120 results about "Doppler velocity" patented technology

The invention discloses a robot obstacle avoidance method and system based on millimeter wave radar sparse point cloud, and relates to the technical field of obstacle avoidance recognition. A robot obstacle avoidance system based on millimeter wave radar sparse point cloud comprises a point cloud acquisition module, a negative obstacle identification module, a weak obstacle identification module, a point cluster identification module, a risk map module, a tentative verification module and an obstacle avoidance decision module. According to the invention, suspected obstacle point clusters are extracted based on a reflection intensity threshold and a spatial proximity relation in an enhanced point cloud, a theoretical parallax model of a real static obstacle is constructed under the constraint of a robot motion trajectory, and Doppler velocity distribution of each frame is combined with a static obstacle Doppler physical law for comparison. And classifying the point clusters which do not meet the multi-view geometric consistency or Doppler physical law, and distinguishing multipath false point clusters from dynamic point clusters.

The invention discloses a composite precipitation cloud layer identification method based on a laser radar-cloud radar, and the method comprises the steps: obtaining the observation data of the laser radar and the cloud radar, and carrying out the data matching of the observation data; processing a signal of the laser radar in a height interval of 18-20 km to obtain a preprocessed laser radar signal; performing laser radar cloud boundary identification based on a VED algorithm, and endowing different laser radar cloud scores according to the signal attenuation rate and the signal gradient; removing earth surface clutters by using a threshold method based on observation of spectral width and Doppler velocity; carrying out cloud radar significant echo recognition based on a threshold method, and determining the cloud score of the cloud radar according to different reflectivity factor signal intensities; determining a light rain area and a heavy rain area according to the Doppler velocity; cloud layer boundary information and a hairy rain area are obtained through cloud layer recognition result fusion, and cloud layer recognition and rainfall area recognition are completed; according to the invention, the accuracy of weather prediction is improved.

The invention provides a synchronous positioning and mapping method for underwater pipeline detection, and belongs to the technical field of underwater robot navigation and positioning. In order to solve the problems of limited illumination, strong echo interference, high structural repeatability and the like in a seawater pipeline environment, the invention provides a factor graph optimization-based tight coupling pose estimation framework fusing a two-dimensional imaging sonar, a Doppler velocity meter DVL and an inertial measurement unit IMU. Through joint constraint and optimization of multi-source sensing information, the method can realize high-precision positioning and continuous mapping of the ROV in an environment with extremely low visibility and a complex pipeline structure, and effectively improves autonomy and data reliability of an underwater inspection process. The method is clear in structure, easy and convenient to implement, high in calculation efficiency, capable of stably running on a conventional ROS platform and suitable for various types of underwater pipeline detection and inspection tasks.

The invention provides a broadband beam forming acoustic Doppler velocity measurement system and method based on time delay control, which can transmit and receive broadband signals and solve the problem that the measurement precision of the existing acoustic Doppler velocity measurement system is influenced by bandwidth. The velocity measurement system comprises a transducer module, a beam forming module and a conversion module, the transducer module comprises a planar transducer array and an impedance matching module connected with the planar transducer array; the transducer module is in signal connection with the beam forming module through the conversion module, and the beam forming module is used for performing time delay compensation and weighting processing on a received signal; and the conversion module is used for converting the echo signal acquired by the transducer module into a digital signal and inputting the digital signal into the beam forming module, or converting a to-be-transmitted signal received from the beam forming module into an analog signal and transmitting the analog signal through the transducer module.

The invention discloses a mapping method and device based on a 4D millimeter wave radar and a computer readable medium, and the method comprises the steps: carrying out the noise reduction of a 4D millimeter wave radar point cloud based on the coordinate information and RCS information of the 4D millimeter wave radar point cloud in a preset sliding window; based on the Doppler velocity, performing dynamic point cloud filtering processing on the preprocessed point cloud to obtain static point cloud; and for any current frame point cloud in the static point clouds, performing conversion processing on the current frame point cloud based on the pose conversion matrix, and performing feature point registration on the converted current frame point cloud and a previous frame sub-map to generate a current frame sub-map. According to the embodiment of the invention, based on RCS information and Doppler velocity, filtering processing is carried out on point clouds collected by a 4D millimeter wave radar; and feature point registration is carried out on the static point cloud obtained after filtering to form a local sub-map. Therefore, the point cloud in the target scene can be subjected to high-precision registration, so that high-precision positioning of the unmanned equipment is realized.

