Devices, systems, and methods for removing non-linearities in an inverse synthetic aperture radar (ISAR) image are provided. A method includes estimating pitch and roll about range and doppler axes of a time series of ISAR images including the ISAR image, interpolating ISAR image data based on the estimated pitch and roll resulting in interpolated ISAR image data, and resampling based on the interpolated ISAR image data and the time series of TSAR images resulting in an enhanced image.

One or more aspects of this disclosure relate to the usage of an impulse radio ultra-wideband (IR-UWB) radar to reconstruct a cross-sectional image of subject in a noninvasive fashion. This image is reconstructed based on the pre- and post-processing of recorded waveforms that are collected by the IR-UWB radar, after getting reflected-off the subject. Furthermore, a novel process is proposed to approximate the different tissues' dielectric constants and, accordingly, reconstruct a subject's cross-sectional image.

The image processing device 60 includes an image deformation unit 61 which deforms object presence areas in two object presence images, in which one or more objects are present, obtained from each of two observed images to generate two deformed images, based on an observation angle of each of the two observed images and a size of the object appearing in each of the two observed images, and an image generation unit 62 which generates a synthesized image by synthesizing the two deformed images, determines difference of the object between the two object presence images, and generates an image capable of identifying the determined difference.

An object of an example embodiment of the present disclosure is to stably estimate a navigation status of a target ship at a predetermined time from time-series position information of the ship. A ship behavior analyzing device according to the example embodiment of the present disclosure includes a ship detection means for detecting a ship from synthetic aperture radar data, a wake extraction means for extracting a wake of the detected ship, a wake pattern generation means for generating a wake pattern image by using the extracted wake, and a navigation status estimation means for estimating a navigation status of the target ship by using the generated wake pattern image.

One or more aspects of this disclosure relate to the usage of an impulse radio ultra-wideband (IR-UWB) radar to reconstruct a cross-sectional image of subject in a noninvasive fashion. This image is reconstructed based on the pre- and post-processing of recorded waveforms that are collected by the IR-UWB radar, after getting reflected-off the subject. Furthermore, a novel process is proposed to approximate the different tissues' dielectric constants and, accordingly, reconstruct a subject' cross-sectional image.

An information processing device according to one aspect of the present invention includes at least one memory storing instructions; and at least one processor coupled to the memory and configured to execute the instructions to: extract a candidate point which is a point contributing to a signal at a target point, based on a position of the target point in a three-dimensional space and a shape of an observed object, the target point being a point specified in an intensity map of the signal from the observed object, the intensity map being acquired by a radar; and generate an image indicating a position of the candidate point in a spatial image capturing the observed object.

Systems and methods according to one or more embodiments are provided for registration of synthetic aperture range profile data to aid in SAR-based navigation. In one example, a SAR-based navigation system includes a memory comprising a plurality of executable instructions. The SAR-based navigation system further includes a processor adapted to receive range profile data associated with observed views of a scene, compare the range profile data to a template range profile data of the scene, and estimate registration parameters associated with the range profile data relative to the template range profile data to determine a deviation from the template range profile data.

One example includes a radar image interface system. The system includes an image processor configured to receive synthetic aperture radar (SAR) image data associated with a region of interest and to generate a radar image of the region of interest based on the SAR image data. The image processor can be further configured to divide the radar image into a plurality of sequential units corresponding to respective zones of the region of interest. The system also includes a display system configured to display zoomed sequential units corresponding to respective zoomed versions of the sequential units of the radar image to a user. The system further includes an input interface configured to facilitate sequentially indexing through each of the zoomed versions of the sequential units on the display system in response to an indexing input provided by the user.

A method, a system, a device and a medium for landslide identification based on full Polarimetry Synthetic Aperture Radar (full PoISAR) are provided. The method mainly includes: registering target full PoISAR data with target optical remote sensing data and target digital elevation model data to obtain a first registration result and a second registration result; determining a polarization feature, a decomposition feature, and a terrain feature of a target area according to registration results; determining a texture feature and a hue feature of the target area according to the target full PoISAR data; determining a spectrum feature of the target area according to the target optical remote sensing data; fusing abovementioned multi-dimensional features to obtain a target fusion feature; and inputting the target fusion feature into a landslide mass identification model for identifying a landslide mass, so as to determine a landslide area in the target area.

A method (100) for referencing a digital elevation model (10), involving a step of obtaining (110) two SAR images (12, 14) having a common area (15) that their area of overlap (16, 17) shares with the digital model (10); the method (100) involving, for the SAR images (12, 14), steps of: selecting (120) an AOI (18) in the common area (15); calculating (130) a simulated image (22) in the AOI (18); estimating (140) an offset (di, dj) between the simulated image (22) and the SAR image (12); the method (100) involving steps of selecting a reference point (26) in the AOI (18); projecting (160) the reference point (26) into the SAR images (12, 14) to obtain one connection point per SAR image (12, 14); correcting (170) the connection points by the offsets (di, dj); calculating (180) the readjusted reference point (26); referencing (190) the digital model (10).