Hybrid integration for highly maneuvering radar target detection based on generalized radon-fourier transform

It is known that long-time integration is an effective method for improving the detection performance ofweak and maneuvering radar targets.However, with the increase of integration time, the problems of across range unit (ARU) and across Doppler unit (ADU) may severely limit the integration performance for high-speed and maneuvering targets. The generalized Radon-Fourier transform (GRFT) can optimally deal with the above problems, but its implementation needs an ergodic multidimensional search. To reduce the complexity, a novel hybrid integration approach is proposed in this paper to speed up the realization of GRFT. It divides a long integration time into several subapertures and implements coherent integration for each subaperture via Doppler filter banks. Subsequently, it accomplishes noncoherent integration among all subapertures with compensation of high-order ARU and ADU motions via generalized Radon transform. Due to the hybrid integration over a long time, the proposed method strikes a balance between integration performance and computational efficiency for the detection of high-speed and highly maneuvering targets. Finally, some results of numerical experiments are provided to demonstrate the effectiveness of the proposed method.