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Doppler aliasing free micro-motion parameter estimation algorithm based on the spliced time-frequency image and inverse Radon transform

机译:基于拼接时频图像和Radon逆变换的多普勒无混叠微运动参数估计算法

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Micro-Doppler is induced by the micro- motion of target and serves as an important characteristic for target recognition once extracted via parameter estimation, but it is generally too significant to result in aliasing in terahertz band. To solve this problem, we analyze the theoretical model and characteristics of aliased micro-Doppler and propose a Doppler aliasing free micro-motion parameter estimation algorithm based on the combination of spliced time-frequency image and the Inverse Radon transform. The basic idea is getting a certain number of aliased time-frequency images spliced, and then make Inverse Radon transform to the spliced image and extract micro-motion parameters. The simulation results show that this method has the advantages of high precision and strong noise suppression and can estimate parameters of aliased micro-Doppler correctly and effectively.
机译:微多普勒是由目标的微运动引起的,并且一旦通过参数估计提取出来就成为目标识别的重要特征,但是它通常太重要而无法导致太赫兹频带的混叠。为了解决这个问题,我们分析了混叠微多普勒的理论模型和特点,提出了一种基于时频拼接和逆Radon变换相结合的多普勒无混叠微运动参数估计算法。基本思想是获取一定数量的混叠时频图像,然后进行反Radon变换到该拼接图像并提取微运动参数。仿真结果表明,该方法具有较高的精度和较强的噪声抑制能力,可以正确,有效地估计混叠微多普勒参数。

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