226 results about "Doppler effect" patented technology

The invention relates to an unmanned aerial vehicle detection countering method, which comprises the following steps of: deploying a multi-dimensional sensing network to carry out full-band instantaneous scanning, synchronously acquiring noise characteristics of radio signals, material characteristics of a terahertz wave band and Doppler effect characteristics, mapping to a virtual twinborn body, reconstructing physical parameters, a communication protocol and a behavior mode of a target unmanned aerial vehicle, performing depth comparison by combining a disguise sample library generated by the antagonism generation network, and generating a holographic target file containing a three-dimensional motion vector, an energy feature and a potential threat intention; a target quantum encryption communication link is interfered through a quantum entanglement signal, a controllable plasma cloud cluster is generated, navigation and image transmission signals of the controllable plasma cloud cluster are selectively attenuated, the controllability of the target is judged, and an uncontrollable target is repelled through coded sound waves; and sending a control instruction containing a biological heuristic obstacle avoidance algorithm in stages, and guiding the control instruction to an intelligent recovery cabin. According to the invention, accurate detection, intelligent identification, safe countering and reliable takeover of the unmanned aerial vehicle are realized, and the airspace safety guarantee capability is improved.

The invention discloses an optical time stretching sweep frequency interference measurement Doppler effect compensation method and device, and relates to the technical field of non-cooperative target absolute distance measurement. In order to solve the defect that the absolute distance measurement precision is reduced due to the fact that the Doppler effect cannot be efficiently suppressed in a complex environment in the prior art, the technical scheme provided by the invention comprises the following steps: generating a sweep frequency laser signal and splitting the sweep frequency laser signal to form measurement light, reference light and resampling light; performing time stretching processing on the reference light to obtain a chirp signal; performing interference on measurement light and the chirp signal to obtain a measurement interference signal; performing interference on the reference light and the resampling light to obtain a reference interference signal; performing cross-correlation processing on the measurement interference signal and the reference interference signal, and extracting an optical path difference; and carrying out distance calculation by combining the resampling data, and outputting a target distance after the Doppler effect is compensated. The method is suitable for optical measurement work for performing high-precision absolute distance measurement on a non-cooperative target in a tiny vibration or disturbance environment.

The invention discloses a hydropower station water level detection method and system. The method comprises the steps that an original water flow characteristic parameter set is obtained through multiple sets of Doppler effect radar flow measuring devices; performing segmentation extraction to obtain a water flow feature sub-data set; inputting a Transform network coding layer to generate a water flow feature coding vector; outputting a preliminary water level predicted value sequence through a decoding layer; a radar flow measurement model is called for correction to obtain a correction sequence; time sequence integration is carried out to obtain a water level change curve. The system comprises a multi-source Doppler radar signal acquisition unit, a spatial-temporal feature segmentation extraction unit, a Transform coding processing unit, a water level preliminary prediction unit, a radar model correction unit and a time sequence integration output unit. According to the method and system, multi-source parameters are deeply fused, the environmental adaptability is improved, the continuity and reliability of a detection result are enhanced, the water level of the hydropower station can be accurately monitored, and support is provided for scheduling decision and safety prevention and control.

The invention provides an underwater ultrasonic signal analysis method based on the Doppler effect, and relates to the technical field of data processing, and the method comprises the steps: carrying out the segmentation processing of echo signal data according to a preset time window, carrying out the envelope demodulation and phase unwrapping operation of a signal in each time window, and carrying out the phase unwrapping operation of the signal in each time window; amplitude sequence, phase sequence and instantaneous frequency sequence data are extracted; extracting frequency change, amplitude change and phase change data, performing clustering processing, and distinguishing and marking different underwater target components; respectively calculating an amplitude stability index and a phase change synchronism index for each frequency track in all time windows, and screening a main frequency track according to the amplitude stability index and the phase change synchronism index; frequency shift values in the time windows are extracted, the speeds of the underwater targets in the time windows are calculated based on the Doppler effect, and the motion direction is judged in combination with frequency change data and phase change data; according to the invention, the autonomy and accuracy of underwater ultrasonic signal analysis are improved.

