Army 17. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions

REFERENCES:

1. Stevanovic, Stefan, Joerger, Mathieu, Khanafseh, Samer, Pervan, Boris, "Atomic Clock Aided Receiver for Improved GPS Signal Tracking in the Presence of Wideband Interference," Proceedings of the 28th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS

2. Preston, Sarah E., Bevly, David M., "CSAC-Aided GPS Multipath Mitigation," Proceedings of the 46th Annual Precise Time and Time Interval Systems and Applications Meeting, Boston, Massachusetts, December 2014, pp. 228-234

3. Chan, F-C., Joerger, M., Khanafseh, S., Pervan, B., Jakubov, O., "Performance Analysis and Experimental Validation of Broadband Interference Mitigation Using an Atomic Clock-Aided GPS Receiver," Proceedings of the 26th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2013), Nashville, TN, September 2013, pp. 1371-1379

KEYWORDS: GPS, Precision Timing, PNT, Kalman Filter, GPS Integration, Clock Integration, Sensor Fusion

TECHNOLOGY AREA(S): Electronics

OBJECTIVE: Develop a Multi-spectral adjunct sensor consisting of either single element detectors or a linear array with a variety of spectral bands in the UV/Visible/Infrared that can be used to aid in detection of aviation threats (Missiles, Hostile Fire, etc.). This sensor will be used as an adjunct to current Missile Warning/Hostile Fire Indication systems for improved capability.

DESCRIPTION: Current State of the Art Threat Warning Systems for platform protection have included imaging detector arrays in the UV and single or two-color IR that detect spectral, spatial, and temporal features of the threat and perform threat identification and classification while operating in cluttered environments. These systems usually use single broadband or 1-2 narrowband sensors, with minimal spectral discrimination capability to address accurate threat classification/identification and emerging threats where signatures are likely to be different. Due to manufacturing techniques needed to develop multispectral, high spatial resolution imaging sensors, it is impractical for the primary sensor to cover additional bands at high resolution and framerate. Multispectral (~ 10 detection bands) and hyperspectral (~ hundreds of detection bands) adjunct sensors are able to improve the current state of the art systems by adding orthogonal and/or complimentary data. Fusing this broader data set will improve declaration performance for existing threats in complex background environments and be more robust in detecting new or unknown threats. A low spatial/high temporal resolution multispectral adjunct sensor will allow for added capability at lower cost while enabling the overall system to be flexible for future algorithm developments as the threat environment evolves.

Our unique application of this concept can take two formats: A single linear array with the appropriate filters and a single optic, or a constellation or ring of 1-n single element detectors with separate optics in the appropriate bands. The data from this sensor will be correlated temporally with imaging threat detection sensors. Resolving the threat with a resolution finer than the field of regard is not required.

Some system-level specifications include:

This topic will address a threat list of descending priority to include: Man-portable Air Defense Systems (MANPADS), Rocket Propelled Grenades (RPGs), Anti-Aircraft Artillery (AAA) and small arms. Sensors detect the propellant signatures associated with these threats. Since the phenomenology features for each wavelength varies, no single detection range can be specified. However the goals of any survivability system is to detect and counter the threat at its max effective range. This adjunct sensor must therefore be sensitive enough to detect threat phenomenology as early in the engagement as possible. The intention of this sensor is not to provide a specific false alarm rate for each wavelength, but to instead select the correct combination of wavelengths that allows threat signature fingerprinting, which will improve identification and classification for the primary sensor.

For the purposes of this SBIR, form factor is not a primary concern, as the main deliverable is a brassboard prototype sensor. However, the desired SWaP growth path for this adjunct sensor would be to ultimately integrate it with the fielded primary sensor, either around the sensor as an attachment, or internally integrated. For reference, comparable primary sensor systems are typically 5”x5”x8” per sensor, weighing anywhere from 3.5 to 5lbs. The preliminary SWaP goals are to have the adjunct sensor have design path that supports the 5”x5” dimension of each primary sensor, adding minimal depth, and a maximum weight increase of <2 lb. The main focus of this SBIR is to develop and design the hardware using existing sensor components, and to begin initial design of the processing techniques to take the individual sensor output data and correlate with the primary sensor outputs for a robust solution.

PHASE I: Investigate the ideal spectral bands that will aid in threat identification and classification, reduction in FAR and increase in Pdec for existing Missile Warning Systems. Begin designing an adjunct multi-spectral system prototype. Deliverables include final report detailing design process, Preliminary Design Review and documentation, and supporting data.

