基于Radon傅里叶变换和加速度滤波的运动目标检测方法

IF 3.6 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xijia Chen , Yongping Song , Jun Hu , Tian Jin , Fang Xu , Zengping Chen
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引用次数: 0

摘要

高速小型飞机的稳定探测通常需要长期的相干积累,这给距离和多普勒偏移带来了挑战。基于广义Radon傅里叶变换(GRFT)的聚焦前检测方法在解决这些问题上是有效的。然而,GRFT涉及在高维空间中搜索和补偿运动参数,导致大量的计算负担。本文提出了一种将Radon傅里叶变换(RFT)与加速滤波器(AF)相结合的方法,即AF-RFT。具体而言,首先对采集到的信号进行RFT处理,消除速度引起的距离偏移(RM),将目标投影到距离-速度空间中。然后,为了解决由加速度引起的多普勒调频(DFM)问题,提出了一种沿慢时间维度的加速度滤波器。该滤波器对分布在各个速度单元上的目标能量进行集合,使目标能够在距离-速度-加速度空间中聚焦。仿真结果表明,该方法有效地解决了RM和DFM问题,提高了检测性能,同时保持了较低的计算负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient detection method for moving targets based on the Radon Fourier transform and acceleration filter
For stable detection of High-speed small aircraft, long-term coherent accumulation is generally required, which presents challenges due to range and Doppler migration. The focus-before-detection method based on the generalized Radon Fourier transform (GRFT) has proven effective in addressing these issues. However, GRFT involves searching and compensating for motion parameters in a high-dimensional space, resulting in a substantial computational burden. This paper proposes a method that combines Radon Fourier transform (RFT) and an acceleration filter (AF), i.e. AF-RFT. Specifically, the RFT is first applied to the collected signals to eliminate the range migration (RM) caused by speed, projecting the target into range-speed space. Then, to address the Doppler frequency modulation (DFM) introduced by acceleration, an acceleration filter along the slow-time dimension is developed. This filter gathers the distributed target energy across speed units, enabling the target to focus in range-speed-acceleration space. Simulation results reveal that the proposed method effectively resolves RM and DFM, thereby improving detection performance while maintaining low computational burden.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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