Air force 16. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions

DESCRIPTION: Due to onerous requirements imposed by anti-access/area denial (A2/AD) environments, it is imperative to develop innovative signal and data processing techniques for delivering sophisticated sensing capabilities to the warfighter. Recent advances pertaining to fully-adaptive and distributed radar hold promise. The understanding of the underlying phenomenology and incorporation of radar signal processing techniques for these approaches require further maturation. Modeling and simulation (M&S) plays a critical role for fully-adaptive radar due to the need for real-time generation of representative scenarios from the standpoint of capturing the dynamically varying statistical and spectral properties of the environment.

Prior M&S efforts treat the scattering from distributed radar scenarios via a pair-wise approach which employs a Mono-static Bi-static Equivalence Theorem (MBET) approximation. This approximation is valid only for a small range of bi-static angles and fails to capture the broad gamut of scenarios that arise in this context. A sophisticated MATLAB-based distributed radio frequency (RF) scattering model is currently being developed via a Small Business Technology Transfer (STTR) Program to overcome the limitations of the MBET approximation. A key gap in previously developed radar M&S tools, such as the Air Force's Space Time Adaptive Processing, is the lack of a comprehensive distributed radar scenario generation capability. Therefore, the Air Force seeks an M&S capability for fully adaptive radar from a distributed perspective to include multi-fidelity representations such as the radar range equation, true covariance matrix, mean clutter radar cross section (RCS), clutter amplitude statistics, clutter spectral characteristics, and site specific models.

Additionally, this must permit inclusion of a variety of system and environmental factors such as internal clutter motion, mutual coupling, and antenna errors. The M&S environment must permit experimental validation of signal processing algorithms to include the impact of sensor/platform system effects, allow for incorporation of a priori information, and afford a 3D spatial visualization of scattered clutter, beam patterns, and signal-to-noise ratio (SNR), sensor and target placement, as well as trajectory.

PHASE I: Develop the M&S capability for a scenario generation which lends itself to use in a MATLAB environment for performance of signal processing algorithms for radar. Validation must be carried out using statistical and spectral techniques. Validation will be quantified in terms of statistical goodness of fit test discrepancy indices, mean square error, SNR, detection and false alarm probability.

PHASE II: Continue the validation and maturation for integration of the M&S capability into the Air Force Research Laboratory's M&S tools of choice for this purpose to afford a prediction capability for distributed radar sensing and processing to validate fully adaptive radar concepts and techniques. Validation efforts will be quantified in terms of statistical goodness of fit test discrepancy indices, mean square error, SNR, detection and false alarm probability analysis.

PHASE III DUAL USE APPLICATIONS: Validation of models via experiments in controlled and realistic environments.

REFERENCES:

1. “Modeling and Simulation for Multistatic Coherent MIMO Radar,” K. Bell, C. Baker, J. Johnson, G. Smith, and M. Rangaswamy, IEEE Radar Conference, Ottawa, Canada, April 2013.

2. “Cognitive Fully Adaptive Radar (CoFAR),” Joseph Guerci, Raymond Guerci, Muralidhar Rangaswamy, Jamie Bergin, and Michael Wicks, Proceedings of the IEEE Radar Conference, Cincinnati, OH, May 2014.

3. “The Monostatic-Bistatic Equivalence Theorem and Bistatic Radar Clutter,” J.T. Johnson, C. J. Baker, G.E. Smith, K.L. Bell, and M. Rangaswamy, Proceedings of the European Radar Conference, Rome, Italy, October 10-12, 2014.

4. Fully Adaptive Radar for Target Tracking Part I: Single Target Tracking,” Kristine Bell, Christopher Baker, Graeme Smith, Joel Johnson, and Muralidhar Rangaswamy, Proceedings of the IEEE Radar Conference, Cincinnati, OH, May 2014.

5. “Cognitive Radar,” J. Guerci, CRC Artech House, Norwood, MA, 2010.

KEYWORDS: radar, modeling, simulation, cognitive, adaptive, distributed, visualization

AF161-133

TITLE: Radar Agnostic, Low Computation Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR)

TECHNOLOGY AREA(S): Sensors

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. Gail Nyikon, gail.nyikon@us.af.mil.

OBJECTIVE: Develop a reduced feature SAR ATR technique to classify ground vehicles based on simple features in order to simplify/reduce the overhead and logistics of maintaining SAR ATR capability for multiple platforms against evolving target sets.