PHASE II: Build a brass-board prototype system that will be used for Hardware-in-the-Loop or Field testing for technology demonstration and performance analysis. Also identify areas to explore for a finalized system design and technical/programmatic risks. Deliverables include Critical Design Review and Documentation, Prototype Hardware that will be used in Government Lab and Field Data collections.

PHASE III DUAL USE APPLICATIONS: I2WD will serve as the Transition partner with matching funding to leverage Phase 2 design and further mature the technology, preparing for a technology insertion program for existing programs of record that this technology may enhance. Deliverables include finalized prototype design and Hardware, including Algorithms that integrate with existing Missile warning systems. Additional PM transition partners also identified.

PM transition partners:
•Project Manager Office Aircraft Survivability Equipment (PMO-ASE)
•PEO-Ground Combat Systems
•PM-UAS

REFERENCES:

1. Examples of primary Warning Systems: http://www.northropgrumman.com/MediaResources/MediaKits/SOFIC/Documents/ATW_datasheet.pdf

2. Examples of primary Warning Systems: http://www.baesystems.com/en/product/anaar57-common-missile-warning-system-cmws

3. Example of unique spectral bands: http://www.cis.rit.edu/files/CiszThesis2002.pdf

4. Multispectral references: http://www.ugpti.org/smartse/research/citations/downloads/Tack-Compact_HSI_Imager-2012.pdf

5. Multispectral references: http://spie.org/Publications/Proceedings/Paper/10.1117/12.900971

6. Multispectral references: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1026047

7. General sensor references: https://www.ida.org/idamedia/Corporate/Files/Publications/IDA_Documents/SED/ida-document-d-4642.pdf

KEYWORDS: Threat Warning, Missile Warning, Hostile Fire Indication, Multi-spectral, Multispectral, Hyperspectral, Adjunct, Single Element Array, Sensors, Electro-Optical Infrared

TECHNOLOGY AREA(S): Information Systems

OBJECTIVE: Deployment of an analytic which would recognize repeated actions, interactions, and transactions that an analyst performs on device(s) to display information relevant to the analyst ex. in support of Multi-INT.

DESCRIPTION: The scope of this SBIR is to investigate the deployment of a cloud based analytic which would recognize repeated actions, interactions, and transactions that an analyst performs on a device to ultimately display information relevant to the analyst. This information may be derived from [not be limited to] mission objectives, user roles, sensors, email, and other data feeds. The analytic should be able to capture, analyze, and then display relevant information to the user in a simplified manner. Relevancy may be inferred based on fields such as search queries, location, role, calendar, mission objectives etc. An analyst should also have the capability to perform semantic search based on the underlying analytic.

Commercial analytical capabilities exist [Google Now] which analyze a user’s behavior, coupled with inferences, to display relevant information. These relevancies however generally draw on data banks with a pre-set ontological standard such as email and location. As such these analytics do not expand beyond specified devices [Android; IOS; Windows] where data format and subject may differ. With direct affect to military application, this additional data bank may be sourced from mission objectives, user roles, sensor information, tactical chatrooms, analyst data repositories, and non-standard data types & operating systems.

To address these gaps and opportunities Analytic for Federated Data (ALFRED) should provide for analytical capabilities, where data may be sourced from any number of different data banks. The analytic should recognize repeated actions, interactions, and transactions to facilitate displaying of relevant information. Inference of relevancy should be established though standard and non-standard data sources. The results of this inference may then include: specified alerts to developing situations; event alerts; threat updates; weather alerts; and nearby situational awareness. The analytic should be deployable across different data banks and devices. Additionally a semantic search capability should be embedded, leveraging ALFRED’s analytical capabilities so as to improve search accuracy by understanding of searcher’s intent and context.

PHASE I: Develop a system design the incorporates an analytic which is able to capture, analyze, and then display relevant information to the user. Relevancy may be inferred based on fields such as search queries, location, role, calendar, mission objectives etc.

PHASE II: Develop, test, demonstrate, and report on a prototype system that showcases an analytics which is able to capture, analyze, and then display relevant information to the user in a simplified manner. Relevancy may be inferred based on fields such as search queries, location, role, calendar, mission objectives etc.

PHASE III DUAL USE APPLICATIONS: This cloud based analytic solution could be implemented on top of different data sources within the Intelligence or Mission Command Domains to enhance the operator’s situational awareness and assist with daily tasks. Commercially this solution could operate as an analytic to streamline and simplify daily operations within call centers, logistics operations, healthcare facilities, and the financial industries.

