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Formal Reports

Report of results of completed projects or major milestones either in scientific terms or in terms acceptable to a wider audience. Note: Unless linked to the full text, reports are only available to NATO member nations from designated distribution centres. 

Documents

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A survey of multi-agent strategies for ASW applications A survey of multi-agent strategies for ASW applications

Date added: 10/21/2015
Date modified: 10/27/2015
Filesize: Unknown

A survey of multi-agent strategies for ASW applications. Ferri, Gabriele. CMRE-FR-2015-011. September 2015.

The CMRE multi-static ASW network is composed of fixed nodes and mobile robots working together to achieve common objectives (this kind of network is named in the literature as hybrid). In the ASW littoral scenario the CMRE ASW network offers the promise to provide effective ASW capabilities at a fraction of the cost of traditional assets. To realize an effective network we need to endow every node with autonomy and with the capability to collaborate with one another. Autonomy is crucial for the agents to make effective decisions when communication with other network members and with the command and control centre is limited or impossible. Collaboration between nodes can increase the network robustness and the effectiveness in accomplishing ASW tasks. In this report we start from an analysis of how an effective collaboration between nodes and autonomy can benefit the CMRE ASW network in a littoral surveillance scenario. We then present a thorough review of multi-robot cooperation topics with a special focus on task allocation. Task allocation is the process of allocating tasks to the most suited robots to increase the group's benefit. These studies suggest that a market-based approach can be a viable solution for task allocation. These methods are flexible and provide a good compromise between required communication bandwidth and quality of the task allocation. Guiding principles are presented to design a market-based task allocation scheme tailored to the ASW scenario. In particular, the tasks constituting a complex ASW mission are presented along with a suited utility function. An example of an auction is also presented and discussed. The approach presented can be used as a template to develop auctions also for other tasks of interest.

A risk game to measure the impact of information quality on human threat assessment and decision making A risk game to measure the impact of information quality on human threat assessment and decision making

Date added: 10/07/2015
Date modified: 10/07/2015
Filesize: Unknown

A risk game to measure the impact of information quality on human threat assessment and decision making.  Jousselme, Anne-Laure; Pallotta, Giuliana; Locke, Jonathan. CMRE-FR-2015-009. June 2015.

This document describes the Risk Game, a general methodology developed at CMRE to elicit experts knowledge and know-how, including their ability to deal with information of different nature (from sensors to human witnesses), to consider the information quality (including source quality) and to reason about concurrent events. It is a "contrived" technique aimed at capturing data expressing human reasoning features while performing a specific task of maritime situation assessment. The main focus of the Risk Game is the study of the impact of information quality on the ability of human operators to assess threat and make decisions. A new methodology is presented where information is abstracted away by cards, and the quality is randomly selected by dice roll. The game has been tested during the Table Top Exercise (TTX) for harbour protection held at CMRE in November 2014. The game has been played by 32 experts, most of them OF-3 and above of the maritime domain, from 9 NATO Nations. The preliminary results obtained are promising and allowed us to identify research challenges as a basis for definition of future work. We in particular validated the elicitation method and highlighted for instance that the players? perceived relevance of information may differ from the effective relevance, that a high amount of false information increases the uncertainty of the player before decision and may lead to wrong decisions, or that the context has a high impact on the decision taken. We also draw some research avenues to be addressed in future work, such as the definitions of information quality measures which would be consistent across different domains of definition (resolution and type of scale).

Stochastic motion model for maritime traffic Stochastic motion model for maritime traffic

Date added: 10/07/2015
Date modified: 12/22/2015
Filesize: Unknown

Stochastic motion model for maritime traffic.  Millefiori, Leonardo; Braca, Paolo; Pallotta, Giuliana ; Bryan, Karna. CMRE-FR-2015-008. Juney 2015.

Driven by real-world issues in maritime surveillance, we consider the problem of long-term prediction for estimating the state of a non-manoeuvring target, such as the case of a vessel underway in open sea. Traditionally, target dynamic models assume a white noise process on the target velocity, which is otherwise nearly-constant. Such a process model is an implausible hypothesis for a significant portion of the maritime ship traffic, as vessels underway tend to continuously adjust their velocity around a desired speed. Also vessels are obliged to observe traffic regulations in some areas and will seek to optimise fuel consumption. Using historical ship traffic data, we have found that the nearly-constant velocity model with white noise tends to overestimate the actual uncertainty of the prediction. In this work we present a novel method for predicting long-term target states based on mean-reverting stochastic processes. We used the Ornstein-Uhlenbeck stochastic process, leading to a revised target state prediction equation and to a completely different time scaling law for the related uncertainty, which is shown to be orders of magnitude below than under the nearly-constant velocity assumption. To support the proposed model, a large-scale analysis of a significant portion of the real-world maritime traffic in the Mediterranean Sea is presented in this paper. As modelling long-term prediction is not a commonly addressed problem in the target tracking literature, it is possible that this approach could offer a new methodology also for other moving target applications.

Cost-benefit analysis for piracy counter-measures effectiveness Cost-benefit analysis for piracy counter-measures effectiveness

Date added: 10/07/2015
Date modified: 10/07/2015
Filesize: Unknown

Cost-benefit analysis for piracy counter-measures effectiveness.  De Rosa, Francesca; Funk, Ronald; Turnbull, Adrienne. CMRE-FR-2015-007. June 2015.

