DRDC Valcartier and MDA have created an advanced simulation testbed for the purpose of evaluating the effectiveness
of Network Enabled Operations in a Coastal Wide Area Surveillance situation, with algorithms provided by several
universities. This INFORM Lab testbed allows experimenting with high-level distributed information fusion, dynamic
resource management and configuration management, given multiple constraints on the resources and their
communications networks. This paper describes the architecture of INFORM Lab, the essential concepts of goals and
situation evidence, a selected set of algorithms for distributed information fusion and dynamic resource management, as
well as auto-configurable information fusion architectures. The testbed provides general services which include a multilayer
plug-and-play architecture, and a general multi-agent framework based on John Boyd's OODA loop. The testbed's
performance is demonstrated on 2 types of scenarios/vignettes for 1) cooperative search-and-rescue efforts, and 2) a noncooperative
smuggling scenario involving many target ships and various methods of deceit. For each mission, an
appropriate subset of Canadian airborne and naval platforms are dispatched to collect situation evidence, which is fused,
and then used to modify the platform trajectories for the most efficient collection of further situation evidence. These
platforms are fusion nodes which obey a Command and Control node hierarchy.
Soil moisture conditions influence practically all aspects of Army activities and are increasingly affecting its systems and
operations. Regional distributions of high resolution soil moisture data will provide critical information on operational
mobility, performance of landmine and UXO sensors, and meteorological conditions at the km scale. The objective of
this study is to calibrate RADARSAT-2 surface soil moisture estimates with field measurements in the semi-arid Middle
Rio Grande Valley of New Mexico. RADARSAT-2 was launched in December 2007 and is the first SAR sensor to offer
an operational quad-polarization mode. This mode allows to generate soil moisture (and cm-scale surface roughness)
maps from single data sets. Future combination of such maps into time series will lead to further accuracy enhancement
through additional exploitation of soil moisture evolution constraints. We present RADARSAT-2 soil moisture maps,
field soil moisture measurements, and soil moisture maps derived from optical imagery. In addition, future work is
proposed that may contribute to enhanced algorithms for soil moisture mapping using RADARSAT-2.
A PRECARN partnership project, called CanCoastWatch (CCW), is bringing together a team of researchers from
industry, government, and academia for creating an advanced simulation test bed for the purpose of evaluating the
effectiveness of Network Enabled Operations in a Coastal Wide Area Surveillance situation. The test bed allows
experimenting with higher-level distributed information fusion, dynamic resource management and configuration
management given multiple constraints on the resources and their communications networks.
The test bed provides general services that are useful for testing many fusion applications. This includes a multi-layer
plug-and-play architecture, and a general multi-agent framework based on John Boyd's OODA loop.
We propose a highly adaptive and auto-configurable, multi-layer network architecture for distributed information
fusion to address large volume surveillance challenges, assuming a multitude of different sensor types on multiple
mobile platforms for intelligence, surveillance and reconnaissance. Our focus is on network enabled operations
to efficiently manage and improve employment of a set of mobile resources, their information fusion engines
and networking capabilities under dynamically changing and essentially unpredictable conditions. A high-level
model of the proposed architecture is formally described in abstract functional and operational terms based on
the Abstract State Machine formalism. This description of the underlying design concepts provides a concise and
precise blueprint for reasoning about key system attributes at an intuitive level of understanding.
DRDC Valcartier has initiated, through a PRECARN partnership project, the development of an advanced simulation
testbed for the evaluation of the effectiveness of Network Enabled Operations in a coastal large volume surveillance
situation. The main focus of this testbed is to study concepts like distributed information fusion, dynamic resources and
networks configuration management, and self synchronising units and agents. This article presents the requirements,
design and first implementation builds, and reports on some preliminary results. The testbed allows to model distributed
nodes performing information fusion, dynamic resource management planning and scheduling, as well as configuration
management, given multiple constraints on the resources and their communications networks. Two situations are
simulated: cooperative and non-cooperative target search. A cooperative surface target behaves in ways to be detected
(and rescued), while an elusive target attempts to avoid detection. The current simulation consists of a networked set of
surveillance assets including aircraft (UAVs, helicopters, maritime patrol aircraft), and ships. These assets have electrooptical
and infrared sensors, scanning and imaging radar capabilities. Since full data sharing over datalinks is not
feasible, own-platform data fusion must be simulated to evaluate implementation and performance of distributed
information fusion. A special emphasis is put on higher-level fusion concepts using knowledge-based rules, with level 1
fusion already providing tracks. Surveillance platform behavior is also simulated in order to evaluate different dynamic
resource management algorithms. Additionally, communication networks are modeled to simulate different information
exchange concepts. The testbed allows the evaluation of a range of control strategies from independent platform search,
through various levels of platform collaboration, up to a centralized control of search platforms.
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