Mission-driven sensor management

This paper describes research into generic sensor management principles that enable the development of a support system that is capable of bridging the growing gap between the available knowledge and the required sensor management related knowledg

Mission-Driven sensor management analysis, design, implementation and simulation

The management of sensors onboard of the vessels operated by the Royal Netherlands Navy is becoming increasingly knowledge intensive due to the fact that these vessels are equipped with state-of-the-art sensor systems that provide more functionality and more accurate information at the cost of more complex control mechanisms and due to the shift of operational areas from the fairly stable environment of the Atlantic Ocean into littoral waters with often dense civil traffic and rapidly changing geographical and meteorological conditions. The shrinking defence budgets on the other hand drive a demand for crew reduction, shorter education times and less training opportunities thus reducing the synergy created within teams of operators and the knowledge and experience of individual operators. This perception led to the following problem definition: management of a set of complex sensor systems under often rapidly changing environmental, operational conditions and temporal constraints requires more skills and knowledge than is currently available. Within the research generic sensor management principles were formulated that were used to construct a three-stage sensor manager. Furthermore a new, object-oriented Command and Control (C2) concept was developed that provides the sensor manager with the required information. Utilising these results, a basic C2 system with integrated sensor manager was designed, that was tested in a simulated maritime scenario by deploying a model of a Multi-Function Radar. The execution of this scenario showed that it was possible to deploy the multi-function radar completely autonomously by utilising prior information and from this result it can be deduced that mission-driven, autonomous sensor management is feasible. The prototype also provides the possibility to integrate radar performance prediction tools that predicts the sensor performance for the prevailing meteorological and environmental conditions. The generic sensor management principles that were postulated do not restrict the sensor suite to being located at a single platform and therefore a sensor manager that is developed along these principles is theoretically capable of handling a suite of distributed sensors. The research showed that the management principles could also be used to manage other resources and the sensor manager may well be expanded into a resource manager.Electrical Engineering, Mathematics and Computer Scienc

Consequence Management: Declarative Modelling of Maritime C2-systems

Item does not contain fulltextMAST Asia 2017: Maritime/Air Systems & Technologies, Makuhari Messe, Tokyo, Japan Monday 12 June 2017 to Wednesday 14 June 201

Dynamic resource and task management

Carrying out maritime missions comprises many phases from preparation to execution. In the long term, we would like to have an integrated toolchain that supports the crew at every phase. In this chapter, we study concepts for resource and task management in the execution phase. When the tasks to be executed have been identified, the question arises who should be assigned to them. This is both a scheduling and an assignment problem. We narrow down what kind of problem we have at hand to get an understanding what a first step towards an integrated command and control system could look like. This also enables us to classify our problem with the existing literature on planning and scheduling. We develop a domain model for tasks and resources, their connection via capabilities, together with assessment functions to compare assignments. We study what kind of information would be needed to give useful scheduling advice

A mission-driven C2 framework for enabling heterogeneous collaboration

The deployment of naval vessels requires much specialised knowledge. Firstly, about the mission: what goals have to be reached (the command-aim), and what has to be done to achieve this aim? Secondly, about the situation: how can sufficient information about the situation be gathered to determine whether the planned tasks can still be executed successfully? Thirdly, about the available systems and operators: what are their capabilities and capacities, and how can these be utilised to their full extent? This knowledge is also required to determine the consequences of system failure or the non-availability of human resources. This chapter models these categories, constructs relationships between them and uses them to answer the aforementioned questions. This is done in two phases. First, a formal model is described that translates the command aim into operational tasks, determines which resources are the most suitable to execute these tasks, and determines which alternative resources are available. The model can also be used to reason about the viability of the command-aim, should certain resources become unavailable. Second, the viability of this model is investigated by implementing an executable prototype using highly portable declarative programming techniques. The model and the implementation can be used to experiment with how ship design decisions can have operational consequences on the systems and the command aim, both at design time and during operational use. To determine whether they are generally applicable, it was tested in a realistic scenario involving a potential terrorist threat on a drilling rig in the North Sea and in a damage control operation

Military sensor technology. Modern developments and challenges

In this paper the authors illustrate developments in sensor technology with a number of examples. From their own research they discuss radar, image processing and sensor networks. Radar performance is affected by propagation characteristics of electromagnetic waves. Experience has shown that this may lead to considerable errors and even failure to detect threatening targets. Characterization of these propagation effects helps to determine their consequences and to counter or even utilize them. Image processing in a maritime environment provides challenges with complex variable backgrounds and a diversity of objects and appearance. This requires characterization of meteo and environmental effects and development of new image analysis algorithms. Finally the authors consider networks of large numbers of sensors that are made possible by ongoing miniaturization and offer new deployment possibilities but also pose new challenges because the limited resources of individual sensors must be overcome by efficient network organization. In combination this offers an overview of limits of current technologies and how attempts are made to overcome these

Automatic sensor management: Challenges and solutions

Due to technical advances and the changing political environment sensor management has become increasingly knowledge intensive. Aboard navy ships however, we see a decrease of available knowledge, both quantitative and qualitative. This growing discrepancy drives the need for automation of sensor management. Since the goal of sensor deployment is to have a complete and accurate operational picture relative to the mission we propose a three-stage sensor manager, where sensor task requests are generated based on the uncertainty in the (expected) objects’ attributes. These tasks are assigned to available and suited sensors, which in turn are fine-tuned for the task at hand. When trying to reduce the uncertainty in the classification solution one must first define how the classification process actually works. We discuss why the classification process needs to be automated as well and show how such classification algorithms will most likely work in the future.Electrical Engineering, Mathematics and Computer Scienc