WO2007071113A1 - Procede interferometrique de correlation d'isolignes en trois images pour la generation d'un interferogramme de radar - Google Patents

Procede interferometrique de correlation d'isolignes en trois images pour la generation d'un interferogramme de radar Download PDF

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Publication number
WO2007071113A1
WO2007071113A1 PCT/CN2005/002287 CN2005002287W WO2007071113A1 WO 2007071113 A1 WO2007071113 A1 WO 2007071113A1 CN 2005002287 W CN2005002287 W CN 2005002287W WO 2007071113 A1 WO2007071113 A1 WO 2007071113A1
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Prior art keywords
window
images
image
complex
interference phase
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PCT/CN2005/002287
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English (en)
Chinese (zh)
Inventor
Qifeng Yu
Sihua Fu
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Qifeng Yu
Sihua Fu
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Priority to PCT/CN2005/002287 priority Critical patent/WO2007071113A1/fr
Publication of WO2007071113A1 publication Critical patent/WO2007071113A1/fr

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88Radar or analogous systems specially adapted for specific applications
    • G01S13/89Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021SAR image post-processing techniques
    • G01S13/9023SAR image post-processing techniques combined with interferometric techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/30Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/32Determination of transform parameters for the alignment of images, i.e. image registration using correlation-based methods

Definitions

  • the invention relates to the fields of geodesy, earth science and spatial information science, and further relates to a three-graph processing method for accurately registering interferometric synthetic aperture radar complex image pairs and generating interferometric synthetic aperture radar interferometric phase maps.
  • Synthetic Aperture Radar Interferometry (InSAR) technology successfully synthesizes Synthetic Aperture Radar (SAR) imaging principles and interferometric techniques, using the sensor's system parameters, attitude parameters [and the geometric relationship between the orbits, etc. Measure the position of a three-dimensional space at a point on the surface and its small changes.
  • InSAR technology is developing in the direction of practical use, and continues to expand the application field.
  • the first two main steps of InSAR processing techniques are: accurate registration of complex image pairs and generation of interference phase maps.
  • the single-view complex image pair used contains four images: 2 real data and 2 imaginary data.
  • the registration algorithm for InSAR complex image pairs proposes the coherence coefficient method, the maximum interference spectrum method, and the phase difference image average wave function method.
  • the purpose is to find the control points accurately and reliably, and all of them must be used.
  • Four map information for the image pair is to find the control points accurately and reliably, and all of them.
  • the generation of the interference phase map mainly adopts the method of conjugate multiplication.
  • Record (: r, X) and V 2 (r, X) are the complex values of the two complex images after accurate registration (called V i ⁇ x) as the main image, and V 2 (r, x) as the auxiliary image. ), then -
  • a and A are the echo phases of the two antennas containing noise, respectively, which consist of two parts: one is the phase A determined by the round-trip path. And, the other part is the random phase ⁇ and ⁇ caused by different scattering characteristics.
  • the interference phase obtained by this method contains de-correlated noise.
  • the existing method uses the four map information of the single-view complex image pair to accurately register the complex image pair and generate the interference phase map, and the generated interference phase map speckle noise is very serious.
  • Figure 1 shows the interference phase diagram obtained by this method. The existence of such high noise seriously affects the phase unwrapping and the acquisition of high-precision digital elevation maps, which has become a bottleneck in the processing of interferometric synthetic aperture radar data. Summary of the invention
  • the technical problem to be solved by the present invention is that, in view of the defects existing in the prior art, a three-pattern isoline correlation interferometry method for generating a radar interference phase map is proposed, including a complex image pair fine registration method and an interference phase map generation method.
  • the method of real imaginary part of the window such as a rectangle
  • the method of the real part of the fringe contour window is replaced by the traditional method
  • the InSAR complex image pair is registered
  • the interference phase map is generated; It is necessary to take three frames from the four images of the complex image pair to complete the processing process, and the registration accuracy is improved, and the obtained interference phase map has high signal-to-noise ratio.
