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Columbia, MD, United States

Roesener A.G.,U.S. Air force | Gerber J.D.,Applied Defense Solutions Inc.
IEEE Aerospace and Electronic Systems Magazine | Year: 2015

Over-the-horizon radar (OTHR) systems, or skywave propagation systems, use the high frequency (HF) band (3 to 30 MHz) to bounce or refract a signal off the ionosphere to detect tracks of interest (TOIs) between 500 and 2000 nautical miles from the transmitter/receiver pair. This range is an order of magnitude greater than is possible with conventional line-of-sight radars [1]. Since their initial employment, OTHR systems have significantly improved in abilities to detect and track TOIs such as aircraft, ballistic and cruise missiles, and ships [2]. © 2015 IEEE. Source


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 98.53K | Year: 2008

Leveraging existing demand-based frequency and spatial allocation methods we will attempt to provide a baseline algorithm set and architecture for the development of a system wide frequency reuse planning tool for UHF satellite communications


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: SBIR | Phase: Phase I | Award Amount: 99.83K | Year: 2010

ADS proposes to apply the Communication Taxonomy (CommTax) toolkit developed under a previous SBIR contract (current in the final stages of Phase II development). CommTax will be applied to the specific case of of nuclear scintillation in order evaluate how configuration parameters can be adjusted to achieve optimal performance. In addition, we will evaluate CommTax''s underlying technologies for suitability for use in prototyping and testing various radiation hardening techniques and solutions


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.52K | Year: 2015

ABSTRACT:Applied Defense Solutions (ADS) has embarked upon a new approach to data correlation and aggregation. The ADS Hierarchical Reasoning Tool (HRT) provides a set of unique signatures for automatically recognizing and classifying a resident space object (RSO). Here, we seek to leverage hierarchical reasoning to provide innovative and automated analysis capabilities that capture and learn the normal status and behavior of satellites, detect changes, and assess the implications all within the context of events in the space domain. To assess orbital events and provide for timely decision analysis and courses of action, ADS proposes the development of a scalable automated workflow to support an Orbital Event Characterization Tool (OECT) within a distributed service oriented based architecture. Our primary research goal will be to connect the RSO feature hypothesis generation capabilities of HRT into the OECT capability to provide high level hypothesis management of events, characterize anomalous events, and detect changes in both object appearance and behavior all within context provided by a multi-INT event timeline. Our proposed approach will model and/or learn the normal behavior of space-based objects via Bayesian update process and leverage ADS operational expertise of satellite operations to generate a hierarchy reflecting mission level object life cycles.BENEFIT:Hierarchical reasoning capabilities provide a structured and mathematically rigorous methodology to correlate and aggregate sparse data from disparate sensors. The completed software tools could be used by both government and commercial entities that wish to not only provide indications of and attribution for anomalous events but also predict the likelihood of future intention and warn of possible threats.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.67K | Year: 2014

ABSTRACT: Current photometric calibration techniques take away too much time from performing actual collections of interest, which decreases the efficiency and usefulness of important SSA resources. In response to the AF141-013 SBIR Solicitation for Efficient Photometry, the ADS-PDS team proposes to study in-frame photometric calibration feasibility and to provide an approach that is implementable for current operations. We plan to leverage existing in-frame astrometric and photometric algorithms and software previously developed by PDS. Under this Phase I effort, ADS will add in-frame photometric calibration techniques. Furthermore, the ADS team will study the algorithm"s calibration accuracies and applicability to a diverse set of sensor field-of-views (FOVs) and signal-to-noise ratios, while validating and testing the software with actual astronomy images to ensure that it is low cost, globally applicable, near-real-time, and requires no additional collection time. We plan to pair the software with the latest, most robust photometric catalog currently available, the SST-RC3 catalog, to maximize the potential to identify stars in even the smallest FOVs. Furthermore, we will optimize the software for robustness, usability, and efficiency. The effort will conclude with a demonstration of the algorithm on standard computing hardware. BENEFIT: The ADS team"s proposed solution is expected to provide photometric calibrations of 10% or better using in-frame techniques with no a priori calibration collections, even for non-photometric sky collection nights (such as nights with dynamic photometric properties, e.g. clouds, water vapor extinction, light pollution, etc.). Since the approach works for a wide range of sensor FOVs and signal-to-noise ratios and requires no special hardware, the approach should be easily applicable to a wide range of currently operational optical SSA sensors, ranging from Raven-class telescopes to SST, and even SBSS. The approach can be shown to be beneficial even for clear filtered sensors.

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