Dayton, OH, United States
Dayton, OH, United States
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Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase II | Award Amount: 749.99K | Year: 2014

ABSTRACT: Matrix and CSU are poised to develop algorithms to suppress radar WTC while preserving signals from targets of interest such as aircraft and weather. Our processing approach will be capable of utilizing radar data from either stationary- or scanning-mode ground-based systems. We will work closely with our transition partner to develop a Phase II transition plan to integrate our approach onto specific customer-operated platforms. BENEFIT: The statistical WTC model, along with its associated mitigation algorithm, will provide a revolutionary new capability for improving detection performance of both existing and future radar assets. Our primary industrial customer is Raytheon, which currently serves both military and civilian customers, including the Air Force, the Federal Aviation Administration, and the National Weather Service. Although the nature of the targets of interest differ between air surveillance radar and weather radar, the underlying wind turbine clutter model is the same. Upon successful demonstration of our algorithm in Phase II, we fully expect to be able to bring our algorithm to these markets.


Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase II | Award Amount: 749.99K | Year: 2014

ABSTRACT: The objective of this effort is to demonstrate innovative methods for deriving a sparse set of physical target features that can be used for exploitation of air-to-ground signature data collected from sensor systems including electro-optical, infrared, ladar, and radar. Current classification methods require near exact replication of the original imaging parameters, or extensive modeling in order to generalize the signature to novel operating conditions. By understanding the physical constraints on the target information, one can better construct and refine a classification system. In Phase I, we applied recent bounds, developed for electromagnetic scattering, to analyze optical wavelengths, and we now propose to develop and transition tools to use these bounds to explore feature salience, recognition, and classification. BENEFIT: The primary benefit of successful completion of this effort is improved exploitation systems wherein we can explicate why and where features are informative. This capability has numerous commercial applications in various business sectors such as defense, communication, and medical imaging.


Patent
Matrix Research Inc and National Cancer Center | Date: 2014-05-28

The purpose of the present invention is to provide a novel monoclonal antibody which binds to SLC6A6 or an extracellular domain thereof. The present invention relates to a monoclonal antibody which recognizes native SLC6A6 or a polypeptide of an extracellular domain of SLC6A6.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.94K | Year: 2015

ABSTRACT:The contractor shall develop a toolbox for understanding and predicting quantitative perfor- mance bounds for detection, geolocation, and tracking of moving targets using SAR.BENEFIT:By completion of the Phase II effort, we intend to have a software toolbox that will assist in the development and characterization of detection, geolocation, and tracking of moving targets in SAR data. The greatest potential for commercialization of such a toolbox is in the military sector. For example, such a suite will assist in performing the trade studies necessary to optimize the parameters during the development of the next generation of radar hardware.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.93K | Year: 2014

ABSTRACT: The goal of this SBIR is to explore the art of the possible and buy back performance using synergy and data fusion between multiple RF sensor munitions cooperating in flight. Our team, Matrix Research and Wright State University, will show how signal-to-noise ratio (SNR) can be improved using cooperative RF sensors. In particular, we will explore the techniques of cohere-on-transmit (COT) and cohere-on-receive (COR). For a monostatic radar, SNR can be improved by increasing power or aperture, or decreasing noise figure or range. The improvements in SNR we seek are due only to the cooperation of RF sensor munitions. Any improvement in an individual RF sensor SNR or resolution would be further improved by cooperative RF sensing. COT and COR can benefit all radar modes, including synthetic aperture radar (SAR) and ground moving target indicator (GMTI). During Phase I of this SBIR, our team will analyze the use of a software defined radar to aid in synchronizing time and measuring platform motion within a RF sensor network comprised of a group of munitions. We will then analyze the improvement in SNR and resolution expected using both COT and COR techniques as a function of key design parameters. BENEFIT: There is an increasing need for detection, tracking and identification of targets within an A2AD environment. This need exists primarily within the Department of Defense (DoD). In order to reliably detect targets in a contested environment, the cooperation of multiple radar systems will greatly improve sensor performance. In order to achieve the increased performance, cohere-on-transmit and cohere-on-receive will be required. The commercialization strategy for military application of this technology will most likely involve one or more of the large DoD contractors involved in munition manufacturing. Our intent is to partner with a missile systems hardware design team to build to the determined specifications and incorporate the software developed under this SBIR. In addition to the military application of this technology, there may also be commercial applications to explore in automated vehicle navigation systems for cars and especially aircraft and UAVs.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 749.95K | Year: 2014

