Ground Maneuvering Target Imaging and High-Order Motion Parameter Estimation Based on Second-Order Keystone and Generalized Hough-HAF Transform

Huang, Penghui; Liao, Guisheng; Yang, Zhiwei; Xia, Xiang-Gen; Ma, Ji; Zheng, Jianhua

doi:10.1109/tgrs.2016.2606436

Cited by 89 publications

(63 citation statements)

References 51 publications

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“…To this goal, two approaches of the Radon-CPF transform (RCT) in [18] and Hough generalized high-order ambiguous function (Hough-GHAF) method in [20] have been developed to suppress the cross-terms, spurious peaks for multicomponent QFM signal. To utilize the energy of auto-terms, for the RCT, the integration was performed along the slope line defined by the polar distance

ρ_{T}

(radius) from the origin and polar angle

θ_{T}

formed by the perpendicular to the line in the radon domain.…”

Section: Proposed Algorithm Descriptionmentioning

confidence: 99%

“…The similar idea based on multilinear function of fourth-order GHAF is also adopted by Hough-GHAF method in [20]. The Hough-GHAF is defined by

\begin{matrix} left \\ S_{Hough - GHAF} (ρ_{T}; θ_{T}) = Θ_{t_{m}} [GHAF (t_{m}, f_{τ_{m}})] \\ = \int_{- T_{a} / 2}^{+ T_{a} / 2} | GHAF (t_{m}, f_{τ_{m}}) | δ [ρ_{T} - t_{m} \cos θ_{T} - f_{τ_{m}^{2}} \sin θ_{T}] d t_{m} \end{matrix}

where

Θ_{t_{m}}

represents the Hough-GHAF transform operator.…”

Section: Proposed Algorithm Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

Zeng

Qin

Liu

et al. 2018

Sensors

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The inverse synthetic aperture radar (ISAR) imaging for targets with complex motions has always been a challenging task due to the time-varying Doppler parameter, especially at the low signal-to-noise ratio (SNR) condition. In this paper, an efficient ISAR imaging algorithm for maneuvering targets based on a noise-resistance bilinear coherent integration is developed without the parameter estimation. First, the received signals of the ISAR in a range bin are modelled as a multicomponent quadratic frequency-modulated (QFM) signal after the translational motion compensation. Second, a novel quasi-time-frequency representation noise-resistance bilinear Radon-cubic phase function (CPF)-Fourier transform (RCFT) is proposed, which is based on the coherent integration of the energy of auto-terms along the slope line trajectory. In doing so, the RCFT also effectively suppresses the cross-terms and spurious peaks interference at no expense of the time-frequency resolution loss. Third, the cross-range positions of target’s scatters in ISAR image are obtained via a simple maximization projection from the RCFT result to the Doppler centroid axis, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Compared with the existing time-frequency analysis-based and parameter estimation-based ISAR imaging algorithms, the proposed method presents the following features: (1) Better cross-term interference suppression at no time-frequency resolution loss; (2) computationally efficient without estimating the parameters of each scatters; (3) higher signal processing gain because of 2-D coherent integration realization and its bilinear function feature. The simulation results are provided to demonstrate the performance of the proposed method.

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ρ_{T}

(radius) from the origin and polar angle

θ_{T}

formed by the perpendicular to the line in the radon domain.…”

Section: Proposed Algorithm Descriptionmentioning

confidence: 99%

“…The similar idea based on multilinear function of fourth-order GHAF is also adopted by Hough-GHAF method in [20]. The Hough-GHAF is defined by

\begin{matrix} left \\ S_{Hough - GHAF} (ρ_{T}; θ_{T}) = Θ_{t_{m}} [GHAF (t_{m}, f_{τ_{m}})] \\ = \int_{- T_{a} / 2}^{+ T_{a} / 2} | GHAF (t_{m}, f_{τ_{m}}) | δ [ρ_{T} - t_{m} \cos θ_{T} - f_{τ_{m}^{2}} \sin θ_{T}] d t_{m} \end{matrix}

where

Θ_{t_{m}}

represents the Hough-GHAF transform operator.…”

Section: Proposed Algorithm Descriptionmentioning

confidence: 99%

An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

Zeng

Qin

Liu

et al. 2018

Sensors

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show abstract

“…계산량을 줄이기 위한 방법으로 실제 도로 환경에 대 한 사전 지식(a priori knowledge)을 이용한 연구 [6] 와 second order Wigner-Ville distributuion(WVD)을 통한 timefrequency analysis 기법 [7] 을 이용한 연구 등이 진행되어왔 다. 또한, multiple signal classification(MUSIC), Capon 기법 을 이용하여 속도를 추정 [8] 하거나 segmented keystone transform(SKT)과 Doppler Lv's transform을 결합한 SKT-DL-VT [9] 와 같은 새로운 방법에 대한 연구들도 계속해서 보 고되고 있다.…”

Section: ⅰ 서 론unclassified

Ground Moving Target’s Velocity Estimation in SAR-GMTI

Bae¹,

Jeon²,

Yang³

et al. 2017

J. Korean Inst. Electromagn. Eng. Sci.

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A ground moving target's velocity estimation algorithm applicable for a SAR-GMTI system using 2 channel displaced phase center antenna(DPCA) is proposed. In this algorithm, we assume target's across-track velocity can be estimated by along-track interferometry (ATI) and present a method to estimate target's along-track velocity. To accomplish this method, we first transform a radar-target geometry in which a moving target has zero velocity via altering a radar velocity such that target's velocity is reflected into it and next manipulate the spectral centers of the subapertures within the synthetic aperture. The validity of the proposed algorithm is demonstrated through simulation results showing the performance of the target's velocity estimation and the enhancement of reconstructed target image quality in terms of resolution and SINR.

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“…Generally speaking, target detection, parameter estimation and target imaging are the three most important functions of modern radars [7,8,9], where the performance of target detection and parameter estimation will significantly affect the imaging quality for the target [10,11,12]. Therefore, how to improve the performances of target detection and parameter estimation have become important topics in radar research [13,14,15].…”

Section: Introductionmentioning

confidence: 99%

WRFRFT-based coherent detection and parameter estimation of radar moving target with unknown entry/departure time

Sun

Zhang

et al. 2020

Signal Processing

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A moving target may enter a radar coverage area unannounced and leave after an unspecified period, which implies that the target's entry time and departure time are unknown. In the absence of these time information, target detection and parameter estimation (DAPE) will be severely impacted. In this paper, we consider the coherent detection and parameters estimation problem for a radar moving target with unknown entry time and departure time (that is, the time when the target appears-in/leaves the radar detection field is unknown), involving across range cell (ARC) and Doppler spread (DS) effects within the observation period. A new algorithm, known as window Radon Fractional Fourier transform (WRFRFT) is proposed to detect and estimate the target's time parameters (i.e., entry time and departure time) and motion parameters (i.e., range, velocity and acceleration). The observation values of a maneuvering target are first intercepted and extracted by the window function and searching along the motion trajectory. Then these values are fractional Fourier transformed and well accumulated in the WR-FRFT domain, where the DAPE of target could be accomplished thereafter. Experiments with simulated and real radar data sets prove its effectiveness.

show abstract

Ground Maneuvering Target Imaging and High-Order Motion Parameter Estimation Based on Second-Order Keystone and Generalized Hough-HAF Transform

Cited by 89 publications

References 51 publications

An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

Ground Moving Target’s Velocity Estimation in SAR-GMTI

WRFRFT-based coherent detection and parameter estimation of radar moving target with unknown entry/departure time

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