In this paper, we present a resilient detection algorithm for multiple targets in a distributed environment with limited information sharing. The problem setup is as follows. There are M agents (detectors/sensors), which will be used to collaboratively detect the behaviors of N targets. The number of agents is much smaller than that of targets (i.e., M << N). Targets are assumed to be located in a 2D environment (The extension to 3D is straightforward). Each agent has a limited sensing/communication range and can only detect a small group of targets in its sensing range. Agents only maintain a strongly connected communication topology at certain time intervals and each agent can communicate with its neighboring agents about their situation of target detection. The proposed distributed detection algorithm is based on consensus theory. The resilience of the proposed detection algorithm is verified through extensive simulations under four different scenarios: (1) agents with limited sensing/limited communication capabilities; (2) the existence of unexpected agent failure; (3) the existence of unexpected communication link dropout; and (4) the situation with intermittent communications. The proposed design provides a new solution for control and estimation of unmanned autonomous systems.
Graphical fusion methods are popular to describe distributed sensor applications such as target tracking and pattern
recognition. Additional graphical methods include network analysis for social, communications, and sensor
management. With the growing availability of various data modalities, graphical fusion methods are widely used to
combine data from multiple sensors and modalities. To better understand the usefulness of graph fusion approaches, we
address visualization to increase user comprehension of multi-modal data. The paper demonstrates a use case that
combines graphs from text reports and target tracks to associate events and activities of interest visualization for testing
Measures of Performance (MOP) and Measures of Effectiveness (MOE). The analysis includes the presentation of the
separate graphs and then graph-fusion visualization for linking network graphs for tracking and classification.
In this paper, we propose the Composition Modeling Framework (CMF) as a standards-based information
engineering methodology that tackles existing and emerging Department of Defense (DoD) interoperability
problems using a bottom-up approach. We introduce CMF capabilities within the context of an
<i>information space</i> composed of repositories and a catalog that enables consumers' and producers'
information requirements to be met. This information space supports dynamic and unscripted interaction
among various producers and consumers, but its power as an information management tool is best
harnessed when its participants share common goals operating in unison as a Community of Interest (COI).
We present the CMF as one approach for representing the structure, meaning and abstract implementation
of the underlying information space that services a COI and its participants. In addition to facilitating intra-
COI interoperability, we demonstrate how CMF concepts can be used to construct cross-domain interoperability solutions by supporting inter-COI communication and understanding.
The Joint Battlespace Infosphere (JBI) Information Management (IM) services provide information exchange and persistence capabilities that support tailored, dynamic, and timely access to required information, enabling near real-time planning, control, and execution for DoD decision making. JBI IM services will be built on a substrate of network centric core enterprise services and when transitioned, will establish an interoperable information space that aggregates, integrates, fuses, and intelligently disseminates relevant information to support effective warfighter business processes. This virtual information space provides individual users with information tailored to their specific functional responsibilities and provides a highly tailored repository of, or access to, information that is designed to support a specific Community of Interest (COI), geographic area or mission. Critical to effective operation of JBI IM services is the implementation of repositories, where data, represented as information, is represented and persisted for quick and easy retrieval. This paper will address information representation, persistence and retrieval using existing database technologies to manage structured data in Extensible Markup Language (XML) format as well as unstructured data in an IM services-oriented environment. Three basic categories of database technologies will be compared and contrasted: Relational, XML-Enabled, and Native XML. These technologies have diverse properties such as maturity, performance, query language specifications, indexing, and retrieval methods. We will describe our application of these evolving technologies within the context of a JBI Reference Implementation (RI) by providing some hopefully insightful anecdotes and lessons learned along the way. This paper will also outline future directions, promising technologies and emerging COTS products that can offer more powerful information management representations, better persistence mechanisms and improved retrieval techniques.