Sensors and Environment -- Projects

Advanced Coding Techniques for Complex Sensor Systems

Affordable Moving Surface Target Engagement (AMSTE)

Biometrics: Calibration and Systems Engineering

Collaborative Investigations
of Multi-target Tracking and Sensor Cueing for Netted Sensor Fields

Dynamic Scheduling for MC2C

Innovative Space-Based Radar Antenna Technology (ISAT)

Joint Time Critical Targeting (TCT) Experimentation

Multi-Sensor and Multi-Platform Sensor Exploitation for Combat ID

Netted RF Sensors

Networked Embedded Software Technology (NEST)

Pathogen Capture Using Floating Films

Resource Management for Netted Sensors

State Predicted Interference Cancellation and Equalization (SPICE)

Synergistic Signal Processing Methods for Sensor Fields

Three-Dimensional
(3D) Sensor Exploitation

Vegetation Forensics

Sensors and Environment

Sensors and Environment researches technologies employed to detect, monitor, and characterize the environment (terrain, weather, targets, etc.) to determine position within that environment (geoposition), and to manage, exploit and disseminate positional data (geographic information systems). The use of radar, optical, sonic, and multispectral sensors is covered.

Advanced Coding Techniques for Complex Sensor Systems

Joseph Creekmore, Co-Principal Investigator

Jeff Woodard, Co-Principal Investigator

Washington

Problem
As the Navy moves toward network centric undersea warfare and remote sensors, the data collection rate greatly exceeds the radio bandwidth available to exchange it over the network, or even store it once it is received. Further, traditional signal processing techniques have become less effective as adversary submarines have become quieter and a new emphasis on littoral areas results in increased clutter from interfering noise sources.

Objectives
We will develop and tailor commercial lossless and lossy compression technology for acoustic intelligence (ACINT) applications. This will reduce physical storage requirements and volume of data that must be transmitted from collector to analyst. We will apply multirate signal processing techniques to provide sharper frequency resolution and better clutter rejection for low strength signals.

Activities
We have provided a lossless Burrows-Wheeler compression tool to the ACINT division of the Office of Naval Intelligence (ONI) for evaluation. We have also applied lossy compression to tactical ACINT data provided by ONI and returned the results to them over a range of compression ratios for comparison on their own in-house analysis systems. We will apply multirate spectral analysis to the same data to compare with traditional signal processing methods currently in use. These methods are also applicable to submarine sonar development, and we will brief them to the Advanced Systems Technology Office working groups that review new algorithms for introduction via Advanced Processor Builds.

Impacts
The transition of lossless compression technology to ONI will reduce the amount of physical media required for archiving acoustic data. The transition of lossy compression technology should permit tactical ACINT data to be transmitted to analysts in near real time. The transition of high resolution spectral analysis technology to ONI and other sponsors should improve detection and analysis capabilities in difficult environments.

Affordable Moving Surface Target Engagement (AMSTE)

DARPA Office: IXO
DARPA PM: Mr. Charles Taylor

Sean D. O’Neil, Principal Investigator

Bedford and Washington

Problem
Engagement of static, nonmoving targets is a well-developed area of endeavor for the US military, with a set of options available for both standoff and close-in engagement in a wide variety of conditions. This is not the case for targets that can move, and this fact is increasingly being exploited as a countermeasure by opponents of our armed forces.

Objectives
The primary objective is to enable the rapid engagement of moving targets with precision, standoff weapons in all weather conditions. The chosen method is to use multiple, standoff, ground moving target indicator sensors to maintain threat track from nomination to engagement and to provide rapid fire-control updates on the target to the weapon in flight.

Activities
The first major task is to demonstrate long-term threat track maintenance in the presence of expected operational complications such as dense traffic, terrain and foliage masking, move-stop-move maneuvers, and platform dropouts. The second is to demonstrate AMSTE in an unscripted scenario with full Air Operations Center C2 involvement, including nomination and weapon-target pairing, at Roving Sands 03.

Impacts
When fully developed and deployed, AMSTE will deny adversaries the sanctuary of mobility, while providing the DoD with an affordable solution against a mixture of high-value and asymmetric threats and maintaining a minimal level of collateral damage.

Biometrics: Calibration and Systems Engineering

Nicholas Orlans, Principal Investigator

Washington

Problem
Biometrics are widely heralded as part of the solution to weak or broken security. However, the increased hype and momentum have resulted in hasty and often inappropriate solutions being piloted or deployed. Very little effort has been spent on examining the calibration, systems engineering, and integration of biometrics into supporting infrastructures and across environments—honest and objective evaluations are short in supply.