The invention provides an outdoor cross-modal robust positioning and navigation method for extreme severe weather, and relates to the field of online positioning and navigation of mobile robots. The method comprises the following steps: acquiring and preprocessing data; generating a path point set based on a CMR network, perfecting the path point set through local trajectory fitting and error optimization, and constructing a path point relative pose measurement-topology hybrid map; motion prior estimation is carried out based on Doppler velocity, effective matching prior estimation is generated in combination with LiDAR odometer information, cross-modal pose estimation is carried out through a CMR network, and a pure tracking strategy and PD controller path point tracking are adopted; and geometric and intensity alignment is carried out on the forward 4D millimeter wave radar point cloud and the omnidirectional 3D laser radar point cloud through a CMR network, a rotation matrix and a translation vector are output, and accurate positioning is completed. According to the invention, the sensing and positioning defects in extreme weather in the prior art are overcome, and the positioning precision and robustness are improved.

The invention discloses a Doppler blood flow velocity estimation method based on high-frequency pulse differential frequency, and solves the problems of velocity estimation resolution reduction and artifacts caused by alternate transmission of a B mode and Doppler pulses in an ultrasonic dual-mode system. The method comprises the following steps: transmitting a high-frequency broadband ultrasonic signal compatible with B-mode imaging; the method comprises the following steps: receiving a superficial blood vessel echo signal, performing time domain sampling, converting into a discrete signal, extracting a narrow-band frequency spectrum through frequency sampling, and generating a low-frequency equivalent signal by using a multi-frequency-point differential frequency technology; calculating a covariance matrix of each signal, performing average weighting to remove artifacts, and generating low-frequency equivalent covariance data; and estimating the blood flow velocity through eigenvalue decomposition and spectral peak search. According to the method, two pulses do not need to be transmitted alternately, resolution reduction and artifacts are avoided, Doppler velocity estimation precision is remarkably improved, integrated waveform design is supported, and hardware implementation is simplified.

The invention relates to the technical field of medical instrument volume detection, and discloses a medical instrument internal volume detection system. A continuous wave and a pulse modulation signal are simultaneously transmitted through an annular phased array microwave antenna array, three-dimensional dielectric constant distribution is reconstructed by adopting a compressed sensing algorithm, and Doppler time-frequency domain characteristics are extracted through short-time Fourier transform; and inputting the phase gradient field and Doppler velocity field features into a convolutional neural network to generate a four-dimensional space-time volume evolution model, separating a macroscopic volume trend and a microcosmic pulsation component by adopting an adaptive Kalman filtering algorithm, and predicting an abnormal hemodynamic event through a long-short-term memory network. The technical problem of real-time precise detection of the multi-dimensional volume parameters of the blood circulation medical instrument under the complex pulsating flow condition is solved, and accurate evaluation of the instantaneous volume value, the pulsation amount and the pulsating frequency spectrum and early warning of abnormal events are achieved.

A computer-implemented method for estimating a travelling speed of a wireless device in a wireless communications network, where the wireless device has transmitted a signal sequence to a network node via two or more signal paths. The method includes obtaining data indicative of a Doppler speed difference between respective multipath components of the signal sequence transmitted via the two or more signal paths; obtaining data indicative of direction of departure, DoD, (nUE,P1, nUE,P2) of the two or more signal paths at the wireless device; and estimating the travelling speed of the wireless device based on the data indicative of the Doppler speed difference and the data indicative of DoD.

