一种改进的复合运动空间目标微动周期估计方法
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TN95

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江西省教育厅科技项目(GJJ161042,GJJ161677)资助


Improved micro-motion period estimation method for space targets with compound motion
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    摘要:

    提出一种基于Viterbi算法与时频差值平方和序列的微动周期估计方法。雷达目标的微动状态与目标动力、结构高度相关,不同目标具有显著的差异性,反映了目标的重要信息,可用于辅助目标探测及识别,具有重要作用。在雷达目标微动特性的研究中,诸如导弹等空间目标是研究的热点,目前已发表了大量关于空间目标的微动特征提取方法。对空间目标,其通常是平动与微动相耦合的复合运动目标,在进行微动特征提取时需考虑平动的影响。针对复合运动空间目标进行研究,提出一种基于Viterbi算法与时频差值平方和序列的微动周期估计方法,其中Viterbi算法可在低信噪比情况下目标瞬时多普勒的鲁棒估计,时频差值平方和序列则能够有效去除目标平动的影响,所提方法具有良好的估计性能。仿真结果验证了估计方法的有效性。

    Abstract:

    Problem: A micromotion period estimation based on the Viterbi algorithm and the timefrequency squared difference sequence is proposed. Procedure and method: The micromotion states of the radar target is dependent on the dynamics, structure of the target, and they are usually different for different targets. As a result, the micromotion states reflect some important information of the target and can be used to aid the target detection and recognition, which has a great importance. In the research of the micromotion features, space targets such as missile are hot points. Numerous micromotion feature extraction methods for space targets are published. Usually, the motion of the space target is compound of the translation and the micromotion. The implication of the translation on the micromotion feature extraction should be considered. This work focuses on the space target with compound motion. A micromotion period estimation based on the Viterbi algorithm and the timefrequency squared difference sequence is proposed, in which the Viterbi algorithm can provide robust instantaneous Doppler estimation in low signaltonoise ratio (SNR) and the timefrequency squared difference sequence can remove the effect of the translation. Thus, the proposed method has a good performance. Results: Numerical results prove the effectiveness of the proposed method.

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赵燕,龙桂铃.一种改进的复合运动空间目标微动周期估计方法[J].电子测量与仪器学报,2020,34(2):60-66

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  • 在线发布日期: 2023-06-15
  • 出版日期: 2020-01-31
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