Autonomous ground vehicles that are outfitted with radar sensors and inertial measurement units accurately determine states of the autonomous ground vehicles, e.g., estimates of the vehicles' positions, orientations, or velocities or accelerations along or about one or more axes, based on data captured by the radar sensors and the inertial measurement units. Where objects are detected in radar scans, the objects are determined to be static (or fixed), or dynamic (or moving), and landmarks representing static objects are identified. Constraints on estimates of states may be calculated based on doppler effects, inertial measurement unit effects, or locations of landmarks, and the states may be determined as solutions to optimization problems based on the data and the calculated constraints. Odometry messages representing the determined states may be generated and stored or utilized for any purpose.

The invention discloses a grating displacement encoder grating spacing error in-situ detection and self-compensation method, and belongs to the technical field of optical measurement, and the method comprises the steps: generating elliptically polarized light, modulating the elliptically polarized light into S polarized light, reflecting the S polarized light through a polarization beam splitter, converting the S polarized light into circularly polarized light through a quarter-wave plate, and enabling the circularly polarized light to enter a diffraction grating ruler; the diffraction grating ruler diffracts incident light to form first-order diffraction light and second-order diffraction light; processing and interference detection are carried out on the first-order diffraction light, and precise displacement conversion is carried out in combination with the Doppler effect of grating displacement; constructing an auto-collimation angle detection sensing module by using second-order diffraction light, and converting the distance manufacturing deviation of diffraction gratings by detecting the tiny change of a diffraction angle; and compensating the displacement measurement error of the grating encoder in real time according to the real-time detection result of the grating spacing manufacturing deviation. According to the invention, the off-line detection time and cost of the grating are greatly saved.

The invention relates to the field of network security and the deep learning field, in particular to a satellite internet-oriented Tor website fingerprint identification method, which is implemented by constructing a self-supervised contrast learning framework and is implemented by generating a multi-view sample; extracting a feature matrix of the time sequence granularity; generating a synthesized negative sample based on linear insertion, and constructing a contrast with the positive sample; and track representation is extracted, and joint optimization is carried out in combination with cross entropy loss and mask reconstruction loss. Compared with a traditional website fingerprint identification method, the robustness of the model to satellite inherent noise caused by the Doppler effect can be enhanced. According to the method, multi-scale semantic features are provided for the weak enhancement view and the strong enhancement view, the inter-class distinction degree is improved by synthesizing negative samples, and the misjudgment rate is reduced; the joint loss optimization framework enables the model to give consideration to global statistical characteristics and local burst characteristics, and under the conditions of strong dynamic topology and limited labeling of satellite internet constellations, the accuracy and adaptability of website fingerprint recognition are remarkably improved.

A system for millimeter RADAR object recognition and classification using sub-band frequency interference and resonance effects from primary targets signals and reflected signals from secondary target preferably in the form of Wideband Chaos Generating Material (WCGM) objects, preferably detecting frequency dependent absorbing material, frequency dependent resonance effects from the second and primary target objects, frequency signal resonance effects caused by water molecule dipole effects in different sugar solutions, impedance of material, shape of metamaterial, and interference effects due to combination of signal sources resulting in a wider range of transmitter and scanning frequency band for RADAR based interrogation of target objects. The RADAR system makes opportunistic use of traditionally seen problematic interference signals, as extra signal sources providing extended range and frequency bandwidth for frequency-based interrogation of target object signatures in a frequency-intensity plane, a frequency-polarization plane, and a frequency-phase shift plane for doppler effects.

The invention provides an intelligent reflection surface assisted low-altitude unmanned aerial vehicle Doppler-polarization combined beam forming system, and relates to the technical field of low-altitude communication, and the system comprises an unmanned aerial vehicle-mounted communication platform, a ground base station, a distributed deployment intelligent reflection surface array and a cooperative control system. According to the method, a joint channel model capable of capturing high-speed movement and a polarization effect is constructed; a Doppler polarization combined sensing and beam forming algorithm based on the model is designed, and processing is carried out on an unmanned aerial vehicle platform and / or a base station side; an IRS reflection coefficient optimization strategy considering Doppler and polarization characteristics is provided; and a set of self-adaptive cooperative control mechanism is established. Through cooperative work among the unmanned aerial vehicle end, the base station end and the IRS, the system can effectively compensate the Doppler effect and intelligently reconstruct a propagation environment by using polarization information and by means of the IRS, so that high-reliability, strong-anti-interference and large-coverage wireless communication is realized in a complex low-altitude dynamic environment.

