Radar Imaging of Non-Uniformly Rotating Targets via  a Novel Approach for Multi-Component AM-FM Signal  Parameter Estimation

Wang, Yong

doi:10.3390/s150306905

Cited by 6 publications

(3 citation statements)

References 32 publications

(38 reference statements)

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“…As for ISAR imaging of maneuvering targets, the existing methods [3,5,6] always assume that the translational motion compensation has been accomplished and focus on the azimuth compression. However, translational motion compensation is an essential step and needs to be considered carefully.…”

Section: Introductionmentioning

confidence: 99%

An Iterative Phase Autofocus Approach for ISAR Imaging of Maneuvering Targets

Wang

Cha

Zhou³

et al. 2021

Electronics

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Translational motion compensation and azimuth compression are two essential processes in inverse synthetic aperture radar (ISAR) imaging. The anterior process recovers coherence between pulses, during which the phase autofocus algorithm is usually used. For ISAR imaging of maneuvering targets, conventional phase autofocus methods cannot effectively eliminate the phase error due to the adverse influence of the quadratic phase terms caused by the target’s maneuvering motion, which leads to the blurring of ISAR images. To address this problem, an iterative phase autofocus approach for ISAR imaging of maneuvering targets is proposed in this paper. Considering the coupling between translational phase errors and quadratic phase terms, minimum entropy-based autofocus (MEA) method and adaptive modified Fourier transform (MFT) are performed iteratively to realize better imaging results. In this way, both the translational phase error and quadratic phase terms induced by target’s maneuvering motion can be compensated effectively, and the globally optimal ISAR image is obtained. Comparison ISAR imaging results indicates that the new approach achieves stable and better ISAR image under a simple procedure. Experimental results show that the image entropy of the proposed approach is 0.2 smaller than the MEA method, which validates the effectiveness of the new approach.

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Section: Introductionmentioning

confidence: 99%

An Iterative Phase Autofocus Approach for ISAR Imaging of Maneuvering Targets

Wang

Cha

Zhou³

et al. 2021

Electronics

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“…ISAR imagery plays an important role especially in military applications such as target identification, recognition, and classification [1,2,3,4,5,6]. For ground-based radars, a perspective blind zone will exist when the height of the measured target is too low.…”

Section: Introductionmentioning

confidence: 99%

Non-Stationary Platform Inverse Synthetic Aperture Radar Maneuvering Target Imaging Based on Phase Retrieval

Shi

Xia

Qin

et al. 2018

Sensors

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As a powerful signal processing tool for imaging moving targets, placing radar on a non-stationary platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the received signal due to the instability of the radar platform, making it difficult for popular algorithms to accurately perform motion compensation, which leads to severe effects in the resultant ISAR images. Moreover, maneuvering targets may have complex motion whose motion parameters are unknown to radar systems. To overcome the issue of non-stationary platform ISAR autofocus imaging, a high-resolution imaging method based on the phase retrieval principle is proposed in this paper. Firstly, based on the spatial geometric and echo models of the ISAR maneuvering target, we can deduce that the radial motion of the radar platform or the vibration does not affect the modulus of the ISAR echo signal, which provides a theoretical basis for the phase recovery theory for the ISAR imaging. Then, we propose an oversampling smoothness (OSS) phase retrieval algorithm with prior information, namely, the phase of the blurred image obtained by the classical imaging algorithm replaces the initial random phase in the original OSS algorithm. In addition, the size of the support domain of the OSS algorithm is set with respect to the blurred target image. Experimental simulation shows that compared with classical imaging methods, the proposed method can obtain the resultant motion-compensated ISAR image without estimating the radar platform and maneuvering target motion parameters, wherein the fictitious target is perfectly focused.

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“…The target’s moving parameters, such as radial velocity, along-track velocity, and original azimuth position, play an important role in monitoring ground vehicles. Using these parameters, we can reposition them to the true azimuth location and extrapolate a target’s future position [7,8]. Generally, the interferometric phase is employed to determine the radial velocity while the along-track velocity is acquired by the target’s Doppler parameters.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization

2016

Sensors

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Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target's velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms.

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Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

Cited by 6 publications

References 32 publications

An Iterative Phase Autofocus Approach for ISAR Imaging of Maneuvering Targets

An Iterative Phase Autofocus Approach for ISAR Imaging of Maneuvering Targets

Non-Stationary Platform Inverse Synthetic Aperture Radar Maneuvering Target Imaging Based on Phase Retrieval

Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization

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