基于多帧并行恢复方法的微动目标不完全雷达数据时频分析

IF 5.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Shichao Xiong;Hongwei Zhang;Kaiming Li;Ying Luo;Qun Zhang
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引用次数: 0

摘要

传统的时频分析方法在数据缺失和低信噪比的情况下会出现性能下降。稀疏信号处理(SSP)方法是一种从不完整数据中恢复TF图像的有效方法,但其计算量和存储空间要求较高。为了解决这些问题,本研究提出了一种称为多帧并行恢复(MFPR)深度展开分割网络的TF图像恢复方法。首先,基于MFPR信号模型,构建了基于近端梯度(PG)方法的TF恢复优化问题,该方法可以同时从所有帧中恢复TF图像;这可以消除对矢量化的需要,从而减少计算和存储成本。然后,提出了包含两个子网的MFPR深度未展开分割网络(MDUS-Net),从不完整的数据中获得完整的TF图像。第一个子网络是MFPR的深度展开网络,实现了对不完整数据的高质量TF恢复。第二个子网络为分割网络,通过图像分割技术实现TF曲线骨架提取。仿真和实测数据的实验结果表明,即使在数据不完整、信噪比较低的情况下,该方法也能生成高质量的TF图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-Frequency Analysis for Incomplete Radar Data of Micromotion Targets via Multiframe Parallel Recovery Approach
Conventional time-frequency (TF) analysis methods deteriorate under the condition of data missing and low signal-to-noise ratio (SNR). Sparse signal processing (SSP) method is an effective solution for recovering TF images from incomplete data, but it is burdened by significant computational and storage requirements. To address these challenges, this study proposed a TF image recovery method called multiframe parallel recovery (MFPR) deep unfolded segmentation network. First, the TF recovery optimization problem solved by the proximal gradient (PG) method is constructed based on the MFPR signal model, which can simultaneously recover TF images from all frames. This can eliminate the need for vectorization and thereby reduce computational and storage costs. Then, the MFPR deep unfolded segmentation network (MDUS-Net), which contains two subnetworks, is proposed to obtain a complete TF image from incomplete data. The first subnetwork is a deep unfolded network of MFPR, which achieves high-quality TF recovery from incomplete data. The second subnetwork is a segmentation network, which achieves TF curves skeleton extraction via image segmentation technique. The experimental results on both simulated and measured data demonstrate that the proposed method can generate high-quality TF images even under conditions of incomplete data and low SNR.
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来源期刊
IEEE Transactions on Instrumentation and Measurement
IEEE Transactions on Instrumentation and Measurement 工程技术-工程:电子与电气
CiteScore
9.00
自引率
23.20%
发文量
1294
审稿时长
3.9 months
期刊介绍: Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications. The scope of these papers may encompass: (1) theory, methodology, and practice of measurement; (2) design, development and evaluation of instrumentation and measurement systems and components used in generating, acquiring, conditioning and processing signals; (3) analysis, representation, display, and preservation of the information obtained from a set of measurements; and (4) scientific and technical support to establishment and maintenance of technical standards in the field of Instrumentation and Measurement.
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