Multihypothesis Multimodel Elliptic Radon Transform for Low-Observability Maneuvering Range-Ambiguity Target Detection

Long-time echo signal integration is a well-known effective method for low-observability radar target detection. However, for near-space hypersonic target detection, with the increase in target speed and acceleration, the radar signal integration will suffer from issues such as across range unit (ARU), across Doppler unit (ADU), even across beam unit (ABU), and across ambiguous interval (AAI), which may significantly impact the integration performance. Some methods can deal with the problems of ARU and ADU, such as generalized Radon Fourier transform, but when the target echo signals are ABU or AAI, the integration time will be limited. To resolve the problems of ABU and AAI, this article proposes a curve-track interframe integration approach named multihypothesis multimodel elliptic Radon transform. After coherent integration with compensation of high-order ARU and ADU motions in a beam, it accomplishes noncoherent integration with compensation of high-order cross-beam motions via multimodel elliptic Radon transform. For the range ambiguity problem of remote near-space targets, the ambiguity interval multiple hypothesis procedure is proposed to map the ambiguous measurements, which transforms the problem of range ambiguity resolution into a potential continuous track detection. Compared to other long-time integration methods, the proposed method can extend the integration time to a longer extent without being limited by ARU, ADU, ABU, and AAI.