ABSTRACT: Specialized aircraft coatings can degrade over time and impact desired performance. Current reflectometers measure at normal incidence to the surface which does not accurately predict the electrical performance of the material across the aircraft's surface. It is desirable to measure the interaction of the non-specular component or traveling wave to fully characterize the electrical performance of the coatings. Under a Phase I SBIR effort Matrix Research designed a prototype RF traveling wave inspection tool that can be used to measure dB/in attenuation of coatings along the surface. After studying the phenomenology of traveling waves Matrix used a full wave electromagnetic simulator to design traveling wave transducers. These transducers were then used the prototype traveling wave inspection tool. This proposal describes the work Matrix will perform during a Phase II effort to further mature the traveling wave inspection tool. The main objective of the Phase II effort will be to create a more rugged, conformable, easier to operate prototype that could be used by technicians on the flight line to evaluate the performance of a vehicles surface coatings. BENEFIT: With the number of platforms in the United States arsenal that use specialized coatings expected to be well over a thousand, the maintenance community is going to require new tools to help guide their sustainment and repair decisions. The traveling wave tool that is being developed in this effort will help to significantly improve maintenance efficiency by helping maintainers quickly identify problematic materials/aircraft regions. Being able accurately determine where there are material performance problems will also significantly reduce the number of unnecessary repairs. As such, this tool can find wide acceptance throughout the community.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.87K | Year: 2014

Matrix will develop algorithms for airborne passive Synthetic Aperture Radar (SAR) relevant to commercial transmitters of opportunity in an urban area. These algorithms will include new image-formations techniques tailored the airborne passive SAR scenario specified by the customer. Additionally, relevant metrics will be defined and utilized when comparing image-formation techniques and various illuminators as part of a trade study.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 749.84K | Year: 2013

ABSTRACT: Matrix Research, Inc. proposes to prototype, test, analyze, and demonstrate novel feature representations in multi-agent simultaneous localization and mapping (MA-SLAM) systems for enhanced navigation accuracy/reliability. The objective of this effort is to develop a framework to integrate data from various air and ground sensor systems employed for exploitation and interdiction tasks, focused on compact, multi-modal feature representations tailored for navigation applications in which low-bandwidth, low-rate communications between agents constrains data throughput. A layered sensing processing framework is needed that combines information, gleans meaning from the collected data, and re-tasks sensor-seekers in a timely manner to garner actionable intelligence and execute a course of action. This is only possible if the platforms have sufficient context and are able to jointly localize and coordinate. Initially, this effort will focus on multi-view descriptors for wide-baseline correspondence. Then it will demonstrate these methods for joint localization and coordination to accomplish an objective. Our thesis is that tightly coupled"vision-based"navigation will provide the necessary foundation, context, and features for MA-SLAM. We have two transition paths lined up to commercialize our results, both of which contribute to the AFRL mission. These will include both indoor and outdoor navigation demonstrations. BENEFIT: The primary benefit of successful completion of this effort is a revolutionary new capability for extracting features for mapping systems. This capability has numerous commercial applications in various business sectors such as defense, search and rescue, mapping, mining, and robotics.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 748.98K | Year: 2013

ABSTRACT: The objective of this Phase II SBIR topic is to develop and demonstrate an automated move-stop-move combat identification system under realistic scenarios. In addition, we require the resulting system must work on bistatic radar data. This additional requirement is applied so that our solution addresses the A2AD problem. Algorithm development includes effort in detection, tracking, and classification routines for both bistatic synthetic aperture radar and range-Doppler maps. BENEFIT: As a result of this work, the Government will have a code set for testing various exploitation algorithms to address move-stop-move scenarios for A2AD applications. Commercialization is anticipated through licensing software to DoD prime contractors.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 748.23K | Year: 2015

ABSTRACT:Matrix will further develop algorithms for airborne passive Synthetic Aperture Radar (SAR) relevant to commercial transmitters of opportunity in an urban area. Building off our theoretical results from Phase I, we intend test our new image-formations techniques in the passive SAR scenario specified by the customer. Additionally, relevant metrics will be defined and utilized when comparing image-formation techniques during the test and evaluation stages of the project.BENEFIT:The passive SAR system will provide a revolutionary new capability for exploiting ambient RF transmissions from commercial terrestrial sources. There is a clear need for passive surveillance in the military sector. Also, we expect elements of our approach to be applicable to civilian simultaneous localization and mapping problems (SLAM) such as autonomous-navigation systems. Our techniques may be useful in SLAM systems that exploit illuminators of opportunity to discover information about the environment.

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