Friday, November 24, 2017
      CMRE Facebook page  CMRE LinkedIn page  CMRE PAO Youtube page
   
Text Size
CMRE banner

Memorandum Reports

Report that covers interim results during the course of a project. Note: Unless linked to the full text, reports are only available to NATO member nations from designated distribution centres.

Documents

Order by : Name | Date | Hits [ Ascendant ]

Predictions of a highly dynamic ocean environment: first results and lessons learned Predictions of a highly dynamic ocean environment: first results and lessons learned

Date added: 10/25/2016
Date modified: 10/25/2016
Filesize: Unknown

Predictions of a highly dynamic ocean environment: first results and lessons learned. Oddo, Paolo; Borrione, Ines; Falchetti, Silvia; Russo, Aniello. CMRE-MR-2016-014. October 2016.

Two high resolution Ocean Observing and Prediction Systems (OOPSs) have been developed and implemented in the framework of the LOGMEC16 (Long-Term Glider Mission for Environmental Characterization) experiment with the ultimate goal to provide operational support for marine environmental and acoustic characterizations. Data collected by two deep gliders monitoring continuously the Ligurian Sea from 2 May to 27 June 2016, have been assimilated in the OOPSs to constrain model error growth and improve system performance. The two OOPSs implemented differ in terms of adopted numerical models and data assimilation schemes. The first OOPS consists of a very high resolution (600m) NEMO (Nucleus for European Modelling of the Ocean) model implementation coupled with a 3D variational assimilation system. The second OOPS implemented is based on a ROMS (Regional Ocean Modelling System) configuration with approximatively 1.8 Km resolution and it assimilated observational data using an Ensemble Kalman Filter ocean data assimilation scheme. Gliders, independent CTDs and METOC buoy data collected during the experiment have been used to validate real-time operational system results and quantify the improvements with respect to the existing, publicly available environmental products (provided by the Copernicus Marine Environment Monitoring Service, CMEMS). Both the high resolution OOPSs outperform CMEMS in terms of environmental characterization (here evaluated in terms of sound speed profile) for acoustic applications. The ROMS-EnKF significantly reduces large scale errors introduced through initial and lateral open boundary conditions, while the relatively high computational cost poses limitations on model resolution and frequency of the forecast. The NEMO-3DVar system only partially mitigates the parent model's large scale errors but better reproduces the observed variability.

Selection of environmental parameters to estimate on board autonomous security networks for ASW Selection of environmental parameters to estimate on board autonomous security networks for ASW

Date added: 10/25/2016
Date modified: 10/25/2016
Filesize: Unknown

Selection of environmental parameters to estimate on board autonomous security networks for ASW. Nielsen, Peter L. CMRE-MR-2016-011. September 2016.

This memorandum report documents the status of the environmental characterisation algorithm intended for implementation in Autonomous Underwater Vehicles (AUV) for Anti-Submarine Warfare (ASW) operations. The focus is to establish superiority in the underwater domain by increasing the likelihood of detecting, classifying, localising and tracking submarine targets. The success of detection depends on estimating the state of the underwater environment the sonar system is operating in which is controlled by ambient noise levels (sea state, distant shipping, land-based noise sources), the boundary conditions of the ocean (sea state, seabed properties) and the sound speed profile in water column. Optimisation over the location, depth and heading of the AUVs as well as their sonar settings can be pursued if the environmental parameters are known to a degree of confidence sufficient to be used in a sonar performance prediction model such as CMRE's Multi-Static Tactical Prediction Aid.

Operator interaction within a real time acoustic prediction framework Operator interaction within a real time acoustic prediction framework

Date added: 10/25/2016
Date modified: 10/25/2016
Filesize: Unknown

Operator interaction within a real time acoustic prediction framework. Strode, Christopher; Oddone, Manlio. CMRE-MR-2016-010. October 2016.

This document describes the existing real time acoustic prediction architecture afforded by recent developments made to the CMRE Multi Static Tactical Planning Aid (MSTPA) software. A description of the current architecture that has been successfully demonstrated at CWIX 2015 and 2016 is given. Further details are then provided for proposed methods by which the software may be transitioned to a web service architecture for operators and planners allowing for increased interaction. Specifically the need for the operator to configure sensor parameters is described. This document describes the existing real time acoustic prediction architecture afforded by recent developments made to the CMRE Multi Static Tactical Planning Aid (MSTPA) software. A description of the current architecture that has been successfully demonstrated at CWIX 2015 and 2016 is given. Further details are then provided for proposed methods by which the software may be transitioned to a web service architecture for operators and planers allowing for increased interaction. Specifically the need for the operator to configure sensor parameters is described.

