Non-cooperative Target Detection/Identification (ID)
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AbstractTo achieve desired levels of operational performance, airborne surveillance systems require a capability for identifying non-cooperative targets within the surveillance space. Effective non-cooperative target recognition (NCTR) systems reduce the time to engagement and also the incidence of fratricide. Advances in imaging sensor technologies such as synthetic aperture radar (SAR), synthetic aperture ladar (SAL), and high range resolution (HRR) radar, offer enhanced target recognition capabilities at long distances. Sensor technology such as airborne MTI radar and ESM can also provide target recognition information at long range. This program seeks to develop a multi-sensor multi-platform NCTR system that fuses feature and classification data to produce a robust estimate of the target identity. A key capability of the proposed solution is the ability to fuse information from dissimilar sensors, and this will enable the coordination and cooperation of these sensors in the NCTR solution. Another important attribute in the proposed solution is the ability to account for ambiguities present in the NCTR problem. The ambiguity detection and management is achieved using a multiple hypothesis data association framework, with which Numerica has extensive experience and expertise. BENEFIT: Under various advanced sensing programs, such as the Advanced Laser Sensing program, the Air Force is actively pursuing advanced sensor capabilities to aid in the recognition of non-cooperative targets. The impact of these improvements can be multiplied by a system that fuses the information from dissimilar sensors into coherent target identification hypotheses. Moreover, the availability of the fusion products allows each sensor to leverage information from other sensors to improve its performance. Examples of this cross-cuing include improved detection, accuracy, and response time. Numerica’s multi-sensor fusion system for non-cooperative target recognition will include the ability to fuse both feature and classification data from dissimilar sensors into a coherent hypothesis of the target’s identity. The NCTR technology to be developed will use multi-hypothesis data association technology and ambiguity detection and management techniques to provide robust target identifications. These two features combine to provide an NCTR system that will perform well even in complex, highly ambiguous, scenarios and in particular will mitigate the occurrence of mis-identification decisions. Provided that the NCTR technology is successful, Numerica intends to pursue a transition path with the AWACS Program Office, the sponsor of the SBIR topic; Numerica is already working with the program office on a related fusion technology. Numerica also intends to work with Boeing, which has provided a letter of interest, on opportunities to transition the technology to AWACS and to relevant Unmanned Arial System (UAS) programs. The NCCT Program, with which Numerica is already working with, is another potential beneficiary of the NCTR technology, as there are needs for this capability within the NCCT system as well.
* information listed above is at the time of submission.