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ISAR imaging of multiple targets using particle imaging of multiple targets using particle swarm optimisation - adaptive joint time frequency approach

机译:使用粒子群优化算法的多目标粒子成像的ISAR成像-自适应联合时频方法

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摘要

When multiple radar targets are close to each other, the returned signals from these targets are overlapped in time. Therefore by applying conventional motion compensation algorithms designed for single target, the multiple targets cannot be resolved, and individual one cannot be clearly imaged. The authors conclude that whether the radar transmits linear frequency modulated (LFM) or stepped-frequency waveform, the chirp rate in the Doppler frequency shift induced by the translation motion is only concerned with the acceleration of the target. For different targets, the chirp rates are different from each other. Based on the different chirp rates, the signals from each target can be separated. Then a new algorithm based on the adaptive joint time frequency (AJTF) technique is proposed to separate the signals from different target in each cross-range cell. The use of the particle swarm optimisation (PSO) for multiple targets separation is a unique application of this evolutionary search. By the CLEAN technique, the number of targets need not be appointed. The simulation results confirm the efficiency of the proposed algorithm for multiple moving targets imaging.
机译:当多个雷达目标彼此靠近时,这些目标的返回信号会在时间上重叠。因此,通过应用为单个目标设计的常规运动补偿算法,无法解析多个目标,并且不能清晰地成像单个目标。作者得出的结论是,无论雷达是发射线性调频(LFM)还是步进频率波形,由平移运动引起的多普勒频移中的线性调频率仅与目标的加速度有关。对于不同的目标,线性调频率彼此不同。根据不同的线性调频率,可以分离来自每个目标的信号。然后提出了一种基于自适应联合时频(AJTF)技术的新算法,将每个跨距离小区中来自不同目标的信号分离。粒子群优化(PSO)用于多目标分离是这种进化搜索的独特应用。通过CLEAN技术,无需指定目标数。仿真结果证实了该算法在多运动目标成像中的有效性。

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  • 来源
    《Signal Processing, IET》 |2010年第4期|p.343-351|共9页
  • 作者

    Li Y.; Fu Y.; Li X.; Le-wei L.;

  • 作者单位

    College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China;

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  • 正文语种 eng
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