The present disclosure relates to a method, a system, a device and a storage medium for non-contact velocity estimation of a moving target. The method comprises the following steps: acquiring channel state information or other information that includes motion information of a moving target through at least two receiving devices, eliminating a random phase offset of the channel state information or other information to acquire newly constructed signals, and performing a denoising and filtering process on the newly constructed signals; identifying a motion state of the target according to the newly constructed signals, and dynamically selecting two optimal receiving devices if the target is moving; respectively extracting a Doppler frequency shift caused by the motion of the target from the two selected optimal receiving devices, and calculating a velocity of the moving target according to the Doppler frequency shifts.

An ad hoc approach denoted as devoid clutter capture and filling (DeCCaF) that addresses the nonstationarity effects that arise when input radar waveform returns exhibiting dynamic spectra variations are processed to combat dynamic RFI is disclosed. Portions of the spectra of each input waveform return of a set of input radar waveform returns processed during the CPI may be filled with clutter information borrowed from other waveform returns of the set of waveform returns. DeCCaF may combined with an appropriate filter (e.g., a matched filter, a mismatched filter) to achieve results that are nearly indistinguishable from input radar waveform returns in which no spectral variation are present.

An object detection device includes processing circuitry configured to acquire wave data; acquire the moving velocity of a radar device; estimate a relative distance between the radar device and a target, angle of incidence of a reflection signal from the target, and a first relative velocity between the radar device and the target, by using the wave data; and estimate a second relative velocity between the radar device and the target in a case where the target is a static object, on the basis of the acquired moving velocity and the relative distance and the angle of incidence, and determine whether the target is a static object by comparing the first relative velocity and the second relative velocity.

A method of generating a reference signal for transmission over a wireless communication channel comprises generating a first signal of a first characteristic, generating a second signal with second characteristic, scaling the second signal at least in time and an amplitude to form a scaled signal and iteratively adding the scaled signal to the first signal to generate the reference signal. The iteratively adding comprises time indexing the first signal with plurality of time points, adding the scaled signal to first signal at each time point in the plurality of time points, computing a cost function to determine the cost of adding the scaled signal at each time point in the plurality of time points, selecting a set of time points that indicate reduction in the cost when the scaled signal is added and adjusting the amplitude of the scaled signal at each time point in the set of time points to reduce the cost.

Disclosed are devices, systems and methods for compensating radar measurements of a vehicle. One exemplary method includes generating a set of velocity hypotheses of a target object based on a first measurement data obtained from sensors mounted on the vehicle; generating cluster velocity estimates by applying a clustering algorithm to a second measurement data obtained from the sensors; and providing one or more selected velocity hypotheses from the set of velocity hypothesis as compensated radar measurements for the target object based on the cluster velocity estimates.

This document describes techniques, apparatuses, and systems for a parameter defined stepped frequency waveform for a radar system. A radar system transmits radar transmit signals including a parameter defined stepped frequency waveform with a specific change in frequency between chirps. The specified change in frequency may increase the signal to noise ratio of radar receive signals reflected off an object in the field of view. The radar receive signals may then be transformed into the frequency domain to determine a range and range rate of the object in the field of view. The range and range rate determined from the representation of the radar receive signals in the frequency domain may be output to a radar tracker to enable tracking of the object in the field of view. In doing so, accurate radar tracks may be generated that robustly track objects in the field of view of the radar system.

A method and system for a vehicle control system generates maps utilized for charting a path of a vehicle through an environment. The method performed by the system obtains information indicative of vehicle movement from at least one vehicle system and images including objects within an environment from a camera mounted on the vehicle. The system uses the gathered information and images to create a depth map of the environment. The system also generates an image point cloud map from images taken with a vehicle camera and a radar point cloud map with velocity information from a radar sensor mounted on the vehicle. The depth map and the point cloud maps are fused together and any dynamic objects filtered out from the final map used for operation of the vehicle.

A radar apparatus at a vehicle may transmit a set of radar energy that is reflected off an object after which the reflected radar energy may be received at the radar apparatus. When relative motion of a radar apparatus and an object include movement in two different directions, power of the reflected radar signals may be spread out in a manner that makes data associated with the reflected radar signals difficult to interpret. This spreading out of the radar signals can make mappings of the received radar data appear to be smeared or distorted. To compensate for this smearing effect, mappings of this smeared radar data may be compared with curves from which compensation factors may be identified. These compensation factors may allow a processor to perform calculations to generate updated mappings of the radar data that may allow the processor to more accurately identify characteristics of the object.

Systems and methods for using velocity measurements to adjust Doppler filter bandwidth are provided herein. In certain embodiments, a method for adjusting bandwidth for at least one Doppler filter in a Doppler beam sharpened radar altimeter comprises receiving a velocity measurement; adjusting the bandwidth of the at least one Doppler filter based on the velocity measurement; and transmitting a radar beam, wherein the radar beam is aimed toward a surface. The method further comprises receiving at least one reflected signal, wherein the at least one reflected signal is a reflection of the radar beam being reflected off of at least one portion of the surface; and filtering the at least one reflected signal with the at least one Doppler filter to form at least one Doppler beam.

This disclosure provides a signal processing method and apparatus. The method includes: obtaining Nr1×M1 signals, where the Nr1×M1 signals are echo signals of M1 signals that are sent by a radar to a target in a SIMO mode; obtaining Nt×Nr2×M2 signals, where the Nt×Nr2×M2 signals are echo signals of M2 signals that are sent by the radar to the target in a MIMO mode; performing first signal processing on the Nr1×M1 signals to obtain first processing data, where the first signal processing includes sequentially performing range FFT analysis, linear prediction, and Doppler FFT analysis; performing second signal processing on the Nt×Nr2×M2 signals to obtain second processing data, where the second signal processing includes range FFT analysis and Doppler FFT analysis; and performing velocity matching ambiguity resolution processing based on the first processing data and the second processing data.