Air force 12. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions
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Military Application: Multiple intelligence, surveillance and reconnaisance assets currently used and in development will benefit from improved geo-location accuracy and/or lower costs required to achieve needed accuracy. Commercial Application: Law enforcement, border patrol, and other civilian tasks requiring aerial video assets will also benefit from improved geo-location accuracy.
1. F. Mirzaei and S. Roumeliotis, “A Kalman Filter-based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation,” IEEE Transactions on Robotics, v. 24(5), October 2008. 2. E. Andersen and C. Taylor, “Improving MAV Pose Estimation Using Visual Information,” in Proceedings, IEEE International Conference on Intelligent Robots and Systems, San Diego, CA, Oct-Nov, 2007. 3. H. Durrant-Whyte and T. Bailey, "Simultaneous localisation and mapping (SLAM): Part I the essential algorithms," Robotics and Automation Magazine, 2006. KEYWORDS: geo-registration, accuracy, data fusion AF121-140 TITLE: Multi-Sensor Data Compression TECHNOLOGY AREAS: Sensors Technology related to this topic is restricted under the International Traffic in Arms Regulation (ITAR) (DFARS 252.204-7009). As such, export-controlled data restrictions apply. Offerors must disclose any proposed use of foreign citizens, including country of origin, type of visa/work permit held, and the Statement of Work (SOW) tasks to be performed. In addition, this acquisition involves technology with military or space application. Therefore, only U.S. contractors registered and certified with the Defense Logistics Services Center (DLSC), Federal Center, Battle Creek MI 49017-3084, (800) 352-3572, are eligible for award. If selected, the firm must submit a copy of an approved DD Form 2345, Militarily Critical Technical Data Agreement. OBJECTIVE: Develop, build and demonstrate standard compression hardware/software for the MQ-1 ACES HY program. Facilitate timely use of airborne Hyperspectral (HSI) sensor data by tactical users and analysts. Support compression extendibility to other sensors. DESCRIPTION: Compression approaches applied to airborne data reduce required data bandwidth requirements while preserving features required for exploitation in operationally significant timelines. Sensors such as electro-optical, infra-red (IR), full motion video, and synthetic aperture radar (SAR) use data compression techniques approved by Department of Defense (DoD) to meet communication limitations, however DoD has not yet developed and/or approved a standardized means of compressing/decompressing HSI data. The Airborne Cross Cuing Exploitation Systems – Hyperspectral (ACES HY) is the Air Force’s first operational airborne HSI sensor due to fly on DoD Remotely Piloted Aircraft (RPA) in 2012. The Air Force and DoD have been experimenting with airborne HSI sensors for the last twenty years as a means to recognize targets based upon their unique spectral signatures. However, HSI sensors are high-data output sensors that are capable of quickly overwhelming the capacity of current air to ground communications links. ACES-HY partially solves this problem through on-board processing and reporting on a limited set of spectral signatures and recording all data for later analysis post-mission. A key objective of the program is to compress HSI data and to pass it real-time over existing communications links to tactical and theater users and imagery analysts. The goal is to achieve the desired sensor data bit rate without compromising the data quality required for tactical analysis using current applications. Decompression is to be done concurrently without introducing unacceptable latency into the defined imagery processing timeline. In addition, the Air Force is looking to develop a standards-based family of compression methods for other existing airborne sensors, and those being added to the inventory over the next ten years. Data compression is the science of finding efficient representations for digital data in order to reduce: • Bandwidth and/or the time required for their transfer across communication channels • Memory required for their storage • Effective data access time when reading from storage devices
Military Application: Military applications include using these compression capabilities in support of real-time operations on-board all DoD platforms carrying spectral sensors and for reduced data storage requirements in exploitation ground stations. Commercial Application: Commercial applications include using this compression capability to reduce storage requirements for air and space derived hyperspectral and multispectral data of agricultural crops.
