Abstract: A radar system for use in a vehicle moving in a first direction may include a plurality of antenna elements spaced apart in a second direction; and a controller operably connected to the plurality of antenna elements. The controller may be configured record signals received by each antenna element at each time instant of a plurality of time instants; calculate a position in the first direction of each antenna element for each time instant based on a velocity hypothesis; calculate a virtual two-dimensional antenna array response based on the signal received by each antenna element at each time instant and the position in the first direction of each antenna element at each time instant; calculate a beamforming spectrum based on the virtual two-dimensional antenna array response; and identify a peak in the beamforming spectrum to identify an elevation angle from the vehicle to a target relative to the first direction.

Abstract: Systems and methods involve transmitting both horizontal and vertical polarizations from a radar system. A method includes receiving, using a first antenna of the radar system, first reflected signals with horizontal polarization, and receiving, using a second antenna of the radar system, second reflected signals with vertical polarization. The first reflected signals and the second reflected signals are processed together to obtain one or more angles to respective one or more objects detected by the radar system.

Abstract: A vehicle radar system and calibration method that provide for system calibration so that target object parameters can be calculated with improved accuracy. Generally speaking, the calibration method uses a number of hypothesized calibration matrices, which represent educated guesses for possible system or array calibrations, to obtain a number of beamforming images. A blurring metric is then derived for each beamforming image, where the blurring metric is generally representative of the quality or resolution of the beamforming image. The method then selects hypothesized calibration matrices based on their blurring metrics, where the selected matrices are associated with the blurring metrics having the best beamforming image resolution (e.g., the least amount of image blurriness). The selected hypothesized calibration matrices are then used to generate new calibration matrices, which in turn can be used to calibrate the vehicle radar system so that more accurate target object parameters can be obtained.

Abstract: Systems and methods to perform object surface estimation using a radar system involve receiving reflected signals resulting from reflection of transmit signals by an object. The method includes processing the reflected signals to obtain an image. The image indicates an intensity associated with at least one set of angle values and a set of range values. The method also includes processing the image to provide the object surface estimation. The object surface estimation indicates a subset of the at least one set of angle values and associated ranges within the set of range values.

Abstract: A method and system involve obtaining reflected signals in a radar system using a first one-dimensional array of antenna elements and a second one-dimensional array of antenna elements. The reflected signals result from reflection of transmitted signals from the radar system by one or more objects. The method includes processing the reflected signals obtained using the first one-dimensional array of antenna elements to obtain a first array of angle of arrival likelihood values in a first plane, and processing the reflected signals obtained using the second one-dimensional array of antenna elements to obtain a second array of angle of arrival likelihood values. A four-dimensional image indicating a range, relative range rate, the first angle of arrival, and the second angle of arrival for each of the one or more objects is obtained.

Abstract: A radar system may include an antenna structured to transmit a radar signal and receive reflected radar signals from targets and a processor operably connected to the antenna. The radar system may receive a first reflected signal, having a first arrival angle, at a first time. The radar system may receive a second reflected signal, having a second arrival angle at a second time. The second arrival angle may be equal to the first arrival angle plus an angle offset calculated based on a velocity hypothesis. The radar system may translate the first vector by applying the angle offset, thereby calculating a translated first vector. The radar system may calculate a beamforming spectrum based on the translated first vector and the second vector. The radar system may identify peaks in the beamforming spectrum to identify angular positions of multiple targets.

Abstract: A system and method using a multi-node radar system involve receiving reflected signals at each node of the multi-node radar system, the reflected signals resulting from reflection of transmitted signals by one or more objects, and generating velocity lines associated with each of the reflected signals received at each of the nodes, each velocity line being derived from a radial velocity Vr and an angle of arrival ? determined from the reflected signal received at the node. The method also includes determining one or more intersection points of the velocity lines, and estimating a velocity of each of the one or more objects based on the one or more intersection points. Each intersection point corresponds with the velocity for one of the one or more objects and the velocity is a relative velocity vector between the one of the one or more objects and the radar system.