  • the main image and the auxiliary image are registered by a registration quality evaluation criterion g directly related to the noise term, and the matching window in the template window and the auxiliary image in the main image are both x (m, n is greater than 0) Number of rectangles;
  • the ⁇ > operator represents the mean value of a variable in the range of x pixels; ⁇ represents various decorrelated noise; represents the amplitude of the main image; A 2 represents the amplitude of the secondary image.
  • the method for generating an InSAR interference phase map of the three images is:
  • the window may be a striped contour window or a rectangular and other form of window.
  • the relevant formulas used may be various mathematical expressions such as standardization correlation and standardization covariance correlation.
  • standardization correlation and standardization covariance correlation.
  • standardization correlation and standardization covariance correlation.
  • standardization covariance correlation The following is an example of standardizing related formulas.
  • the mxn operator represents the mean of a variable over the range of m ⁇ pixels.
  • the phase change amount is in the x « pixel window area.
  • the relevant formulas used may be direct mathematical correlations, covariance (mean normalization) correlations, standardization correlations, and standardized covariance correlations.
  • the following is an example of a direct correlation formula.
  • the direct correlation formula is as follows:
  • equation (17) is available:
  • the above-mentioned derivation process can be satisfied by taking three of the four images of the complex image pair, that is, an interference phase diagram containing no noise can be obtained.
  • the optimal window for correlation operations is the fringe contour window, which provides the best interference phase map of quality and precision. You can also select rectangles and other forms of windows to get better approximation results.
  • the fringe contour window is a kind of curved window, which is a window formed by a certain length and width along the stripe direction of the interference phase diagram, which can be obtained from the interference phase map generated by the conjugate multiplication method, or can be a window such as a rectangle.
  • the interference phase map generated by the three graph methods ie, taking three of the four images of the complex image pair
  • Stripe contour windows can be obtained by different algorithms, which are not part of the present invention and will not be described here.
  • the present invention is a three-pattern isoline correlation interferometry method for generating a radar interferogram phase map, including three map contour correlation interferometry methods for accurately registering InSAR complex image pairs and generating an interference-free spotted InSAR interferogram phase map.
  • the real imaginary part correlation method of the window and the real part of the fringe contour window are replaced by the traditional method, the nSAR complex image pair is registered, and the interference phase map is generated.
  • the method of the present invention only needs to take three frames from the four images of the complex image pair to complete the processing process, and the registration precision is improved, and the obtained interference phase map has high signal-to-noise ratio.
  • the method of the present invention only needs to transmit the three image information of the complex image pair to the ground, thereby realizing the subsequent data processing process of InSAR, which can be very large. The transmission time and bandwidth are saved to a certain extent.
  • the method of the present invention provides a new approach to InSAR data processing.
  • Figure 1 is an interference phase diagram generated by conjugate multiplication of two complex images after accurate registration, with an image size of 800 x 800 pixels.
  • Figure 2 (a), (b), (c), (d) are three images of a rectangular window with 1 X 1, 3 X 3, 5 X 5, 7 X 7 after exact registration.
  • the interference phase map obtained by the method.
  • Figure 3 is an interference phase diagram generated by the three-strip contour method of two complex images after precise registration.
  • the stripe contour window size is 31 X 3 .
  • Example 1 The InSAR complex image pair registration method for the three images is:
  • the template window in the main image and the matching window in the secondary image are both (m, n is a number greater than 0) rectangular window ⁇ .
  • the matching window in the template window and the secondary image in the main image is w " (m, n is a number greater than 0) the line contour window.
  • Embodiment 2 The InSAR interferogram phase map generation method of the three pictures is:
  • Fig. 2 (a), (b), (c), and (d) are interference phase diagrams obtained by rectangular windows of 1 X 1, 3 X 3, 5 X 5, and 7 X 7, respectively.
  • Figure 3 is a thousand phase diagram generated with a fringe contour window with a stripe contour window size of 31 X 3 .