Objectives
This research strives to create an evaluation environment and methodology for estimating the overall accuracy of systems that support detection and classification of nefarious human elements. We will explore the upper limit of predictive accuracy for systems constructed with today’s biometric devices and also hypothesize performance for the next generation of systems. Through scenarios, researchers will validate performance predictions and better understand integration issues.

Activities
In the area of synthetically generated biometric test data, we will generate large parametrically controlled facial images, perform isolation and parametric control of known performance variables for facial recognition, and simulate lesser known performance variables. A new BioGame laboratory will explore high-level scenarios for authentication, identification, and detection of furtive behavior using a predictive model in conjunction with an actual sensor environment.

Impacts
All MITRE centers have interest and some involvement in biometrics. The two primary project activities—testing with synthetically generated 3D facial images and laboratory experimentation—will explore concepts and provide results closely aligned to real-world problems and sponsor interests. Although standards are still incomplete, biometric component technologies are available now and commercial biometrics is increasingly becoming a part of the DoD and other federal government work programs.

Collaborative Investigations of Multi-target Tracking and Sensor Cueing for Netted Sensor Fields

Garry Jacyna, Co-Principal Investigator

Michael Otero, Co-Principal Investigator

Washington

Problem
The timely cueing of stand-off sensors by a field of netted proximate sensors and the distributed fusion of multi-target track information across heterogeneous sensor networks are challenging signal processing and communications-related problems. By leveraging expertise across a number of related MSR projects in the netted sensors area, we can begin to develop a company-wide perspective on these problems.

Objectives
The objective of this project is to collaboratively develop multi-target tracking and cueing algorithms for a field of proximal and stand-off sensors. Sensor resources must be managed so as to limit power consumption, communications bandwidth, and algorithmic processing subject to the constraints of a netted sensor system.

Activities
This project will develop a proof-of-concept demonstration of a multi-target tracking and cueing system based on fields of proximate RF sensors and stand-off radars. We will demonstrate the utility of the approach for tracking tank movements on a simulated battlefield.

Impacts
This project collaboratively addresses two difficult problems associated with netted sensor systems — the cueing of stand-off sensors from a proximal network of sensors and the fusion of target track information from a heterogeneous field of sensors. Progress towards solving these problems would be of considerable interest to the netted sensors community.

Dynamic Scheduling for MC2C

David M. Zasada, Principal Investigator

Bedford and Washington

Problem
No techniques currently exist to dynamically manage multiple, dissimilar, tactically responsive platforms and sensors.

Objectives
Our objective is to develop techniques for the real-time, dynamic management of multiple, dissimilar platforms and sensors. A key objective is to automate the sensor management process, making it highly machine assisted, while maintaining human-in-control oversight. We intend to develop strategies that achieve operational requirements and optimize performance of the Multi-sensor Command and Control Constellation (MC2C).

Activities
We will exercise a complete sensor task-post-process-use web, concentrating on BMC2 functions and the sensor system resource manager. We emphasize dynamic multi-platform system retasking in response to time-critical targets and events. We will first consider synthetic aperture radar imagery and moving target indication products derived from space-based radar (SBR) and the Multi-sensor Command and Control Aircraft (MC2A), and then extend our research to Global Hawk.

Impacts
This project is intended to build a sound technical basis of dynamic sensor management and retasking capabilities for MC2C simulations and acquisitions. It is also intended to illuminate potential problem areas in the emerging task post, process, and use cycles. Potentially, opportunities exist to transition this work into MC2C, MC2A, SBR, Multi-Platform Radar Technology Improvement Program, and Global Hawk.

Innovative Space-Based Radar Antenna Technology (ISAT)

L. Danny Tromp, Principal Investigator

Bedford and Washington

Joint Time Critical Targeting (TCT) Experimentation

Sean O'Neil, Principal Investigator

Bedford and Washington

Multi-Sensor and Multi-Platform Sensor Exploitation for Combat ID

Walter S. Kuklinski, Principal Investigator

Bedford and Washington

Netted RF Sensors

Michael F. Otero, Principal Investigator

Bedford and Washington

Problem
Netted sensor concepts are based on the supposition that modestly performing distributed sensors, netted together using ubiquitous communication and advanced processing, provide an output significantly greater than both the performance of any single sensor and the sum of individual contributors. However, there is no general theory to validate this supposition;, simulations and experiments would be needed to support it.

Objectives
We plan to develop a set of principles to guide the application of netted sensors for measurable performance and cost. This will be done by using simulation and experimentation to study the tradeoffs between the number of sensors, their deployment, and sensor complexity.

Activities
We will address the specific problem of using RF sensors to detect and track vehicles in a battlefield environment. Modeling and simulation tools are being developed to simulate multiple RF sensors observing moving entities on a battlefield. Experiments will be conducted with COTS hardware to validate and complement the simulation effort. The results from this specific problem will then be extended to more general ones.