Abstract: A system and method to eliminate false detections in a radar system involve arranging an array of antenna elements into two or more sub-arrays with a spacing between adjacent ones of the antenna elements of one of the two or more sub-arrays being different than a spacing between adjacent ones of the antenna elements of at least one other of the two or more sub-arrays. The method includes receiving reflected signals at the two or more sub-arrays resulting from transmitting transmit signals from the antenna elements of the two or more sub-arrays, and processing the reflected signals to distinguish an actual angle from the radar system to an object that contributed to the reflected signals from ambiguous angles at which the false detections of the object are obtained. A location of the object is determined as a result of the processing.

Abstract: A vehicle, radar system of the vehicle and method of operating a radar system. The radar system includes a first sensor that generates a first chirp signal; a second sensor for generating a second chirp signal and which received reflected signals. One of the first sensor and second sensor receives a signal that includes a first reflected signal related to the first chirp signal and a second reflected signal related to the second chirp signal. A processor multiplies the received signal by one of the first chirp signal and the second chirp signal to obtain a desired signal indicative of one of the first reflected signal and the second reflected signal and an interference signal indicative of the other of the first reflected signal and the second reflected signal, and applies a filter to the mixed signal to separate the interference signal from the desired signal.

Abstract: A vehicle radar system, such as a multiple input multiple output (MIMO) radar system, for estimating a Doppler frequency shift and a method of using the same. In one example, a modulated signal is mixed with an orthogonal code sequence and is transmitted by a transmit antenna array with a plurality of transmitting antennas. The signals reflect off of a target object and are received by a receive antenna array with a plurality of receiving antennas. Each of the received signals, which likely includes a Doppler frequency shift, is processed and mixed with a number of frequency shift hypotheses that are intended to offset the Doppler frequency shift and result in a series of correlation values. The frequency shift hypothesis with the highest correlation value is selected and used to correct for the Doppler frequency shift so that more accurate target object parameters, such as velocity, can be obtained.

Abstract: A system and method to use deep learning for super resolution in a radar system include obtaining first-resolution time samples from reflections based on transmissions by a first-resolution radar system of multiple frequency-modulated signals. The first-resolution radar system includes multiple transmit elements and multiple receive elements. The method also includes reducing resolution of the first-resolution time samples to obtain second-resolution time samples, implementing a matched filter on the first-resolution time samples to obtain a first-resolution data cube and on the second-resolution time samples to obtain a second-resolution data cube, processing the second-resolution data cube with a neural network to obtain a third-resolution data cube, and training the neural network based on a first loss obtained by comparing the first-resolution data cube with the third-resolution data cube. The neural network is used with a second-resolution radar system to detect one or more objects.

Abstract: Deep learning in a radar system includes obtaining unaliased time samples from a first radar system. A method includes under-sampling the un-aliased time samples to obtain aliased time samples of a first configuration, matched filtering the un-aliased time samples to obtain an un-aliased data cube and the aliased time samples to obtain an aliased data cube, and using a first neural network to obtain a de-aliased data cube. A first neural network is trained to obtain a trained first neural network. The under-sampling of the un-aliased time samples is repeated to obtain second aliased time samples of a second configuration. The method includes training a second neural network to obtain a trained second neural network, comparing results to choose a selected neural network corresponding with a selected configuration, and using the selected neural network with a second radar system that has the selected configuration to detect one or more objects.

Abstract: A method and system to determine angle of arrival of a target include one or more transmitters, one or more receivers, and one local oscillator to provide a local reference signal each in two or more transceiver nodes. The system also includes a controller to determine obtained phase differences for each of the two or more transceiver nodes. Each of the obtained phase differences is between a signal transmitted by one of the one or more transmitters and received by one of the one or more receivers of a same one of the two or more transceiver nodes. The controller estimates the angle of arrival of the target based on the obtained phase differences determined for the two or more transceiver nodes.

