Disclosed herein are systems and methods for linearizing frequency chirp in a frequency-modulated continuous wave (FMCW) coherent LiDAR system. Exemplary methods can include generating a continuous wave laser signal having a frequency characteristic, in which the frequency characteristic can include a frequency chirp over a frequency band in at least one period; and receiving a signal based on the generated laser signal. The methods can further include mixing the received signal with a local oscillator signal, the local oscillator signal having the frequency characteristic; determining at least one beat frequency based on the mixed signal; sampling the mixed signal at a rate equal to at least two times the beat frequency; determining a correction signal based on the sampled signal; and applying the correction signal to the laser signal.

A frequency modulated continuous wave (FMCW) radar system includes an antenna array having C antennas where (C=A+B−1), a first integrated circuit (IC) device including A first sensor inputs, and a second IC device including B second sensor inputs. The first sensor inputs are coupled to a first A of the antennas, and the second sensor inputs are coupled to a last B of the antennas such that a common one of the first sensor inputs and a common one of the second sensor inputs are both coupled to a common antenna. Each IC device receives reflected signals on each sensor input, and mixes the reflected signals to associated baseband signals based upon a local oscillator (LO) signal. Each LO signal has a different phase shift. The LO signals are based upon a common LO signal.

Disclosed is a method and apparatus for processing a radar signal by correcting a phase distortion. The method includes generating radar data based on a radar transmission signal transmitted through an array antenna of a radar sensor based on a frequency modulation model and a radar reception signal received through the array antenna as the radar transmission signal is reflected by a target, correcting the radar data using a correction vector for correcting a feedline error occurring due to a feedline delay difference between channels of the array antenna, and estimating a direction of arrival corresponding to the corrected radar data using a direction matrix reflecting a phase shift of the corrected radar data according to frequency modulation characteristics of the frequency modulation model.

The present disclosure discloses a method for lane alignment detection based on millimeter wave radar data. An embodiment of the method comprises: acquiring the vehicle trajectory data and radar reflection data detected by the millimeter wave radar which are installed on the road to sense the moving vehicles; setting up two datasets in the database, including vehicle track dataset and waypoint dataset obtained after rasterizing the road; filtering vehicle track data and vehicle radar reflection data detected by millimeter-wave radar and eliminate erroneous data; performing radial clustering and horizontal initial stable point clustering on the filtered data; extracting and outputting the lane alignment. Compared with the prior art, the invention possesses the advantages of obtaining more accurate lane alignments, low cost and good adaptability, etc.

Disclosed herein are systems and methods for linearizing frequency chirp in a frequency-modulated continuous wave (FMCW) coherent LiDAR system. Exemplary methods can include generating a continuous wave laser signal having a frequency characteristic, in which the frequency characteristic can include a frequency chirp over a frequency band in at least one period; and receiving a signal based on the generated laser signal. The methods can further include mixing the received signal with a local oscillator signal, the local oscillator signal having the frequency characteristic; determining at least one beat frequency based on the mixed signal; sampling the mixed signal at a rate equal to at least two times the beat frequency; determining a correction signal based on the sampled signal; and applying the correction signal to the laser signal.

A device comprising circuitry configured to: obtain radar signal measurements simultaneously acquired by two or more radar sensors having overlapping fields of view, derive range information of one or more potential targets from samples of radar signal measurements of said two or more radar sensors acquired at the same time or during the same time interval, the range information of a single sample representing a ring segment of potential positions of a potential target at a particular range from the respective radar sensor in its field of view, determine intersection points of ring segments of the derived range information, determine a region of the scene having one of the highest densities of intersection points, select a ring segment per sensor that goes through the selected region, and determine the most likely target position of the potential target from the derived range information of the selected ring segments.

A method and processor to determine spatial information regarding a vehicle. The method includes receiving at least one initial frame of FMCW radar data including spatial information regarding the vehicle associated with a radar signal reflected back from the vehicle via a surface of at least one stationary object other than the vehicle. The method also includes receiving at least one further frame of FMCW radar data including: spatial information regarding the vehicle associated with a radar signal reflected back from the vehicle via the surface of at least one stationary object other than the vehicle, and spatial information regarding the vehicle associated with a radar signal reflected directly back from the vehicle. The method further includes using the at least one initial frame of radar data to correct for static clutter associated with the at least one stationary object in the at least one further frame of radar data.

In imaging radar, examples are directed to uses of multiple sets of transmit antenna included with transceiver circuitry, for transmitting in a plurality of modes. Transmissions may involve having at least one transmit antenna, from each of at least two of the multiple sets, to transmit continuous-wave energy concurrently (simultaneously) in one or more of the plurality of different modes. Transceiver circuitry may include multiple receive antennas which may be receiving reflections of the continuous-wave energy from various targets. Signals from the multiple receive antennas may route to signal processing circuitry. The signal processing circuitry may respond to the received reflections of the continuous-wave energy by assessing differences in antenna gain and/or phase due to transmit antenna position associated with the received reflections. This signal processing assessment may mitigate or resolve at least one spatial ambiguity in at least one direction of arrival dimension associated with the received reflections.

A multiple input multiple output imaging array for incident angle resolved images with respect to a device under test is provided. The multiple input multiple output imaging array comprises a redundant array of transmit and receive antennas and a controller. In this context, the controller is configured to implement a selection scheme, wherein the selection scheme selects the respective transmit and receive antenna pairs used to create the corresponding image.

This document describes techniques and systems to enable a radar system to detect angles in bistatic and monostatic scenarios. In some examples, an automotive radar system includes one or more processors. The processors can obtain electromagnetic (EM) energy reflected by objects and generate, based on the reflected EM energy, a two-dimensional (2D) data matrix. The 2D data matrix has a number of rows corresponding to the number of antenna elements in a transmitter array and a number of columns corresponding to the number of antenna elements in a receiver array. Using the 2D data matrix, the processors can determine DoA estimates and DoD estimates in monostatic and bistatic scenarios. By comparing the DoA estimates to the DoD estimates, the processors can determine an angle associated with the objects. In this way, the described techniques and systems can enable angle detection in monostatic and bistatic conditions with improved angular resolution and reduced cost.