Department of the navy (don) 17. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions introduction

REFERENCES:

1. The 2015 Naval Power and Energy Systems Technology Development Roadmap, Retrieved 1 February 2016. http://www.navsea.navy.mil/Resources/NPESTechDevelopmentRoadmap.aspx

2. Fal, Alex. Zero-Volt: Medical and Satellite Battery Technology Can Help Improve Safety of Electric Vehicles. Battery Power May/June 2012, Retrieved 25 January 2016 http://www.batterypoweronline.com/main/markets/batteries/zero-volt-medical-and-satellite-battery-technology-can-help-improve-safety-of-electric-vehicles

3. Bard, Allen, and Zoski, Cynthia. Electroanalytical Chemistry: A Series of Advances, Volume 24. CRC Press Nov 16, 2011. Science. Retrieved 25 January 2016. http://file.ebook777.com/004/EleCheASerOfAdvVol24.pdf -

KEYWORDS: Lithium battery; low-voltage battery storage; pulse power battery output; long-term energy storage for batteries; battery management system; uninterruptible power supply.

Questions may also be submitted through DoD SBIR/STTR SITIS website.

N171-047

TITLE: Advanced Minehunting Sonar Data Fusion

TECHNOLOGY AREA(S): Battlespace, Electronics, Sensors

ACQUISITION PROGRAM: AN/AQS-20C Minehunting Sonars

OBJECTIVE: Develop a process to filter and fuse data from volume and side-scan active towed sonars to reduce false classifications and extract detection features for downstream Automatic Target Recognition (ATR) processing.

DESCRIPTION: The Navy needs to enhance the effectiveness of existing Navy Minehunting high-frequency sonar systems by fusing sonar data to reduce false classifications of mines. The fusion of data from Wideband horizontally projected (volume) and vertically projected (side-scan) active sonars has the potential to greatly enhance the Minehunting observation process by combining the inherent strengths from the volume and side-scan sensors. These active sensors were developed along separate development efforts and were recently installed on the same towed sensor platform. Today’s Minehunting towed systems are now configured with both volume and side-scan sensors. Synthetic Aperture Sonar (SAS) processing techniques are being applied to side-scan sensors to further improve the quality of side-scan sensor data.

The Navy’s existing Minehunting systems primarily use side-scan sensors to detect, classify, and localize mines resting on the sea floor. Volume search sonars are used to detect and localize mines, tethers, and anchors for moored mines tethered to the sea floor. The technical challenges with current sensors are; (1) the tow body discretely processes sensor data from the side-scan and volume search sonars; (2) the operators must look at multiple sonar displays to view the output of the time series data from the side-scan and volume sensors; (3) the contact localization data is listed in a separate table; (4) the water depth is in a separate table; and, (5) the side-scan and volume sensors search the same track at different time periods making Post Mission Analysis (PMA) geo-synchronization challenging for the operators.

Innovative solutions are sought for the following technical challenge areas: (1) multi-sensor data fusion approaches and algorithms which include fusion of acoustic data from the side-scan and volume search sonars into a single contact list with the attributes and the detection features used for fusing the data (such as kinematics, signal excess, size, contact depths); (2) PMA Visualization Algorithms, based on the data fusion approach, used to process the sensor data and display contacts to the operators used to reduce false classifications by 50% and improve localization accuracy by 25%.

The design should include fusion methods and algorithms to reside either in the tow-body sensor processors or in the back-end PMA processors. The proposed solution should demonstrate reduction in the reported total number of contacts by removing the false classifications (e.g. 8 false calls reduced to 4 false calls). Developing advanced algorithms that fuse volume search and side-scan search SONAR sensors should reduce search and analysis timelines by a minimum of 50%, adding significant value to mission commanders. Candidate minehunting systems include AN/AQS-20 and AN/AQS-24.

Although Phase II work may require secure access, the proposal for Phase II will be UNCLASSIFIED. If the selected Phase II contractor does not have the required certification for classified work, NAVSEA will assist the contractor in processing the DD 254 to facilitate certification of related personnel and facility.

