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Performances Analysis of Coherently Integrated CPF for LFM Signal Under Low SNR and Its Application to Ground Moving Target Imaging

机译:低信噪比下LFM信号相干积分CPF的性能分析及其在地面目标成像中的应用

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The detection and parameters estimation of linear frequency-modulated (LFM) signal are important for modern radar applications, but they are also challenged by the fact that echo signal is often of low signal-to-noise ratio (SNR) due to reasons of long imaging distance and/or limited transmitted power, and the target of small size and/or hidden characteristics. To enhance the SNR, in our previous work, a novel coherently integrated cubic phase function (CICPF) was recently developed for the parameters estimation of the multicomponent LFM signal. In the CICPF, the auto-terms are coherently integrated to enhance the performance in the case of low SNR and also to suppress the cross-terms and spurious peaks. In this paper, as an extension of our previous work, the theoretical performance analyses including several important properties and the fast implementation are provided. Furthermore, the asymptotic mean squared error of a CICPF-based estimator as well as the output SNR of a CICPF-based detector are theoretically derived in closed-forms. From the performance point of view, the proposed CICPF attains the Cramer-Rao bound at low input SNR. The complexity analysis also indicates that the CICPF with the nonuniform fast Fourier transform is computationally efficient without needing the interpolation operation and parameter search. Numerical studies of the CICPF confirm the theoretical analysis and demonstrate superior performance of the proposed approach compared with other state-of-the-art approaches, especially under the low-SNR condition. Finally, the proposed CICPF is applied for the ground moving target imaging in synthetic aperture radar. Results using simulated and experimental data demonstrate that it provides an effective means to obtain well-focused image for ground moving targets.
机译:线性调频(LFM)信号的检测和参数估计对于现代雷达应用非常重要,但是由于回声信号因其较长的原因而常常具有低信噪比(SNR)的事实,也给它们带来了挑战。成像距离和/或受限的发射功率,以及目标尺寸小和/或隐藏特性。为了提高SNR,在我们先前的工作中,最近开发了一种新颖的相干积分三次相位函数(CICPF)用于多分量LFM信号的参数估计。在CICPF中,自动项相干地集成在一起,以在低SNR的情况下增强性能,并抑制交叉项和虚假峰值。在本文中,作为我们先前工作的扩展,提供了包括几个重要属性和快速实现的理论性能分析。此外,理论上以封闭形式得出基于CICPF的估计器的渐进均方误差以及基于CICPF的检测器的输出SNR。从性能角度来看,建议的CICPF在低输入SNR时达到Cramer-Rao界。复杂度分析还表明,具有非均匀快速傅立叶变换的CICPF在计算上高效,而无需插值运算和参数搜索。 CICPF的数值研究证实了理论分析,并证明了与其他最新技术相比,该方法的优越性能,尤其是在低SNR条件下。最后,将所提出的CICPF应用于合成孔径雷达的地面运动目标成像。使用模拟和实验数据的结果表明,它为获取地面移动目标的聚焦图像提供了有效的手段。

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