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All MITRE Projects (with summaries and presentations where available)
Listing of project titles in alphabetical order
Pages: 1234567891011121314151617
3D SLAM: Simultaneous Localization and Mapping in 3D for Unmanned Systems
Primary Investigator:Robbins, Scott
Problems:
Operations in cluttered urban and interior settings pose unique challenges to unmanned vehicle operations. Narrow field of view cameras andpoor localization can lead to a loss of situation awareness.
By exploiting 3D sensing with simultaneous localization and mapping (SLAM) we are addressing these problems by providing unmanned vehicle operators with a real-time sensor-generated 3D map of the environment. We are specifically focused on applications for use on small UAVs and UGVs operating in urban canyon and interior environments.
By providing both human and machine operators with a synthesized third person "3D mosaic" and alternate localization to GPS, we will demonstrate improvements to situational awareness in these critical areas.
Objectives:
Demonstrate 3D localization (self-tracking) for small UGVs in interior environments
Demonstrate generation of 3D maps from UGVs in real time
Coordinate with Army sponsors at the ARDEC IS&R branch
Demonstrate applicability of visual navigation to UAVs in GPS denied environments
Activities:
We will identify and test various approaches for real-time 3D SLAM suitable for application to small military UGVs and UAVs. Localization approaches will be characterized in terms of precision and drift from ground truth. Mapping approaches will be characterized in terms of fidelity to the operational environment and mission requirements.
Impact:
This research will provide a set of demonstrated technologies for 3D localization and mapping suitable for integration into exiting military small UGVs and UAVs operating in urban and interior environments.
Public Release No:09-0847
[Presentation]
Exhibit Date(s):May 5, May 6, May 7
3x2 Fingerprint Challenge
Primary Investigator:Barry, Steven H.
Problems:
Complete hardware fingerprint matcher and fingerprint indexing work and transition products of this project to sponsors.
Objectives:
Decrease the cost per fingerprint match by 3 orders of magnitude and increase the speed by2 orders of magnitude.
Activities:
1. Complete the FPGA hardware implementation with on-board clocking, memory access, bus inteface, and driver software
2. Complete implementation and testing of two candidate fingerprint indexing approaches.
3. Transition results to sponsors.
Impact:
Progress already demonstrated by this project and anticipated from this year's work will have a profound affect on:
1. DHS (U.S.-VISIT) - the owner of the IDENT biometric identity verification system
2. DOJ (CJIS) - The owner of the FBI IAFIS biometric identification system
3. DoD - the owner of the Army biometric identification system
We expect each sponsor organization to be able to use the results we have produced to increase government leverage on price and performance in near-term acquisitions of major biometric matching system components.
Public Release No:09-1282
[Presentation]
Exhibit Date(s):May 5, May 6
A Multi-Source Recommender System for Intelligence Analysis
Primary Investigator:Barteee,Tom
[Presentation]
Exhibit Date(s):May 5
A Secure Biotoken for Border Management
Primary Investigator:Barry, Steven H.
Problems:
The FY09 goals of this project are to add to the demonstrated successful long-range biometric identity card state-of-the-art security and anti-tamping safeguards and advanced power storage and management capabilities to increase useful time between charges.
Objectives:
Provide the technical advances needed to make a low-cost, hardened, easy-to-use biometric identity card secure, usable, and reliable for use in large quantities.
Activities:
1. Security and anti-tamper analysis and redesign
2. Power storage, use and management analysis and redesign.
Impact:
The hardened long-range identity credential (the MITRE Biotoken) is expected to provide proof-of-concept and a reference design for sponsors to use in acquiring a low cost, secure, and highly functional biometrically validated identity card for use in portal access applications.
Public Release No:09-1289
[Presentation]
Exhibit Date(s):May 6
A Universal Bio-Sensing Platform
Primary Investigator:Diggans, James C.
Problems:
Current biosensors are primarily based on previous observations; they detect organisms known to be pathogenic. Future biowarfare agents, however, are likely to contain completely novel or re-engineered proteins and nucleic acid sequences. These areintended either to make previously harmless organisms pathogenic, to increase the pathenogenicity of existing agents, or expressly render the agent undetectable by conventional serotype- or PCR-based methods.
This project is designing a prototype software-defined biosensor: a sensing platform that can identify a large number of organisms while minimizing cost and time required to extend detection to emerging or engineered pathogens.
Objectives:
Design roughly orthogonal model-driven microarray probes taking into account secondary structure, melting temperature, etc.
