TECHNOLOGY AREA(S): Air Platform, Weapons

ACQUISITION PROGRAM: PMA280 Tomahawk Weapons Systems

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 3.5 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 innovative Inverse Synthetic Aperture Radar (ISAR) imaging and associated Automatic Target Recognition (ATR) approaches that will support high-resolution, two-dimensional (2-D) imaging and classification of maritime targets for when the radar is operating in real beam mode.

DESCRIPTION: Radar sensors on future weapon systems that form high-quality Synthetic Aperture Radar (SAR) and ISAR images must have an offset look angle on the target. During the final stage of flight, just before impact, the radar-equipped missile that was flying at a squint angle to the target to obtain ISAR/SAR imagery must turn the missile velocity vector directly at the target, which eliminates high-quality ISAR images and the radar is forced into a real-beam degraded imagery mode. As a consequence of the image degradation in real-beam mode, the monopulse angle is distorted due to Doppler folding and the signal-to-clutter ratio is reduced according to the radar backscattering theory of the illumination response. As a result, traditional ISAR imaging algorithms used to form 2-D images of the target no longer work, and thus traditional ISAR-based ATR algorithms fail. In recent years, new advances in sparse signal processing approaches have demonstrated that for data such as ISAR, the observation time on the target required for imaging and ATR can be significantly reduced. The significant reduction in observation time can be exploited in the signal processing approach to dramatically improve the imaging and ATR performance while the radar operates in real-beam mode. The features on the target that are used to classify the targets will be encoded in the sparse representation of the radar signal and on the quality of the image formed. The Navy seeks an innovative ATR-based imaging approach that fully integrates the imaging and ATR together to leverage the sparse target information and significantly reduce the observation time to allow the radar to operate in real-beam mode. Performance of the algorithm will be assessed through simulations, captive flight tests, and live fire events when integrated into a weapon system. The real-beam ATR results will be compared to traditional ISAR ATR results for performance assessment.

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by DoD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this project as set forth by DSS and NAVAIR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advanced phases of this contract.

PHASE I: Determine the feasibility of an innovative ATR-based imaging approach that fully integrates imaging and ATR together in order to support high-confidence vessel classification in real-beam radar mode. Develop a novel real-beam ISAR image formation approach that leverages limited radar return of targets to greatly reduce the amount of data and acquisition time required to precisely reconstruct the ISAR images as compared to the traditional ISAR imaging approach. Determine a corresponding ATR approach tuned to the type of features of the targets that are consistent with the image quality of the real-beam ISAR processor; and determine the approach to assess the algorithm performance in terms of image quality and probability of correct classification against simulated data of targets in real-beam mode, to be provided by the Government. The Phase I effort will include prototype plans to be developed under Phase II.

PHASE II: Further develop and demonstrate algorithm performance in terms of image quality and probability of correct classification against simulated and emulated collected data of targets in real-beam mode. Demonstrate the performance of the novel ATR-based ISAR process developed in Phase I against collected radar data on maritime targets. Perform automatic target recognition performance assessment of the ISAR images generated as a function of ship type, operational environment (e.g., sea state, wind condition), radar parameters (e.g., bandwidth, frequency), and robustness against jamming attacks.

It is probable that the work under this effort will be classified under Phase II (see Description section for details).

PHASE III DUAL USE APPLICATIONS: Finalize and integrate the algorithms into operational radar system hardware and execute real-time implementation in detailed system of systems digital simulations as well as captive flight and live fire demonstrations as determined by the transition Program of Record. Although this is primarily a weapon application, it is directly applicable to the private sector Defense contractors. The algorithm could be applied in ocean surveillance systems significantly reducing the observation time of the targets.

REFERENCES:

1. Candes, E., and Tao, T. �Near-Optimal Signal Recovery from Random Projections: Universal Encoding Strategies.� IEEE Transactions on Information Theory, 2006, pp. 5406-5425. https://statweb.stanford.edu/~candes/papers/OptimalRecovery.pdf

2. Zhang, L., Qiao, Z., Xing, M., Sheng, J., Guo, R., and Bao, Z. �High-Resolution ISAR Imaging by Exploiting Sparse Apertures.� IEEE Transactions on Antennas and Propagation, 2012, pp. 997-1008. http://faculty.utrgv.edu/zhijun.qiao/Qiao-IEEE-TAP-06058607.pdf

3. Zhang, L., Xing, M., Qui, C., Li, J., and Bao, Z. �Achieving Higher Resolution ISAR Imaging with Limited Pulses via Compressed Sampling.� IEEE Geoscience and Remote Sensing Letters, 2009, pp. 567-571. https://ieeexplore.ieee.org/document/5061612/

KEYWORDS: ISAR; ATR; Algorithms; Maritime; Back Scatter; Real-Beam; Inverse Synthetic Aperture Radar; Automatic Target Recognition