The invention discloses an under-water flow tumble detection system based on multi-scale fusion and decision, which comprises the following steps of: acquiring radar signals in a detection area by utilizing a millimeter wave radar, constructing a distance Doppler spectrum, calculating a water flow dynamic clutter index based on energy distribution statistical characteristics, identifying a background noise type and dynamically generating a detection threshold; target point cloud extraction under a complex dynamic water flow background is realized; the method comprises the following steps: performing track initialization and state updating by constructing a two-stage gating and evidence judgment framework, executing online parameter self-adaption and target physical size estimation, extracting time sequence characteristics such as a centroid position and Doppler velocity, and constructing a characteristic vector; and establishing a finite state machine model based on the feature vectors, identifying state transition, fall confirmation and state rollback conditions, and outputting a fall judgment result or a rollback result. According to the invention, accurate identification and dynamic determination of a fall event in a wet, slippery and water flow complex environment are realized.

The invention provides an autonomous underwater robot cluster cooperative positioning method and system, and the method comprises the steps: carrying out the interaction of the pose information of a master underwater robot and a slave underwater robot through underwater acoustic communication, calculating the relative distance between the master underwater robot and the slave underwater robot through underwater acoustic two-way distance measurement, and enabling the navigation system of the slave underwater robot to be an inertial navigation system assisted by a Doppler speedometer. The navigation information and the underwater sound ranging information are fused, so that the navigation reference in the underwater robot cluster is unified with the main underwater robot, and the cooperative positioning of the underwater robot cluster is completed.

A radar data processing device and method is provided. The method generates a radar image map, predicts a region of interest (ROI) based on the generated radar image map, senses radar data with a radar sensor, identifies the sensed radar data based on steering information, adjusts the steering information based on the predicted ROI, and determines direction-of-arrival (DoA) information corresponding to the sensed radar data based on the adjusted steering information. The radar data processing device may locally adjust at least one of a range resolving power, an angular resolving power, or a Doppler velocity resolving power based on the ROI predicted based on a radar image map, and generate an accurate radar data processing result of a major region.

The invention discloses a coherent radial velocity spectrum target detection method based on a backtracking filter. The method comprises the following steps: constructing a sea surface echo model and a multi-frame joint detection problem; the method comprises the following steps: based on a sea surface echo model and a multi-frame joint detection problem, performing coherent accumulation on a radar receiving pulse sequence, and calculating test statistics of intra-frame coherent accumulation under each frame, each distance unit and each radial speed; based on the inconsistency of the sea clutter structural texture between the slow time Doppler velocity and the frame time radial velocity and the velocity consistency of the target on two time scales, inter-frame accumulation is carried out on the test statistics of each frame, each distance unit and each radial velocity in a distance-frame time plane along the radial velocity direction; constructing a coherent radial velocity spectrum; and in an inter-frame accumulation process, replacing a linear search accumulation mode of the coherent radial velocity spectrum between scanning by using the backtracking filter bank to obtain a coherent radial velocity spectrum based on the backtracking filter bank, and carrying out target detection by using the coherent radial velocity spectrum.

The application provides a conveyor speed detection method, device and equipment based on a dual-antenna RFID. The method comprises: tracking and processing an RFID tag by using a first antenna, and recording a first phase sequence of the RFID tag; tracking and processing the RFID tag by using a second antenna, and recording a second phase sequence of the RFID tag; determining a phase difference between the first phase sequence and the second phase sequence, and determining a phase difference speed according to the phase difference; determining a Doppler speed according to movement data of the RFID tag; fusing the phase difference speed and the Doppler speed by using a Kalman algorithm, determining a final conveyor belt speed, and outputting the final conveyor belt speed. The phase difference speed is determined according to the phase difference between the phase sequences of the two antennas. The Doppler speed is also determined. The phase difference speed and the Doppler speed are fused by using the Kalman algorithm, and the final conveyor belt speed is determined, so that the conveyor belt speed is accurately detected with high precision.