DESCRIPTION: Automatic target recognition (ATR) algorithms are required to reduce operator workload because ground surveillance systems are reducing onboard and ground-based analysts. Current algorithms require complex features to operate, leading to large overhead and logistics tails to develop and maintain the target database. A reduced feature set will be developed, along with a feature discovery methodology, to reduce collection requirements while maintaining performance; 60 percent database reduction with no worse than 15 percent reduction in probability of correct classification is required.

Current approaches require each target to be represented within 2 to 5 degrees of the observed sensing depression and aspect angle, and employ both physical and derived features to achieve top performance (typically 90 percent probability of correct identification). Derived features are often specific to both the sensor characteristics collecting the preparatory data and to the mission sensor. Approaches to consider for this effort include: (1) more reliance on physical features that can be estimated more directly from surrogate data and (2) use of features that span classes so that each target need not be represented explicitly.

Additionally, a portable approach for a radar agnostic ATR algorithm is needed to employ with multiple radars with limited code revision. Radar-specific parameters should be encapsulated in a distinct module to provide radar-specific adaptation. This approach enables use of the algorithm and its database for multiple radars.

If successful, this effort will ease collection and training requirements, reduce the need for multiple algorithms, and provide a classification capability for new targets.

PHASE I: Assess the feasibility of using physical features to perform classification of targets in SAR data. Identify the most promising features as well as radar parameters that need to be encapsulated outside of the ATR algorithms to allow use with multiple radars. Provide performance estimates based on feature and sensing options.

PHASE II: Develop reduced feature set SAR target classification techniques and quantify the level of effort needed to sustain and add to the target list. Develop a modular, reduced feature set SAR target classification algorithm and assess performance compared to current approaches.

PHASE III DUAL USE APPLICATIONS: Mature reduced feature set SAR target classification system, including adapting encapsulation module for transition to radar programs of interest. Develop effectiveness measures for transition candidates.

REFERENCES:

1. L.M. Novak, G.J. Owirka, and W.S. Brower. "An Efficient Multi-Target SAR ATR Algorithm." Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on, Volume: 1.

2. Office of the Deputy Assistant Secretary of Defense, Systems Engineering, "Open Systems Architecture," http://www.acq.osd.mil/se/initiatives/init_osa.html.

3. K. E. Dungan and Lee C. Potter. "Classifying Transformation-variant Attributed Point Patterns." Pattern Recognition 43, no. 11 (2010): 3805-3816.

4. Kerry E.Dungan, and Lee C. Potter. "Classifying Vehicles in Wide-angle Radar Using Pyramid Match Hashing." Selected Topics in Signal Processing, IEEE Journal of 5, no. 3 (2011): 577-591.

5. Julie A. Jackson, and Randolph L. Moses, "Synthetic Aperture Radar 3D Feature Extraction for Arbitrary Flight Paths," Aerospace and Electronic Systems, IEEE Transactions on 48, no. 3 (2012): 2065-2084.

6. T Scott Brandes, James R Baxter, and Jonathan Woodworth, "Feature Selection Using Sparse Bayesian Inference," In SPIE Defense+ Security, pp.90930E-90930E, International Society for Optics and Photonics, 2014.

KEYWORDS: SAR, Synthetic Aperture Radar, ATR, Automatic Target Recognition, ISR, Radar Agnostic, OSA, Open Systems Architecture

AF161-134

TITLE: Low Profile Multiband Airborne Satellite Communications (SATCOM) Antenna

TECHNOLOGY AREA(S): Sensors

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. Gail Nyikon, gail.nyikon@us.af.mil.

OBJECTIVE: Develop a low-profile, low-weight, low-cost active electronically steered array for the X/Ku/Ka/Q-band satellite communications for aircraft and Group 5-sized unmanned air vehicles (UAVs).

DESCRIPTION: Many Air Force aircraft currently have capability gaps for transmitting and receiving BLOS data updates during mission execution. Mission data updates could include lower data rate transmissions of Air Tasking Order (ATO) updates or target positions updates or could include higher data rate updates such as imagery intelligence or streaming video.

