Exemplary aspects are directed to or involve a radar transceiver to transmit signal and receive reflected radar signals via a communication channel. The exemplary method includes radar receiver data processing circuitry that may be used to differentiate a subset of representations of the received signals. This differentiation may be used to select signals that are more indicative of target(s) having a given range than other ones of the received signals. The received signal's representations may then be compressed by using variable-mantissa floating-point numbers having mantissa values that vary based, at least in part, on at least one strength characteristic of the respective representations.

This invention is directed to an image processing apparatus that generates an evaluation index of a persistent scatterer likelihood without any influence of a large phase change with respect to a target whose displacement is nonlinear, a target whose elevation is high, or a target whose displacement is large. The image processing apparatus includes a phase array accumulator that accumulates phase arrays of respective pixels over a plurality of images, a clustering unit that classifies the respective pixels into a plurality of clusters based on the phase arrays, and a phase correlation calculator that calculates a correlation between a phase change in each of the plurality of clusters and the phase array at the respective pixels.

This invention is directed to an image processing apparatus that generates an evaluation index of a persistent scatterer likelihood without any influence of a large phase change with respect to a target whose displacement is nonlinear, a target whose elevation is high, or a target whose displacement is large. The image processing apparatus includes a phase array accumulator that accumulates phase arrays of respective pixels over a plurality of images, a clustering unit that classifies the respective pixels into a plurality of clusters based on the phase arrays, and a phase correlation calculator that calculates a correlation between a phase change in each of the plurality of clusters and the phase array at the respective pixels.

The Fractional Fourier Transform (FrFT) may be used to extract multiple radar targets in clutter where some targets may be relatively weak. To do this, stronger targets may be removed by rotating to the proper axis t.sub.a using rotational parameter a, in which the target signal becomes a strong tone. By searching for the maximum peak over all values of a, stronger moving target echoes can be found and notched out, and weaker targets can then be extracted.

The methods and device disclosed herein provide an array such as a Radio Frequency (FR) antenna array for measuring the array movement or displacement of the array relative to a reference location. In some cases the array may be attached to or in communication with the device. The array comprises at least two transducers (e.g. RF antennas), wherein at least one of the at least two transducers is configured to transmit a signal towards the object, and at least one transceiver attached to said at least two transducers, the at least one transceiver is configured to repetitively transmit at least one signal toward an object and receive a plurality of signals affected or reflected while the array is moved in proximity to the object/medium or scene; and at least one processor unit, configured to: process the affected signals to yield a plurality of signal measurements and compare said signal measurements obtained at different locations over time of said second object and calculate a movement of the object relative to a reference location.

Systems and methods for satellite Synthetic Aperture Radar (SAR) artifact suppression for enhanced three-dimensional feature extraction, change detection, and/or visualizations are described. In some aspects, the described systems and methods include a method for suppressing artifacts from complex SAR data associated with a scene. In some aspects, the described systems and methods include a method for creating a photo-realistic 3D model of a scene based on complex SAR data associated with a scene. In some aspects, the described systems and methods include a method for identifying three-dimensional (3D) features and changes in SAR imagery.

Disclosed are an optimization method and apparatus for an Interferometric Synthetic Aperture Radar (InSAR) time-series phase. The optimization method includes: obtaining a time-series SAR data set, and performing registration and L-looks processing on the time-series SAR data set to obtain an L-looks intensity data set and an interferometric data set respectively; taking the L-looks intensity data set as a reference, obtaining a preset digital elevation model (DEM) and a preset land cover image, performing registration and geocoding on the preset DEM to obtain a digital elevation in a SAR image coordinate system, and performing registration and geocoding on the preset land cover image to obtain a land cover image in the SAR image coordinate system; performing a differential operation on the interferometric data set to obtain a differential interferometric data set; and estimating a covariance matrix at each spatial pixel position, and estimating and obtaining an optimized time-series phase.

An aerial vehicle system for mapping an object buried in a subterranean surface, the aerial vehicle system including an aerial vehicle, an electronic sensor, a processor, and a memory. The memory includes instructions, which when executed by the processor, cause the system to receive a first input data set by the electronic sensor, the first input data set based on an electromagnetic signal and geographic location data, generate a raw image based on the first input data set, and compare the raw image to a calibration data set, the calibration data set based on material calibration data. The material calibration data is based on unique spectral reflection patterns of an object in a controlled environment at predefined heights and subterranean conditions.

A computer includes a processor and a memory storing instructions executable by the processor to receive radar data including a radar pixel having a radial velocity from a radar; receive camera data including an image frame including camera pixels from a camera; map the radar pixel to the image frame; generate a region of the image frame surrounding the radar pixel; determine association scores for the respective camera pixels in the region; select a first camera pixel of the camera pixels from the region, the first camera pixel having a greatest association score of the association scores; and calculate a full velocity of the radar pixel using the radial velocity of the radar pixel and a first optical flow at the first camera pixel. The association scores indicate a likelihood that the respective camera pixels correspond to a same point in an environment as the radar pixel.

An example autonomous or remotely piloted aircraft includes a virtual aperture radar system including a plurality of antennas relationally positioned on one or more surfaces of the aircraft such that individual beams from each of the plurality of antennas scan respective volumes around the aircraft and the respective volumes together substantially form an ellipsoidal field of regard around the aircraft, and a computing device having one or more processors configured to execute instructions stored in memory for performing functions of: combining the respective volumes together to form an image representative of the ellipsoidal field of regard around the aircraft, and identifying one or more objects within the image.