Patent classifications
G01S7/40
DEVICE AND METHOD FOR TESTING A DISTANCE SENSOR
A testing device for testing a distance sensor that operates using electromagnetic waves includes: a receiving element for receiving an electromagnetic free-space wave as a receive signal (S.sub.RX); and a radiating element for radiating an electromagnetic output signal (S.sub.TX). In a test mode, a test signal unit generates a test signal (S.sub.test), and the radiating element is configured to radiate the test signal (S.sub.test) or a test signal (S′.sub.test) derived from the test signal (S.sub.test) as the electromagnetic output signal (S.sub.TX). In the test mode, an analysis unit is configured to analyze the receive signal (S.sub.RX) or the derived receive signal (S′.sub.RX) in terms of its phase angle (Phi) and/or amplitude (A) and store a determined value of phase angle (Phi) and/or amplitude (A) synchronously with the radiation of the test signal (S.sub.test) or of the derived test signal (S′.sub.test) as the electromagnetic output signal (S.sub.TX).
Method and System for Self-Calibrating a Scanning System Using Inertial Measurement Spatial and Temporal Data
A self-calibrating scanning system and method provides a novel way to eliminate errors in scanning systems, such as lidar or radar detection, using an inertial measurement unit. The system includes an energy transmission source configured to transmit an energy signal through a transmittal area. A detector receives a return energy signal of at least one target object of the energy transmitter source within the transmittal area. The system calculates at least one of the range and position of an object from information relating to at least one of the time and phase of the return energy signal relative to the transmittal energy signal. The spatial or angular displacement of the detector relative to the light source is measured using data from the inertial measurement unit, and at least one of calculated range and position of the object is adjusted based on the spatial or angular displacement of the detector.
Method and System for Self-Calibrating a Scanning System Using Inertial Measurement Spatial and Temporal Data
A self-calibrating scanning system and method provides a novel way to eliminate errors in scanning systems, such as lidar or radar detection, using an inertial measurement unit. The system includes an energy transmission source configured to transmit an energy signal through a transmittal area. A detector receives a return energy signal of at least one target object of the energy transmitter source within the transmittal area. The system calculates at least one of the range and position of an object from information relating to at least one of the time and phase of the return energy signal relative to the transmittal energy signal. The spatial or angular displacement of the detector relative to the light source is measured using data from the inertial measurement unit, and at least one of calculated range and position of the object is adjusted based on the spatial or angular displacement of the detector.
SENSOR CALIBRATION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM
A sensor calibration method and apparatus, and a storage medium are provided. In the method, multiple scene images and multiple first point clouds of a target scene are acquired by an image sensor and a radar sensor. A second point cloud of the target scene is constructed according to the multiple scene images. A first distance error between the image sensor and radar sensor is determined according to first feature point sets and a second feature point set. A second distance error of the radar sensor is determined according to multiple first feature point sets. A reprojection error of the image sensor is determined according to a first global position of the second feature point set in the global coordinate system and first image positions of pixel points corresponding to the second feature point set in the scene image. The radar sensor and image sensor are calibrated.
SENSOR CALIBRATION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM
A sensor calibration method and apparatus, and a storage medium are provided. In the method, multiple scene images and multiple first point clouds of a target scene are acquired by an image sensor and a radar sensor. A second point cloud of the target scene is constructed according to the multiple scene images. A first distance error between the image sensor and radar sensor is determined according to first feature point sets and a second feature point set. A second distance error of the radar sensor is determined according to multiple first feature point sets. A reprojection error of the image sensor is determined according to a first global position of the second feature point set in the global coordinate system and first image positions of pixel points corresponding to the second feature point set in the scene image. The radar sensor and image sensor are calibrated.
METHOD FOR CALIBRATING A PHASED ARRAY
A method for calibrating a phased array including an antenna array comprising a plurality of antenna elements, comprising the steps: measuring with a probe a first antenna element pattern of a first antenna element of the plurality of antenna elements; performing a spherical near-field to far-field transformation of the first antenna element pattern; transforming the far-field first antenna element pattern to a plane-wave spectrum; back transforming the plane-wave far-field first antenna element pattern to a reference point within the near-field of the antenna array; normalizing the first antenna element pattern according to, at least, the value at the phase center of the plane-wave near-field first antenna element pattern; and calibrating the first antenna element based, at least in the part, on the normalized first antenna element pattern.
LiDAR localization using 3D CNN network for solution inference in autonomous driving vehicles
In one embodiment, a method for solution inference using neural networks in LiDAR localization includes constructing a cost volume in a solution space for a predicted pose of an autonomous driving vehicle (ADV), the cost volume including a number of sub volumes, each sub volume representing a matching cost between a keypoint from an online point cloud and a corresponding keypoint on a pre-built point cloud map. The method further includes regularizing the cost volume using convention neural networks (CNNs) to refine the matching costs; and inferring, from the regularized cost volume, an optimal offset of the predicted pose. The optimal offset can be used to determine a location of the ADV.
CALIBRATION SYSTEM FOR CALIBRATING RADAR DEVICE MOUNTED ON VEHICULAR APPARATUS
A vehicular apparatus is provided with a radar device. A station apparatus has a stop position for the vehicular apparatus. The station apparatus is provided with a signal source located at a position and transmitting a radio signal to the radar device. A receiver circuit of the radar device receives a radio signal from a signal source to output a received signal, when the vehicular apparatus stops at the stop position. A signal processing circuit of the radar device estimates distance and direction of the signal source with respect to the radar device based on the received signal. A control circuit of the radar device calibrates the receiver circuit, or the signal processing circuit based on known distance and direction of the signal source with respect to the radar device of the vehicular apparatus stopping at the stop position, so as to minimize errors of the estimated distance and direction.
INTERFERENCE MITIGATION IN AN FMCW RADAR SYSTEM
Technologies are described herein that are configured to identity detections output by a frequency-modulated continuous-wave (FMCW) radar system that are caused by an interfering signal. The detections are detected as being caused by an interferer based upon numbers of detections assigned to bins in a velocity-direction histogram.
SYSTEM AND METHOD FOR PROCESSING RADAR SIGNAL
Provided are a system and method for processing a radar signal for deriving a Doppler frequency from a sampled digital input signal radiated by a frequency modulation continuous wave (FMCW) radar. The system includes a transmission module that repeatedly transmits a radar signal having a unique frequency variation and a pulse repetition interval, a variation module that varies the frequency variation or pulse repetition interval of the radar signal transmitted by the transmission module, an extraction module that, upon occurrence of interference between the radar signal having the varied frequency variation or pulse repetition interval and another radar signal, extracts an interference signal from the varied radar signal, and an adjustment module that adjusts the radar signal to reduce the extracted interference signal.