High-level autonomous asset planner High-level autonomous asset planner

Date added: 10/25/2016
Date modified: 10/25/2016
Filesize: Unknown

High-level autonomous asset planner. Ferri, Gabriele. CMRE-MR-2016-009. October 2016.

In this report we investigate the high level asset management for the autonomous nodes of the CMRE ASW multistatic network. Specifically, our objective is to find a policy to assign the network agents to the tasks which compose an ASW mission. This problem is known as Multi Robot Task Allocation problem in the robotics community. Achieving an effective task allocation is a key driver to fully exploit the benefits of cooperation between the network agents. By "effective" we mean that the allocation scheme, by taking into consideration the evolution of the tactical scene, optimises the team?s objective function by using the agents to the best of their capabilities. A proper task allocation scheme can in fact exploit the synergies that the nodes can offer. For instance, the mobile nodes (robots) can coordinate themselves to patrol a certain area or decide to cooperatively prosecute a track to ease the data fusion process aiding proper target classification. Furthermore the nodes of the network may be heterogeneous, in which case effective task allocation will assign a task to the most suited robot. However, the underwater scenario presents difficult challenges from a task allocation perspective. This is particularly true in littoral waters in which the CMRE network usually operates. In littorals, the typical limitations of underwater communications (low throughput, low range and low reliability) makes the exchange of messages be-tween the robots and between the robots and the C2 centre intermittent and sometimes impossible. A centralised control of the network, which could allow optimal task allocation, is not realisable under these conditions. The network must therefore be capable to allocate the tasks to the different nodes in a distributed way, thereby coping with the severe limitations brought by the underwater acoustic channel. In this report, we propose a market-based approach as a viable solution to task allocation in the ASW scenario. The method works in a completely distributed way and, through periodic auctions, performs the dynamic assignment of robots to tasks during the mission. The algorithm works by using negotiations among neighbouring nodes and requires only local communications. There is no central auctioneer and each robot is able to resolve the current auction and declare the winner by exploiting its local knowledge and the information received by the other nodes. Through periodic auctions, all the robots are sequentially allocated to tasks. In our scenario, we consider continuous tasks (i.e. tasks which do not terminate) consisting of the surveillance of adjacent areas of interest. The proposed utility for the tasks encompasses a measure of the coverage of the area (based on the cumulative probability of detection) within specific frequency constraints. The robots are requested to survey the same area with a certain temporal frequency given the intrinsic dynamic nature of the problem (the target location is dynamically changing). Furthermore, more than one robot can be allocated to the same area introducing cross-schedule dependencies Particular attention has been paid to make the auction scheme robust to intermittent communications. Each robot waits for messages from collaborators for several consecutive communications frames before taking a decision. The periodicity of the auctions makes the scheme robust to the temporary lack of communications. The proposed task allocation policy also allows task reallocations to deal with the evolution of the tactical scene. Results from Matlab simulations are reported and discussed. These results show the robustness of the algorithm to poor communications and how the proposed task al-location policy can improve the network performance by exploiting the cooperation among its nodes.

Optical payloads for unmanned systems Optical payloads for unmanned systems

Date added: 10/25/2016
Date modified: 10/25/2016
Filesize: Unknown

Optical payloads for unmanned systems. Sanjuan Calzado, Violeta. CMRE-MR-2016-008. October 2016.

An optical closure study was developed with a one-of-a-kind optical buoy, designed to acquire simultaneous measurements of the radiant flux field and inherent optical properties. The exercise aims to understand the sources of uncertainty when these measurements are related with the radiative transfer equation. Systematic uncertainties due to sensor inaccuracies were observed together with random uncertainties, due to ambient light variability and different water masses. The results show a departure of up to 70% variability in very clear water. This high variability can potentially have a major impact when optical data is used on cal/val activities and sources of uncertainty should be quantified and presented.

User Login