The present application relates to an apparatus for determining the ego-motion of a radar apparatus, the apparatus configured to: process radar-point-cloud information comprising a plurality of points by neural network models, the processing comprising: pointwise mapping the features thereof to a greater number of mapped-features to provide mapped-radar-point-cloud information, determining a global feature vector indicative of characteristics of the mapped-radar-point-cloud information, generating a feature matrix wherein each point therein is characterized by a feature-set based on a combination of the features, the mapped-features and the global feature vector, determining a pointwise-weight representing a likelihood that the point represents a stationary object in the space, a pointwise-offset comprising a correction to be applied to the Doppler velocity measurement to at least reduce the Doppler velocity measurement for points having a greater than expected Doppler velocity, and providing an estimate of the motion of the radar apparatus.

According to the present invention: a continuous sine wave signal is emitted toward an object serving as a target; a reflected wave comprising the sine wave signal reflected by the object is received; a frequency component of the sine wave signal that has been Doppler-shifted in accordance with the relative speed of a moving body and the object is extracted from the received reflected wave and output as a Doppler shift signal; a plurality of Doppler shift signals having a second duration are generated by cutting out, at a plurality of mutually different timings within a predetermined time period, a part of the Doppler shift signal having a predetermined first duration corresponding to the predetermined time period; a Doppler velocity for each of the Doppler shift signals having the first and second durations are calculated on the basis of the Doppler shift signals having the first and second durations; and the speed of the moving body in the current time period is determined on the basis of the calculated Doppler velocities of each of the Doppler shift signals having the first and second durations.

The present application relates to radar signal processing technical field, specifically provide a kind of staggered pulse repetition interval time-frequency domain dual-polarized radar detection variable estimation method, comprising: in frequency domain, the estimation of echo signal-to-noise ratio, reflectivity factor, differential reflectivity of horizontal / vertical polarization based on power spectral density;And the estimation of average Doppler velocity and velocity spectrum width;In time domain, after ground clutter filtering based on odd-even pulse, respectively, odd-even pulse correlation parameter estimation is carried out, so that two detection variables of dual-polarized radar correlation coefficient and differential propagation phase shift of odd-even pulse are obtained respectively, then odd-even combination can obtain the estimation result of accurate correlation coefficient and differential propagation phase shift.The present application realizes the accurate estimation of dual-polarized radar multi-class detection variable, ensures that estimation result is not disturbed by ground clutter interference, simultaneously adapts single pulse repetition interval and staggered pulse repetition interval two working modes, improves the reliability and applicability of radar detection.

The invention discloses a tunnel concrete pouring quality monitoring method, equipment and a medium, belongs to the field of artificial intelligence and the technical field of tunnel safety, and is used for solving the problems that in the existing tunnel concrete pouring process, the flow velocity detection of concrete slurry is inaccurate, and the working efficiency is low. And the pouring quality is affected by structural defects caused by uneven flow velocity. The method comprises the following steps: carrying out global and local edge feature modulation processing on an edge contour of a concrete slurry surface image in a tunnel; edge feature fusion processing under related multi-scale features is carried out; carrying out edge curve region extraction and filling processing on the slurry edge binary image, and calculating and obtaining slurry surface centroid coordinates; feeding back and obtaining a laser Doppler speed measurement signal related to the flowing of the concrete slurry; carrying out adaptive windowing processing on the laser Doppler velocity measurement signal under related signal-to-noise ratio threshold judgment; and frequency interpolation correction processing under asynchronous sampling is carried out on the noise-reduced laser Doppler velocity measurement signal.

A method of processing reference signals at an apparatus includes: obtaining, at the apparatus, a reference signal (RS) configuration corresponding to a set of pilots to be transmitted on a set of resource elements in at least one RS repetition of an allocated RS; and selectively processing, at the apparatus, only a subset of the set of resource elements, to process fewer than all resource elements of the set of resource elements, based on at least one Doppler / velocity RS measurement consideration corresponding to at least one of a Doppler RS measurement or a velocity RS measurement.

