Advanced Sensor Integration & Design

Multi-sensor integration is the process of intelligently integrating data and information from multiple sources in order to derive synthesized information that will facilitate decision making.  The application of information fusion in multi-sensor data integration is referred to as “data fusion.” Multi-sensor data fusion involves a formal framework that expresses the means and tools for fusing data originating from different sensor sources, and for exploiting the synergy of this fusion in order to obtain information whose quality cannot be achieved otherwise. Multi-sensor fusion technology uses detection, preprocessing, fusion, and data interpretation to derive useful information.  This method has emerged as the method of choice for implementing robust systems that can handle imperfect inputs. 

Sensor fusion has application in a wide variety of fields including artificial neural networks, artificial intelligence, and pattern recognition.  The effective implementation multi-sensor data integration requires a team with expertise in NDI, multi-sensor data fusion and modeling using advanced signal and image processing techniques, Artificial Neural Networks (ANN), fuzzy logic, and wavelets.  KBSI has successfully completed a number of initiatives on sensor analysis, image analysis, fusion, multi-sensor and multi-target tracking, neural networks, detection of objects in images, and data mining (rule association, statistical analysis, clustering, etc.).

 

 

Parasitic Power Pack (P3)

KBSI is developing an innovative power pack for remotely deployed buoys. The buoys enable communication, via a distributed sensor network, among the Navy's underwater assets and assets above water. The P3 technology uses wave power rather than batteries to power the buoy sensors.

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Entropy-Trust-Homology Operational Security (ETHOS™)

KBSI investigated various trust metrics and algorithms with the goal of defining a set of trust metrics that use information entropy as the basis for the calculations of the reputation of a node in a sensor network.  Trust entropy metrics were created based on the pattern of information entropy flow between nodes and on usage behavior. 

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Framework for Intelligent support of Smart Transducers (FIST™)

KBSI is building the framework to provide a plug-and-play capability for large-scale smart transducer deployments.  FIST™ will revolutionize the way in which flight test and instrumentation engineers design, implement, test and manage sensor networks by exploiting the inherent benefits of the smart transducer technology. 

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Intelligent Asset Tracking and Management System (IATMS)

KBSI developed a unified framework for geolocation knowledge that provides instant visualization of MRO assets, improving asset utilization and scheduling and MRO flow-times.  The IATMS technology also allows for knowledge discovery of equipment-task and equipment-resource relationships using geolocation data and other external data sources. 

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Intelligent System for Abstraction & Integration of Instrumentation Hardware (ISAIIH)

KBSI is developing an XML-based language that acts as an intermediary between the Instrumentation Support Systems (ISS) and the many vendor-specific languages involved. This functionality will support the programming of instrumentation systems prior to testing and evaluation (T&E).

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Multi-Spectral Feature Fusion Framework (MSFF)

KBSI developed an innovative Multi-Spectral Feature Fusion (MSFF) framework for the automatic fusion of mission-critical data from hyper spectral data sources. The MSFF framework improves target detection from data that has been obtained from sensors with a wide diapason spectrum.

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Adaptive Trajectory Reshaping and Control System (ATRC)

KBSI developed requirements for the design, development and demonstration of algorithms and real time solution techniques for an adaptable and reconfigurable Reusable Launch Vehicle (RLV) command, control, and guidance system.

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Wireless-enabled Workflows for Ship Manufacturing and Repair (AWSM™)

KBSI is developing a new paradigm for ship manufacturing based on a redesign of manufacturing processes and the use of computing and wireless technologies that will deliver information--activity statuses, resource availabilities, design and scheduling changes--to every user, work crew, or process, regardless of location, involved in the ship production or repair.

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Faraday Chromate

KBSI is performing analyses of Electro Impedance Spectroscopy (EIS) data in order to study the effectiveness and life of particular coatings on accelerated corrosion environments. 

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Non Destructive Inspection Data and Evidence Fusion Program (NDI)

KBSI applied advanced data fusion technologies in investigating methods for increasing the accuracy of non-destructive inspection imaging technology. Using both ultrasonic and eddy current images of KC-135 lap joint coupons, KBSI developed image processing techniques, both classical and wavelet-based, for the pre-processing of image data prior to corrosion quantification and fusion.

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Test & Evaluation Metadata PLaza (TEMPL)

KBSI is developing component-based technology that will support the Air Force’s use of current test and evaluation (T&E) metadata and their definition of metadata for future test activities.  KBSI is leveraging its experience in the application of ontologies and semantic web technologies to develop methods and tools that facilitate metadata extraction from legacy data and the formulation of metadata for ongoing and proposed test missions.

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