Rotation Estimation for ISAR Targets With a Space–Time Analysis Technique

Yeh, Chunmao; Yang, Jian; Peng, Yingning; Shan, Xiuming

doi:10.1109/lgrs.2011.2132752

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…On account of the micro‐motion‐induced radial range and Doppler modulation, the echo of ISAR is a time‐varying frequency signal in azimuth, which may cause the invalidity of the traditional range–Doppler algorithm [22]. Hence, the radial range, velocity and acceleration may be estimated and the range and Doppler shift in the slow‐time domain may be compensated to form a focusing ISAR image [23]. Then, the scattering centres are extracted and mapped onto the range–velocity plane in every coherent processing interval (CPI).…”

Section: Key Steps For Parameter Estimationmentioning

confidence: 99%

Precession parameter estimation method of the cone‐shaped target based on inverse synthetic aperture radar image sequence analysis

Wang

Yeh

Shu-liang

et al. 2019

IET Radar, Sonar & Navigation

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Section: Key Steps For Parameter Estimationmentioning

confidence: 99%

Precession parameter estimation method of the cone‐shaped target based on inverse synthetic aperture radar image sequence analysis

Wang

Yeh

Shu-liang

et al. 2019

IET Radar, Sonar & Navigation

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“…RWT[e(t)] = e t + t 2 2 e * t − t 2 2 exp(−j2p(Kt + h)t 2 ) dt dt 2 = exp(j2ph 0 t 2 ) exp(j2pK 0 tt 2 ) exp(−j2p(Kt + h)t 2 ) dt dt 2 (14) www.ietdl.org according to (17),â 2m can be acquired aŝ…”

Section: Second-order Phase Coefficient Estimationmentioning

confidence: 99%

“…For ISAR targets with uniform motion, the rotating angle can be obtained via the rotating angular velocity multiplied by the CPI. Extensive algorithms on the ISAR images scaling have been proposed [9][10][11][12][13][14][15][16][17][18][19][20]. For multi-static ISAR, several methods based on dominant scatters [9], randomised Hough transform [10] and time-frequency distribution analysis and CLEAN technique [11] have been proposed for the interferometric ISAR (In-ISAR) image scaling.…”

Section: Introductionmentioning

confidence: 99%

“…However, these algorithms assume that ISAR images at different interval share the same rotating centre, which may not be satisfied in real data processing. Through exploiting the two‐dimensional (2D) space‐variant characteristic of ISAR imaging, a novel method for estimating the rotational motion of a non‐cooperative target is presented [14], but heavy computation load limits its application. Based on the analysis of the phase of the range echoes, several methods are presented in [15, 16] to estimate the rotating angular velocity.…”

Section: Introductionmentioning

confidence: 99%

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Cross‐range scaling method of inverse synthetic aperture radar image based on discrete polynomial‐phase transform

Liu

Zhou

Tao

et al. 2015

IET Radar, Sonar & Navigation

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The cross-range scaling of inverse synthetic aperture radar image depends on both the radar wavelength and the rotating angle of the target relative to the radar line-of-sight. After compensating the translational motion, the second-order phase coefficients of the range echoes are a linear polynomial of the rotating angular velocity and range geometry. In this study, a novel method for estimating the rotating angular velocity of the targets with dominant scatters is proposed. The range cells where the amplitudes have smaller normalised variances are selected, and then frequency domain windowing is applied to extract echoes of dominant scatters. Based on the discrete polynomial-phase transform, the second-order phase coefficients of the strong scatter echoes are estimated, and thus the rotating angular velocity can be obtained through the least-square-error method. Simulated and real-data results have shown the effectiveness and robustness of this method.

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“…While the technique is practically effective and reasonably accurate, it is computational demanding. On the other hand, the target rotation rate can be estimated from ISAR data via the methodology of sensor array data processing [4,5]. In these approaches, several prominent points are required to be identified from the unfocused image.…”

mentioning

confidence: 99%

Target rotation rate estimation via ISAR frame processing

Huang

Wang²,

et al. 2013

Electron. lett.

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A method is proposed for estimating the target rotation rate for ISAR imaging based on the frame processing technique. The method utilises the intrinsic structures of the frame which span the Hilbert space of radar return from which the rotational information of the target is extracted. For a prominent point, the intensity of the projection is maximum when the frame component corresponding to the prominent point is built with the target rotation rate.Introduction: Knowledge of the target rotational motion is a crucial requirement for recovering the cross-range scale of an image and compensating for image defocusing in conventional ISAR imaging processing [1]. The frame processing (FP) imaging method, proposed in [2], considers radar returns in a Hilbert space where the frame of the space can be identified. The ISAR image is therefore a projection of radar returns onto the (dual) frame viewed on a range-Doppler plane.To construct the frame of radar data space, knowledge of the target rotation rate is explicitly required. Although the FP result is likely to be acceptable by using a guessed value, an accurate rotation rate of the target is a general requirement to guarantee the image from defocusing.The estimation of target rotation rate from radar data can be carried out either in image or in signal domains. For example, the minimum entropy method for refocusing an image described in [3] is an image domain processing. While the technique is practically effective and reasonably accurate, it is computational demanding. On the other hand, the target rotation rate can be estimated from ISAR data via the methodology of sensor array data processing [4,5]. In these approaches, several prominent points are required to be identified from the unfocused image. An optimisation procedure can then applied to optimise timespace correlation of the signals based on the geometry of these prominent points with respect to target rotation rate, or maximise energies of the signals constructed based on the time-space model at these prominent points with respect to target rotation rate.Following the work in [2], a target rotation rate estimation method based on the FP technique is proposed. When the dual frame is built with the correct rotation rate, the intensity of the projection of the prominent point will be the maximum. Therefore, if a prominent point can be identified, it is possible to estimated the rotation rate of a target based on the corresponding frame component under the criterion of maximising the projection value with respect to target rotation rate. After a short introduction of the FP technique for ISAR imaging, an online target rotation rate estimation procedure based on the FP method is presented.

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Rotation Estimation for ISAR Targets With a Space–Time Analysis Technique

Cited by 9 publications

References 10 publications

Precession parameter estimation method of the cone‐shaped target based on inverse synthetic aperture radar image sequence analysis

Precession parameter estimation method of the cone‐shaped target based on inverse synthetic aperture radar image sequence analysis

Cross‐range scaling method of inverse synthetic aperture radar image based on discrete polynomial‐phase transform

Target rotation rate estimation via ISAR frame processing

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