1. A. Singh, "Digital change detection techniques using remotely-sensed data", International Journal of Remote Sensing, Vol. 10 (6), 1989, pp. 989-1003. 2. R. Radke, et. al., "Image change detection algorithms: A systematic survey", IEEE Trans. on Image Processing, Vol. 14 (3), 2005, pp. 294-307. 3. A. Schaum and A. Stocker, "Hyperspectral change detection and supervised matched filtering based on covariance equalization", Proc. SPIE, Vol. 5425, 2004, pp. 77-90. 4. Schaum, et. al., "Hyperspectral change detection in high clutter using elliptically contoured distributions", Proc. SPIE, Vol. 6565, 2007, pp. 656515-1 - 656515-12. 5. J. Meola, et. al., "A Model-based Approach to Hyperspectral Change Detection", Proc. SPIE, Vol. 7695, 2010, pp. 76951G-1 - 76951G-12. KEYWORDS: Hyperspectral, HSI, Multispectral, MSI, compression, data link, Change Detection, ACES HY, RPA, NITFS, IMINT AF121-142 TITLE: Unified Move Stop Move Combat Identification TECHNOLOGY AREAS: Sensors Technology related to this topic is restricted under the International Traffic in Arms Regulation (ITAR) (DFARS 252.204-7009). As such, export-controlled data restrictions apply. Offerors must disclose any proposed use of foreign citizens, including country of origin, type of visa/work permit held, and the Statement of Work (SOW) tasks to be performed. In addition, this acquisition involves technology with military or space application. Therefore, only U.S. contractors registered and certified with the Defense Logistics Services Center (DLSC), Federal Center, Battle Creek MI 49017-3084, (800) 352-3572, are eligible for award. If selected, the firm must submit a copy of an approved DD Form 2345, Militarily Critical Technical Data Agreement. OBJECTIVE: Develop a radio frequency (RF)-based combat identification system capable of maintaining target identification (ID) through move-stop-move scenarios. DESCRIPTION: Tracking and ID of high value targets (HVT) is critical to counter asymmetric threats. This capability is needed across a wide range of weather conditions, making radar-based solutions preferred. Significant research has been performed individually on the topics of moving-target and stationary-target ID. While there has been success in each individual endeavor, missing is the work that unifies these two fields. These two fields have remained independent as moving-target ID typically employs the use of ultra high-range resolution (UHRR) profiles while stationary-target ID uses synthetic aperture radar (SAR) images. A moving only or stationary only target ID system is insufficient as HVTs are equally likely to occur in either state. Thus the next step for HVT Combat Identification (CID) is the development of a system that can maintain track and ID through typical HVT maneuvers. Such a capability could be achieved by combining high-range resolution (HRR) and SAR imaging into a single classification system. One design approach is to leverage existing feature-aided tracking (FAT) technology. The typical inputs to a FAT system are UHRR profiles. Thus SAR data would first have to be reduced into range profiles. While reducing the dimensionality of SAR data to 1D would likely result in the reduction of information, there are several potential benefits to this approach. First, the developed classifiers associated with FAT systems could be leveraged. Second, the primary weakness of FAT systems is their inability to classify stationary targets. Inclusion of ultra high-range resolution (UHRR) profiles derived from SAR maps of stationary targets would provide a potential solution to this current limitation. Third, this approach will greatly enhance the ability to fuse classifier discriminates between moving and stationary target states. PHASE I: Identify the appropriate feature extraction and classification techniques required for a CID system of HVTs in both moving and stationary states. PHASE II: Develop and demonstrate an automated Move-Stop-Move CID system under realistic scenarios. Deliverables include an analysis of system performance for multiple targets and scenarios, utilizing standard CID performance metrics. PHASE III DUAL USE COMMERCIALIZATION: Military Application: This improved method is directly applicable to ongoing programs supporting military aircraft and all other weapons platforms requiring a moving target ATC/R capability. Commercial Application: Commercialization of this approach is applicable to multiple problems currently of interest for public safety, border surveillance, and homeland security.
