Air force 14. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions
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| Some typical artifacts and desired types of data (undesirable or mission) are listed below:
1. Reflections from ground (undesirable) 2. Reflections from the internal parts of the system (undesirable) 3. Noisy detectors (many types of noise) (undesirable) 4. High temperature detectors (undesirable) 5. Thermal distortion (undesirable) 6. Poor focus (undesirable) 7. Blinking detectors (undesirable) 8. Slow-moving objects – Tactical Parameter Estimates (TPE) such as trajectories and state vectors (mission) 9. Fast-moving objects – TPEs (mission) 10. Static sources (mission) a. Environmental b. Other 11. Transients (mission) 12. Geolocation – without stars (mission) 13. Closely-spaced objects (mission) 14. Cloud edges (mission and non-mission) 15. Technical parameter estimation (mission) The small business doing this work must be certified for SECRET work. This project is restricted to no foreign release. PHASE I: Develop real-time algorithms and evaluate them against supplied data to establish feasibility and payoff. Identify requirements for, and limits of, sensor technology on expected detection performance: framerate, wavebands, pointing stability, charge capacity, etc. PHASE II: Code algorithms and test them against supplied data. Identify and test variations for framerate, wavebands, pointing stability changes as given in provided datasets. Propose CONOPs variations to improve performance. PHASE III DUAL USE APPLICATIONS: Military: Space-based surveillance programs by DoD programs of record and new approaches for OPIR replenishment and modernization. Commercial: These IR specific algorithms are relevant to space-based weather information services, and may even enable new environmental monitoring capabilities. REFERENCES: 1. A library of unclassified simulated data will be available for algorithm testing in Phase I. 2. A classified library of data will be available for algorithm testing against truth in Phase II. 3. H.l. Van Trees, "Detection, Estimation and Modulation Theory, Part I," Wiley-Interscience, 2001. 4. Levy, B.C., "Principles of Signal Detection and Parameter Estimation," Springer, New York, NY. 5. Sah, S. et al, "GPU accelerated real time rotation, scale and translation invariant image registration method," in proceeding of: International Conference on Image Analysis and Recognition, Volume: Image Analysis and Recognition Lecture Notes in Computer Science Volume 7324, 2012, pp 224-233. DOI:10.1007/978-3-642-31295-3_27. 6. Miaoqing Huang; Kilic, Ozlem, "Reaping the Processing Potential of FPGA on Double-Precision Floating-Point Operations: An Eigenvalue Solver Case Study," Field-Programmable Custom Computing Machines (FCCM), 2010 18th IEEE Annual International Symposium on , vol., no., pp.95,102, 2-4 May 2010. doi: 10.1109/FCCM.2010.23. KEYWORDS: Infrared data, data processing, algorithm, electro-optical, space sensor AF141-106 TITLE: Innovative Technologies for Operationally Responsive Space KEY TECHNOLOGY AREA(S): Space Platforms OBJECTIVE: Develop technologies for spacecraft/space lift that provide game-changing "responsiveness" (ability to implement the same missions much faster and lower cost with adequate reliability and comparable capability thresholds/environmental constraints). DESCRIPTION: The DoD is actively pursuing the capability to create and field a space mission within days (even hours) of a battlefield commander's notification. Achieving this capability for real-world missions is essential to the disruptive vision of the Operationally Responsive Space (ORS) Office. We believe implementing "big" missions to be done on "small" satellites is a game-changing approach for responsiveness, since smaller platforms (i.e., spacecraft) are easier to store, integrate, and launch. For this, technologies are the key. Can we find ways to more effectively miniaturize satellite sub-systems, components, and spacelift subsystems and components without compromising capability? Can we reduce the mass fraction of the spacecraft vehicle, so that more of it can be allocated to payloads? How can we pack more capable payloads into smaller containers, perhaps to be deployed once in orbit? Can we commoditize/modularize these approaches, so that they can easily be duplicated or commoditized to support multiple mission needs? Can we find similar improvements to space lift components to improve mass margin and launch capability? We seek innovative concepts in miniaturized systems such as: compact, reconfigurable bus and payload components; modular/open/standardized payload configurations; high-performance, compact sensors; flexible operations schemes; space lift components and rapid integration; and improved on-ground and on-orbit