The invention relates to a radar identification warning method applied to an electric power line protection area, and relates to the technical field of electric power monitoring. According to the method, radar working parameters are configured by using an environment-corrected radar equation and a genetic algorithm considering a radar coverage range, radar detection accuracy and radar energy consumption; the radar detects a target in a power line protection area to obtain radar point cloud data; in the process, multi-frequency fusion ranging is used for measuring the distance of a target, and the Doppler effect is used for resolving the speed of the target; detecting and repairing abnormal values of the radar point cloud data based on an isolated forest algorithm; inputting the preprocessed radar point cloud data into a pre-trained integrated learning classifier for target identification, and obtaining target category information, speed, distance, environment data and facility operation data as risk assessment data; the risk assessment model assesses a target risk according to the risk assessment data to obtain a target risk value and a risk level probability; and performing graded warning according to the target risk value and the risk grade probability.

The invention discloses an unmanned aerial vehicle monitoring method and system in a complex electromagnetic environment, and the method comprises the steps: extracting a signal feature from a spectrum signal collected in real time, and obtaining a first feature vector; adopting a pre-constructed random forest model to classify the first feature vectors and match the first feature vectors with known unmanned aerial vehicle information to obtain a first model and a first serial number of the unmanned aerial vehicle; according to the coordinates of the at least three measurement stations, calculating the three-dimensional coordinates of the unmanned aerial vehicle by adopting a time difference of arrival positioning technology and an angle of arrival measurement technology; calculating the radial speed of the unmanned aerial vehicle relative to each measurement station by adopting a Doppler effect, and calculating a three-dimensional speed vector of the unmanned aerial vehicle according to the radial speed; and according to the three-dimensional coordinates and the three-dimensional speed vector of the unmanned aerial vehicle, predicting the change trend of the three-dimensional coordinates and the three-dimensional speed vector of the unmanned aerial vehicle in a preset time window by adopting a particle filtering algorithm. By adopting the embodiment of the invention, the identification accuracy, the positioning precision and the anti-interference capability of unmanned aerial vehicle monitoring in a complex electromagnetic environment can be improved.

The invention provides an inter-satellite link bidirectional measurement method based on a same-time same-frequency full-duplex system, which overcomes the problem that receiving and transmitting of a traditional time-division half-duplex system cannot work at the same time and at the same frequency, and can effectively improve the information transmission rate and the ranging precision. The inter-satellite transmission rate, the measurement frequency and the data updating rate can be doubled; simultaneous and same-frequency measurement between satellites can greatly eliminate distance measurement errors caused by relative motion between satellites, clock skew and Doppler effect; a complex orbit model does not need to be established to improve the distance measurement precision, the time scale reduction error is greatly reduced, and the overall measurement performance is improved.

The invention provides a low earth orbit satellite signal capturing method based on PMF-FFT. The low earth orbit satellite signal capturing method comprises the steps that firstly, low earth orbit satellite downlink signals are received and frequency mixing is carried out; carrying out adjustable parameter window adding processing on the frequency-mixed signal; inputting the windowed signal into a PMF module, and carrying out correlation calculation on the windowed signal and a local pseudo code to obtain PMF module output; carrying out adjustable parameter window adding processing on the output of each segmented matched filter in the PMF module; performing N-point FFT on the output result of the segmented matched filter; performing normalization processing on the FFT result of the # imgabs0 # point to obtain a normalized amplitude-frequency response; and performing threshold judgment according to the normalized amplitude-frequency response to realize capture. The method not only solves the problems of difficulty in broadband capture, long capture time and poor anti-Doppler effect of the traditional signal capture method, but also solves the problem that the traditional PMF-FFT method cannot break through a preset capture threshold and misses capture due to the fact that the normalized power spectral density at the target Doppler frequency shift is reduced due to energy loss under the condition of low signal-to-noise ratio. Therefore, the low-orbit satellite navigation signal can be quickly captured.