The application discloses a mapping method and device based on a 4D millimeter wave radar and a computer readable medium, the method comprising: performing noise reduction processing on 4D millimeter wave radar point clouds based on coordinate information and RCS information of the 4D millimeter wave radar point clouds in a preset sliding window; performing dynamic point cloud filtering processing on the preprocessed point clouds based on Doppler velocity to obtain static point clouds; for any current frame point cloud in the static point clouds: performing conversion processing on the current frame point cloud based on a pose conversion matrix, performing feature point registration on the converted current frame point cloud and a previous frame submap, and generating a current frame submap. In this embodiment, the RCS information and the Doppler velocity are used to perform filtering processing on the point clouds collected by the 4D millimeter wave radar; then, the static point clouds obtained after the filtering are subjected to feature point registration to form a local submap. Thus, the point clouds in a target scene can be subjected to high-precision registration, and high-precision positioning of an unmanned device can be realized.

Embodiments of the present disclosure disclose a SPP positioning model construction method and device based on factor graph optimization. The specific implementation of the method comprises: constructing a variable node set of a factor graph structure, wherein the to-be-estimated state quantity of each variable node in the variable node set at an epoch includes three-dimensional coordinates of a receiver and four parameters related to clock bias of the receiver; constructing a pseudorange factor set according to the variable node set, wherein the pseudorange factor set includes at least four pseudorange factors; correlating the position parameters between two adjacent epochs in each epoch in an observation window to construct a Doppler velocity factor, obtaining a Doppler velocity factor set, wherein the Doppler velocity factor is a binary factor; constructing a graph optimization cost function according to the pseudorange factor set and the Doppler velocity factor set, and obtaining a SPP positioning model. The implementation can improve the GNSS positioning accuracy in a complex environment.

The application provides a wideband beamforming acoustic Doppler velocity measurement system and method based on time delay control, which can transmit and receive wideband signals and solves the problem that the measurement accuracy of an existing acoustic Doppler velocity measurement system is affected by bandwidth. The velocity measurement system comprises a transducer module, a beamforming module and a conversion module; the transducer module comprises a planar transducer array and an impedance matching module connected to the planar transducer array; the transducer module is signal-connected to the beamforming module through the conversion module, the beamforming module is used for time delay compensation and weighting processing of the received signals; and the conversion module is used for converting the echo signals collected by the transducer module into digital signals and inputting the digital signals into the beamforming module, or converting the signals to be transmitted received from the beamforming module into analog signals and transmitting the analog signals through the transducer module.

The invention relates to a target sensing method based on a communication signal, and the method comprises the steps: receiving a communication signal transmitted by an active target, the communication signal being a signal combining frequency shift keying and linear frequency modulation spread spectrum modulation; carrying out carrier demodulation on the communication signal to obtain a double-channel baseband signal; performing digital beam forming processing on the double-channel baseband signal to obtain sum beam data and difference beam data; performing matched filtering processing on the sum beam data and the difference beam data; performing multi-pulse coherent accumulation processing on a matched filtering result to obtain distance-Doppler information; determining angle information of the active target based on a ratio relationship between the sum beam data and the difference beam data; and determining the distance, Doppler velocity and angle of the active target according to the distance-Doppler information and the angle information.

The application discloses an acoustic Doppler velocity information solving method and system, and relates to the technical fields of integrated navigation and underwater acoustic positioning. The application is used to solve the problem that the existing DVL velocity solving method has errors in the solved velocity and is not orthogonal, thereby leading to low navigation precision. The application comprises the following steps: acquiring eight beam angles alpha L , theta i of DVL four-beam in a carrier coordinate system by using the navigation information output by the integrated SINS / GPS and the radial velocity information V i of the DVL four-beam; obtaining the instantaneous mass estimation parameters of the four velocity measuring beam output velocities by using the echo acoustic signals collected by the DVL four-beam; and acquiring the three-dimensional velocity information output by the DVL by using the eight beam angles alpha i , theta i of the DVL four-beam in the carrier coordinate system and the instantaneous mass estimation parameters of the four velocity measuring beam output velocities. The application is used for DVL velocity solving.