calibration/check-out techniques. Can we break the perennial cycle of building custom hardware, software, and interfaces that leads to growing expense, schedule, and complexity? The ORS Office will also consider novel modification endeavors to existing commercial-off-the-shelf (COTS) components to meet the needs of this solicitation. These technologies cover a broad range of the technical spectrum. The technical objective is to reduce the size of current satellites and space lift to one-half of their current mass and volume without loss of capability. More specifically, this effort involves development of innovative advances in structures, power systems, microelectronics, wiring systems, propulsion, attitude knowledge and control, space lift, and sensor systems that maintain capability while reducing volume and mass for an ORS-class mission. These systems should use standardized interfaces and integration schemes that make the launch of the satellite more responsive and operable for missions and launch campaigns associated with the ORS-class missions. Contractors are strongly encouraged to work closely with the ORS Office and its contractors, if necessary, to ensure technical efforts are consistent with overall responsive satellite and space lift development goals. Proposed concepts should strive for designs that can eventually achieve a component fabrication and system integration time of a few days for the widest range of relevant satellite and space lift capability. In the near term, these techniques should cut integration time and component/mission costs in half. PHASE I: Work out a convincing feasibility proof for the proposed concepts, ideally backed by simulation models, designs, fabrication, and other demonstrations. Establish the realism of these concepts and provide strong evidence that it will be possible to make meaningful progress in a Phase II program to achieve a "gettable" product, as opposed to a "fragment" needing other fragments to be useful. PHASE II: Design, fabricate, and test a prototype-level concept that has functional specifications, interfaces, and protocols consistent with the ORS Office’s mission configurations. Ensure that the concept can work in the harsh environments of launch and space (e.g., shock, vibration, thermal cycling, radiation, spacecraft charging, etc.). Establish an integration strategy that will support the assembly and checkout of a small satellite within a few days based on the proposed concept. PHASE III DUAL USE APPLICATIONS: Military: The ORS Office will have urgent use for this kind of technology. Commercial: The Commercial space industry will also have the ability to exploit such compact, capable systems for rapid deployment of communications and other commercial space missions. REFERENCES: 1. Rapid Spacecraft Development: Results and Lessons Learned by William A. Watson, Rapid Spacecraft Development Office, GSFC 2002 IEEE Aerospace Conference, Big Sky, Montana. 2. Taking Advantage of Excess Spacelift Capacity—A vision for the Future, S. Buckley, Annual AIAA/Utah State University Conference on Small Satellites,” Utah State University, Logan, Utah, 13 August 2008. 3. Microsats for On-orbit Support Missions, DoE Report, Dr. A. G. Ledebuhr, UCRL-JC-142900. 4. Astrobiology Small Payloads, NASA/ARC Workshop Report, B. Yost, NASA/CP—2007–214565. KEYWORDS: satellite bus, modular satellite, standardized satellite interfaces, spacecraft, payload, satellite, responsive space, responsive bus, space lift AF141-107 TITLE: Improved AFSCN FCT Simulator KEY TECHNOLOGY AREA(S): Space Platforms The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the solicitation and within the AF Component-specific instructions. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. Please direct questions to the AF SBIR/STTR Contracting Officer, Ms. Kristina Croake, kristina.croake@us.af.mil. OBJECTIVE: Develop a low-cost hardware/software satellite testing system which can provide the functionality of the TSTR electronics and the RBC TSTR core electronics. This system will be used to demonstrate satellite system compatibility with the AFSCN. DESCRIPTION: The Transportable Space Test and Evaluation Resource (TSTR) system provides deployable support for factory and launch site satellite compatibility tests. The deployable TSTR system, operated by the Mobile Range Flight (MRF) at the Space and Missile Systems Center (SMC) Space Development and Test Directorate, is used to accomplish satellite Factory Compatibility Tests (FCTs) with the Air Force Satellite Control Network (AFSCN) prior to satellite launches. Deploying and operating the TSTR for testing satellites for AFSCN compatibility has become painfully unaffordable for many satellite programs. As budgets are reduced, satellite programs are seeking lower-cost testing alternatives.