A low profile, multiband active electronically steered array (AESA) antenna is required to provide BLOS connectivity to both commercial Ku/Ka-band satellites and military X/Ka and Q-band satellites antennas. It must support commercial Ku-band operations at 10.95 to 12.2 GHZ receive and 14.0 to 14.5 GHz transmit; commercial Ka-band operations at 17.7 to 20.2 receive and 27.0 to 30 GHz transmit. Must support military satellite X-band operations at 7.25 to 7.75 GHz receive and 7.9 to 8.4 GHz transmit; Ka-band operations at 20.2 to 21.2 GHz receive and 30 to 31 GHz transmit; and Q-band operations at 43 to 45 GHz transmit.

Antenna should support both right hand circular polarization (RCHP) and left hand circular polarization (LCHP) and provide a scanning coverage of continuous azimuth with an elevation threshold of 20 to 90 degrees threshold and -20 to 95 degrees objective. Equivilent Isotropic Radiated Power (EIRP) should be on the order of 45 to 50 dBw.

Since many Air Force aircraft will require BLOS communications, even when in contested and denied environments, the contractor should emphasize compatibility with military X/Ka/Q-band satellites that provide protected, jam resistant communications. In particular, interoperability with advanced EHF (AEHF) and wideband global satellite (WGS) military satellite communications is required. The antenna design must meet environmental requirements for operations at altitudes up to 50,000 feet and be capable of operating in temperatures ranging from -54 to 71 degrees C.

Technical challenges in this technology include size and weight constraints, conformal profiling to the platform, co-site interference, and operations in jammed environments.

The contractor should also focus on antenna technologies that reduce size, weight, and cost.

Commercial applications should be considered in addition to military utility.

PHASE I: Propose novel concepts for antenna design and evaluate performance characteristics through models and/or simulation. Perform initial studies to trade size, weight, and cost for technical performance.

PHASE II: Leverage either existing or newly designed technologies/products to build and test prototype low profile, multiband AESA antenna.

PHASE III DUAL USE APPLICATIONS: Low-profile, low-weight multiband AESA SATCOM antennas can support low-to-medium data rate for command and control (C2) applications for many Air Force missions on different aircraft. The technology could also provide higher data rate BLOS communications in support of ISR missions.

REFERENCES:

1. Contribution of Meta-Materials in Multiple Band and Wideband Tile Phased Arrays Christian Renard, THALES Airborne Systems (TSA), France, http://www.array2013.org/techprogdw.html.

2. Low-Cost Phased Array Antenna for Satellite Communications on Mobile Earth Stations J. B. L. Rao, Sotera Defense Solutions, Inc. USA, R. Mital, D. P. Patel, M. G. Parent, and G. C. Tavik, U.S. Naval Research Lab, USA, http://www.array2013.org/techprogdw.html.

3. B-2 New AESA Communications Concept Demonstrated with AEHF Satellite, 8 Jul 2013, http://www.deagel.com/news/B-2-New-AESA-Communications-Concept-Demonstrated-with-AEHF-Satellite_n000011727.aspx.

KEYWORDS: communications, antennas, SATCOM, multi-band

AF161-135

TITLE: Lightweight Infrared Search and Track Systems

TECHNOLOGY AREA(S): Sensors

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. Gail Nyikon, gail.nyikon@us.af.mil.

OBJECTIVE: Develop a lightweight infrared (IR) search and track (IRST) system for applications to air-launched, air-recoverable airborne platforms.

DESCRIPTION: The increasing proliferation of radio-frequency (RF) denial techniques will require air platforms to operate in an anti-access/Area-denial (A2AD) environment threatening U.S. air superiority. IRST systems offer a passive alternative to active radar systems for detecting and tracking airborne threats. IRST systems have demonstrated long range detection and tracking of air targets. IRST systems can also prove valuable in applications with homeland security.

Although highly capable, pod-mounted, gimbaled IRST systems have several distinct disadvantages which limit the platforms on which they can be deployed. The narrow field of view and wide search areas requires short integration times to maintain low system scan periods. Wide area surveillance necessitates the use of large optical apertures and with it large gimbals to meet the needed performance. This has significant size, weight, and power (SWaP) limitations and aircraft integration implications.

Some of the challenges that should be addressed are detecting and tracking targets with wide field-of-view (WFOV) staring infrared sensors capable of line-of-sight stabilization over the kinematic envelope of a representative unmanned aerial vehicle (UAV). The minimum WFOV requirements are +/- 35 degrees in azimuth and +5/-15 degrees in elevation. Consideration should be given to appropriate IR band selection, line-of-sight stabilization versus sensor instantaneous FOV, performance when looking into clutter, and how available technology can be used to reduce SWaP while maximizing system performance. The host UAV platform is envisioned to be capable of operating from 30 to 35 kft altitude with a flight radius of 300 nmi and a loiter time of 2 hours and have a 30 lb., 400 Watt payload allocation. This solicitation requests a tradeoff, design, construction, and delivery of a prototype lightweight IRST system.

