Abstract: A multi-arm robot used for tunnel lining inspection and defect diagnosis in an operation period, including a moving platform, where an environment detection device and a defect infection device are disposed on the moving platform, the defect infection device is disposed on the moving platform by using a multi-degree-of-freedom mechanical arm, and an attitude detection module is disposed on each multi-degree-of-freedom mechanical arm; a controller receives environmental data and mechanical arm attitude data sensed by the environment detection device and the attitude detection module, and sends a control instruction to the moving platform and the multi-degree-of-freedom mechanical arm according to the environmental data, to implement movement of the robot; and the controller receives tunnel lining structural data sensed by the defect infection device, and performs defect diagnosis. Overall automatic inspection can be implemented both on the surface and inside of the tunnel lining.

Abstract: Improvements to airborne weather radar systems onboard an aircraft that apply forecasting modeling techniques to output a forecast of future 3-dimensional (3D) radar reflectivity returns, forecasted composite radar image data, forecasted changes to potentially hazardous weather cells, including forecasts of future expected hail size and forecast which regions of airspace may be associated with future convective storms. The range of the forecast may be limited to approximately the range of the weather radar, which may be a few hundred nautical miles. Depending on the type and speed of the aircraft, the forecast duration may be approximately thirty minutes or less, e.g., the amount of time to reach the limits of the radar range.

Abstract: A method is provided for facilitating radar detection robust to IQ imbalance. The method comprises the step of generating a radar signal in digital domain comprising a number of M periodic repetitions of a code sequence with a length Lc, multiplied with a progressive phase rotation e j · ? K · n , where Lc and M are integers, K is an integer or a non-integer, and n is a discrete integer variable. The method further comprises the step of generating a process input signal in digital domain from a reflection signal corresponding to the radar signal by multiplying the reflection signal with a progressive phase rotation e - j · ? K · n . In this context, K is defined such that a ratio Lc K is a non-integer, and M is defined such that a ratio Lc · M K is an integer.

Abstract: A method of automatically managing a center pivot irrigation machine comprising steps of: (a) providing at least one center pivot irrigation machine and positioning said center pivot irrigation machine such that said center pivot irrigation machine is movable within an irrigated plot around a center thereof; (b) providing a ground penetration radar; (c) mounting said ground penetration radar on said center pivot irrigation machine; (d) moving said center pivot irrigation machine about said center of said irrigated plot; (e) scanning said irrigated by said ground penetration radar at frequencies ranging between 200-1200 MHz; (f) calculating a distribution of soil moisture over a depth from a soil surface; and (g) creating an irrigation plan according to said distribution.

Abstract: A radar sensor device including a first radar sensor arrangement configured to measure a fill level of a medium in a container and a second radar sensor arrangement configured to monitor an environment of the radar sensor outside the container.

Abstract: This beam formation device includes: a Doppler bin detection unit that detects a target Doppler bin which is a Doppler bin in which a target signal is present, from a correlation matrix calculated by a correlation matrix calculation unit and a reception signal vector calculated by a Doppler analysis unit; a target signal removal unit that removes, from the correlation matrix calculated by the correlation matrix calculation unit, the target signal in the target Doppler bin detected by the Doppler bin detection unit and thereby calculates a target-signal-removed correlation matrix from which the target signal has been removed; and a weighting calculation unit that calculates an adaptive weighting of the reception signal vector from the target-signal-removed correlation matrix calculated by the target signal removal unit. A beam formation unit forms an adaptive beam from the reception signal vector calculated by the Doppler analysis unit and the adaptive weighting calculated by the weighting calculation unit.

Abstract: A method for estimating a speed of a radar target using a radar sensor, in particular a radar sensor for motor vehicles, on the basis of signals that are contained in respective evaluation channels that correspond to different center antenna positions of relevant transmitting and receiving antennas in a direction, having the steps: determining, for the various evaluation channels, a respective individual radial speed assigned to the respective evaluation channel, of the radar target; and estimating a speed of the radar target based on the determined individual radial speeds of the radar target, the speed including information about a tangential speed; and a radar sensor for carrying out the method.

Abstract: An apparatus comprises a first and second coherent radar system on a first chip configured to operate in a terahertz range to provide a frequency modulated continuous wave, and having a first and second field of view, respectively. The apparatus further comprises a first processor in communication with the first coherent radar system and configured to include instructions to send a first signal to the first coherent radar system to scan a target with the first field of view, and a second processor in communication with the second coherent radar system and configured to collaborate with the first processor, and further configured to include instructions to send a second signal to the second coherent radar system to scan a target within the second field of view.

Abstract: A method including: detecting that an aerial vehicle is located at a reference axis of a sensor, or at a predetermined or calculated angle of the reference axis of the sensor, the method further comprising, by a processor and memory circuitry: obtaining a given position Paerial of the aerial vehicle upon its detection at the reference axis of the sensor, or upon its detection at the predetermined or calculated angle of the reference axis of the sensor, and position Psensor of the sensor, and determining, based at least on Paerial and Psensor, a cardinal direction with respect to the reference axis.

Abstract: A radar system, apparatus, architecture, and method are provided with a transmitter that produces a plurality of distinct FanTOM signals that are transmitted as N RF-encoded transmit signals in an overlapped fashion such that the pulse repetition interval and frame length are kept short; a receiver that processes target return signals reflected from the N RF-encoded transmit signals with a mixer to produce an IF signal which is filtered with one or more notch filters clocked with a sampling clock frequency to control harmonic notch frequencies to suppress transmitter spill-over and close-in self-clutter interference, thereby producing a filtered IF signal that is converted to a digital signal with an analog-to-digital converter that is clocked with the sampling clock frequency; and a radar processor that processes the digital signal to generate a range spectrum comprising N segments that correspond, respectively, to the N RF-encoded transmit signals.