PHASE I: The company will develop a concept for multi-sensor data fusion of acoustic data from both the volume and side-scan sensors, including SAS, to reduce false classifications. They will provide detailed technical performance specification and design, in-tow-body processing and data collection requirements for back-end PMA processing. The company will detail the feasibility of developing the advanced algorithms required to fuse acoustic data from both volume and side-scan sensors. The Phase I Option, if awarded, will address technical risk reduction and provide performance goals and key technical milestones.

PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), the small business will develop a prototype for evaluation and delivery. The prototype will be evaluated to determine its capability in meeting the performance goals defined in the Phase II SOW and the Navy requirements for the Advanced Minehunting Sonar Data Fusion in the description. System performance will be demonstrated through prototype evaluation and modeling or analytical methods over the required range of parameters including numerous deployment cycles. Evaluation results will be used to refine the prototype into an initial design that will meet Navy requirements. The company will prepare a Phase III development plan to transition the technology to Navy and potential commercial use.

PHASE III DUAL USE APPLICATIONS: The company will be expected to support the Navy in transitioning the technology for Navy use. The company will further refine the Advanced Minehunting Sonar Data Fusion algorithm(s) according to the Phase II SOW for evaluation to determine its effectiveness in an operationally relevant environment. The expected transition of the prototype is into minehunting systems such as the AN/AQS-20 and AN/AQS-24. The company will support the Navy for test and validation to certify and qualify the system for Navy use. Private Sector Commercial Potential: Towed active acoustic sonar systems have been successfully towed from small 11-meter boats. As these sensor systems become more compact due to breakthroughs with robust computing processors, the need to automate signal processing of the increasing number of sensors is quickly expanding. Techniques developed under this SBIR may transition to commercial use for application in search and rescue systems deployed around littoral regions of the world.

REFERENCES:

1. Urick, R.J., Principles of Underwater Sound. McGraw–Hill Book Company, New York, 1983

2. David L. Hall & James Llinas, Handbook of Multisensor Data Fusion. CRC Press LLC, 2001.

3. Eric J. Tollefson, Advanced Minehunting Sensors, 2016 Naval Post Graduate School Mine Warfare Technology Symposium, 24-26 May 2016.-

KEYWORDS: Minehunting acoustic systems; multisensor data fusion; underwater acoustics; side-scan SONAR; AN/AQS-20; AN/AQS-24.

Questions may also be submitted through DoD SBIR/STTR SITIS website.

TECHNOLOGY AREA(S): Battlespace, Electronics, Sensors

ACQUISITION PROGRAM: Surface ASW Combat System Integration, 1916: Surface ASW System Improvement

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 Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Develop a closed-loop active adaptive sonar to improve detection, localization, and classification performance and reduce manning requirements.

DESCRIPTION: Active sonar control on Cruisers, Destroyers, and Littoral Combat Ships currently requires a tremendous amount of hands-on operator involvement, multi-faceted decisions informed by models, and in-situ observations and training. Thus, active sonar may operate at times in a degraded mode. Development of a closed-loop active adaptive sonar will improve sonar and combat system performance, and streamline the tasks for transmit control that will provide improved detection, localization, and classification performance as well as reduced operator workload and staffing.

The concept of Fully Adaptive Active Sonar (FAAS) seeks to exploit all available degrees-of-freedom to adapt the transmitted waveform and receive processing in order to maximize target detection performance. This area of study has received great interest in radar application where it has shown to produce 3 to 10 dB improvement in target signal-to-noise ratio. Adaptive receive beamforming has been employed for underwater imaging and in medical ultrasound applications. It is a logical extension to consider the benefits of joint transmit and receive adaptation for both pulsed active sonar (PAS) and continuous active sonar (CAS).

Closed loop sonar operation is replete with open problems spanning a broad gamut of research areas in detection, tracking, and classification. The focus of this effort is the optimal sonar target detection problem in environments with unknown spectral properties. Two important issues that arise in the context of FAAS for adaptive target detection are deriving the performance limit (optimal performance) afforded by FAAS, and developing the criteria for adaptive processor performance to lie within a prescribed level of possible optimal performance.

