单脉冲雷达对抗角电子攻击中未分辨目标的闭角估计

IF 1.1 4区 工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Habib Rezaei, Mohammad Ali Sebt, Nadali Zarei, Goudarz Saadati Moghadam
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引用次数: 0

摘要

典型的单脉冲雷达无法在一个分辨率单元中检测到两个近距离目标的角度。作者提出了一种闭合形式的技术,通过使用四个雷达接收机信道的单个快照来估计两个未解决目标的角度。本文解决了单脉冲雷达的相位比较和幅度比较问题。利用对角差分信道对单脉冲雷达角度估计系统进行了改进。利用单个脉冲,该技术可以准确地确定欺骗性诱饵和真实目标的角度和幅度。如果两个目标具有相同的方向,则所提出的方案无法检测到它们;因此,为了估计这些目标的角度,我们使用了一个额外的天线。通过比较精确解和仿真,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Closed-form angle estimation of unresolved targets in monopulse radar to counter the angular electronic attack

Closed-form angle estimation of unresolved targets in monopulse radar to counter the angular electronic attack

Typical monopulse radar cannot detect the angle of two closely-spaced targets in one resolution cell. The authors propose a closed-form technique to estimate the angle of two unresolved targets by using a single snapshot of four radar receiver channels. In this work, phase comparison and amplitude comparison problems for monopulse radar are resolved. The monopulse radar angle estimation system has been enhanced using the diagonal difference channel. Using a single pulse, this technique can accurately determine the angle and amplitude of the deceptive decoy and the real target. If both targets have the same direction, the proposed scheme cannot detect them; therefore, to estimate the angle of such targets, we used an additional antenna. The effectiveness of the proposed method is validated by comparing the exact solutions and simulations.

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来源期刊
IET Signal Processing
IET Signal Processing 工程技术-工程:电子与电气
CiteScore
3.80
自引率
5.90%
发文量
83
审稿时长
9.5 months
期刊介绍: IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems. The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more. Topics covered by scope include, but are not limited to: advances in single and multi-dimensional filter design and implementation linear and nonlinear, fixed and adaptive digital filters and multirate filter banks statistical signal processing techniques and analysis classical, parametric and higher order spectral analysis signal transformation and compression techniques, including time-frequency analysis system modelling and adaptive identification techniques machine learning based approaches to signal processing Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques theory and application of blind and semi-blind signal separation techniques signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals direction-finding and beamforming techniques for audio and electromagnetic signals analysis techniques for biomedical signals baseband signal processing techniques for transmission and reception of communication signals signal processing techniques for data hiding and audio watermarking sparse signal processing and compressive sensing Special Issue Call for Papers: Intelligent Deep Fuzzy Model for Signal Processing - https://digital-library.theiet.org/files/IET_SPR_CFP_IDFMSP.pdf
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