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.
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 745.39K | Year: 2013
ABSTRACT: The objective of this effort is to develop an algorithmic framework for joint utilization of GPS/INS/SAR in order to simultaneously improve the localization accuracy and integrity of an airborne sensor system's navigation system. The primary challenges from a SAR-processing perspective are a) the estimation of position and velocity states directly from SAR phase history data and b) the development of a realistic model to calculate uncertainty estimates associated with the SAR-based (position, velocity)-state estimates for use in an integrated navigation system. From a more traditional navigation viewpoint, a significant challenge arises in the incorporation of the noisy SAR-based (position, velocity) estimates -- which are inherently associated with the approximate phase center of the SAR antenna -- within an overall navigation system. This effort will focus on developing real-time implementations of the algorithms proved successful in the prior Phase I effort (the autofocus- and feature-based motion estimation algorithms, as well as the generic navigation filter). The efficiency and efficacy of these algorithms will be demonstrated through real-time data collections measured on an Air Force platform. Although the demonstration will be application-specific, our approach is general enough to apply to several different types of (airborne and ground-moving) ISR platforms. BENEFIT: The primary benefit of successful completion of this effort is a revolutionary new capability for improving overall geolocation accuracy and integrity for platforms with radar assets. This capability has numerous commercial applications in various business sectors such as defense, mapping, and transit.
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.
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.
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.