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Radar Maneuvering Target Motion Estimation Based on Generalized Radon-Fourier Transform

机译:基于广义Radon-Fourier变换的雷达机动目标运动估计

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摘要

The slant range of a radar maneuvering target is usually modeled as a multivariate function in terms of its illumination time and multiple motion parameters. This multivariate range function includes the modulations on both the envelope and the phase of an echo of the coherent radar target and provides the foundation for radar target motion estimation. In this paper, the maximum likelihood estimators (MLE) are derived for motion estimation of a maneuvering target based on joint envelope and phase measurement, phase-only measurement and envelope-only measurement in case of high signal-to-noise ratio (SNR), respectively. It is shown that the proposed MLEs are to search the maximums of the outputs of the proposed generalized Radon-Fourier transform (GRFT), generalized Radon transform (GRT) and generalized Fourier transform (GFT), respectively. Furthermore, by approximating the slant range function by a high-order polynomial, the inherent accuracy limitations, i.e., the Cramer-Rao low bounds (CRLB), and some analysis are given for high order motion parameter estimations in different scenarios. Finally, some numerical experimental results are provided to demonstrate the effectiveness of the proposed methods.
机译:雷达机动目标的倾斜范围通常根据其照明时间和多个运动参数建模为多元函数。该多元范围函数包括相干雷达目标回波的包络和相位调制,并为估计雷达目标运动提供了基础。本文基于联合包络和相位测量,仅相位测量和高信噪比情况下的仅包络测量,推导了最大似然估计器(MLE)用于机动目标的运动估计, 分别。结果表明,提出的MLE将分别搜索提出的广义Radon-Fourier变换(GRFT),广义Radon变换(GRT)和广义傅里叶变换(GFT)的输出最大值。此外,通过用高阶多项式逼近倾斜范围函数,固有的精度限制即Cramer-Rao下界(CRLB)以及针对不同情况下的高阶运动参数估计给出了一些分析。最后,提供了一些数值实验结果以证明所提方法的有效性。

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