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

La présente invention concerne un procédé interférométrique de corrélation d'isolignes en trois images pour la génération d'un interférogramme de radar comprenant un procédé d'enregistrement conjoint précis d'images complexes comprenant les étapes suivantes: la réalisation d'un enregistrement conjoint d'une image maîtresse et d'une image esclave grâce à une règle d'estimation g de corrélation à un élément de bruit Δu, toutes les fenêtres d'appariement d'images étant de fenêtres rectangulaires; la génération d'un interférogramme par un procédé en trois images afin d'obtenir une image à direction de bande et une fenêtre d'isoligne de bande; une nouvelle réalisation d'enregistrement conjoint d'images. L'invention concerne également un procédé de génération d'interférogramme comprenant les étapes suivantes: le prélèvement d'une fenêtre centrée sur chaque pixel correspondant dans les deux images complexes, la corrélation entre elles des données des deux images complexes dans les fenêtres afin d'obtenir leur coefficient de corrélation C1; la corrélation de la partie réelle de la donnée de la première image complexe avec la partie imaginaire de la donnée de la deuxième image complexe de manière similaire, permettant ainsi l'obtention d'un coefficient de corrélation C2; l'obtention de l'interférogramme à partir de l'arc tangente d'arc du rapport C2 sur C1. Le procédé ne peut être réalisé que par trois images.
PCT/CN2005/002287 2005-12-22 2005-12-22 Procede interferometrique de correlation d'isolignes en trois images pour la generation d'un interferogramme de radar WO2007071113A1 (fr)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102323570A (zh) * 2011-05-24 2012-01-18 中国人民解放军国防科学技术大学 一种雷达目标回波信号模拟器的幅相特性估计方法
CN107085208A (zh) * 2017-04-20 2017-08-22 中国人民解放军海军工程大学 基于分段曲面拟合的干涉合成孔径声纳复图像配准方法
CN108663678A (zh) * 2018-01-29 2018-10-16 西北农林科技大学 基于混合整数优化模型的多基线InSAR相位解缠算法
CN112034457A (zh) * 2020-07-21 2020-12-04 西安电子科技大学 基于干涉条纹方向的多基线高程干涉相位估计方法
CN113592930A (zh) * 2021-08-04 2021-11-02 桂林电子科技大学 一种空间外差干涉图像配准预处理方法
CN114609635A (zh) * 2022-03-17 2022-06-10 电子科技大学 一种基于视频合成孔径雷达的干涉测量方法
US11933883B2 (en) 2021-09-24 2024-03-19 Aloft Sensing, Inc. System and method for self-contained high-precision navigation

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CN1680826A (zh) * 2004-04-09 2005-10-12 中国人民解放军国防科学技术大学 生成无干涉斑合成孔径雷达干涉相位图的实虚部相关方法

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US6795590B1 (en) * 2000-09-22 2004-09-21 Hrl Laboratories, Llc SAR and FLIR image registration method
CN1680826A (zh) * 2004-04-09 2005-10-12 中国人民解放军国防科学技术大学 生成无干涉斑合成孔径雷达干涉相位图的实虚部相关方法

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102323570A (zh) * 2011-05-24 2012-01-18 中国人民解放军国防科学技术大学 一种雷达目标回波信号模拟器的幅相特性估计方法
CN107085208A (zh) * 2017-04-20 2017-08-22 中国人民解放军海军工程大学 基于分段曲面拟合的干涉合成孔径声纳复图像配准方法
CN107085208B (zh) * 2017-04-20 2022-12-13 中国人民解放军海军工程大学 基于分段曲面拟合的干涉合成孔径声纳复图像配准方法
CN108663678A (zh) * 2018-01-29 2018-10-16 西北农林科技大学 基于混合整数优化模型的多基线InSAR相位解缠算法
CN112034457A (zh) * 2020-07-21 2020-12-04 西安电子科技大学 基于干涉条纹方向的多基线高程干涉相位估计方法
CN112034457B (zh) * 2020-07-21 2022-02-22 西安电子科技大学 基于干涉条纹方向的多基线高程干涉相位估计方法
CN113592930A (zh) * 2021-08-04 2021-11-02 桂林电子科技大学 一种空间外差干涉图像配准预处理方法
US11933883B2 (en) 2021-09-24 2024-03-19 Aloft Sensing, Inc. System and method for self-contained high-precision navigation
CN114609635A (zh) * 2022-03-17 2022-06-10 电子科技大学 一种基于视频合成孔径雷达的干涉测量方法

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