A distributed microwave radar imaging method includes obtaining a first echo signal received by a first microwave radar, where the first microwave radar is disposed at a first height; obtaining a second echo signal received by a second microwave radar, where the second microwave radar is disposed at a second height, and the first height is lower than the second height; determining a first radar imaging result image of a detected target based on the first echo signal; determining a second radar imaging result image of the detected target based on the second echo signal; fusing the first radar imaging result image and the second radar imaging result image to obtain a target fused image; and determining outline information of the detected target based on the target fused image.

A vehicle (AV) includes a radar sensor and a hardware logic component. The radar sensor receives a radar return from a driving environment of the vehicle and outputs radar data that is indicative of the return to the hardware logic component. The hardware logic component further receives data indicative of a velocity of the vehicle from a sensor mounted on the vehicle. The hardware logic component is configured to employ synthetic aperture radar (SAR) techniques to compute a three-dimensional position of a point on a surface of an object in the driving environment of the vehicle based upon the radar data and the velocity of the vehicle.

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 radar anti-spoofing system for an autonomous vehicle includes a plurality of radar sensors that generate a plurality of input detection points representing radio frequency (RF) signals reflected from objects and a controller in electronic communication with the plurality of radar sensors. The one or more controllers execute instructions to determine a signal to noise ratio (SNR) distance ratio for the input detection points generated by the plurality of radar sensors, where a value of the SNR distance ratio is indicative of an object being a ghost vehicle. The one or more controllers also determine an effective particle number indicating a degree of particle degradation for the importance sampling for each variable that is part of the state variable. In response to determining the effective particle number is equal to or less than a predetermined threshold, the one or more controllers estimate a ghost position for the ghost vehicle.

A radar anti-spoofing system for an autonomous vehicle includes a plurality of radar sensors that generate a plurality of input detection points representing radio frequency (RF) signals reflected from objects and a controller in electronic communication with the plurality of radar sensors. The controller executes instructions to determine time-matched clusters that represent objects located in an environment surrounding the autonomous vehicle based on the input detection points from the plurality of radar sensors. The controller determines an adjusted signal to noise (SNR) measure for a specific time-matched cluster by dividing an SNR of the specific time-matched cluster by a range measurement of the specific time-matched cluster. The controller determines a velocity-ratio measure of the time-matched cluster by dividing a motion-based velocity by a Doppler-frequency velocity, and identifies the time-matched cluster as either a ghost object or a real object.

Disclosed is a synthetic aperture radar (SAR) system for target recognition with complex range profile. The SAR system comprising a memory, a recurrent neural network (RNN), a multi-layer linear network in signal communication the RNN, and a machine-readable medium on the memory. The machine-readable medium is configured to store instructions that, when executed by the RNN, cause the SAR system to perform various operations. The various operation comprise: receiving raw SAR data associated with observed views of a scene, wherein the raw SAR data comprises information captured via the SAR system; radio frequency (RF) preprocessing the received raw SAR data to produce a processed raw SAR data; converting the processed raw SAR data to a complex SAR range profile data; processing the complex SAR range profile data with the RNN having RNN states; and mapping the RNN states to a target class with the multi-layer linear network.

A millimeter-wave three-dimensional holographic imaging method and system. The method comprises: transmitting a continuous frequency wave to a measured human body, and receiving an echo signal reflected back; performing Fourier transform, phase compensation, inverse Fourier transform, and “non-uniform sampling to uniform sampling” interpolation; and projecting three-dimensional echo data to obtain two-dimensional reconstruction data, and generating a two-dimensional reconstructed image.

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. The radar image processing device performs range compression on the radar echoes by deconvolving the transmitted radar pulses and a radar measurement to obtain frequency-domain signals, generate a graph model represented by sequential positions of the moving radar platform and a graph shift matrix computed using the frequency-domain signals, iteratively denoise and align the frequency-domain signals to obtained denoised data and time shifts by solving a graph-based optimization problem represented by the graph model, wherein the approximated time shifts compensate phase misalignments caused by perturbed positions of the moving radar platform, and perform radar imaging based on the denoised data and the estimated time shifts to generate focused radar images.

Embodiments include a system and a method for determining a geographic location corresponding to pixels in a scan. For a scan of an area including a plurality of pixels, measurements of at least one physical property may be received. An embodiment may include identifying in the scan at least a first pixel and a second pixel corresponding to known at least a first and a second geographical locations; creating a set of pixel values vectors, for each pixel values vector calculating a correlation factor between the pixel values vector and a vector that includes the measurements; selecting a pixel values vector, from the set of pixel values vectors, for which a correlation factor higher than a threshold value was calculated; and determining the actual geographic location of the area represented by each pixel in the selected pixel values vector based on the known geographic locations.

A method for detecting a horizontally buried linear object is provided, the horizontally buried linear object having a longitudinal extension. The method comprises moving, with a flying platform comprising a radar for synthetic aperture radar, SAR, vertical imaging, along a trajectory corresponding to a synthetic aperture. The method further comprises transmitting and receiving radar signals while moving along the trajectory corresponding to the synthetic aperture. The method also comprises forming a SAR image based on collected data representing radar signal reflections received from the ground. The method additionally comprises detecting one or more features in the formed SAR image relating to the horizontally buried linear object. Said trajectory is oriented in a direction substantially perpendicular to an expected orientation of the longitudinal extension of the horizontally buried object and traversing the horizontally buried object.