基于立方相位信号模型的船舶目标三维干涉测量反合成孔径雷达成像

IF 1.4 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Iet Radar Sonar and Navigation Pub Date : 2024-06-11 DOI:10.1049/rsn2.12603
Junting Yang, Yong Wang
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引用次数: 0

摘要

干涉反合成孔径雷达(InISAR)系统实现了对三部雷达在一组正交基线上获得的成像结果进行干涉处理,从而获得船舶目标的三维(3D)成像。船舶目标在航行过程中会经历复杂的运动特性,如滚动、俯仰和偏航。这些运动会导致二维(2D)图像模糊不清,进一步影响 InISAR 过程中的干扰性能。因此,本文提出了一种基于立方相位信号(CPS)模型的船舶目标三维 InISAR 成像算法。该方法将方位回波信号近似为 CPS,并利用粒子群优化算法估计高阶相位系数。在保留相位信息的同时,高分辨率二维图像之间的干涉处理可实现三维图像结果。在不同基线长度和信噪比条件下进行的模拟实验验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Three-dimensional interferometric inverse synthetic aperture radar imaging of ship target based on cubic phase signal model

The interferometric inverse synthetic aperture radar (InISAR) system realises the interferometric processing on the imaging results obtained from three radars on a set of orthogonal baselines and can get the three-dimensional (3D) imaging for the ship target. The ship targets experience complex motion characteristics such as roll, pitch and yaw in the course of navigation. These motions lead to the blurred two-dimensional (2D) images and further affect the interference performance during the InISAR procedure. Therefore, this paper proposes a 3D InISAR imaging algorithm for the ship targets based on the cubic phase signal (CPS) model. This method approximates the azimuth echo signal as a CPS and utilises the particle swarm optimization algorithm to estimate the higher-order phase coefficients. While preserving the phase information, the 3D image result can be achieved by the interference processing between the high-resolution 2D images. The effectiveness of the algorithm is validated through the simulation experiments under different baseline lengths and signal-to-noise ratios.

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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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