Abstract
Today, in our landscape perception exists a gap that needs to be fulfilled. It's important to increase the coverage, temporal and spatial resolution in order to cover this gap, as well as reduce costs with human resources that usually take this kind of tasks. Unmanned Autonomous vehicles with their inherent autonomy and reduced needs of human and communication resources, can provide additional capabilities and a new innovative solution to this problem This paper presents and describes the participation of ICARUS Team at euRathlon 2015 and the importance of this type of events performed with multiple unnamed systems.

Abstract

Abstract
In those positioning systems based on the detection of acoustic signals, an accurate detection of the arrival times is crucial for a correct estimation of the distance between nodes, and therefore, for the precise estimation of the node that wants to be located. In order to obtain this arrival time more accurately, acoustic signals can be coded using pseudorandom noise, but these coded signals are still affected by underwater channel phenomena. In this work, the detection of spread-spectrum modulated signals is analyzed in underwater environments that are highly affected by multipath and reverberation. A spread-spectrum signal, which consist of a modulated Kasami code, has been emitted through two different pools, reaching a receiver where it has been captured after following several line-of-sight and non-line-of-sight paths. Then, a correlation process has been performed offline to provide information about the arrival times (times-of-flight) that form the multipath structure. These times-of-flight are compared with those provided by an underwater acoustic propagation model, in order to test the performance of this model and its capacity to predict the outcome of signal detection in underwater environments with a strong multipath and reverberation component. That way, the validated propagation model could be later used in future studies to predict the detection of spread-spectrum signals and the performance of systems that use them in these adverse environments.

Abstract

Abstract
The demand for accurate ocean sampling is continuously growing to provide a better understanding of the complex sea environment. Current economic and social activity is strongly dictated by knowledge built on data collected from thousands of sensors around the world, ranging from space-borne remote sensors to underwater devices transported by profilers. Autonomous sailboats have great potential to gather long-term data to understand multiple aspects of the ocean environment. In terms of oceanography, they can be used to study many processes occurring at the surface, like the energy exchange between the ocean and the atmosphere and how it affects the climate. They can also be a valuable tool to understand the dynamics of episodic events that evolve on a timescale of weeks or months, like harmful algae blooms or the evolution of pollution plumes. Even though these incidents can already be tracked by satellite, the ability to capture in-situ data for the full cycle can provide valuable data about the phenomena.

Abstract
In this article we introduce a method to estimate the water current in AUV operation scenarios. The method is based on reciprocal sound transmission between pairs of acoustic navigation beacons, with a minimum of three beacons being required to obtain an estimate of both current velocity and direction. We analyse the sensitivity of the current estimation with respect to the geometry of the beacon location. We demonstrate the applicability of the method with a case study.