Location of Spaceborne Sar Imagery

Curlander, John C.

doi:10.1109/tgrs.1982.350455

Cited by 215 publications

(123 citation statements)

References 1 publication

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“…According to Tables 2-6, it can be concluded that the proposed localization method has a higher quality of accuracy and can obtain targets' height information compared with that proposed in [11,12]. Table 7.…”

Section: Discussion and Comparisonmentioning

confidence: 94%

“…As a contrast, the localization result proposed in [11,12] with the same parameters in Table 1 is listed in Table 7. Since it is monostatic SAR, the location and velocity of the first transmitter parameter are used here.…”

Section: Discussion and Comparisonmentioning

confidence: 99%

“…In addition, we set targets with height information, which is shown in Figure 10. The localization result proposed in [11,12] is shown in Table 9. It is clear in Table 9 that localization error is too large, and this method cannot be applied to obtain the target height information.…”

Section: Discussion and Comparisonmentioning

confidence: 99%

“…However, the target height information that is obtained with interferometric SAR has large error in areas with dramatic altitude changes, such as mountain terrain. Positioning with a single SAR image is based on the range-Doppler (RD) model for spaceborne monostatic SAR [11,12]. Additionally, target coordinates can be obtained by solving the range equation and Doppler equation.…”

Section: Introductionmentioning

confidence: 99%

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A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization

Zhong

et al. 2017

Remote Sensing

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Abstract:In traditional localization methods for synthetic aperture radar (SAR), the range sum estimation and Doppler centroid estimation (DCE) are required. The DCE error can influence the localization accuracy greatly. In addition, the target height information cannot be obtained by these methods. In this paper, a three-dimensional localization method for multistatic SAR based on the numerical range-Doppler (RD) algorithm and entropy minimization principle is proposed. In this method, the raw data from each transmitter and receiver (T/R) pair are focused by the numerical RD algorithm with the initial location value of the reference target. Then, Newton iteration is used to solve the target location value with the information of the bistatic range sum (BRS) in different SAR images with respect to different T/R pairs. Generally, the initial location value of the reference target is not accurate, and it can influence the imaging quality and accuracy of other target locations. We use entropy to measure image quality and iterate imaging with the new location value of the reference target, until the entropy gets the minimum value. Therefore, we can get the optimal location value of the reference target, which can make image entropy reach the minimum. Finally, all targets can be located by the Newton iteration method with their BRS in each T/R pair that are obtained from the images with minimum entropy. Compared with traditional localization methods for monostatic SAR, the proposed method not only effectively eliminates the influences of DCE errors, but also can get the target height information. Therefore, it improves the localization accuracy and can achieve three-dimensional localization. The effectiveness of the localization approach is validated by a numerical simulation experiment.

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Section: Discussion and Comparisonmentioning

confidence: 94%

Section: Discussion and Comparisonmentioning

confidence: 99%

Section: Discussion and Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization

Zhong

et al. 2017

Remote Sensing

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“…The geometric correction method, based on whether it takes use of control points (CP), can be divided into two main categories: the method based on imaging model [2][3][4][5] and the method based on SAR image simulation [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Automated Sar Reference Image Preparation for Navigation

Ren¹,

Chang²,

Jin³

et al. 2011

PIER

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Abstract-The preparation of good navigational synthetic aperture radar (SAR) reference image is critical to the SAR scene matching aided navigation system, especially for complex terrain. However, few papers discuss the problem, and almost none of the methods proposed by them are fully automatic. Based on the practical requirements, a fully automated method of SAR reference image preparation is introduced. Firstly, a number of distinctive control points (CP) in the simulated SAR image is detected based on a method of image segmentation and clustering. Then, the corresponding tie-points in the real SAR image are searched based on local similarity by means of template matching. To improve the accuracy of CP, a method for segmentation threshold calculation, outlier screening and sub-pixel location computation is presented. Finally, the real SAR image is warped to the simulated one, and then projected to the frame of digital elevation model (DEM) by the polynomial mapping function. Experimental results on real data sets demonstrate the accuracy and efficiency of the proposed method.

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Solid‐Surface Sensing: Microwave and Radio Frequencies

Elachi

Zyl

2006

Introduction to the Physics and Techniques of Remote Sensing

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Location of Spaceborne Sar Imagery

Cited by 215 publications

References 1 publication

A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization

A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization

Automated Sar Reference Image Preparation for Navigation

Solid‐Surface Sensing: Microwave and Radio Frequencies

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