PHASE I: Perform analysis of AFSCN compatibility testing requirements to determine the optimal low-cost hardware and software capabilities necessary to perform ground system functional testing that verifies compatibility between Satellite Operation Centers (SOCs) via a simulated AFSCN Automated Remote Tracking Station (ARTS) and a RBC node represented by the TSTR and RBC TSTR systems. PHASE II: Design and develop a prototype system that has the necessary hardware components and AFSCN simulator software to perform the required testing activities. Conduct a demonstration using both the prototype simulator suite and TSTR systems to successfully execute factory satellite-to-AFSCN compatibility test functions. PHASE III DUAL USE APPLICATIONS: This system will reduce satellite development risk by ensuring AFSCN compatibility during AI&T, reducing the number of issues discovered during pre-launch checkout. Developing a largely software-based TSTR simulator will provide a much lower cost and robust test capability. REFERENCES: 1. AFSCN Support for Operational Responsive Space (ORS), http://www.responsivespace.com/Papers/RS6/SESSIONS/SESSION%20I/1006_HODGES/1006P.pdf. KEYWORDS: AFSCN Compatibility, Verification Test, Factory Compatibility Test, FCT, TSTR AF141-108 TITLE: Forecasting of Solar Eruptions using Statistical Mechanics, Ensemble, and Bayesian Forecasting Methods
OBJECTIVE: Modify, develop and apply automated, machine-based learning systems and algorithms to assimilate, classify and identify solar eruptive activity and use the derived meta-data signals to predict and forecast solar eruptions. DESCRIPTION: Solar eruptions (solar flares and coronal mass ejections) cause disruptions to communication and navigation in DOD and civilian systems. This SBIR seek solutions to forecasting solar eruptions using data modeling, from the perspectives of statistical mechanics, complexity, ensemble forecasting and Bayesian forecasting methods. Current consistent solar activity forecasts are issued once a day (24-hours), and require "human-in- the-loop". This SBIR seeks efforts at automated data-driven (no human in the loop) forecasts of 6-24 hour advance, which will be an improvement over current forecasts. It will require probabilistic predictions of future solar activity levels, greater than 50% confidence levels. Consistent and reliable solar imaging data is openly available from many sources. They include NASA’s Solar Dynamics Observatory (SDO) and its Atmospheric Imaging Assembly (AIA; ~ 12 layers) and Heliospheric Magnetic Imager (HMI ~ 3 layers) instrument, and other observatories/instruments that produce continuous high cadence solar imaging data. Hence it is now feasible to research and develop data driven models for supporting near-real-time advanced forecasting of solar activity. Such models can include auto-regressive forecasting models, machine learning, statistical physics data models (such as fluctuation dissipation theorem), complexity analysis, Bayesian learning systems, support vector machines, neural networks, multivariate discriminant analysis and genetic algorithms. Such algorithms have been applied to the forecasting of terrestrial weather. A key objective of this work will the development of a verifiable set of test algorithms on independent test and training data sets based on a variety of eruptive and non-eruptive active region measurements. It will require algorithms to (a) automatically (no human in the loop) ingest solar imaging and non-imaging data from open sources to characterize current state of solar activity from various solar regions; (b) demonstrating meta-data relevant to characteristics of eruptive solar activity prior to eruptions' (c) developing Bayesian, statistical and/or machine-learning models specifically ingesting the relevant meta-data developed in item b to show continuous eruptive probabilities for application into 6-hour, 12-hour and 24-hour predictions; and (d) demonstrate the use of the data in real-time probabilistic prediction by using training and test cases. The references below point to potential algorithms that have been attempted. Adapting Bayseian and related statistical algorithms tested and used in domains such as terrestrial numerical weather forecasting, Internet data mining and prediction tools, decision theory, or other statistical applications should be considered. AFRL/RV plays a key role in understanding and predicting solar drivers of space weather, whose signals show significant impact on DoD communications and navigation systems and on its space assets. Providing impending/imminent status and an advance warning of the solar electromagnetic, particle and mass radiation on near-Earth and terrestrial systems, by a rapid ingestion and analysis of solar data, is vital to this process. PHASE I: Develop & apply machine based learning systems to data-mine and rapidly extract meta-data specifying eruptive signals to classify eruptive solar activity. Develop verifiable forecast algorithms (no human in loop), using multi-spectral and near-simultaneous imaging data from SDO and other observatories. Demonstrate applications of algorithm robustness using limited training and test data. PHASE II: Refine concept from Phase I and demonstrate ensemble forecasting from a variety of data sources and applied on a few thousand independent training and test cases. Apply to probabilistic forecasting of near-real-time data, for short-term (minutes), mid-term (hours < day) to longer-term (days) forecasting. Show results. Demonstrate statistical validation of results. PHASE III DUAL USE APPLICATIONS: Implementation of ensemble forecasting for real-time applications for the DoD and/or other U.S. entities and organizations, such as U.S. Air Force, NOAA and NASA. Commercial Application: Same application for commercial. REFERENCES: 1. Barnes, G., K. D. Leka, E. A. Schumer, and D. J. Della-Rose (2007): Probabilistic forecasting of solar flares from vector magnetogram data. Space Weather, 5, S09002. 