Translate 
Abstract
Recently, terahertz (THz) radar has been widely researched for its high-resolution in space target imaging. Due to the high rendezvous speed and the short wavelength of THz radar, the traditional stop-and-go model, along with its supporting algorithms, is not applicable. Therefore, a method that jointly compensates the intra- and inter- pulse errors of space targets’ echo is proposed. The algorithm includes the following steps: firstly, a coarse estimation of targets’ translational velocity at part of pulses is conducted through Fractional Fourier transform (FrFT). Then, the improved least square fitting (ILSF) is employed to parameterize the velocity–time dependency of the target. Furthermore, the concept of synthetic waveform entropy (SWE) of a one-dimensional range profile is put forward as the accuracy metric of envelope alignment. Finally, with SWE serving as the fitness function, the Grey Wolf Optimizer (GWO) algorithm is used to search for optimal estimated translation parameters. After several iterations, a fine-grained estimation of target motion parameters is achieved, while simultaneously accomplishing precise joint compensation for intra-pulse and inter-pulse errors. The validity of the proposed method is verified by numerical simulation, electromagnetic calculation data, and field-measured data.
Published Version
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
