Abstract
In-situ calibration of marine sensors requires close-range positioning. In turn, localization relative to a given object of interest is necessary. This paper deals with the detection of a vertical cable hanging from a marine observatory implemented by means of a moored buoy. An algorithm composed of sequential image filtering, segmentation and template matching is proposed. Two approaches for generating the cable's acoustic image template are introduced. The performance of the approaches, obtained by comparison with ground-truth measurements, are illustrated over challenging cluttered acoustic images collected in a test tank. The results indicate a performance better than 74% of the best candidate to match the actual cable.

Abstract
This paper addresses the localization of an unsynchronized acoustic source using a single receiver and a synthetic baseline. The enclosed work was applied in a real search of an electric glider that was lost at sea and later recovered, using the described approach. The search procedure is presented along with the localization methods and a metric based on the eigenvalues of the Fisher Information Matrix is used to quantify the expected uncertainty of the estimate.

Abstract
Autonomous underwater vehicles (AUV) are increasing in popularity and importance for the realization of underwater explorations. Nowadays, these types of vehicles are implemented in underwater environments to accomplish tasks for military, scientific and industrial purposes. These vehicles can use imaging sonars that are effective in detecting the AUV's distance to an obstacle. The main goals of this paper were to extract meaningful information gathered by sonar, use it to map the surrounding environment, and locate the vehicle on the estimated map. To accomplish these goals, the system is composed of a constant false alarm rate (CFAR) algorithm to filter the sonar information, a feature extractor that filters the first obstacle for each sonar beam in a 360 degrees revolution, an Octomap to build the estimated map and a Particle Filter (PF) to locate the vehicle in the environment. This system was developed using a set of measurements in a rectangular tank where the AUV was in static positions and in motion.

Abstract
As humanity progresses and globalization advances, humanized environment and associated systems increase in complexity and size. In earth systems, oceans represent an essential element of equalization and normal functioning. Ocean-atmospheric interactions are nowadays believed to be at the heart of all earth vital signs and climatic behaviours, and therefore are essential to accurate monitoring and understanding of earth systems. The work presented is a preliminary result of the K2D- Knowledge and Data from the Deep to Space, project which addresses the challenge of creating underwater network nodes to provide power and communication to land through the submarine fiber optic cable repeaters. The N2ODE system will consist of a set of subsystems that will allow continuous monitoring and interaction with fixed and mobile underwater devices.

Abstract
Wall and other planar structures are common in environments as harbors, marinas, or dams. In this paper we introduce an algorithm aimed at the identification of these structures through acoustic images retrieved from an imaging sonar, building on an application of the Hough Transform algorithm. We employ a polar-based line parametric model for improved computational efficiency and further adapt the core Hough Transform blocks to the characteristics of acoustic imaging. The developed solution was subjected to experimental tests employing acoustic data acquired in a water tank, from different viewpoints and under different sonar gain configurations.

Abstract
Long-term and reliable marine ecosystems monitoring is essential to address current environmental issues, including climate change and biodiversity threats. The existing oceans monitoring systems show clear data gaps, particularly when considering characteristics such as depth coverage or measured variables in deep and open seas. Over the last decades, the number of fixed and mobile platforms for in situ ocean data acquisition has increased significantly, covering all oceans' regions. However, these are largely dependent on satellite communications for data transmission, as well as on research cruises or opportunistic ship surveys, generally presenting a lag between data acquisition and availability. In this context, the creation of a widely distributed network of SMART cables (Science Monitoring And Reliable Telecommunications) - sensors attached to submarine telecommunication cables - appears as a promising solution to fill in the current ocean data gaps and ensure unprecedented oceans health continuous monitoring. The K2D (Knowledge and Data from the Deep to Space) project proposes the development of a persistent oceans monitoring network based on the use of telecommunications cables and Autonomous Underwater Vehicles (AUVs). The approach proposed includes several modules for navigation, communication and energy management, that enable the cost-effective gathering of extensive oceans data. These include physical, chemical, and biological variables, both registered with bottom fixed stations and AUVs operating in the water column. The data that can be gathered have multiple potential applications, including oceans health continuous monitoring and the enhancement of existing ocean models. The latter, in combination with geoinformatics and Artificial Intelligence, can create a continuum from the deep sea to near space, by integrating underwater remote sensing and satellite information to describe Earth systems in a holistic manner.