A method for radar signal processing separates an electric signal generated by Doppler processors of a radar into alternating current (AC) magnitudes with Doppler frequencies corresponding to absolute values between 0.1 and 4 Hz and direct current (DC) magnitudes with no Doppler frequency. An AC line and a DC line are generated, based on the AC magnitudes and the DC magnitudes, respectively, by adding respective energies across Doppler cells for each range cell and subsequently applying CFAR detector algorithm respectively. An energy level difference between an energy spike in the AC line and another energy spike in the DC line is calculated and compared with a threshold set for detecting a breathing target that is stationary. If the energy level difference is greater than the threshold, the breathing target that is stationary is detected and reported to the radar operator.

The present disclosure relates to a cargo protection method, device and system, and a non-transitory computer-readable storage medium, relating to the technical field of unmanned aerial vehicles. The method of the present disclosure includes: determining whether an unmanned aerial vehicle is in a falling state or not according to a current acceleration in a vertical direction of the unmanned aerial vehicle and a current vertical distance from the unmanned aerial vehicle to the ground; and opening at least one airbag in a cargo hold of the unmanned aerial vehicle in a case where the unmanned aerial vehicle is in the falling state to protect a cargo in the cargo hold.

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.

An architecture is provided for cooperative target tracking and signal propagation learning using mobile sensors. A method can comprise as a function of sensing data representative of a location of a target device at a first defined moment and model data relating to a motion model representing a probability density function, determining, by a system comprising a processor, a group of locations for the target device at a second defined time point, wherein the probability density function facilitates determining, based on the location of the target device at the first defined moment, a current location of the target device at a third defined moment; and as a function of the group of locations, generating, by the system, a data structure representing a matrix of received signal strength values; and identifying, by the system, a location of the group of locations for the target device at the third defined moment based on the data structure.

A tracking system for tracking an expanded state of an object is provided. The tracking system comprises at least one processor and a memory having instructions stored thereon that, when executed by the at least one processor, cause the tracking system to execute a probabilistic filter that iteratively tracks a belief on the expanded state of the object, wherein the belief is predicted using a motion model of the object and is further updated using a compound measurement model of the object. The compound measurement model includes multiple probabilistic distributions constrained to lie on a contour of the object with a predetermined relative geometrical mapping to the center of the object. Further, the tracking system tracks the expanded state of the object based on the updated belief on the expanded state.

Embodiments of this disclosure provide a radar-based posture recognition apparatus, method and an electronic device. The method includes: acquiring radar reflection point information based on radar echo signals reflected from a detected target, and clustering radar reflection points; in a first time period, calculating spatial morphological feature information and/or motion feature information of a target point set obtained by clustering; in a second time period, counting the spatial morphological feature information and/or the motion feature information of a plurality of first time periods to obtain motion process feature information in the second time period; and taking the motion process feature information within a second time period in which a current moment is present and the spatial morphological feature information and/or the motion feature information in a first time period in which the current moment is present as a feature set, to determine the posture of the detected target.

A method includes receiving from a transceiver, at a processor of an electronic device, a radar signal, the radar signal including a set of signal strength values across a range of Doppler frequency shift values and a range of time values. The method further includes extracting a time series of frequency features from the radar signal, wherein frequency features of the time series of frequency features include a determined Doppler frequency shift value for each time value of the range of time values, identifying segments within the time series of frequency features, analyzing the segments to determine a start time for a classification engine, at the start time, analyzing, by the classification engine, at least one of a subset of the time series of frequency features or a subset of the radar signal to identify a control gesture, and triggering a control input associated with the control gesture.

A distributed microwave radar imaging method includes obtaining a first echo signal received by a first microwave radar, where the first microwave radar is disposed at a first height; obtaining a second echo signal received by a second microwave radar, where the second microwave radar is disposed at a second height, and the first height is lower than the second height; determining a first radar imaging result image of a detected target based on the first echo signal; determining a second radar imaging result image of the detected target based on the second echo signal; fusing the first radar imaging result image and the second radar imaging result image to obtain a target fused image; and determining outline information of the detected target based on the target fused image.

Various embodiments of the present technology generally relate to systems, methods, and computer-readable media for simulating synthetic aperture radar (SAR) images to be captured by a radar-based imaging system. SAR technology can be used to capture large areas on Earth, from a satellite in space for example, over a single pass. A further pass over the target area can help identify changes in the landscape, scenery, and/or infrastructure providing insight on change detection, temporal analysis, or other measures; however, repeat passes over the target area may have been made from differing angles resulting in artifacts in one or both of the processed images from the two passes. In various embodiments, information about the topology of the target area, and information about the SAR platform's flight path are used to simulate the slant range distortion effects that are to be expected in the SAR image of for that pass.

A method of recognizing consecutive objects on a conveying path in a detection zone arranged on the conveying path comprises the following steps: generating an electromagnetic radio frequency field radiating into the detection zone by way of a radio frequency sensor; measuring a time curve of a dielectric conductivity in the detection zone by using of the radio frequency field of the radio frequency sensor; and determining contour information of the consecutive objects from the time curve of the dielectric conductivity.