited in European waters. In combination with seafloor moored acoustic receivers, we detected and tracked the movements of 33 tagged lobsters at 400-m depth for more than 3 months. We also identified the best procedures to localize both the acoustic receivers and the tagged lobsters, based on algorithms designed for off-the-shelf acoustic tags identification. Autonomous mobile platforms that deliver data on animal behavior beyond traditional fixed platform capabilities represent an advance for prolonged, in situ monitoring of deep-sea benthic animal behavior at meter spatial scales.

In this paper, a possible solution to track a mobile underwater source in a closed environment with N Autonomous Underwater Vehicles (AUV) in a swarm formation is adressed. The source tracking algorithm is defined as successful when the range between the source and the swarm is sufficiently low during a given duration, short enough to perform a specified action (for example a source localization). A source is defined as an entity that releases a scalar information affected by transport and diffusion in the environment. We use a generic time-varying information f (pi(t)), where pi at time t is the m-dimensional position of a tracker i and function f (.) is a function that represents sensor information. In this paper, we propose an innovative tracking method inspired by the Particle Swarm Optimization (PSO) algorithm that we call the Local Charged Particle Swarm Optimization (LCPSO). The proposed algorithm is adapted to range-dependant communication that characterizes the underwater context and includes flocking parameters. Comparison of the LCPSO against state of the art methods demonstrate the interest of our approach in an underwater scenario.

The objective of this study is to investigate a novel Underwater Acoustic Communication (UWAC) system based on a modulated chirp signal termed as Orthogonal Chirp Division Multiplexing (OCDM). Originating from the Fresnel transform, OCDM uses chirp signals to exploit the multipath diversity of the channel, achieving a good robustness against frequency fading, especially in the underloaded scenario where only a subset of the available waveforms is modulated. The implementation of the OCDM system for the UWAC scenario is described, and the performance results over an experimental water tank and realistic replayed underwater channel are compared against the traditional Orthogonal Frequency Division Multiplexing (OFDM) transmission scheme.

Time synchronization is an important, yet challenging, problem in Underwater Sensor Networks (UWSN). This challenge can be attributed to: 1) Messaging time stamping; 2) Node mobility; and 3) Doppler scale effect. To mitigate these problems we present a time synchronization algorithm for UWSN, where we compare several message time stamping algorithms besides different Doppler scale estimators.

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