Abstract: Proposed is a GPS error correction method performed through comparison of three-dimensional HD-maps in a duplicate area, and more particularly, a method that can calculate a correction value for a GPS error by comparing three-dimensional HD-maps of a corresponding duplicate area when the duplicate area is generated on a GPS route in the process of acquiring raw data to be used in a HD-map for autonomous driving. Particularly, in the method, an accurate correction value for the GPS error can be calculated by comparing three-dimensional point cloud data acquired by utilizing basically installed LiDAR, an Inertial Measurement Unit (IMU) and the like, without using expensive equipment such as a plurality of high-precision GPS receivers, stereo cameras or the like.

Abstract: Various embodiments of the present technology generally relate to detecting and manipulating radar image data. More specifically, some embodiments relate to systems, methods, and computer-readable storage media for detecting, processing, viewing, and manipulating radar images in an image viewer application. Radar image data captured by a radar imaging system, such as a synthetic aperture radar (SAR) or other satellite-based equipment, comprises data unreadable by image viewers. In an implementation, an open-source plug-in for an image viewer application obtains SAR data, performs one or more algorithms on the SAR data to detect an image, and provides the detected image to an image viewer for display on a graphical user interface. Further, requests for manipulation of the detected image made by the image viewer application may be performed by the plug-in and exported in complex data formats for use downstream.

Abstract: In various examples, a sensor model may be learned to predict virtual sensor data for a given scene configuration. For example, a sensor model may include a deep neural network that supports generative learning—such as a generative adversarial network (GAN). The sensor model may accept an encoded representation of a scene configuration as an input using any number of data structures and/or channels (e.g., concatenated vectors, matrices, tensors, images, etc.), and may output virtual sensor data. Real-world data and/or virtual data may be collected and used to derive training data, which may be used to train the sensor model to predict virtual sensor data for a given scene configuration. As such, one or more sensor models may be used as virtual sensors in any of a variety of applications, such as in a simulated environment to test features and/or functionality of one or more autonomous or semi-autonomous driving software stacks.

Abstract: Systems, devices, and methods related to a radar and an artificial neural network are described. For example, the radar can have at least one processing unit configured to execute instructions implementing matrix computation of the artificial neural network. The artificial neural network is configured to identify features in the radar image in an output responsive to an input containing a radar image. Optionally, the radar can further include an image sensor to generate an optical image as part of the input to artificial neural network. Instead of outputting the radar images and/or the optical images, the radar may output a description of the features identified via the artificial neural network from the radar image.

Abstract: A radar system receives threat relevant data with pulses sufficiently separated to provide sufficient long-range imaging, analyzes the return data to identify features of the threat, and generate a second set of pulses to acquire more detailed, higher granularity data specific to the threat. The system may include an ESA that is configured for pulses in a higher frequency to acquire higher resolution data specific to the threat.

Abstract: A Global Navigation Satellite System (GNSS) receiver includes a wideband signal correlator and a multipath mitigator. The wideband signal correlator generates wideband correlation signals of at least one of a plurality of GNSS signals with respect to corresponding locally generated code replica signals in which a bandwidth of the wideband signal correlation module is at least about 20 MHz. The multipath mitigator determines a Line of Sight (LOS) signal from the wideband correlation signals. The GNNS receiver may include a narrowband signal correlator to generate narrowband correlation signals of the at least one GNSS signal with respect to corresponding locally generated code replica signals in which a bandwidth of the narrowband signal correlation module is less than about 6 MHz. The multipath mitigator further corrects a range and range-rate measurement generated from the narrowband correlation signals based on a code phase and a carrier estimated based on the LOS signal.

Abstract: A method of emulating echo signals reflected from an elongated target during radar testing includes identifying first and second end points do the target; acquiring a radar signal from a radar sensor that includes multiple receive elements; generating emulated echo signals, responsive to the acquired radar signal, corresponding to target points on the target, including the first and second end points and reference points located on a line connecting the first and second end points, by repeatedly identifying descriptive attributes corresponding to each of the target points during an integration period of the radar sensor, where the descriptive attributes are identified by interpolating between the corresponding descriptive attributes of the first and second end points; and applying the emulated echo signals to the receive elements of the radar sensor, respectively, during the integration period, where radar sensor calculates a relative position of the target using the descriptive attributes.

Abstract: 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.

Abstract: A radar target simulator front end, configured to simulate at least one radar target for testing a radar device under test is provided. The radar target simulator front end comprises at least two antenna units, arranged along a first angle under investigation. The at least two antenna units are configured to be selectively activated and deactivated. Whereby each antenna unit of the at least two antenna units generates a simulated radar target along the first angle under investigation, when activated.

Abstract: A method and apparatus for processing a transceiver signal (115) detected by a transceiver (110). The method includes obtaining (S1) a processed signal from the transceiver signal (115), the processed signal having frames (200, 300) corresponding to respective time intervals (t1, t2, t3, t4), wherein the frames define bins (210, 310) configured according to a quantized resolution (dr) of the transceiver signal (115). The method further includes obtaining (S2) data related to a relative motion of the transceiver (110) during a time interval (t1, t2, t3, t4) and initializing (S3) a residual distance to zero.