Based on a reception signal of a reflected wave of pulsed undulation repeatedly transmitted into a space, a Doppler spectrum derived from the reception signal, and a topographic-echo-removed spectrum resulting from removal of a topographic echo from the Doppler spectrum, a first weather echo region is found by using a weather parameter among weather parameters that is different in behavior between a weather echo and the topographic echo, and a second weather echo region is found by using a weather parameter among the weather parameters a behavior of which is not dependent on a Doppler velocity. The weather echo region is determined based on the first weather echo region and the second weather echo region. A signal processing apparatus and a signal processing method with which a zero-Doppler weather echo attenuated, that is, erroneously suppressed, by topographic echo removal processing is readily reconstructed are thus obtained.

The invention relates to a method for determining at least one parameter of an object, wherein the method comprises the following steps: a. provision of a range-Doppler matrix, b. transfer of at least one part of the range-Doppler matrix to a neural network and c. identification of the at least one parameter by the neural network.

The invention relates to a method for determining at least one parameter of an object, wherein the method comprises the following steps: a. provision of a range-Doppler matrix, b. transfer of at least one part of the range-Doppler matrix to a neural network and c. identification of the at least one parameter by the neural network.

A radar apparatus and a radar signal processing method are provided. The radar apparatus includes a plurality of transmitting antennas, a plurality of non-uniformly and linearly deployed receiving antennas, a sensor signal processor configured to calculate target range-Doppler data from signals input from a receiving antenna arrangement according to virtual antennas while sequentially driving the plurality of transmitting antennas, and a target position calculator configured to calculate position data of a target from arrangement mapped data obtained by rearranging the virtual antenna-specific range-Doppler data output from the sensor signal processor with reference to antenna configuration related information.

A radar apparatus and a radar signal processing method are provided. The radar apparatus includes a plurality of transmitting antennas, a plurality of non-uniformly and linearly deployed receiving antennas, a sensor signal processor configured to calculate target range-Doppler data from signals input from a receiving antenna arrangement according to virtual antennas while sequentially driving the plurality of transmitting antennas, and a target position calculator configured to calculate position data of a target from arrangement mapped data obtained by rearranging the virtual antenna-specific range-Doppler data output from the sensor signal processor with reference to antenna configuration related information.

In an azimuth estimation device, a center generation unit configured to generate, for each peak bin extracted by the extraction unit, a center matrix which is a correlation matrix obtained using values of the same peak bin collected from all of transmitting/receiving channels. A surrounding generation unit is configured to generate, for each of one or more surrounding bins of each of the peak bins, a surrounding matrix which is a correlation matrix obtained using values of the same surrounding bin collected from all of the transmitting/receiving channels. An integration unit is configured to generate, for each peak bin, an integrated matrix which is a correlation matrix obtained by weighting and adding the center matrix and the one or more surrounding matrices. An estimation unit is configured to execute an azimuth estimation calculation using the integrated matrix generated by the integration unit.

In an azimuth estimation device, a center generation unit configured to generate, for each peak bin extracted by the extraction unit, a center matrix which is a correlation matrix obtained using values of the same peak bin collected from all of transmitting/receiving channels. A surrounding generation unit is configured to generate, for each of one or more surrounding bins of each of the peak bins, a surrounding matrix which is a correlation matrix obtained using values of the same surrounding bin collected from all of the transmitting/receiving channels. An integration unit is configured to generate, for each peak bin, an integrated matrix which is a correlation matrix obtained by weighting and adding the center matrix and the one or more surrounding matrices. An estimation unit is configured to execute an azimuth estimation calculation using the integrated matrix generated by the integration unit.

In one embodiment, a method includes configuring a radar transceiver to transmit a first number of radar pulses at a first pulse repetition frequency (PRF); and determining a first value corresponding to a first object based on a first radar data received in response to the first number of radar pulses. The first object is identified based on the first value being higher than a predetermined threshold value. The method also includes configuring the radar transceiver to transmit a second number of radar pulses at a second PRF that is higher than the first PRF; determining a second value of the first object based on a second radar data received in response to the second number of radar pulses; and associating the second value with information of the first object.

In one embodiment, a method includes configuring a radar transceiver to transmit a first number of radar pulses at a first pulse repetition frequency (PRF); and determining a first value corresponding to a first object based on a first radar data received in response to the first number of radar pulses. The first object is identified based on the first value being higher than a predetermined threshold value. The method also includes configuring the radar transceiver to transmit a second number of radar pulses at a second PRF that is higher than the first PRF; determining a second value of the first object based on a second radar data received in response to the second number of radar pulses; and associating the second value with information of the first object.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting a frame-of-reference change. In particular, a radar system includes a frame-of-reference machine-learned module trained to recognize whether or not the radar system's frame of reference changes. The frame-of-reference machine-learned module analyzes complex radar data generated from at least one chirp of a reflected radar signal to analyze a relative motion of at least one object over time. By analyzing the complex radar data directly using machine learning, the radar system can operate as a motion sensor without relying on non-radar-based sensors, such as gyroscopes, inertial sensors, or accelerometers. With knowledge of whether the frame-of-reference is stationary or moving, the radar system can determine whether or not a gesture is likely to occur and, in some cases, compensate for the relative motion of the radar system itself.