Subaperture autofocus for synthetic aperture radar

Calloway, Terry M.; Donohoe, G.W.

doi:10.1109/7.272285

Cited by 105 publications

(42 citation statements)

References 5 publications

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“…As in other sub-aperture methods [12], the SAT is divided into N non-overlapping segments (u 1 , . .…”

Section: Estimation Of the ϕ L (T) By Sub-aperture Methodsmentioning

confidence: 99%

A Hybrid Sar Autofocus Technique by Two Methods of Sub-Aperture Estimation and Iterative Golden Section Search

Koh¹,

Choi²,

Chun³

2014

PIER M

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Abstract-In a real airborne synthetic aperture radar (SAR), its major phase errors are usually composed of two categories, such as slow-time varying phase errors (less than several cycles of change in phase during synthetic aperture time) and fast-time varying phase errors (otherwise, including wide band random) according to the motion of aircraft. If the fast errors are no more negligible compared to the slow errors, they should be estimated and then compensated accurately to obtain a well focused image. However, it is not proper to estimate all phase errors at the same time like conventional autofocus techniques because the estimation of the fast-time varying phase errors are seriously affected by blurring in image due to the slow-time varying phase errors. In this paper, we presents an accurate hybrid phase estimation technique using two independent estimation stages of sub-aperture and an iterative golden section search method, which has advantages over several existing methods, because of its better estimation accuracy and less sensitive to the quality of extracted range bins as well as requiring less computation time. The performance of our method is illustrated by simulations of point targets and an experiment with real SAR data.

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“…As in other sub-aperture methods [12], the SAT is divided into N non-overlapping segments (u 1 , . .…”

Section: Estimation Of the ϕ L (T) By Sub-aperture Methodsmentioning

confidence: 99%

A Hybrid Sar Autofocus Technique by Two Methods of Sub-Aperture Estimation and Iterative Golden Section Search

Koh¹,

Choi²,

Chun³

2014

PIER M

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“…In the coordinate descent optimization, each parameter is optimized in turn, while holding the remaining parameters constant. For our application, coordinate descent is applied to maximize the objective function in Equation (10).…”

Section: Coordinate Descentmentioning

confidence: 99%

“…When the residual RCM is within a range resolution cell, residual RCM can be neglected. This is the general presumption for almost all the existing autofocus algorithms, such as phase gradient autofocus (PGA) [8], Mapdrift (MD) [9], phase difference (PD) [10] and metric-based autofocus [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Minimum-Entropy Based Residual Range Cell Migration Correction for Bistatic Forward-Looking SAR

Zha

Chen

et al. 2016

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For bistatic forward-looking synthetic aperture radar (BFSAR), motion errors induce two adverse effects on the echo, namely, azimuth phase error and residual range cell migration (RCM). Under the presumption that residual RCM is within a range resolution cell, residual RCM can be neglected, and azimuth phase error can be compensated utilizing autofocus methods. However, in the case that residual RCM exceeds the range resolution, two-dimensional defocus would emerge in the final image. Generally speaking, residual RCM is relatively small and can be neglected in monostatic SAR, while the unique characteristics of BFSAR makes the residual RCM exceeding range resolution cell inevitable. Furthermore, the excessive residual migration is increasingly encountered as resolutions become finer. To cope with such a problem, minimum-entropy based residual RCM correction method is developed in this paper. The proposed method eliminates the necessity of the parametric model when estimating the residual RCM. Moreover, it meets the practical needs of BFSAR owing to no requirement of exhaustive computation. Simulations validate the effectiveness of the proposed method.

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“…It estimates the quadratic phase error in the data by measuring the linear shift between two SAR images built by dividing the azimuth processing interval on two halves. The multiple-aperture MDA [3,10] estimates the phase error as a higher-order polynomial. Other models, such as a Fourier series, have also been proposed [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…The multiple-aperture MDA [3,10] estimates the phase error as a higher-order polynomial. Other models, such as a Fourier series, have also been proposed [10][11][12]. The problem is that the parametric autofocus methods are restricted by the models applied.…”

Section: Introductionmentioning

confidence: 99%

Autofocusing SAR images via local estimates of flight trajectory

Bezvesilniy

Gorovyi

Vavriv

2016

Int. J. Microw. Wireless Technol.

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Autofocusing SAR images via local estimates of flight trajectory oleksandr o. bezvesilniy, ievgen m. gorovyi and dmytro m. vavriv High-resolution imaging with an airborne synthetic aperture radar (SAR) calls for precise trajectory measurements that can hardly be achieved with common navigation systems. In this paper, an efficient method called the local-quadratic map-drift autofocus is developed for the estimation of residual (uncompensated) motion errors directly from the received radar data. The map-drift autofocus is applied locally on short time intervals to estimate the cross-track components of the aircraft acceleration. The estimated acceleration is then integrated to evaluate the residual trajectory errors on the whole data frame interval. The method has been successfully tested with an X-band airborne SAR system.

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Subaperture autofocus for synthetic aperture radar

Cited by 105 publications

References 5 publications

A Hybrid Sar Autofocus Technique by Two Methods of Sub-Aperture Estimation and Iterative Golden Section Search

A Hybrid Sar Autofocus Technique by Two Methods of Sub-Aperture Estimation and Iterative Golden Section Search

A Minimum-Entropy Based Residual Range Cell Migration Correction for Bistatic Forward-Looking SAR

Autofocusing SAR images via local estimates of flight trajectory

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