Abstract: Embodiment of the present disclosure disclose a tomographic imaging system for reconstructing an image of an internal structure of an object. An incident wavefield is transmitted into the object occupying a background domain embedding the object. The incident wavefield is scattered into multiple scattered wavefield by the object. The incident and scattered wavefields are measured as a total wavefield. The total wavefield propagates through a computational domain and a residual domain in the background domain that are defined by cross-domain and residual measurement operators. The total wavefield is used for the image reconstruction. The image is reconstructed by solving an optimization problem corresponding to the computational domain. The optimization problem is solved iteratively to minimize a difference between the total wavefield and a wavefield synthesized using a measurement operator and a Green's function operator from the reconstructed image.

Abstract: An optical coherence tomography (OCT) system comprises an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern. The OCT system also comprises a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers. A computer-readable memory of the OCT system is configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers. The OCT system further comprises a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.

Abstract: Embodiments of the present disclosure provide a wire electric discharge machine (EDM) including a delivery system with one or combination of a wire electrode and a workpiece for delivering the wire electrode and the workpiece into proximity of each other and an energy source for creating electric discharge between the wire electrode and the workpiece. The wire EDM includes a wire electrode position measurement unit including light source to illuminate the wire electrode with encoded illumination pattern and a camera for acquiring a set of images of the wire electrode illuminated by the encoded illumination pattern. The wire EDM includes a processor to reconstruct positions of a segment of the wire electrode at a reconstruction rate greater than an acquisition rate of the camera by utilization of compressive sensing with sparse reconstruction technique and a controller to control the delivery system and the energy source based on the reconstructed positions.

Abstract: The present disclosure provides a multiple-input multiple-output (MIMO) radar system and a method for detecting an object in a scene. The method comprises transmitting frequency modulated continuous wave (FMCW) in a radio frequency (RF) band, and collecting radar measurements of the scene sampled in a time-frequency domain within an intermediate frequency (IF) bandwidth. The method further comprises transforming the radar measurements into range-doppler space to produce measurements of different segments of the scene for different range-doppler bins formed by intersections of different range bins with different Doppler bins, classifying a presence of the hypothetical transmitter at different segments of the scene according to a signal model with an internal classification, combining the results of the classification to produce parameters of the object, and outputting the parameters of the object.

Abstract: A tracking system for tracking an expanded state of an object is provided. The tracking system comprises at least one processor and a memory having instructions stored thereon that, when executed by the at least one processor, cause the tracking system to execute a probabilistic filter that iteratively tracks a belief on the expanded state of the object, wherein the belief is predicted using a motion model of the object and is further updated using a compound measurement model of the object. The compound measurement model includes multiple probabilistic distributions constrained to lie on a contour of the object with a predetermined relative geometrical mapping to the center of the object. Further, the tracking system tracks the expanded state of the object based on the updated belief on the expanded state.

Abstract: A system and a method for tracking an expanded state of an object including a kinematic state indicative of a position of the object and an extended state indicative of one or combination of a dimension and an orientation of the object is provided herein. The system comprises at least one sensor configured to probe a scene including a moving object with one or multiple signal transmissions to produce one or multiple measurements of the object per the transmission, and a processor configured to execute a probabilistic filter tracking a joint probability of the expanded state of the object estimated by a motion model of the object and a measurement model of the object, wherein the measurement model includes a center-truncated distribution having predetermined truncation intervals. The system further comprises an output interface configured to output the expanded state of the object.

Abstract: Systems and methods for image processing for determining a registration map between a first image of a scene with a second image of the scene, include solving an optimal transport (OT) problem to produce the registration map by optimizing a cost function that determines a minimum of a ground cost distance between the first and the second images modified with an epipolar geometry-based regularizer including a distance that quantifies the violation of an epipolar geometry constraint between corresponding points defined by the registration map. The ground cost compares a ground cost distance of features extracted within the first image with a ground cost distance of features extracted from the second image.