Development of FAAS is more difficult than solving the radar problem due to the relatively slow propagation speed of sound, and potentially by the small number of transmissions available in a given time-span. Key metrics are probability of detection and probability of false alarm for the optimal processor for the target transmission types (single pings, multiple pings, and continuous active waveforms). Other important metrics are latency to achieve optimization parameters, the required training data support, false alarm probability, robustness of detection performance to parameter mismatch, and computational footprint.

This technology should increase mission capability by improving sonar performance through automating and streamlining the task of active sonar transmit control and improving the target signal-to-noise ratio. Adaptive feedback will provide real-time optimizations for waveforms, transmit patterns, and receive processing. This will allow sonar operators to focus on acoustic analysis with improved target detectability.

It is anticipated that Phase II and Phase III work will require a Department of Defense (DoD) security clearance.
The Phase II effort will likely require secure access, and NAVSEA will process the DD254 to support the contractor for personnel and facility certification for secure access. The Phase I effort will not require access to classified information. If need be, data of the same level of complexity as secured data will be provided to support Phase I work.

PHASE I: Develop initial concept and model key elements of fully a adaptive active sonar. Feasibility will be determined through analysis and modeling of the improved detection, localization, and classification performance as well as reduced operator workload and manning. A simulation will be developed using simulated data and will be analyzed for use in the AN/SQQ-89 system. The Phase I Option, if awarded, will include the initial system specifications and a capabilities description to build the prototype in Phase II.

PHASE II: The company will develop, demonstrate and validate a prototype closed-loop active adaptive sonar. Techniques using SQS-53C mono-static, SQS-53C/Multi-Function Towed Array (MFTA) quasi-mono-static, and/or Littoral Combat Ship Variable Depth Sonar (LCS-VDS) active sonars employing pulsed and continuous waveforms will be used to validate the prototype’s capabilities. Performance analysis and validation of the adaptive technique with respect to the training data support, false alarm probability, robustness of detection performance to parameter mismatch, and computational cost are sought. Performance validation must be analyzed using simulated and measured data sets. Secure access to classified data will be required in Phase II. The company will prepare a Phase III development plan to transition the technology for Navy and potential commercial use.

PHASE III DUAL USE APPLICATIONS: The company will be expected to support the Navy in transitioning the technology for Navy use. The company will further refine a fully integrated closed-loop active adaptive sonar and assist in operational testing and integration of the technology into current AN/SQQ-89 combat system future builds via ACB-19/21 and other systems such as LCS-VDS or Surveillance Towed Array Sensor System Compact Low-Frequency Active (SURTASS CLFA). Private Sector Commercial Potential: Commercial applications that currently utilize various forms of active acoustic transmission and reception that could benefit from a fully adaptive active approach include oil exploration; seismic survey; rescue and salvage; and bathymetric survey.

REFERENCES:

1. Guerci, J.R. "Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach." Artech House Inc., Norwood, MA, 2010.

2. Gini, F. and Rangaswamy, M. ed. "Knowledge-Based Radar Detection, Tracking, and Classification." Wiley Interscience Series, May 2008.

3. Ward, J. "Space-Time Adaptive Processing for Airborne Rada.," MIT/LL Technical report 1015, 13 Dec, 1994.

4. Dursun, Safiye, Austeng, Andreas, Hansen, Roy E., and Holm, Sverre. “Minimum variance beamforming in active sonar imaging.” In Bjørnø (ed.) John S., Papadakis & Leif, editor, Proceedings of the 3rd International Conference & Exhibition on Underwater Acoustic Measurements: Technologies and Results, pages 1373--1378, 2009.

5. Synnevag, J. F., Austeng, A., and Holm, S.. “Adaptive beamforming applied to medical ultrasound imaging.” Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on, 54(8):1606 --1613, August 2007.-

KEYWORDS: Fully adaptive active sonar; sonar waveform; adaptive signal processing; cognitive radar; AN/SQQ-89 combat system; ACB-19/21 system

Questions may also be submitted through DoD SBIR/STTR SITIS website.