Systems and methods are provided for adapting automotive mmW radar technology to meet the requirements of autonomous unmanned aerial vehicle (UAV) systems. Embodiments of the present disclosure provide solutions for several design challenges from this adaptation, such as utilizing a limited number of antenna channels to scan in both azimuth and elevation.

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.

A vehicular sensing system includes at least one radar sensor disposed at a vehicle and having a field of sensing exterior of the vehicle. The radar sensor includes multiple transmitting antennas and multiple receiving antennas. The transmitting antennas transmit signals and the receiving antennas receive the signals reflected off objects. Multiple scans of radar data are received at an electronic control unit (ECU) and processed at a processor of the ECU. The ECU detects presence of a plurality of objects exterior the equipped vehicle and within the field of sensing of the at least one radar sensor. The ECU, responsive at least in part to processing at the processor of the received multiple scans of captured radar data and received vehicle motion estimation, tracks objects detected in the received multiple scans over two or more scans.

A method for detecting misalignment of a radar sensor positioned on a vehicle. A Doppler spectrum for the radiation emitted and received by the radar sensor is ascertained. For at least one frequency bin of the Doppler spectrum, an angle of incidence is determined in at least a subinterval. The determined angle of incidence is compared to the angle of incidence expected for the frequency bin. A misalignment of the radar sensor is detected as a function of the difference of the measured angle of incidence from the expected angle of incidence.

A vehicle control system may include a controller that detects an object outside a vehicle, calculates an angle based on a ratio of a relative speed between the object and the vehicle to a speed of the vehicle, and updates a phase curve reflecting a phase distortion of an input signal based on the calculated angle.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular estimation using machine learning. In particular, a radar system 102 includes an angle-estimation module 504 that employs machine learning to estimate an angular position of one or more objects (e.g., users). By analyzing an irregular shape of the radar system 102's spatial response across a wide field of view, the angle-estimation module 504 can resolve angular ambiguities that may be present based on the angle to the object or based on a design of the radar system 102 to correctly identify the angular position of the object. Using machine-learning techniques, the radar system 102 can achieve a high probability of detection and a low false-alarm rate for a variety of different antenna element spacings and frequencies.

In one embodiment, a method includes receiving a first signal associated with a first multipath effect from a first radar installed on a vehicle at a first height, receiving a second signal associated with a second multipath effect from a second radar installed on the vehicle at a second height, wherein the first height and the second height are different, wherein a difference between the first height and the second height is configured to generate a mitigation of the first multipath effect and the second multipath effect, and wherein the first radar and the second radar have an overlapping field of view, and determining that a target exists in the overlapping field of view based on the first signal and the second signal.

The embodiments relate to a radar control device and method. Specifically, a radar control device according to the embodiments may include an antenna device comprising a nonuniform linear array (NLA) antennas spaced apart according to a predetermined ratio, a first uniform linear array (ULA) antenna generated by being spaced apart by a first interval based on the NLA antenna, and a second ULA antenna generated by being spaced apart by a second interval based on the NLA antenna, a transceiver configured to transmit a transmission signal through the antenna device and receive a reflection signal reflected from an object, and a controller configured to determine an angular power spectrum (APS) for the reflection signal and determine an angle at which the object is located based on the APS.

A signal processing device, includes: an azimuth estimation unit configured to estimate an arrival azimuth of a radio wave based on a reception signal of plural antennas; an estimated reception signal calculation unit configured to calculate an estimated reception signal based on an estimation result of the arrival azimuth, for comparison with the reception signal; a residual signal calculation unit configured to calculate a residual signal which is a difference between the reception signal and the estimated reception signal; and a determination unit configured to determine whether the estimation result of the arrival azimuth is correct based on the residual signal.

Distributed radar systems and techniques for processing data received from such distributed radar systems. The distributed radar systems may utilize data on beam spatial pattern for processing collected signals and determining direction of one or more reflection origins (e.g., one or more objects reflecting transmitted signal).