Abstract: A radar image processing device is provided for generating a radar image from a region of interest (ROI). The radar image processing device receives transmitted radar pulses and radar echoes reflected from the ROI at different positions along a path of a moving radar platform and stores computer-executable programs including a range compressor, a graph modeling generator, a signal aligner, a radar imaging generator and a focused image generator.

Abstract: Embodiment of the present disclosure disclose a tomographic imaging system for reconstructing an image of an internal structure of an object. An incident wavefield is transmitted into the object occupying a background domain embedding the object. The incident wavefield is scattered into multiple scattered wavefield by the object. The incident and scattered wavefields are measured as a total wavefield. The total wavefield propagates through a computational domain and a residual domain in the background domain that are defined by cross-domain and residual measurement operators. The total wavefield is used for the image reconstruction. The image is reconstructed by solving an optimization problem corresponding to the computational domain. The optimization problem is solved iteratively to minimize a difference between the total wavefield and a wavefield synthesized using a measurement operator and a Green's function operator from the reconstructed image.

Abstract: A tracking system for tracking an expanded state of an object is provided. The tracking system executes, for a predetermined time period, a probabilistic filter that iteratively tracks a belief on the expanded state of the object, wherein the belief is predicted using a motion model of the object and is further updated using a compound measurement model of the object. After the predetermined time period, the updated beliefs are smoothed to generate a state-decoupled online batch of training data. The compound measurement model includes multiple probabilistic distributions constrained to lie around a contour of the object with a predetermined relative geometrical mapping to the center of the object. The compound measurement model is updated using the online batch of training data. Further, the tracking system tracks the expanded state of the object based on the updated compound measurement model.

Abstract: The present disclosure provides a system and a method for generating a radar image of a scene. The method comprises receiving radar measurements of a scene collected from a set of antennas, wherein the set of antennas are under uncertainties caused by one or a combination of position ambiguities and clock ambiguities of each of the antennas. The method further comprises generating the radar image of the scene by solving a sparse recovery problem. The sparse recovery problem determines, until a termination condition is met, a set of image shifts of the radar image corresponding to different uncertainties of the antennas and updates an estimate of the radar image, based on the determined set of image shifts of the radar image. The sparse recovery problem is solved with a neural network denoiser that denoises a filtering of the estimate of the radar image.

Abstract: A permittivity sensor, for determining an image of a distribution of permittivity of a material of an object in a scene, comprising an input interface, a hardware processor, and an output interface is provided. The input interface is configured to accept phaseless measurements of propagation of a known incident field through the scene and scattered by the material of the object in the scene. The hardware processor is configured to solve a multi-variable minimization problem over unknown phases of the phaseless measurements and unknown image of the permittivity of the material of the object by minimizing a difference of a nonlinear function of the known incident field and the unknown image with a product of known magnitudes of the phaseless measurements and the unknown phases. Further, the output interface is configured to render the permittivity of the material of the object provided by the solution of the multi-variable minimization problem.

Abstract: A system and a method for tracking an expanded state of an object including a kinematic state indicative of a position of the object and an extended state indicative of one or combination of a dimension and an orientation of the object is provided herein. The system comprises at least one sensor configured to probe a scene including a moving object with one or multiple signal transmissions to produce one or multiple measurements of the object per the transmission, and a processor configured to execute a probabilistic filter tracking a joint probability of the expanded state of the object estimated by a motion model of the object and a measurement model of the object, wherein the measurement model includes a center-truncated distribution having truncation intervals. The system further comprises an output interface configured to output the expanded state of the object.

Abstract: Systems and methods for image processing for determining a registration map between a first image of a scene with a second image of the scene, include solving an optimal transport (OT) problem to produce the registration map by optimizing a cost function that determines a minimum of a ground cost distance between the first and the second images modified with an epipolar geometry-based regularizer including a distance that quantifies the violation of an epipolar geometry constraint between corresponding points defined by the registration map. The ground cost compares a ground cost distance of features extracted within the first image with a ground cost distance of features extracted from the second image.

