SAR Minimum-Entropy Autofocus Using an Adaptive-Order Polynomial Model

Wang, Junfeng; Liu, Xingzhao

doi:10.1109/lgrs.2006.878446

Cited by 123 publications

(62 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Phase adjustment via minimum entropy is widely applied in issues of radar imaging [17][18][19][20][21][22]. It usually performs well in presence of strong noise and clutter, and it has no constraints on the error form.…”

Section: Minimum Entropy For Phase Adjustment (Mepa)mentioning

confidence: 99%

“…However, presence of strong noise brings inherent difficulty to precise phase tracking through several dominant scatters. Another group numerically optimizes the phase error correction to improve a global metric consistent with image focus, in which image contrast (IC) [13][14][15][16] and entropy [17][18][19][20][21][22] are utilized as the cost function to optimize the phase error. Image metricbased approaches are usually able to obtain an optimal solution even in the presence of strong background noise and clutter.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Translational motion compensation for ISAR imaging under low SNR by minimum entropy

Zhang

Sheng

Duan

et al. 2013

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

In general, conventional error correction for inverse synthetic aperture radarimaging consists of range alignment and phase adjustment, which compensate range shift and phase error, respectively. Minimum entropy-based methods have been proposed to realize range alignment and phase adjustment. However, it becomes challenging to align high-resolution profiles when strong noise presents, even using entropy minimization. Consequently, the subsequent phase adjustment fails to correct phase errors. In this article, we propose a novel method for translational motion correction, where entropy minimization is utilized to achieve range alignment and phase adjustment jointly. And, a coordinate descent algorithm is proposed to solve the optimization implemented by quasi-Newton algorithm. Moreover, a method for coarse motion estimation is also proposed for initialization in solving the optimization. Both simulated and real-measured datasets are used to confirm the effectiveness of the joint motion correction in low signal-to-noise ratio situations.

show abstract

Section: Minimum Entropy For Phase Adjustment (Mepa)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Translational motion compensation for ISAR imaging under low SNR by minimum entropy

Zhang

Sheng

Duan

et al. 2013

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

show abstract

“…These algorithms often suffer from long processing times. To shorten the processing time and/or to be applicable to scenes without prominent point-like targets, several algorithms have been proposed, including the phase adjustment by contrast enhancement [38,39], autofocus by minimum-entropy [40], coherent map drift [41,42], and others [43,44]. It should be mentioned that spaceborne SARs, in particular interferometric SARs, sometimes suffer from image degradation by tropospheric and ionospheric effects as will be described in Section 4.1.3.…”

Section: Sensormentioning

confidence: 99%

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

2013

View full text Add to dashboard Cite

The present article is an introductory paper in this special issue on synthetic aperture radar (SAR). A short review is presented on the recent trend and development of SAR and related techniques with selected topics, including the fields of applications, specifications of airborne and spaceborne SARs, and information contents in and interpretations of amplitude data, interferometric SAR (InSAR) data, and polarimetric SAR (PolSAR) data. The review is by no means extensive, and as such only brief summaries of of each selected topics and key references are provided. For further details, the readers are recommended to read the literature given in the references theirin.

show abstract

“…Backproject correlated signal for each hypothesized displacement (|ζ| ≤ 20, ζ ∈ Z) with the filter given in (17) and calculate the entropy of the reconstructed image, 4. For the hypothesized displacements which result in the minimum entropy, perform a local-entropy (13-by-13 pixels) measurement for each scatterer and assign the displacement which results in the minimum local-entropy for each scatterer, 5.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Mono-static synthetic aperture radar interferometry with arbitrary flight trajectories

Yanık

Yazıcı

2012

SPIE Proceedings

View full text Add to dashboard Cite

We consider a mono-static synthetic aperture radar (SAR) system flying over a scene of interest, making multiple visits. During each visit, antenna is traversing a different arbitrary, but known trajectory. Therefore, the difference in the positions of the antennas, which we refer to as the baseline vector, is arbitrary and changes at each visit. Our objective is to estimate the displacement in the ground topography and reconstruct the scene radiance. We perform a spatio-temporal correlation of the received signals measured by each antenna. This results in a novel model that relates the correlated signal to the displacement. Next, we estimate the displacement in the ground topography and reconstruct the radiance of the scene by using a filtered-backprojection (FBP) -type method combined with an entropy minimization technique. Finally, we present numerical experiments to demonstrate the performance of the proposed method.

show abstract

SAR Minimum-Entropy Autofocus Using an Adaptive-Order Polynomial Model

Cited by 123 publications

References 11 publications

Translational motion compensation for ISAR imaging under low SNR by minimum entropy

Translational motion compensation for ISAR imaging under low SNR by minimum entropy

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

Mono-static synthetic aperture radar interferometry with arbitrary flight trajectories

Contact Info

Product

Resources

About