SBIR/STTR Research Award

Autonomous Distributed Systems

Award identifier c42d1eb490cbf38bb5d7a9f3604d47de5028e7a843595a6564c4311df95c8762Awarding agency Department of Defense · Navy

Award amount

$69,999

Program and phase

STTR · Phase I

Award year

2001

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
INFORMATION EXTRACTION & TRANSPORT, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

The processing software to support Navy and Marine Corps littoral battlespace operations has not kept pace with advances in sensor and communications hardware. Information Extraction and Transport, Inc. and Oregon State University propose a noveldistributed processing approach to sensor fusion and situation assessment called Collaborating Autonomous Distributed Sensors (CADS). CADS will yield: 1) A distributed hierarchical data fusion approach at the sensor package level that supports adaptivedetection, classification, identification, and tracking of targets such as surface ships, submarines, and mines at an acceptable false alarm rate. This reusable and reprogrammable reasoning hierarchy scales over temporal and spatial/oceanographicparameters so that numerous sensor packages, each with relatively small amounts of computational power, generate a multiplicative effect by computing and sharing results over time. 2) Control of potentially large numbers of sensor packages at the systemlevel by representing each local situation picture generated by an individual sensor package as a Bayesian Network (BN). An evolving picture based on a BN representation allows the propagation of conditional probabilities throughout the CADS network. 3) AnEnterprise Portal interface providing CADS users with tailored viewpoints into the real-time situational models with access to both individual sensor reports as well as retrospective analyses.Market Need and Size Within the DoD and Intelligence Community.The market for littoral battlespace sensor control and processing software will be significant within the DOD and Intelligence Community, which includes: Force Protection (Large parts of any future littoral area of operations will have to be monitoredremotely with a network of heterogeneous sensors.); Facility Monitoring (A dense network of sensors will still provide suboptimal protection for airfields, ports, storage areas, etc. if humans must be in the loop to monitor the output of the sensors inreal time.); and Mobile Target Tracking (Potential adversaries are turning increasingly to mobility as a means of defeating superior U.S. weapon system range and lethality.) Market Need and Size Within Civilian and Commercial Sector.IET has identified several potential markets for our heterogeneous, distributed sensor technology, which include: Oceanographic Exploration and Monitoring (One obvious extension of this technology includes oceanographic exploration and monitoring.Examples include the identification and tracking of hazardous materials, evaluation of difficult to access large-scale marine accidents, or monitoring for espionage/terrorism in littoral waters for industry located on the coast.); and Space Exploration andMonitoring (Technologies for the control of multiple heterogeneous distributed sensors provide opportunities for the control of remote sensor packages for space exploration and monitoring.)

Technology keywords

Not reported

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.