REFERENCES:

1. Dong, Hai (2008). A survey in semantic search technologies. IEEE. pp. 403–408

2. MacGregor, Robert (June 1991). "Using a description classifier to enhance knowledge representation". IEEE Expert 6 (3): 41–46. doi:10.1109/64.87683

3. Schalkoff, Robert (2011). Intelligent Systems: Principles, Paradigms and Pragmatics: Principles, Paradigms and Pragmatics. Jones & Bartlett Learning. ISBN 978-0-7637-8017-3

4. Singhal, Amit (May 16, 2012). "Introducing the Knowledge Graph: Things, Not Strings". Official Blog (of Google). https://googleblog.blogspot.co.uk/2012/05/introducing-knowledge-graph-things-not.html

5. Smith, Reid (May 8, 1985). "Knowledge-Based Systems Concepts, Techniques, Examples" (PDF). http://www.reidgsmith.com

KEYWORDS: Search, queries, intelligent personal assistant, natural language processing, knowledge navigator, structured and unstructured information, inference engine, ontology, machine learning, deep learning, neural networks

TECHNOLOGY AREA(S): Electronics

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 5.4.c.(8) of the Announcement.

OBJECTIVE: The objective of this effort is to develop and demonstrate an algorithm that will allow an airborne or ground-based Ground Moving Target Indicator (GMTI) radar to discriminate among Humans, Vehicles, Animals and ground Clutter (HVAC) in Near Real Time (NRT) by using Doppler signatures, target track characteristics and (where applicable) group dynamics.

DESCRIPTION: GMTI radars are able to reliably detect and accurately track targets moving in various terrain types. These radars, which typically have range resolutions from 1m to 5m, are limited in their ability to accurately discriminate among humans, vehicles, animals and moving clutter (e.g. flowing water, wind-blown trees). As target misclassifications can cause incorrect responsive actions by US forces in critical situations, significantly improving the HVAC classification accuracy of GMTI radars is a high Army priority. Target classification algorithms is applicable to a large number of current and future Army radars.

PHASE I: The Contractor shall develop an approach to enhance HVAC performance. The algorithms must be robust enough to account for missed detections caused by terrain blockage, low target radial velocity, etc. The contractor will estimate how the algorithm performance will vary as a function of radar frequency, Doppler frequency resolution, length of time over which a target is observed, and the number of missed detection reports. The Contractor will show how the algorithm is expected to perform against individuals, groups of various sizes, and mixed groups (e.g. humans and animals). The Contractor will also show how the algorithm will perform under calm and windy conditions, especially in the presence of wind-blown foliage. The product of the Phase I effort will be a final report that recommends a HVAC algorithm approach to be fully developed and demonstrated in the Phase II program.

PHASE II: The Contractor shall develop the HVAC algorithms and test with simulated and actual GMTI data provided by the Army. The initially provided data will be at frequencies ranging from UHF to X-band. The algorithm performance will be quantified as a function of radar frequency, range resolution, Doppler resolution, target observation time, signal-to-noise ratio (SNR) of the data, sensitivity to missed detections, and ground wind conditions. The algorithm performance will be assessed against mixed groups, individual targets, groups of various sizes, groups moving in different directions and speeds. The HVAC algorithm will also be demonstrated in near-real time by processing data provided by an Army GMTI radar undergoing field testing.

PHASE III DUAL USE APPLICATIONS: The Contractor shall develop a fully operational NRT HVAC algorithm for incorporation into one or more Army GMTI radars. The algorithm will also be developed for use in systems such as DHS GMTI radars that are used for border surveillance. The resulting technology will enhance these radars by providing an accurate understanding of the nature of a detected threat, and thereby minimizing the number of responses to non-threatening situations such as the detections of animals and false alarms due to wind-blown clutter.

REFERENCES:

1. Chen, Victor C. The Micro-doppler Effect in Radar. Boston: Artech House, 2011

2. J. Palmer, J. Reed, T. Selee, R. Hersey, E. Culpepper, “Dismount and Animal Discrimination Using Radar Signatures,” in Record 58th Tri-Service Radar Symposium, Boulder, CO, June 2012

3. Moorter, Bram Van, Nils Bunnefeld, Manuela Panzacchi, Christer M. Rolandsen, Erling J. Solberg, and Bernt-Erik Saether. "Understanding Scales of Movement: Animals Ride Waves and Ripples of Environmental Change." Journal of Animal Ecology J Anim Ecol 82.4 (2013): 770-80. Web

KEYWORDS: GMTI Radar, Target Classification, Group Dynamics

A17-055

TITLE: Semantic Mission Plan Representation

TECHNOLOGY AREA(S): Human Systems

OBJECTIVE: Perform research into the techniques for the semantic representation of mission plans and design an associated software tool set that facilitates the creation and manipulation of a mission plan as missions unfold.