Piracy and armed robbery have re-emerged in the last few decades as a global security threat, which constitutes a risk for both seafarers and passengers? safety, as well as for Sea Lines of Communications. Piracy has not only economic impacts, but also political, ethical, social, legal and environmental implications. A comprehensive Cost-Benefit (C-B) analysis for piracy risk needs to consider all of these factors. The focus of this work is on non-military anti-piracy measures. Currently, there is a broad range of protection options available to commercial shipping, but little understanding of the cost-effectiveness of those Counter-Measures. Therefore, a Cost-Benefit analysis method has been set up in order to assist shipping companies in taking informed decision. To lay the foundation of this analysis a Counter-Measure Catalogue was created. Past piracy events have been analyzed to identify reference scenarios to test the final C-B method and to quantify the Counter-Measures Operational Effectiveness. Due to the limited data available a full analysis approach has not been possible, therefore a Multi-Criteria Decision Analysis was adopted to estimate the Counter-Measure Technical Utility. The main driver to operational costs for rerouting is fuel consumption, so an important part of the model has been the development of a Fuel Consumption calculator, which enabled the C-B analysis for the different route options identified in each reference scenario. The C-B analysis is based on the data that was accumulated in a database, which can be expanded to accommodate additional information, thus creating an integrated tool that can automatically calculate the quantitative C-B impact of changes as new data are made available. It is important to highlight that the results of the C-B analysis are meant to be an aid for end users to take informed decisions, but they will always have to apply their professional judgment to select the Counter-Measures that are felt to be the most appropriate for circumstances at hand.

Towards fully autonomous underwater vehicles in ASW scenarios: an adaptive AUV mission management layer Towards fully autonomous underwater vehicles in ASW scenarios: an adaptive AUV mission management layer

Date added: 10/07/2015
Date modified: 10/07/2015
Filesize: Unknown

Towards fully autonomous underwater vehicles in ASW scenarios: an adaptive AUV mission management layer.  Ferri, Gabriele. CMRE-FR-2015-006. June 2015.

In this work we investigate how to improve the decision making of AUVs for their effective use in a multistatic ASW network. In multistatic ASW an acoustic source insonifies a target (a submarine) and the reflected pulse is detected by a hydrophone line array towed by the receiving AUVs. The capability for an AUV to make autonomous decisions is crucial in this scenario, especially if we consider the limited bandwidth of underwater acoustic communications that makes communication with the vehicles limited and sometimes impossible. To be really effective, AUVs need to take decisions autonomously on the basis of the acquired data and the changing tactical scene. Data-driven approaches can increase the performance of the mission by allowing the AUV, for instance, to adapt its path to achieve some mission objectives. Recently we have designed and successfully tested at sea a non-myopic, receding horizon algorithm which controls the heading of the AUV to minimize the expected target position estimation error of a tracking filter. Minimizing this error is typically of the utmost interest in target state estimation since it is one way of maintaining track. A candidate track is used by the non-myopic algorithm to control the AUV to achieve favourable target-source-receiver geometries. The AUV has therefore to select tracks likely being target-generated. ASW scenarios are typically complex from the detection/tracking point of view. The target may not be observable for long time due to the particular sound speed profile or low probability of detection. Several false tracks are usually simultaneously present and may last for several pings and finally the presence of ambiguous tracks (due to the port-starboard ambiguity of contacts in line arrays) increases the number of tracks of possible interest. Only the most interesting tracks should be investigated without wasting time and energy to optimize tracks not target related. In this work we present an adaptive, data driven Mission Management Layer (MML) running on board the vehicles managing all the phases of the AUV missions. The MML receives the tracks and contacts produced by the signal processing chain, takes decisions in real-time on which tracks are interesting to be prosecuted and commands the vehicle control layer operations. First of all, a metric is needed to quantify the quality of a track. The track quality can be defined as the probability of existence of the target corresponding to the track. In this work we propose a track scoring method based on the quality of the measurement to- track associations. The method uses a model of the acoustics and the kinematic features of the target and does not need the knowledge of parameters that are difficult to estimate such as the probability of detection. The real-time track score can then be used to classify the tracks and select which ones are to be prosecuted by the non-myopic optimizer. The MML manages all the phases of an ASW mission: exploration of the area, disambiguation between a track and the relative ambiguous (ghost) track when one firmed track is present, optimization of a confirmed track and target reacquisition when a track breaks. A compromise is found between the exploration/surveillance of the area and behaviours that improve the tracking and classification performance on identified tracks. Only the most interesting tracks are prosecuted to avoid wasting time/energy in pursuing tracks not target generated. These features are necessary for effective data-driven behaviours in real ASW scenarios. Our mission management approach pushes towards the full autonomy of our system since it provides the AUV the capability of adapting its actions to the current tactical situation. In the work we start by proposing a taxonomy for an ASW mission from the AUV perspective. After the description of the track scoring and of the MML we describe the implementation of the proposed architecture in the MOOS-based control architecture of CMRE OEXs. We present results from sea trials (REP14 Atlantic and COLLAB-NGAS14) demonstrating the effectiveness of our approach. These results represent one of the first examples of AUVs autonomously taking decisions in a realistic, complex littoral surveillance scenario.

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