PHASE I: Perform a trade study and develop a concept design that minimizes SWaP using new focal plane array, innovative optical element, and image stabilization technologies for miniaturization of a WFOV staring IRST system.

PHASE II: Refine Phase I design and fabricate a prototype breadboard IRST for evaluation and performance testing from a fixed ground site.

PHASE III DUAL USE APPLICATIONS: Validation of the IRST design through experimentation.

REFERENCES:

1. Koretsky, G.M., Nicoll, J.F., and Taylor, M.S, “A Tutorial on Electro-Optical/Infrared (EO/IR) Theory and Systems,” Institute for Defense Analysis, January 2013.

2. Hintz, R.T, Allen, J, Chen, M, Price, T, and Goetz, G, “UAV Infrared Search and Track (IRST)/Eyesafe Laser Range Finder (ELA) System,” NAVAIR Weapons Division China Lake, CA, October 2005.

3. Infrared Search and Track, Wikipedia.

KEYWORDS: infrared, search, track, unmanned air vehicle, UAV

AF161-136

TITLE: Deployable Lightweight Upper Air Sensing System

TECHNOLOGY AREA(S): Sensors

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. Gail Nyikon, gail.nyikon@us.af.mil.

OBJECTIVE: Develop a lightweight, deployable sensor system to gather meteorological data for the lowest 15,000 feet of the atmosphere.

DESCRIPTION: This topic is looking to develop a lightweight, deployable sensor technology that can sample the atmosphere up to 15,000 feet (objective). Environmental measurements of the atmosphere in many parts of the world are sparse, degraded or non-existent. This hampers the DoD's ability to provide accurate current data in support of battlespace awareness or to seed weather forecasting models for accurate forecasts in those regions. The research developed under this topic will explore the art of the possible using cutting-edge sensor technology and demonstrate a working prototype delivering this capability.

The current upper air sensor system is the Vaisala DigiCora Sounding System MW31. This is a helium balloon-based solution which presents logistical challenges in deployed environments. The hardware for the MW31 is bulky; making it unsuitable for tactical deployments, as lugging around helium canisters is not practical in most deployed situations. The Air Force needs a replacement sensor system that is easy to ship and able to be configured and deployed quickly.

The Air Force is interested in exploring all relevant sensor options that provide the necessary data, including ground based upper air sensor systems or commodity remotely piloted aircraft (RPA) with lightweight sensor systems. The main focus is to develop a new sensor suite that does not require the use of a balloon deployment mechanism or helium. The new system will be used as part of an integrated theater sensing strategy to support service specific and missions and joint operations.

As a replacement for the MW31, this upper air sensing system will need to, at a minimum, sense/derive and record the following atmospheric parameters from the surface up to 15,000 feet:

Additionally, the system must measure parameters, process, store, and disseminate all required information in standard formats for local use and make the collected data available to command and control centers, operational units, and weather forecasting centers within minutes.

The system should be configurable to operate in one of three modes: stand-alone (attended but no network connection), locally (attended and on the network), or remotely (unattended but using a remote interface to control the system). Ideally, the final system would have a small footprint, less than one-cubic foot in size, weigh less than 10 pounds, and be both reconfigurable and reusable while in theater.

The system will need to include its own power source and any transportation packaging associated with the system would need to be reusable. Trade-offs will be considered between system size, power requirements, time on station, turn-around time, precision, and covertness. Logistical concerns and system supportability while deployed shall also be considered. Systems based on technical approaches that are easy to support while deployed are desired.

PHASE I: Conduct an analysis on available and near-term technologies to identify possible solutions. Develop one or more designs that explore the trade-off spaces described in the topic description in order to fulfill the data collection and data dissemination requirements. Additionally, describe the procedures that will be used for deployment, data collection, system reuse, and maintenance.

PHASE II: Develop a prototype based upon the Phase I design and Air Force refinement of requirements and continuity of operations. Identify any gaps between the prototype solution and the Air Force requirements and develop a path forward for addressing the gaps. The Phase II system must be able to address any information assurance concerns such that the prototype can achieve an interim authority to test on the Air Force network.