Impacts
The results and “lessons learned” from this program will have a significant impact on a number of our sponsor’s programs that are currently making use of, or planning to make use of, netted sensors. Several important problems requiring the integration of sensors include combat identification, time critical targeting, electronic attack/electronic protection, underground facility characterization, and nuclear-chemical-biological agent detection.

Networked Embedded Software Technology (NEST)

DARPA Office: IXO
DARPA PM: Dr. Vijay Raghavan

Alex Meng, Principal Investigator

Washington

Networked Embedded Software Technology (NEST)

DARPA Office: IXO
DARPA PM: Dr. Vijay Raghavan

Alex Meng, Principal Investigator

Washington

Problem
Future battlefields will deploy sensors on the scale of 100 to 100,000 nodes depending on the scenario. NEST research focuses on customizable coordination and synthesis services in networked embedded systems. Coordination services include fault-tolerant, self-stabilizing protocols for data exchange, synchronization, and replication. Synthesis services provide time-bounded solutions for complex, distributed constraint satisfaction tasks required for dynamic reconfiguration of applications.

Objectives
Embedded information processing is fast becoming the primary source for superiority in weapons systems. The current trend is toward “information rich” nodes with fine-grained integration of physical processes of sensing and actuation and computational processes such as monitoring, diagnostics, and overall closed loop system control. NEST’s objective is to develop a theoretical foundation and technology for resource-constrained networks of embedded nodes.

Activities
MITRE provides independent and objective evaluation of the Open Experiment Platform (OEP) for NEST challenge problems. MITRE has set up a laboratory to test and evaluate OEPs and develop metrics to evaluate each research team’s technology. MITRE supports NEST meetings or program reviews by providing assessments of the success or failure shown by experiment results. MITRE also helps DARPA to seek transition opportunities.

Impacts
MITRE provides concrete and tangible evaluation to the NEST Program Manager. MITRE lab work provides further insights to the usability of the OEP hardware and software, and assesses the progress of the research

Pathogen Capture Using Floating Films

Elaine H. Mullen, Principal Investigator

Washington

Problem
Contaminated surface water can contribute to the spread of infectious disease through human and animal populations. Scientists need an inexpensive method of concentrating and detecting harmful microbes and toxins in drinking water reservoirs and surface waters worldwide.

Objectives
We will design a prototype film to collect and concentrate specific pathogenic bacteria at the surface of water. Under various environmental conditions and concentrations of organisms we will optimize and quantify the film's stability, specificity, and efficiency. During the course of our research, we will measure the chemical and physical properties of the biocapture films.

Activities
We will float biocapture films on water containing a mixture of pathogenic and harmless bacteria, measuring the effects of varying composition, configuration, pathogen concentration, and mixing time on the adhesion of cells to the film. Periodically we will measure spectral characteristics of the film-pathogen complex. A world-class team of experts will evaluate experimental protocol and test results.

Impacts
Films synthesized from lipids and glycoproteins offer an affordable means of selectively concentrating pathogens at the surface of water reservoirs.

Resource Management for Netted Sensors

Thomas P. Bronez, Principal Investigator

Washington

Problem
A critical enabling element of transformational defense concepts is exquisite situational awareness achieved through distributed networks of heterogeneous sensors. These netted sensors are often highly constrained in terms of energy resources, communications resources, and sensing schedules. As a result, algorithms for effective resource management within ad hoc networks of distributed sensors are essential to fielding the desired situational awareness capability.

Objectives
We believe that a distributed resource management (DRM) approach is important for successfully implementing sensor networks, and that DRM can be pursued in a sensor-independent way. The objective of this research is to develop algorithmic guidelines and principles for managing resources among netted sensors, including both intra-sensor algorithm management and inter-sensor collaboration management.

Activities
Last year we developed a DRM agent for the DARPA ANTS (Autonomous Negotiation Teams) testbed using heuristic criteria. This year we will develop detection-theoretic algorithms that jointly optimize resource consumption and sensing performance. These algorithms will be used to judge and improve our agent. Additionally, we will generalize our software for sensor independence and conduct experiments to evaluate our developments.

Impacts
Sensor-independent resource management algorithms are directly applicable to the Army Future Combat System, the Navy Expeditionary Pervasive Sensing strategy, the Air Force Advanced Remote Ground Unattended Sensor, the Special Operations Command Multi-Intelligence Reporting and Signal Sensor, the DARPA SenseIT and Micro-Internetted Unattended Ground Sensors programs, and Customs Service netted surveillance efforts.

