An image analysis device that ease association between an SAR image and an object is provided. The image analysis device includes: a stable reflection point identification unit that identifies, based on a plurality of synthetic aperture radar (SAR) images, stable reflection points at which reflection is stable in the plurality of SAR images; a phase identification unit that identifies a phase at each of the stable reflection points, based on the plurality of SAR images and a location of the stable reflection point in the plurality of SAR images; and a clustering means that clusters the stable reflection points, based on a Euclidian distance between each of the stable reflection points and a correlation of the phases at each of the stable reflection points.

A method for calculating a sensitivity of a displacement of Synthetic Aperture Radar (SAR) along line-of-sight direction to a slope gradient and a slope aspect is provided, comprising: obtaining SAR data and Digital Elevation Model (DEM) data covering slope bodies, and extracting a local incident angle of an image by utilizing a satellite side-looking imaging principle; carrying out geometric distortion on the slope bodies under ascending and descending orbits by utilizing the local incident angle, to obtain specific locations of geometric distortion areas under ascending and descending orbit; calculating sensitivities of detections to changes of the slope gradient and the slope aspect under ascending and descending orbits according to the extracted parameter information of the SAR satellite in ascending and descending orbits and satellite heights, and dividing a sensitivity distribution by combining the sensitivity and the specific locations of the geometric distortion.

A radar image processing device includes a phase difference calculating unit calculating a phase difference between phases with respect to a first and a second radio wave receiving points in each pixel at corresponding pixel positions among pixels in a first and a second suppression ranges, the first and the second suppression ranges being suppression ranges in a first and a second radar images capturing an observation area from the first and the second radio wave receiving points, respectively; and a rotation amount calculating unit calculating each phase rotation amount in the pixels in the second suppression range from each phase difference, wherein a difference calculating unit rotates phases in the pixels in the second suppression range based on the rotation amounts, and calculates a difference between pixel values at corresponding pixel position among the pixels in the first suppression range and phase-rotated pixels in the second suppression range.

Disclosed is a method for determining a dimension of a ship, the method being implemented by an electronic system with a radar device having two receiving channels. The method includes: acquiring, for each of the two receiving channels of the radar device, a synthetic aperture radar image imaging the ship in an environment; the sum of the respective amplitudes of the pixels of the two radar images to obtain a sum image; extracting pixels from the sum image imaging the ship to obtain a mask of the ship; determining a range of phase differences between the radar signals received by each of the two receiving channels; and determining a dimension of the ship as a function of the mask of the ship and the determined phase difference range.

Sparse phase unwrapping is disclosed. A first image and a second image are received. The first image and the second image are coregistered. The first image and the second image comprise respective phase data. An unwrapped interferogram is generated, including by solving an optimization problem using a nonconvex penalty function, where minimizing the penalty function produces sparse minimizers.

A synthetic-aperture-radar-signal processing device includes a range bin selection unit which selects, from an observed image, range bins including a signal from an isolated reflection point, a phase evaluation unit which evaluates phases in an azimuth direction in the range bins, a window function multiplication unit which designs a window function on the basis of results of the evaluation by the phase evaluation unit and multiply the range bins by the window function, and a phase error correction unit which corrects the observed image by estimating a phase error from the range bins multiplied by the window function.

A dam slope deformation monitoring system and method are provided. The monitoring system monitors an entire dam in a reservoir area by using an unmanned aerial vehicle (UAV) photogrammetry system, and determines an encrypted monitoring area (steep slope) with the relatively large deformation and a relatively large digital elevation difference; determines, in the intensive monitoring area, a first level key monitoring area with the larger deformation by using a ground-based radar interferometry measurement system; determines, in the first level key monitoring area, a second level key monitoring area with the larger deformation by using a ground-based three-dimensional lidar measurement system; determines, in the second level key monitoring area, a key monitoring particle with a high deformation speed by using a global navigation satellite system (GNSS). The core chip stack is used to monitor and warn the collapse process in the area where the key monitoring particles are located.

The image analyzing device includes an inter-image phase difference calculation unit 12 calculating a phase difference image of a pair of images, an inter-pixel phase difference calculation unit 13 calculating a phase difference between close pixels in the phase difference image, an evaluation function generation unit 14 generating an evaluation function that includes at least the phase difference between pixels, an optimization unit 15 optimizing the evaluation function for each pair of pixels or each pair of close pixels, a random number generation unit 21 generating a random number, a threshold setting unit 22 setting a threshold based on a result of evaluation of the random number using the evaluation function, and a merging unit 17 obtaining merged data of an entire image by merging values of variables when the optimization unit 15 performs optimization except for variables for which evaluation value using the evaluation function is below the threshold.

A system and method for identifying damage to an embankment includes acquiring satellite imagery of an area of the embankment, generating a set of input data from the satellite imagery, removing at least one anomaly in the set of input data to obtain a cleaned set of input data, and identifying the damage by determining a dam motion area indicative of ground motion in the embankment from the cleaned set of input data and determining an anomalous vegetation area and an anomalous wetness area indicative of seepage in the embankment from the cleaned set of input data.

Computer-implemented methods for detecting and characterizing surface depressions in a topographical landscape based on processing of high resolution digital elevation model data according to a local tree contour algorithm applied to an elevation contour representation of the landscape, and characterizing the detected surface depressions according to morphometric threshold values derived from data relevant to surface depressions of the topographical area. Non-transitory computer readable media comprising computer-executable instructions for carrying out the methods are also provided.