1. SPIE proceedings on Algorithms for Synthetic Aperture Radar Imagery V, vol. 3370, (Orlando, FL), pp. 73-84, April 1998. 2. Schumacher, R., Schiller, J. , “Non-cooperative target identification of battlefield targets - classification results based on SAR images”, Radar Conference, 2005 IEEE International, pp. 167 – 172, 9-12 May 2005. 3. Kahler, B., Blasch, E., “Robust multi-look HRR ATR investigation through decision-level fusion evaluation”, 2008 11th International Conference on Information Fusion, pp. 1-8, June 30-July 3 2008. 4. R. Williams, J. Westerkamp, D. Gross, and A. Palomino, "Automatic Target Recognition of Time Critical Moving Targets Using ID High Range Resolution (HRR) Radar", IEEE AES Systems Magazine, April 2000. KEYWORDS: sensors, automated target recognition, high range resolution, synthetic aperture radar, combat identification, move-stop-move, ATR, HRR, SAR, CID, HVT AF121-143 TITLE: Inverse Synthetic Aperture Radar (ISAR) For Terrestrial Targets TECHNOLOGY AREAS: Sensors Technology related to this topic is restricted under the International Traffic in Arms Regulation (ITAR) (DFARS 252.204-7009). As such, export-controlled data restrictions apply. Offerors must disclose any proposed use of foreign citizens, including country of origin, type of visa/work permit held, and the Statement of Work (SOW) tasks to be performed. In addition, this acquisition involves technology with military or space application. Therefore, only U.S. contractors registered and certified with the Defense Logistics Services Center (DLSC), Federal Center, Battle Creek MI 49017-3084, (800) 352-3572, are eligible for award. If selected, the firm must submit a copy of an approved DD Form 2345, Militarily Critical Technical Data Agreement. OBJECTIVE: Inverse Synthetic (ISAR) mode to provide enhanced resolution for selected moving targets from a WAS platform for purpose of (Non-Cooperative Target Identification (NCTI); support time critical target detection, tracking, and characterization, to provide added benefit to the warfighter. DESCRIPTION: Inverse Synthetic Aperture Radar (ISAR) uses Doppler frequencies introduced by target non-linear motion to provide enhanced cross-range resolution. ISAR mode can be used to image vehicles as they move through a curve. Moving targets which are defocused in normal SAR imagery can now be imaged. ISAR imagery is formed using relatively short dwells which provides improved Automatic Target Recognition (ATR) capabilities without a long interruption of the Wide Area Surveillance (WAS) function. SBIR will investigate algorithms developed for earlier applications (Navy’s approach on Hairy Buffalo, MITRE’s Ground Moving Target Detection and Imaging approach, etc), and will recommend and develop algorithm suitable for WAS application. Algorithm ( Back projection, etc) will consider approaches for waveforms employing the stepped frequency approach. The study will address waveform issues such as integration time and resolution requirements, Signal-to-Noise Ratio (SNR) requirement, and motion compensation approaches, etc. ISAR supports moving time critical target (TCT) detection, tracking, and characterization and provides added benefit to the warfighter. In addition, SBIR will investigate using ISAR to extract features for target classification algorithms and feature level fusion. Current ISAR and ATR challenges include 1) using radars with narrow instantaneous bandwidths, and 2) estimating target motion to the fidelity required for generating useful ISAR imagery. 3) Choosing target features that provide robust target Identification (ID) 1) Hardware issues often limit airborne radars to narrow instantaneous bandwidths. The resulting range resolution provided by these narrow bandwidth waveforms may not be adequate for effective ATR. One approach to overcome these limitations is to make use of stepped-frequency waveforms. In this approach, multiple narrow-band waveforms are transmitted, each covering a different band. A wide bandwidth result is then synthesized by correctly combining the multiple received signals. Correct signal combination must account for both the clutter and the moving target, as well as any radar hardware practicalities. 2) Air-to-ground ISAR, in its simplest form, exploits the radar signal variations as the target rotates in relation to the radar sensor. The complexities of real-world ground-vehicle motion and scattering can make the generation of “quality” ISAR images challenging. Ultimately, the metric for determining the quality of the ISAR results is whether or not the resulting features provide value for some form of target ID function. 3) To be useful, the resulting target ID function, based on ISAR features, must be robust to the expected variations in target geometry as the target is observed at different times and locations. PHASE I: Develop modeling, simulation and analysis capability to demonstrate ISAR algorithm for air-to-ground surveillance applications. Algorithm will consider approaches for waveforms employing the stepped frequency approach and realistic target and platform motion models. Investigate methods to extract features from ISAR for use in classification algorithms. At end of Phase I effort, demonstrate working ISAR capability, and discuss detailed Phase II plan to develop an NCTI capability based on ISAR features. PHASE II: Develop and demonstrate an effective NCTI capability based on ISAR features. By end of Phase II effort, capability must be demonstrated with actual radar data (not simulated). PHASE III DUAL USE COMMERCIALIZATION: Military Application: Developed technologies are highly applicable for integration into current/future airborne surveillance systems. Commercial Application: Technology is applicable for commercial imaging systems.