Abstract: A multiple input multiple output (MIMO) radar system for detecting a moving object is based on an explicit signal model. The explicit signal model accounts for waveform separation residuals by relating measurements of the virtual array to an auto-term including a Kronecker product of object-receiver signatures and transmitter-object signatures; and a cross-term including a Kronecker product of object-receiver signatures and transmitter-object residual signatures. The radar system uses a spatial MIMO object detector that is based on the explicit signal model to detect the moving object.

Abstract: A tracking system for tracking an expanded state of an object is provided. The tracking system comprises at least one processor and a memory having instructions stored thereon that, when executed by the at least one processor, cause the tracking system to execute a probabilistic filter that iteratively tracks a belief on the expanded state of the object, wherein the belief is predicted using a motion model of the object and is further updated using a compound measurement model of the object. The compound measurement model includes multiple probabilistic distributions constrained to lie on a contour of the object with a predetermined relative geometrical mapping to the center of the object. Further, the tracking system tracks the expanded state of the object based on the updated belief on the expanded state.

Abstract: An imaging system to reconstruct a reflectivity image of a scene including an object moving with the scene. A tracking system to track a deforming object to estimate an object deformation for each time step. Sensors acquire snapshots of the scene, each acquired snapshot of the object includes measurements in the object deformation for that time step, to produce a set of object measurements with deformed shapes over the time steps. Compute a correction to estimates of object deformation for each time step, with matching measurements of the corrected object deformation for each time step to measurements in the acquired snapshot of object for that time step. Select a corrected deformation over other corrected deformations for each time step, according to a distance between the corrected deformation and the estimate of the deformation, to obtain a final estimate of the deformation of the deformable object moving in the scene.

Abstract: Systems, methods and apparatus for image processing for reconstructing a super resolution image from multispectral (MS) images. Receive image data and initialize a fused image using a panchromatic (PAN) image, and estimate a blur kernel between the PAN image and the MS images as an initialization function. Iteratively, fuse a MS image with an associated PAN image of a scene using a fusing algorithm. Each iteration includes: update the blur kernel based on a Second-Order Total Generalized Variation function to regularize a kernel shape; fuse the PAN image and MS images with the updated blur kernel based on a local Laplacian prior function to regularize the high-resolution information to obtain an estimated fused image; compute a relative error between the estimated fused image of the current iteration and a previous estimated fused image from a previous iteration, to a predetermined threshold, to stop iterations stop, to obtain a PAN-sharpened image.

Abstract: A radar system for generating a radar image of a scene. Receive radar measurements of reflectivity of each point in the scene measured by receivers. Solve a radar image recovery (RIR) problem using stored data to produce the radar image. By connecting the radar measurements to a shift of a reflection field with a receiver shift. The receiver shift defines an error between stored receiver positions and actual receivers positions, the reflection field is generated by reflecting the transmitted field from the scene in accordance with the reflectivity of each point in the scene. Connecting the reflection field to a shift of an incident field with a transmitter shift. The transmitter shift defines an error between stored transmitter positions and actual transmitters positions. Solve as a multilinear problem of joint estimation of the reflectivity of each point in the scene, the receiver shift, and the transmitter shift.

Abstract: An imaging system to reconstruct a reflectivity image of a scene including an object moving with the scene. A tracking system to track a deforming object to estimate an object deformation for each time step. Sensors acquire snapshots of the scene, each acquired snapshot of the object includes measurements in the object deformation for that time step, to produce a set of object measurements with deformed shapes over the time steps. Compute a correction to estimates of object deformation for each time step, with matching measurements of the corrected object deformation for each time step to measurements in the acquired snapshot of object for that time step. Select a corrected deformation over other corrected deformations for each time step, according to a distance between the corrected deformation and the estimate of the deformation, to obtain a final estimate of the deformation of the deformable object moving in the scene.