TECHNOLOGY AREAS: Information Systems, Sensors

ACQUISITION PROGRAM: PEO IWS5E Undersea Warfare-Decision Support System

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 3.5.b.(7) of the solicitation.

OBJECTIVE: Develop automated data fusion algorithms and associated visualization tools to associate common contacts from distributed sources at multiple layers.

DESCRIPTION: Current limitations for integrating ASW sensors, control systems, and weapons lead to force-on-force engagements that place Navy platforms at risk. Looking forward, the Navy plans to deploy a �network-centric� ASW combat force that supplements conventional assets with unmanned vehicles, standoff weapons, and intelligent command and control (C2) systems. Sensors, weapons, and C2 devices will often reside on different platforms. Information from these distributed assets needs to be fused to provide a Common Tactical Picture that displays friendly and enemy force positions, mission plan overlays, and in-situ environmental measurements from multiple tactical and intelligence sources.

Recent advances in ASW data fusion have focused on platform-level organic sensor capability. In a distributed sensor/compute environment, data fusion can first be performed on an individual platform using its available input sensors; however, this process does not provide the full integration of available cross-platform information needed to generate an effective tactical picture. The aim would be evaluate candidate algorithms and data processing technologies that will extract the maximum information from multiple data fusion engines. Examples of a distributed environment might include (1) a single vessel whose sensor�s detections are fused on-board or (2) a tuned data fusion engine that is specifically designed to accept only a sub-set of the available sensors. These individual data fusion results need to be recombined or fused in an optimal fashion to provide the clearest, most uncluttered picture.

This topic seeks development of an operating concept and technology to provide Distributed Multilayer data fusion across multiple platforms. Automated Data fusion technology components are needed to de-clutter the common tactical picture to provide improved situational awareness, contact evaluation, and threat assessment. USW combat system performance metrics to be improved by Data Fusion technology transition will include reduced time to evaluate/classify new contacts, increased contact handling capacity, and reduced operator workload.

PHASE I: Research and design a distributed data fusion capability that utilizes best-available data fusion information processing techniques. Emphasis will be placed on implementation practicality. The design shall accept contact, track or object inputs, including kinematic and non-kinematic information, from distributed (or stand-alone) data fusion engines and fuse into a single output. Create simulated data to verify system performance. Use evaluated system performance to investigate optimal hierarchical schemes.

PHASE II: Implement the Phase I approach in a prototype software system. Evaluate
system performance with data collected from at-sea trials.

PHASE III: Integrate the Phase II implementation into [appropriate Navy system]. Demonstrate and report on performance during at-sea trials.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: This technology has direct application to commercial surveillance and security systems comprised of multiple controllable sensors to improve performance and reduce manpower cost. The Distributed Data Fusion technology could be used to implement security sensor systems to provide optimum surveillance coverage with fewest sensors.

REFERENCES: 1. Mathematical Techniques in Multisensor Data Fusion (Artech House Information
Warfare Library) by D. Hall.

2. Handbook of Multisensor Data Fusion (Electrical Engineering & Applied Signal
Processing) by David L. Hall (Editor), James Llinas (Editor)

3. Estimation with Applications to Tracking and Navigation: Algorithms and
Software for Information Extraction (Wiley, 2001) by Y. Bar-Shalom, X. R. Li
and T. Kirubarajan

4. Probabilistic Multi-Hypothesis Tracker: Addressing Some Basic Issues
(Proceedings of the IEE � Radar, Sonar and Navigation) by Peter Willett with
M. Efe and Y. Ruan.

KEYWORDS: Data Fusion, Automation, Distributed Processing

TPOC: J.P. Feuillet
Phone: (202)781-4470
Fax: (202)781-4694
Email: [email protected]
2nd TPOC: Jeff Din
Phone: (202)781-1612
Fax:
Email: [email protected]

** TOPIC AUTHOR (TPOC) **

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