An adaptive non‐searching method for long‐time coherent integration of manoeuvring target with multiple motion models

Abstract

Long-time coherent integration (LTCI) is one of the effective methods to enhance the radar detection capability of manoeuvring targets. In most existing studies, the target is assumed to move at a consistent model during the total integration time. In modern times, this point is not always true. The modern targets often possess strong manoeuvring penetration capability, which enables the presence of multiple motion models (i.e. the target's motion model is changing during the total integration time) with a high possibility, especially when the coherent integration time is long. This factor would reduce the performance of the existing LTCI methods. In this study, an adaptive non-searching method, based on the adjacent cross correlation function (ACCF)/modified ACCF (MACCF), Keystone transform (KT)/second-order KT, Hough transform and fractional Fourier transform, is proposed for LTCI of a manoeuvring target with multiple motion models. First, the motion model change points are identified. Subsequently, the adaptive case prejudgement and parameters estimation for different motion stages are completed. Finally, the LTCI of the manoeuvring target with multiple motion models is realised after motion compensation. Simulation results demonstrate the effectiveness of the proposed method.