Design classification algorithms to identify target organisms against a complex microbial genomic background.
Generate array data on simulant organisms in pure culture and on organisms spiked into a complex genomic background.
Activities:
This fiscal year we'll be exploring alternative technologies including microfluidics and label-free array-based detection strategies to reduce the time and consumables overhead required by the current prototype sensor.
This will be carried out in parallel to the further characterization of the performance of the v2.0 prototype array sensor including assaying additional organisms as well as environmental collection and analysis.
Impact:
The project is developing a flexible sensor capable of identifying a wide array of threat agents not limited to those specifically included in an upfront design as in most modern biosensors. Using this approach, adding additional organisms to the sensor is only a matter of a software patch to deployed infrastructre rather than re-engineering deployed systems.
Public Release No:09-0902
[Presentation]
Advanced Perception for Unmanned Ground Vehicles
Primary Investigator:Grabowski, Robert J.
Problems:
Perception is essential for competent ground robots. Operational expectations for existing robots far exceed current technology as evidenced by recent events like the Urban Grand Challenge. This, in large part, is due to the limitations of existing sensor technology. Robots derive perception of the world directly through sensors. As the mission space becomes more complex, sensor technology must keep pace.
We will demonstrate improved perception capability on an unmanned ground vehicle (UGV), provide a framework for defining the necessary sensing capabilities for unmanned ground vehicles, demonstrate how to enhance vehicle perception by combining multiple sensors to overcome the weakness of an individual technology and investigate novel techniques such as sensor fusion, sensor cueing, sensor steering, and mosaicing.
Objectives:
Demonstrate improved perception capability on an unmanned groundvehicle (UGV).
Provide a framework for defining the necessary sensing capabilities for unmanned ground vehicles.
Demonstrate how to enhancevehicle perception by combining multiple sensors to overcome theweakness of an individual technology.
Investigate novel techniques suchas sensor fusion, sensor cueing, sensor steering, and mosaicing.
Activities:
Identify capabilities of existing sensor technology with respect to four key areas of UGV perception: maneuvering, navigation, safety, and awareness. Characterize the strengths and weaknesses of each approach. Develop new methods for combining and fusing information from multiple sensors to overcome identified limitations and gaps. Test and verify new approaches in a representative urban environment on a real autonomous vehicle.
Impact:
This research will shape how to approach future development of sensing for unmanned ground vehicles with respect to both the vehicle and humans that must operate around it. By developing and testing on an existing autonomous vehicle, this research will also yield a vehicle capable of conducting more complex missions in realistic, operationally relevant environments.
Public Release No:08-0293
[Presentation]
Exhibit Date(s):May 6, May 7
Advanced Signal Processing for Wireless Communications
Primary Investigator:Shapiro, Jerome M.
Problems:
The replacement of hard information binary block codes with soft-information-based turbo and low-density parity check codes changed point-to-point communications profoundly. Recent developments in communication theory make the time ripe for the development of soft-information-based networks. This project will attempt to solve pressing problems with current mobile ad hoc networks (MANETs) by developing simple networks of intelligent nodes capable of advanced signal processing.
Objectives:
We will make fundamental contributions to signal processing for wireless communication that have broad impacts on MANETs, sensor networks, special communications, and low probability of intercept/low probability of detection (LPI/LPD) communications. We will develop capacity-approaching rateless coding solutions, combine rateless coding with cooperative diversity to achieve high-performance wireless ad hoc networks, and combine rateless coding with LPI/LPD techniques to produce a high-throughput waveform.
Activities:
We will develop signal-processing-based physical layer solutions to increase throughput and to simplify the higher layers of the network protocol. This approach to wireless network design reduces overhead, increases spectral efficiency in bandwidth-limited environments, increases power efficiency in power-limited, and secure communications, improves connectivity, reduces network complexity, and shortens session setup time. We will explore how these techniques might affect information assurance and security.
Impact:
We expect our research to change the way engineers view the design of both mobile and sensor ad hoc networks. Additionally, we expect this work to have great value to our traditional customer base in special communications. We will submit contributions to standards bodies so that military requirements relevant to our research can be included.
Public Release No:06-1225
[Presentation]
Exhibit Date(s):May 6, May 7
Advanced Stream Mining for Assistive Analysis
Primary Investigator:Leveille, Peter S.