2. Bornmann, P. L., and D. Shaw (1994): Flare rates and the MacIntosh active-region classifications. Sol. Phys., 150, 127-146. 3. Falconer, David A., Moore, Ronald L., Barghouty, Abdulnasser F., and Khazanov, Igor (2012): Prior Flaring as a Complement to Free Magnetic Energy for Forecasting Solar Eruptions. The Astrophysical Journal, Volume 757, Issue 1, article id. 32 (2012). 4. Crown, M. Validation of the NOAA Space Weather Prediction Center's solar flare forecasting look-up table and forecaster-issued probabilities. Space Weather: The International Journal of Research and Applications, Volume 10, CiteID S06006. 2012. 5. Norquist, D. C. and Balasubramaniam, K. S. Diagnosis of Solar Flare Probability from Chromosphere Image Sequences. DTIC, http://www.dtic.mil/docs/citations/ADA554688. KEYWORDS: solar flares, data mining, forecasting, Bayesian algorithms, fluctuations dissipation theorem, multivariate discriminant analysis, support vector machines, space weather AF141-109 TITLE: Adaptive antenna structures KEY TECHNOLOGY AREA(S): Space Platforms The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the solicitation and within the AF Component-specific instructions. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. Please direct questions to the AF SBIR/STTR Contracting Officer, Ms. Kristina Croake, kristina.croake@us.af.mil. OBJECTIVE: Develop antenna structure(s) or related items, capable of reducing radio frequency interference (RFI) susceptibility in RF-congested environments by controlling radiated and received emissions. DESCRIPTION: The Air Force Satellite Control Network (AFSCN) finds itself operating in regions of increasingly congested Radio Frequency Interference (RFI). The advent of private and commercial 4G use, ad hoc networks, and increasing usage of adjacent bandwidths by these wireless device networks introduces more traffic into the L/S-bands, and threatens AFSCN stability. The advent of mobile data-enabled devices and mobile market expansion realizes unprecedented growth. Current projections call for a 15 times mobile-traffic increase by 2017 (“Traffic and Market Report June 2012”, Ericsson). These projections will necessitate the adaptation of current AFSCN ground sites to prevent threats of possible site closure, disruptions in AFSCN coverage and service. Adaptive Aperture would enable variable beam width operations that can be dynamically optimized once signal reception has occurred, incorporating at least 10 db edge taper improvements over existing 13 meter antenna. Would mitigate RFI and close-in neighbor's RFI to conduct satellite vehicle (SV) uplink activities via suppression shaping technologies (e.g., active spectral tapering and materials and controls technologies). The proposed solution space should provide enhanced sidelobe suppression up to the order of 10 db for uplinks up to 10kW CW. To minimize cost and impact to current AFSCN sites, proposals should be limited to technologies that can be adapted into current 13-meter antennae (including subreflector, surfaces, legs, etc.), or surrounding external structure(s), such as the radome. As the antenna dish itself, and its related focusing elements and the radome have direct pattern and spectral effects, solutions in the form of structural or materials solutions are notionally feasible and implementable. These could include frequency-selective surfaces (FSS) or novel metamaterial-type surfaces on controllable elements, e.g., radome, sub-reflector modifications are approaches to consider. Constraints such as keeping losses low in the transmission bands and reception bands (maintain baseline efficiencies) while effectively reducing managing side-lobes is to be considered across the SGLS (L-band) and USB (S-band) frequency bands. As this call is not for procurement of new antenna assets per se, it does indicate and opens tradeoff with several technologies and techniques that can modify or add capability via hardware and software to existing AFSCN-fielded assets. Some techniques, such as antenna nulling, for instance, may indicate feedhorn modifications or replacements, or development of active surface focusing shaping in the receive hardware, or both via dichroic structures. Introduction of these technologies have the ability to reduce search and acquisition time to resolve SV orbits during launch, and space vehicle early-orbit ops. This can minimize spatial interference with multiple close-in SV contacts that are also not spectrally diverse. Also provides assured access to SVs in congested environments where those SV spatial and frequency/spectral assignments and external incoming interferences, from both ground and space, compete or are hostile. An optimal capability would dynamically reduce beam width upon satellite vehicle contact and also control and contain spectrum (sidelobe management, dynamic gain, nulling). Enhanced capability to suppress side-lobe and spillover to minimize possibility of external RFI, and also reduce overall RF footprint is desired. Proposal should not address new whole antenna structures, or discrete arraying techniques. Directory: wp-content -> uploads -> 2016 2016 -> 2017 afoCo Landmark Scholarship Program 2016 -> Instructions for the Preparation of Camera-Ready Contributions to the Conference Proceedings 2016 -> Step student Scholarships for Year 10-13 2016 -> The united church of canada 2016 -> Idan raichel biography – May 2016 Brief Producer, keyboardist, Lyricist, composer and Performer Idan Raichel 2016 -> An introduction to centre’s interventions expanding access to justice 2016 -> Sanchar Shakti 2016 -> Unit analysis should help here. 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