State Predicted Interference Cancellation and Equalization (SPICE)

James Dunyak, Principal Investigator

Bedford and Washington

Problem
The demand for more data in less time via wireless links has resulted in an increasingly crowded RF spectrum. As a result, in many cases, co-channel interference, instead of noise, has become the primary factor limiting the performance of communication, navigation, and sensor systems. To achieve optimum performance, new interference cancellation methods are needed to remove the co-channel interference.

Objectives
The objective of this project is to develop and assess the performance of advanced nonlinear interference cancellation and equalization methods for next generation communication and sensor systems.

Activities
Research areas include the development and refinement of multi-user detection (MUD) algorithms for CDMA systems. Activities include the assessment of current methods and development of new MUD algorithms tailored to military environments. The project is also developing signal separation algorithms for the case of overlapped narrowband communication signals.

Impacts
The technology being developed in this project is critical to next generation communication, navigation, and sensor systems. These systems will not be able to achieve the needed capacity, detection sensitivity, and navigational accuracy without the performance improvement provided by the new interference cancellation algorithms. Already, the products of this project are being integrated into customer-sponsored sensor development projects.

Synergistic Signal Processing Methods for Sensor Fields

Garry M. Jacyna, Principal Investigator

Washington

Problem
The primary technical focus within the netted sensors community has been on defining network protocols and developing adaptive (mobile) network topologies. There has been little thought given to the signal processing issues associated with deployed distributed sensor systems.

Objectives
The objective of this project is to develop robust signal processing algorithms for distributed sensor detection, classification, localization, and tracking applicable to the Navy littoral and Army battlefield environments as well as to homeland defense/security.

Activities
This project is structured around developing robust acoustic and electromagnetic clutter mitigation algorithms, “tripwire” parametric and nonparametric detection methods, feature-based classifiers, adaptive beamforming under positional uncertainty, and multi-target particle filter-based tracking.

Impacts
This project positions MITRE at the technical forefront of work within the netted sensors community. The ideas advanced in this project are applicable across a broad spectrum of MITRE and potential sponsor work programs. A number of algorithms are anticipated to be of patentable quality.

Three-Dimensional (3D) Sensor Exploitation

Walter S. Kuklinski, Principal Investigator

Bedford and Washington

Problem
Existing military target recognition systems fail to meet many desired operational objectives. Sensor systems that could provide accurate real-time 3D information have the potential to revolutionize target recognition. Since targets and their local environments are three dimensional, 3D sensors coupled with 3D processing and exploitation algorithms can produce significant gains in target recognition.

Objectives
This project will develop a systems-level methodology to design, analyze, and implement 3D sensor target recognition systems. To evaluate this methodology a prototype 3D multiple modality sensor system will be constructed. This prototype system will process sensor data in conjunction with 3D target models and terrain information to reliably recognize targets over broad ranges of obscuration and environmental complexity.

Activities
Statistical signal processing methods based on scattering phenomenology will be applied to the problem of 3D target recognition. 2D SAR image formation methods, at both foliage-penetrating VHF/UHF frequencies and millimeter wavelengths, will be extended to provide a 3D capability. This project will also develop adaptive multi-sensor tasking procedures to optimally task multiple sensor platforms for enhanced 3D imaging applications.

Impacts
Sensor systems that provide accurate real-time 3D information have the potential to revolutionize the target recognition process. The application of advanced signal processing algorithms and intelligent exploitation of 3D image data in conjunction with a priori information will lead to systems resistant to camouflage, concealment and deception, and jamming, providing increased situation awareness to the warfighter.

Vegetation Forensics

Sherry L. Olson, Principal Investigator

Washington

Problem
Nefarious activities are often extremely difficult to detect directly with today’s sensor technology, due to the clandestine and transient nature of activities as well as active denial and deception techniques employed. Indirect sensing techniques may provide the most benefit in some cases.

Objectives
Research shows that environmental pollutants, as well as oil, salt, and metals, affect plants in ways that can be measured both in the laboratory and with remote sensing. The stress to plants can be measured after single events or after long-term exposure. This research will demonstrate the application of indirect sensing of vegetation stress stemming from activities of national security interest.

Activities
We will conduct plant biology experiments on healthy and stressed vegetation to characterize the effects of stress agents on vegetation under varying conditions. We will collect laboratory and field signatures of the vegetation being studied and conduct remote sensing experiments using this ground truth data. Laboratory, field, and remote spectral data will be analyzed to determine the detection limits and the ability to distinguish between types of stresses caused by natural, nefarious, and benign activities.

Impacts
Indirect sensing of indicators, such as vegetation stress, has the potential to have a large impact on difficult problems susceptible to denial and deception. Counter-drug applications and other national security concerns where direct sensing of activities range from difficult to extremely difficult are prime candidates. Transition opportunities for this vegetation stress research will be pursued with national and military intelligence organizations.