Abstract: An automotive radar arrangement includes a radar receiver configured to generate radar reception data from radio signals received by a plurality of radar receive antennas. A radar signal processor is configured to determine an estimate of an angular position of at least one object by processing the radar reception data. A communication interface is configured to receive information about a reference angular position of the at least one object. A determiner is configured to determine a compensation for the radar reception data based on the estimate of the angular position and the reference angular position of the at least one object. The radar signal processor is configured to correct the radar reception data and/or further radar reception data for the detection of a further object based on the compensation. An output interface is configured to provide information about the presence of the further object to a vehicle controller.

Abstract: According to various examples, a radar system is described comprising a radar receiver configured to perform sampling of a radio reception signal and to generate a sample for each of a plurality of sampling times, a machine learning model configured to generate, for each of one or more additional sampling times, a sample from the samples generated for the sampling times and an object detector configured to perform range estimation of one or more detected objects using the samples generated by the machine learning model.

Abstract: According to various embodiments, a radar system is described including a direction of arrival pre-processor configured to, for a detected peak, obtain a Doppler Fourier transform result vector, generate a spatial covariance matrix for the Doppler Fourier transform result vector, and generate an additional spatial covariance matrix by inputting the spatial covariance matrix to a machine learning model trained to predict, from an input spatial covariance matrix, an output spatial covariance matrix such that the output spatial covariance matrix corresponds to a different chirp center frequency than the input covariance spatial covariance matrix and including a direction of arrival estimator configured to perform direction-of-arrival estimation using the additional spatial covariance matrix.

Abstract: According to various embodiments, a radar system is described comprising a radar receiver configured to receive radio signals, a range Fourier transform stage configured to generate, for each of a plurality of chirps, a vector of range Fourier transform coefficients, a machine learning model configured to generate, for each of one or more additional chirps, a vector of range Fourier transform coefficients from the vectors of Fourier transform coefficients generated for the plurality of chirps, and an object detector configured to perform velocity estimation of one or more detected objects using the Fourier transform coefficients generated by the machine learning model.

Abstract: According to various embodiments, a radar system is described including a first radar processing device and a second radar processing device, wherein the first radar processing device is configured to generate radar data and to transmit the radar data partially to the second radar processing device for further processing, wherein the first radar processing device is configured to omit parts of the radar data from the transmission and wherein the second radar processing device is configured to reconstruct the omitted parts using a machine learning model trained to supplement radar data with additional radar data and is configured to further process the transmitted parts of the radar data in combination with the additional radar data.

Abstract: According to various embodiments, a radar system is described comprising a radar receiver configured to receive radio signals, wherein each radio signal is associated with a channel of a plurality of channels, a peak detector configured to perform peak detection using the received radio signals, wherein each detected peak corresponds to a detected object and a direction of arrival estimator configured to, for a detected peak, generate a vector having, for each of the channels, an entry specifying a Doppler Fourier transform result for the channel, supply the vector to a machine learning model trained to output, for each of one or more additional channels, an entry specifying a predicted Doppler Fourier transform result corresponding to the additional channel and perform direction-of-arrival estimation using an output from the machine learning model which the machine learning model outputs in response to being supplied with the vector.

Abstract: Systems, methods and circuitries are disclosed for compressing radar data. In one example, a radar sender unit includes adaptive compression circuitry configured to determine tuning data, wherein the tuning data is based on one or more operating conditions; compress radar data based on the tuning data; and transmit the compressed radar data to a radar control unit for further processing.

Abstract: According to at least one embodiment, a MIMO radar arrangement includes a radar receiver configured to generate radar reception data from radio receive signals received by a plurality of radar receive antennas. The arrangement further includes one or more signal processors configured to: generate frequency domain data for a range-Doppler bin based on the radar reception data and determine one or more peaks from the generated frequency domain data. The radar arrangement further includes a trained machine learning module configured to generate, using frequency domain data corresponding to each of the of the one or more determined peaks as input, one or more output values indicating a number of detected objects within each range-Doppler bin.

Abstract: An automotive radar arrangement includes a radar receiver configured to generate radar reception data from radio signals received by a plurality of radar receive antennas. A radar signal processor is configured to determine an estimate of an angular position of at least one object by processing the radar reception data. A communication interface is configured to receive information about a reference angular position of the at least one object. A determiner is configured to determine a compensation for the radar reception data based on the estimate of the angular position and the reference angular position of the at least one object. The radar signal processor is configured to correct the radar reception data and/or further radar reception data for the detection of a further object based on the compensation. An output interface is configured to provide information about the presence of the further object to a vehicle controller.

Abstract: It is suggested to process radar signals including (i) determining a variation of at least one radar parameter provided from at least one radar device; (ii) determining an estimated value of at least one radar parameter from an error compensation vector; and (iii) determining a safety condition based on the variation and the estimated value for the respective radar parameter.

Abstract: It is suggested to process radar signals including: (i) receiving reception signals via at least one antenna of a first receiving circuit; (ii) determining an interim result by processing the reception signals via a frequency transformation; (iii) determining an error compensation vector based on the interim result and an expected characteristic; and (iv) applying the error compensation vector on other reception signals that have been processed via the frequency transformation.

Abstract: According to one embodiment, a radar receiving system is provided comprising a first receiving circuit, a second receiving circuit, a spectral analyzer, an object detector, and a phase compensation circuit. The spectral analyzer is configured to generate, from a first plurality of reception signals, a first set of Fourier transformation output values and, from a second plurality of reception signals, a second set of Fourier transformation output values. The object detector is configured to determine a range/Doppler bin of a plurality of range/Doppler bins as an estimate of a range and speed of an object. The phase compensation circuit is configured to determine a phase offset between the Fourier transformation output values of the first set and second set of Fourier transformation output values and to compensate the phases of at least a part of the second set of Fourier transformation output values by the determined phase offset.