The present application relates to a real-time measurement method and system for ultrafast space-time-frequency three-domain information based on space-time-frequency compression. The method includes: generating an ultrafast-pulse optical signal in a to-be-observed physical system; performing intensity-modulated spatial encoding on the ultrafast-pulse optical signal; arranging, by a space-time editor, a time-domain series of an encoded ultrafast-pulse optical signal in a horizontal space direction; performing, by a frequency-space editor, frequency spectral processing on a space-time distribution encoding form of the encoded ultrafast-pulse optical signal; performing, by a frequency-time delayer, frequency-time delaying on an encoded space-time-frequency synchronized ultrafast-pulse optical signal; performing, by an area array detector, real-time compression and acquisition on a high-frequency-resolution encoded space-time-frequency synchronized ultrafast-pulse optical signal, to obtain compressed encoded data information; and decompressing and decoding data according to the compressed encoded data information, to obtain space-time-frequency three-domain synchronization information of the ultrafast-pulse optical signal.

Example embodiments relate to radar reflection filtering using a vehicle sensor system. A computing device may detect a first object in radar data from a radar unit coupled to a vehicle and, responsive to determining that information corresponding to the first object is unavailable from other vehicle sensors, use the radar data to determine a position and a velocity for the first object relative to the radar unit. The computing device may also detect a second object aligned with a vector extending between the radar unit and the first object. Based on a geometric relationship between the vehicle, the first object, and the second object, the computing device may determine that the first object is a self-reflection of the vehicle caused at least in part by the second object and control the vehicle based on this determination.

Example embodiments relate to radar reflection filtering using a vehicle sensor system. A computing device may detect a first object in radar data from a radar unit coupled to a vehicle and, responsive to determining that information corresponding to the first object is unavailable from other vehicle sensors, use the radar data to determine a position and a velocity for the first object relative to the radar unit. The computing device may also detect a second object aligned with a vector extending between the radar unit and the first object. Based on a geometric relationship between the vehicle, the first object, and the second object, the computing device may determine that the first object is a self-reflection of the vehicle caused at least in part by the second object and control the vehicle based on this determination.

This disclosure introduces a mapping for creating good Doppler detection capable radar codes. The mapping transfers an existing digital radar code to the warped frequency domain by expressing the code elements as magnitudes and phases of selected frequencies. These frequencies are equispaced in the warped frequency domain to preserve the code's sidelobes after mapping. The frequency warping function may convert the multiplicative Doppler shift into an additive shift of the code pattern in the warped frequency domain, which allows Doppler shift detection.

This disclosure introduces a mapping for creating good Doppler detection capable radar codes. The mapping transfers an existing digital radar code to the warped frequency domain by expressing the code elements as magnitudes and phases of selected frequencies. These frequencies are equispaced in the warped frequency domain to preserve the code's sidelobes after mapping. The frequency warping function may convert the multiplicative Doppler shift into an additive shift of the code pattern in the warped frequency domain, which allows Doppler shift detection.

The present disclosure relates to digital signal processing architectures, and more particularly to a modular object-oriented digital system architecture ideally suited for radar, sonar and other general purpose instrumentation which includes the ability to self-discover modular system components, self-build internal firmware and software based on the modular components, sequence signal timing across the modules and synchronize signal paths through multiple system modules.

The present disclosure relates to digital signal processing architectures, and more particularly to a modular object-oriented digital system architecture ideally suited for radar, sonar and other general purpose instrumentation which includes the ability to self-discover modular system components, self-build internal firmware and software based on the modular components, sequence signal timing across the modules and synchronize signal paths through multiple system modules.

An example system and method provides radiating into the 3D environment a millimeter wave (mmWave) radio frequency (RF) radiation signal that interacts with reflective surfaces, penetrable surfaces, scattering surfaces of the 3D environment, producing respective multipath components, determining information from two or more of the multipath components, including two among, or, optionally, all of angle of arrival (AoA), angle of departure (AoD), time of arrival, relative time of arrival (RTA), and phase and, based on the information and the received multipath components, performs computing the user device’s relative or absolute mobile device location in relation to the surrounding 3D environment, and providing images or video of the surrounding 3D environment to a display or a storage of the user’s mobile device, for displaying or storing.

A method of multi-sensor data fusion includes determining a plurality of first data sets using a plurality of sensors, each of the first data sets being associated with a respective one of a plurality of sensor coordinate systems, and each of the sensor coordinate systems being defined in dependence of a respective one of a plurality of mounting positions for the sensors; transforming the first data sets into a plurality of second data sets using a transformation rule, each of the second data sets being associated with a unified coordinate system, the unified coordinate system being defined in dependence of at least one predetermined reference point; and determining at least one fused data set by fusing the second data sets.

A system for estimating a parameter of an object includes a receiver configured to detect a return signal of a radar signal, and a processing device configured to sample the return signal to generate a series of signal samples, partition a time frame into a plurality of successive segments k, and for each segment k, apply a Doppler Fourier transform and calculate a complex value y.sub.k as a function of Doppler frequencies f.sub.D. The processing device is also configured to calculate an index based on an acceleration hypothesis and a velocity hypothesis of a set of hypotheses, and for each segment, select one or more Doppler frequency bins based on the index and extract components of the complex value y.sub.k (f.sub.D) associated with each selected Doppler frequency bin. The processing device is further configured to calculate a velocity and acceleration spectrum, and estimate an object parameter based on the spectrum.