A Novel ISAR Imaging Method for Maneuvering Target Based on AM-QFM Model Under Low SNR Environment

Abstract

Inverse synthetic aperture radar (ISAR) imaging for long range maneuvering small/stealth target plays an important role in the field of national defense surveillance. Due to low signal-to-noise (SNR) of received echo signal and the nonstationary Doppler frequency modulated (DFM) during the coherent processing intervals (CPI), the conventional range-Doppler (RD) algorithm is unsuitable to generate a well-focused ISAR image. Furthermore, the dihedral or trihedral components of the maneuvering target or range cell migration caused by the target’s complex motion generate the time-varying amplitudes for the received signal, which brings a new challenge for ISAR imaging algorithm design. To overcome those issues, in this work, we propose a new method to obtain the well-focused ISAR image of long range maneuvering small/stealth target. This method consists of two main steps. First, the received signal in a range bin is characterized as multicomponent amplitude modulated-quadratic frequency modulated (AM-QFM) signal with time-varying amplitudes after the translational compensation. After that, a novel coherently integrated general cubic phase function (CIGCPF) is developed to estimate the parameters of multi-component AM-QFM signal. Compared with the existing ISAR imaging methods based on the constant amplitude signal model during the CPI, the well-focused ISAR image can be obtained by the proposed method with time-varying amplitude in a low SNR environment. Finally, the simulation results demonstrate the effectiveness of the proposed algorithm.

Keywords

• Inverse synthetic aperture radar (ISAR)
• maneuvering target
• low SNR environment
• time-varying amplitude
• parameters estimation