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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. 

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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.

Study on using laser imaging and LIDAR on-board an autonomous platform as a multi-modality sensor system for water column and seabed surveying Study on using laser imaging and LIDAR on-board an autonomous platform as a multi-modality sensor system for water column and seabed surveying

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

Study on using laser imaging and LIDAR on-board an autonomous platform as a multi-modality sensor system for water column and seabed surveying.  Trees, Charles; Fournier, Georges. CMRE-FR-2015-005. April 2015.

The GCLAS (Gated Imaging Camera, LIDAR and ADCP/Sonar on a Coastal Glider) feasibility study, combines both acoustic and imaging technologies with autonomous on-board data processing. The approach uses multiple acoustical and optical sensors installed and integrated on a mobile observational platform (Coastal Glider Extended, CGX), that would provide unattended surveying of the water column and seabed, utilizing "reactive behaviour-based" control for both the platform missions and sensor acquisitions and storage. The range-gated imaging and LIDAR sensor SLICaL (Stereoscopic Laser Imaging Camera and LIDAR) would be Radiometrically Characterized and Calibrated (RC2), which has not been done previously to our knowledge, following measurement protocols developed by National Metrology Institutes. With this calibrated imagery and LIDAR data, robust algorithms can be developed to interpret and convert the raw data into derived products at known uncertainties. The optical properties derived from the LIDAR and the other optical sensors would be used to optimize the collection of the laser-gated camera imagery so that only high quality images would be collected for target classification and identification. The sonar would search for targets, whereas the optical camera system would provide the identification and classification. Although the AUV-glider platform is mobile, it does have a mode that can be used to repeatedly sample an area, using a ?virtual station keeping? mission. It can also sit at the surface and with the LIDAR capabilities vertically sample the water column down to 50m or more at 1m intervals. Given the autonomy and endurance of the GCLAS system, it would have the capability to completely characterize the sea column and image the seabed over a path of more than 800km in a two-week period (depending upon improved battery utilization, it's mission may last up to three weeks). This glider data can also be used to better understand and characterize oceanic and coastal physical and bio-optical variability at basin scale, mesoscale, and even sub-mesoscale (ranging from 100 km horizontally in a month to 1 km in an hour).

Extended target tracking using random matrices applied to converted measurements of X-band marine radar data Extended target tracking using random matrices applied to converted measurements of X-band marine radar data

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

Extended target tracking using random matrices applied to converted measurements of X-band marine radar data.  Vivone, Gemine; Braca, Paolo. CMRE-FR-2015-004. February 2015.

X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. They can provide high resolution measurements both in space and time. Such features offer the opportunity to get accurate information not only about the target kinematics, as other conventional sensors, but also about the target size. In this paper we exploit the random matrix framework to track extended targets. A proper measurement model to deal with the radar's measurement noise and its conversion into Cartesian coordinates is here presented. Benefits of the proposed extended target tracking using converted measurements can be mainly related to the problem of the targets' size estimation, while advantages on estimation of the targets' kinematic can be considered negligible. The validity of the proposed approach has been demonstrated by using both simulated and real data. Gains of around 100% for the targets' width estimation accuracy and around 50% for the length are observed on real data.

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