Abstract: A system and method to resolve angle of arrival (AOA) ambiguity in a radar system include receiving received reflections at a plurality of transceiver nodes. Each transceiver node among the plurality of transceiver nodes of the radar system receives one or more of the received reflections at respective one or more receive elements. The method includes determining candidate AOAs {circumflex over (?)}i based on phases differences in the received reflections at the plurality of transceiver nodes, and determining Doppler frequencies fdi based on the received reflections. An estimated AOA {circumflex over (?)} is selected from among the candidate AOAs {circumflex over (?)}i based on matching metrics ?i between the Doppler frequencies and the candidate AOAs {circumflex over (?)}i.

Abstract: A system and method are provided for processing echo signals reflected from one of more targets in a radar field-of-view. The method includes receiving echo signals reflected from one or more targets in the radar field-of-view in response to a sequence of transmit pulses; generating a received signal vector containing samples from the received echo signals; and applying the received signal vector to a set of filters configured to calculate a Doppler spectrum for a set of Doppler frequencies to which each filter is tuned, wherein an integration processing time for each filter varies relative to the Doppler frequency of each filter.

Abstract: Systems, vehicles, and techniques are provided for the estimation of a linear velocity vector of an object. In some embodiments, a technique can include receiving first data indicative of first locations relative to an object at a first instant during movement of the object, and receiving second data indicative of second locations relative to the object at a second instant during the movement of the object. The technique also can include transforming the first data into third data corresponding to the second instant using at least one velocity vector hypothesis for a velocity of the object. The technique can further include solving an optimization problem with respect to a geometric volume of a convex hull of a union of the second data and the third data, and generating an estimate of a velocity of the object using a solution of the optimization problem.

Abstract: Systems, vehicles, and techniques are provided to classify reflection detection points in a sensing system. A reflection detection point can be classified as an apparent reflection or a physical reflection. In some embodiments, a beamforming map can be generated using a response function of an antenna array and data representative of electromagnetic signals received at the antenna array. Multiple reflection detection points can be detected using at least the beamforming map. A second beamforming distribution map also can be generated, using at least the data and a second response function of the array of antennas. The second response function includes minima at respective reflection points. A ratio between (i) a first amplitude of a reflection detection point in the second beamforming map and (ii) a second amplitude of the reflection point in the first beamforming map permits classifying the reflection detection point as an apparent reflection or a physical reflection.

Abstract: A system and method perform calibration of a radar system on a mobile platform. A position of the platform is obtained along with a relative position of one or more stationary objects from the platform using the position of the platform and a mapping algorithm as ground truth and one or more radar parameters regarding the one or more stationary objects using the radar system, the one or more radar parameters including an angle estimate. The method includes determining a correction matrix based on the one or more parameters and the ground truth, and obtaining corrected received signals from subsequent received signals of the radar system based on the correction matrix.

Abstract: A vehicle, radar system and method of determining an angle of arrival of an object is disclosed. A radar array generates a linear frequency modulated source signal and includes a first channel and a second channel for receiving a reflection of the source signal from the object. A processor obtains a channel response for the first radar channel and for the second radar channel over a bandwidth of the source signal, partitions the frequency band into a plurality of frequency sub-bands, determines a variation between the first and second channel responses for a selected frequency sub-band, receives a reflection of the source signal at the first channel and at the second channel, corrects at least the second channel within the frequency sub-band using the determined variation, and determines an angle of arrival for the object based on the correction within the frequency sub-band.

Abstract: A vehicle, radar system and method of operating a radar is disclosed. The radar system includes a radar array and a processor. The radar array includes at least a first radar node and a second radar node, with each of the first radar node and the second radar node having a plurality of subnodes. The processor determines a first far-field parameter measurement for an object for a first node of the radar using sub-nodes of the first node, determines a second far-field parameter measurement for the object for a second node of the radar using sub-nodes of the second node, and obtains a joint parameter measurement for the object by combining the first far-field parameter measurement with the second far-field parameter measurement by correcting for a near-field phase difference between the first node and the second node.