1. Jakowatz, Charles V. JR., et al,"Spotlight Mode Synthetic Aperture Radar: A Signal Processing Approach" Sandia National Laboratories, Albuquerque, New Mexico,1996, Kluwer Academic Publishers Group. 2. John C Curlander, Robert N. McDonough, "Synthetic Aperture Radar Systems and Signal Processing" 1991 John Wiley & Sons Inc. 3. Walter G. Carrara, Ron S. Goodman, Ronald M Majewski, "Spotlight Synthetic Aperture Radar" 1995 Artech House, Inc. KEYWORDS: Sensors, SAR, & ISAR AF121-144 TITLE: Wind Turbine Clutter Mitigation for Terminal Air Traffic Control (ATC) Radars TECHNOLOGY AREAS: Sensors OBJECTIVE: Devise a methodology to mitigate wind turbine clutter interference for existing ATC radar systems. The proposed solutions-based concept should attempt to minimize modification of the existing ATC radar system hardware/software. DESCRIPTION: ATC radar systems detect and track aircraft in the vicinity of homeland airspace. These radars include Air Surveillance Radars (ASRs) and Air Route Surveillance Radars (ARSRs) supporting surveillance missions in the National Airspace (NAS). Their primary mission intent is to provide situational awareness of civilian aircraft, but systems like the ARSR-4 also have the responsibility to detect threat aircraft and report their findings through military and Department of Homeland Security (DHS) channels. Thus, the quality of data from ATC radar systems is critical to every stakeholder. Wind farms are rapidly being installed in the United States and abroad to meet the need for clean, renewable energy. However, wind farms can interfere with ATC radar system performance, mainly through the introduction of non-stationary clutter [1]. For example, most air traffic control radars typically use fan beams that have limited ability to be repositioned above the wind turbines, thereby causing the wind turbines to constantly be within the line-of-sight of the radar system. Wind turbine clutter can prove misleading and has been documented by radar operators to appear as anomalous weather and/or aircraft. Wind turbine induced interference effects also results in the desensitization of the radar, reducing the probability of detection for aircraft, even those at significant altitudes above the wind farm. Suggested mitigation strategies to date have called for modifications to the ATC radar hardware/software to help restore performance to affected systems; unfortunately, many of these suggestions are system specific and have not been proven to significantly increase ATC radar detection performance. The objective of this proposal is to explore alternative, innovative approaches for wind turbine clutter mitigation that can be implemented within existing ATC radar systems architecture; these approaches are focused more on the development of adaptive, knowledge-aided, or other algorithmic solutions-based concepts that will lessen or remove the deleterious effects of clutter effects imposed by wind turbines. The ideal solutions-based concept will enable the ATC radar system to detect and track both civilian and non-cooperative threat aircraft with a high probability of detection, low false alarm rate, at all altitudes and to the ATC radar systems maximum detection range. PHASE I: Propose, develop and validate innovative solutions-based methodology to mitigate wind turbine clutter interference & improve target detection for existing ATC radars; this may be achieved via any combination of modeling, simulation, data analysis, prototyping, or other method suitable to show the benefit of the solutions-based concept. PHASE II: Refine and propose a test methodology to validate the Phase I innovative solutions-based concept for wind turbine clutter interference mitigation and improved target detection (low constant false alarm rate) for existing ATC radar systems. Validation must be performed via integration into a candidate ATC radar system, for real-world verification of operational utility of the proposed mitigation concept. PHASE III DUAL USE COMMERCIALIZATION: Military Application: Mitigation of wind turbine induced clutter effects will permit military ATC radars to provide operationally relevant data for the monitoring and defense of the national airspace by providing full situational awareness of civilian & threat aircraft. Commercial Application: The solution will have immediate application to civilian ATC radars operating in the vicinity of wind farms, improving controller situational awareness and flight safety.