The invention belongs to the technical field of underwater robot navigation, and aims to provide an underwater robot integrated navigation method and system, electronic equipment and a product. According to the invention, data acquired by an inertial navigation system, an acoustic Doppler velocimeter and an ultra-short baseline positioning system are fused, and dynamic error compensation and multi-observation data fusion technologies are combined, so that the problems of limitation and error accumulation of a single sensor in the prior art can be solved; the method can effectively improve the high-precision and robust navigation positioning capability of the underwater robot in a complex environment, provides reliable data support for path planning and navigation control, and is suitable for high-precision and long-time underwater environment operation.

A radar signal processing device (11) is configured to comprise a reception signal acquisition unit (12) that acquires a reception signal related to a reflected wave of a signal reflected from a target after the signal has been transmitted, the signal having a plurality of transmission channels in which data are modulated differently between hits, the plurality of transmission channels including an offset transmission channel in which a phase offset is applied to the data starting partway through a hit. The radar signal processing device (11) further comprises: a map calculation unit (13) that calculates, from the reception signal acquired by the reception signal acquisition unit (12), a range-Doppler map before the phase offset is applied to the data and a range-Doppler map after the phase offset has been applied to the data; and a Doppler velocity calculation unit (15) that calculates a target Doppler velocity on the basis of the range-Doppler maps calculated by the map calculation unit (13).

The application provides a large-scale space debris tracking measurement method based on CEI and belongs to the technical field of satellite signal measurement and processing. Firstly, a large-scale space debris tracking measurement overall scene based on CEI and Beidou satellite signals is constructed. Then, for large-scale space debris of different orbital heights, low-orbit and high-orbit large-scale space debris tracking measurement models based on CEI and Beidou satellite signals are established. Expressions of in-orbit running speeds, maximum Doppler speeds and maximum Doppler frequency shifts of large-scale space debris on low-orbit and high-orbit and Beidou satellites on medium-orbit are obtained. By substituting the most common orbital heights and signal frequency bands in actual tasks into the above expressions, in-orbit running speeds, maximum Doppler speeds and maximum Doppler frequency shift data of large-scale space debris and Beidou satellites in typical tasks are given. Thus, cataloging, long-term effective tracking measurement and timely early warning of abnormal behaviors of large-scale space debris are realized.

This invention relates to a method for estimating the noise floor of a two-dimensional R-V spectrum based on moving averages. This method is used to process radar echo signals to obtain the noise floor. The radar echo signal is a three-dimensional spectrum, with its three dimensions corresponding to the range index R, the Doppler velocity index V, and the signal amplitude Am under the (R,V) index. The estimation method involves traversing all (R,V) values ​​of the radar echo signal and calculating the noise floor using a two-dimensional moving average method during the traversal. This invention uses a cross-shaped two-dimensional moving average method to estimate the noise floor, increasing the noise floor calculation sample from one-dimensional to two-dimensional. The calculated noise floor is more stable and closer to the true noise floor of the R-V spectrum.

Embodiments of the present application provide a key point recognition device and method based on wireless radar signals. The method comprises: performing feature extraction on point cloud data obtained within a period of time to obtain first spatial feature data, Doppler velocity feature data, reflection energy feature data, density distribution feature data and time distribution feature data of the reflection point cloud; using a neural network-based fusion feature extraction model to detect the cascaded feature data to obtain fusion feature information; and using a neural network-based key point detection model to detect the fusion feature information to output key point data of the object. Thus, the key points of the object (such as a human body) can be detected according to the radar point cloud without limiting the action category, the required computing resources are less, and the detection accuracy is high; in addition, it is easy to implement, simple to operate, has strong noise resistance, and high privacy protection.

The application provides a behavior recognition method and device based on channel state information, electronic equipment and storage medium, the method comprises: determining the real Doppler velocity of a passive target for the channel state information of each antenna element; generating a time-Doppler velocity spectrum according to the real Doppler velocities of multiple observation times; constructing an input parameter of a trained behavior recognition model according to the time-Doppler velocity spectrum; and processing the input parameter according to the behavior recognition model to obtain a behavior recognition result. The application scheme realizes accurate recognition of the behavior category of a passive target.