Problems:
Operational data analysts are responsible for processing the increasing amounts of live streaming data. Analysts manually access unique data sources through a set of tools, and perform analysis on the available data. Operationally, analysts can only concentrate on small areas of interest. Abnormalities in the periphery are often not detected until the forensic stage. Forensic analysis has proven to be very effective; therefore research in abnormality detection has primarily focused on the forensic analysis of sensor data. However, any intelligence on suspicious or hostile activities gathered and reported in near real-time can prove invaluable to the situational awareness of warfighters in theatre. Used in conjunction with high fidelity forensic intelligence, near real-time intelligence extracted from streaming data will enable warfighters to proactively meet emerging threats in theatre. Assistance is needed to share the cognitive load in analyzing streaming data.
We intend to employ stream mining methods on incoming data streams to actively alert in analysts theatreof specific, analyst-identified patterns. We hypothesize that employing stream mining methods on live sensor data will improve efficiency in theatre, as evident by a significant increase in near real-time event detection rate. This has the potential to increase situational awareness and shorten decision response time.
Objectives:
The goal of this work is to ultimately help analysts process large volumes of data. Assistive analysis processing has the potential to help the warfighter on the ground receive more prompt situation awareness.
The primary, measurable objective of this effort is stated as follows: Operational analysts will be able to perform more efficiently in theatre, as measured by qualitative user evaluations and quantitative tests resulting in a significant increase in the near real-time event detection rate.
Activities:
To fulfill the primary objective, the following six process objectives must be met:
1. Work with user community to derive valid metrics, includingdetection rate and false positives.
2. Prioritize critical events based on preliminary analyst input. Other events may surface during the course of this effort and will be taken into consideration.
3. Determine the appropriate methods for event detection. Identify existing algorithm work that coincides with the prioritized events.
4. Implement event detection service within the Sensor Data & Analysis Framework (SDAF). This requires programming the algorithm services, modifying the SDAF system as needed, and testing the algorithms on a known data set.
5. Conduct a set of quantitative user evaluations to measure algorithm performance. Data containing the known events will be used here. Users will be asked to identify events in the data with and without event detection cueing. Performance results will be recorded.
6. Conduct qualitative user evaluations to measure implementation effectiveness. The purpose of this is to determine how useful the users find the assistive analysis capability.
Impact:
This effort has the potential to help decrease the analyst’s decision response time and increase their situational awareness, as evident by the increased positive event detection rate through use of the implemented assistive analysis capability. The analysts will be directly impacted by this effort. The true impact of this work will be felt by warfighters in the field whose situational awareness will be augmented with valuable intelligence in near real-time.
The research importance of this work lies in the application of stream mining methods to a time-critical environment. Stream mining is commonly used in financial and scientific applications. We are going to apply existing stream mining methods, and expand on them for the benefit of analysts and warfighters. This work will help advance the stream mining field and reveal additional challenges.
Public Release No:09-0872
[Presentation]
Advanced Visualization Capabilities for NextGen Research
Primary Investigator:Wanke, Craig R.
Problems:
MITRE and others are employing a range of simulation and data analysis tools to understand the impact of planned technology and procedural upgrades in the FAA’s Next Generation Air Transportation System (NextGen). The complexity of the story suggests a need for visual ways to understand data and communicate the impact of decisions. This research effort is intended to broaden MITRE's tools and expertise in visualization and bring that expertise to bear on NextGen's needs.
Objectives:
The goal of this research is to significantly enhance our tools, expertise, and overall visualization skills. Staff also need guidance on what visualization tools are available and how best to use them to effectively communicate their message. This research will investigate an overall framework for the visualization tool and capability landscape, and will communicate recommendations through presentations, demonstrations and web-based communication forums.
Activities:
The research team for this work includes experts from MITRE's Center for Advanced Aviation System Development (CAASD), MITRE's Information Technology Center, the Information and Computing Technology Department, and other acknowledged centers of visualization expertise. The research will survey best practices in information visualization methods and tools, identifying what has succeeded elsewhere. It will then identify a broad set of MITRE needs and lay out a “road map” for meeting those needs. Finally, the project will demonstrate a number of visualizations, targeted at a NextGen-related set of problems.
Impact:
By increasing the range of visual communication tools and techniques available to MITRE staff this research aspires to significantly improve MITRE's impact on customers, stakeholders, and decision makers.
Public Release No:09-0999
[Presentation]
Adversary Emulation
Primary Investigator:Gosnell, Steven K.
[Presentation]
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