DESCRIPTION: Mission plans are currently described through a collection of documents and artifacts that range across a variety of formats, both digital and analog. As a result, the mission plan is not described in a machine-readable format with well-defined semantics and cannot be processed by many automated systems, requiring human users to manually assemble the pieces and refine the plan through the Military Decision Making Process (MDMP). Research is needed to develop a representation of a mission plan with well-defined semantics that:

- Enables human, computer, and combined human-computer understanding and manipulation of the mission plan;
- Represents domain-independent planning concepts including states, goals, actions/tasks, plan fragments, constraints, dependencies, uncertainty, metrics, preferences, contingencies, re-planning, etc.;
- Represents domain-specific militarily relevant entities and relationships including space, time, resources, units, platforms, organizations, coalitions, adversaries, non-combatants, etc;
- Represents hierarchical relationships that allow high-level, abstract plans to be refined with additional information and low-level, detailed plans to be abstracted by aggregating information or hiding irrelevant information;
- Permits distributed interaction though which multiple, external users or systems can simultaneously view relevant information and update the mission plan;
- Permits a variety of planning workflows in which plans or plan details can be proposed, considered, committed, updated, and retracted;
- Is extensible to represent new concepts and relationships in domains that are as yet unpredictable.
Such a mission plan representation could facilitate much better interoperability between Mission Command systems and enable a broad range of capabilities, such as:
- Collaborative workflows that streamline the MDMP across staff functions, echelons, computing environments, and mission phases;
- Course of Action (COA) assessment to measure and compare alternative mission plans;
- Running estimates to track the dynamic state of an ongoing operation during mission execution;
- Tasking and supervision of autonomous systems.

PHASE I: Phase I effort will include the performance of extensive literature research of appropriate topics, and will also be expected to produce an assessment of the applicability of using, combining, modifying, and/or creating specific semantic and software techniques in a potential system. A preliminary design of a functional system is also expected. Practical limitations imposed by network availability and computing platforms across the force structure should be addressed as well. Technical reports for phase I effort should include:

(1) findings related to the individual data and software items that will be considered in the system development, to include the feasibility of capturing, manipulating, and using those items in a representative system
(2) analysis of how those items would be collected and managed during prototype development and in an experimental environment
(3) a preliminary design for a software prototype, in experimental venues as well as integrated with representative and/or relevant MC systems.

PHASE II: During Phase II, the contractor is expected to create and then continue to enhance a software prototype. A first version of prototype software should be completed and delivered to the government for installation, demonstration, and evaluation within 90 days of the start of phase II. The contractor and government will work together to identify a target system for integration. Quarterly builds with incremental improvements are required.

The contractor and government will work together to identify the venue and target system for a capstone installation, demonstration, and experimental evaluation. It will be the responsibility of the government to facilitate that capstone event.

The following tasks are expected:

(1) a detailed design for an operable system in both prototypical and fielded environments
(2) description of all Application Programming Interfaces (APIs)and a Software Development Kit (SDK)
(2) the development and ongoing refinement of prototype software
(3) multiple demonstrations and evaluations of the software in a representative operational setting
(4) capstone demonstration and evaluation of the software

Phase II deliverables will include technical reports, working software prototypes, and associated source code.

Software delivered at the conclusion of phase II should be at a Technology Readiness Level (TRL) 5.

PHASE III DUAL USE APPLICATIONS: The system developed could have broad applicability for any Army planning function, and the work could have commercial viability as well. During phase III, the contractor will continue to mature the prototype software, moving it to at least a TRL 6 level, and will work with the government to identify and then target and tailor the system for transition to an Army Program of Record as part of a current or emerging Army software system, as well as to one or more commercial applications.

As new Army MC solutions targeted to lower echelon and more austere environments are developed, the work should be of immediate interest to the Army Training and Doctrine Command, for use in training schools to help gain insight into how Commanders, during lower-echelon experimentation, perform planning. Additionally, as the Army consolidates more capabilities into systems such as Nett Warrior, a plug-in that could facilitate planning with higher echelons could be invaluable. Lower-echelon systems will be in environments where more agile, less hierarchical command structures are required to maintain operational tempo, and those types of systems would be natural targets.

From a commercial perspective, Emergency Response Services, where remote users must quickly share information and collaborate to save lives, a means to optimize planning, which drives efficiency of operations, should be attractive. The technology developed under this SBIR should also be interest to any organization interested in validating the effectiveness of distributed users performing joint planning and/or collaborative sessions, with a focus on quick and effective decisions. Financial instruments and commodity trading are examples.