1. JASON REPORT - JSR-08-125, Wind Farms and Radar (MITRE) Jan 2008 (see http://www.fas.org/irp/agency/dod/jason/wind.pdf). 2. SAVANAH RIVER NATIONAL RESEARCH REPORT - SRNS-STI-2010-00014, 15 Jan 2010, "Improved Capabilities for Siting Wind Farms and Mitigating Impacts on Radar Observations", OSTI ID: 973589 (see http://www.osti.gov/bridge/product.biblio.jsp?osti_id=973589). 3. OFFICE OF THE DIRECTOR OF DEFENSE RESEARCH AND ENGINEERING REPORT TO CONGRESS, "The Effect of Windmill Farms on Military Readiness", Accession Number: ADA455993, (see http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA455993). KEYWORDS: radar, clutter, mitigation, wind turbine, ASR, ARSR AF121-145 TITLE: HF Digital Receiver TECHNOLOGY AREAS: Sensors OBJECTIVE: High Frequency (HF) Digital Receiver Design and Development for Next Generation Over the Horizon Radar (OTHR). The digital receiver will provide wideband HF data for multiband processing for radar detection and track performance improvements. DESCRIPTION: Next Generation Over the Horizon Radar (OTHR) has the ability to provide wide area surveillance. The radar operates over the 6 – 28 MHz band. By refracting off the ionosphere, the radar can detect targets at ranges from 1000 to 3000 km. Current generation OTHR use linear arrays with analog receivers. A next generation system is expected to have two dimensional (2D) arrays (narrow beam in both elevation and azimuth), arbitrary waveform generator/power amplifier at every transmit element, and digital receivers at every receive element. This fully digital array will have significant capability, including the ability to function in a Multiple Input Multiple Output (MIMO) radar mode. The objective of this effort is to design and develop a large instantaneous bandwidth receiver for the next generation fully digital beamforming HF radar. The receiver design should include an analog front-end processing, analog-to-digital conversion (ADC), digital down conversion and control interface. Each section will be isolated from each other to minimize spurs and signal interferences. A very high dynamic range is needed for a low noise figure in the signal processing path to provide the radar with the capability to resolve weak targets in the presence of clutter and interference. The analog front end will include preamps, attenuators, band-pass filters, pre-selection filters, ADC driver amplifiers, and anti-aliasing filters. Input Voltage Standing Wave Ratio (VSWR) should be less than 2:1, with a noise figure around 7 dB typically. The pre-selection filters should be programmable. The gain of the analog section shall be sufficient that the noise of the external environment at no attenuation shall dominate the overall receiver noise level. The design will maximize the dynamic range. The analog to digital conversion shall be sampled at a minimum of 100 MHz and synchronized to an external clock source. The design should allow the capture of raw analog-to-digital (A/D) output data, stored in onboard memory buffers, with the ability to send the information to a host computer. Directory: osbp -> sbir -> solicitations -> sbir20121 solicitations -> Navy sbir fy09. 1 Proposal submission instructions solicitations -> Army 16. 3 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Army 14. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Navy small business innovation research program submitting Proposals on Navy Topics solicitations -> Navy small business innovation research program solicitations -> Armament research, development and engineering center solicitations -> Army 17. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Navy 11. 3 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Department of the navy (don) 16. 2 Small Business Innovation Research (sbir) Proposal Submission Instructions introduction sbir20121 -> Air force 12. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions Download 1.28 Mb. Share with your friends:
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