The invention belongs to the technical field of mobile communication, and particularly relates to an orthogonal time-frequency air conditioning-based integrated waveform design method, which comprises the following steps of: constructing a receiving and transmitting filter bank with a frequency spectrum shaping characteristic on a time domain level, converting an item with a complex analytic expression in a traditional architecture into a scaling factor capable of being linearly processed, and carrying out linear processing on the scaling factor; architectural simplification of a sensing signal processing flow is realized; on a delay Doppler domain level, aiming at an inter-Doppler interference mechanism caused by static environment clutter coupling and a fractional Doppler effect, a pilot frequency sequence matrix with a strong self-correlation main lobe and a weak cross-correlation side lobe is innovatively constructed, and accurate separation of aliasing echoes is realized by using a sharp delay-Doppler resolution characteristic of the pilot frequency sequence matrix. According to the scheme, through the cross-domain cooperation mechanism, on the premise of maintaining the communication sensing dual-mode performance, double breakthrough of signal processing architecture simplification and pilot frequency overhead optimization is achieved, and an innovative design framework is provided for a communication sensing integrated system in a mobile scene.

The invention provides a radar system for pipeline inner wall modeling and a pipeline inner wall modeling method, and relates to the technical field of radar application, the system comprises a millimeter wave radar and a laser radar; the millimeter wave radar is configured to emit electromagnetic waves to the inner wall of a to-be-measured pipeline and receive reflected waves of the electromagnetic waves. Based on the reflected waves, using Doppler effect and echo analysis operation to generate structural data of the inner wall of the to-be-detected pipeline; the laser radar is configured to emit a laser beam to the inner wall of a to-be-detected pipeline and receive a reflection signal of the laser beam; according to the reflection signal, calculating the flight time or phase difference of the laser beam, and generating 3D point cloud data of the inner wall of the to-be-detected pipeline; the modeling module is configured to fuse the modeling data by using an MLS algorithm to obtain modeling fusion data; and on the basis of the modeling fusion data, utilizing a Poisson reconstruction model to generate an inner wall model of the to-be-measured pipeline, so as to solve the problem that the existing single radar system is difficult to perform high-precision accurate modeling on the inner wall of the pipeline.

In aspects, a coordinating base station that forms an active coordination set (ACS) is described that includes at least the coordinating base station and a non-terrestrial network base station (NTN BS) for joint-communication with a user equipment (UE). Based on an evaluation of terrestrial channel conditions for the UE, the coordinating base station selects one or more non-terrestrial NTN BSs as candidate base stations to add to the ACS. The coordinating base station transmits ephemeris information for the one or more NTN BSs to the UE. The UE acquires and measures signal quality of each of the NTN BSs and sends an indication to the coordinating base station. Based on the indication, the coordinating base station sends an invitation to the NTN BS to join the ACS which communicates using timing and frequency compensation to compensate for distance and Doppler effects.

The invention discloses an OTFS signal-based high-precision target parameter estimation method for a common-inductance integrated system, which is based on a recursive optimization super-resolution estimation algorithm, combines a grid refining method and a recursive optimization strategy, and adopts a two-stage estimation framework. In the first stage, super-resolution estimation of time delay and Doppler frequency shift is realized through a grid refinement technology, and the estimation precision is improved; and in the second stage, a multi-path interference recursive optimization mechanism is combined, so that the influence of a multi-path effect on estimation precision is effectively reduced, and the reliability and robustness of estimation are further improved. Under the condition of processing fractional time delay and Doppler frequency shift, the method provided by the invention obviously improves the estimation precision in a complex channel environment, and can effectively solve the problem of parameter estimation under fractional time delay and Doppler effect.

The invention relates to driver monitoring, in particular to a driver monitoring method based on high-frequency sound wave modeling, and the method comprises the steps: transmitting high-frequency sound waves into a vehicle; when the driver is in the normal driving state, echo signals reflected in the vehicle are received, and a reference sound wave feature library about the limbs of the driver is established; disturbed echo signals in the vehicle are collected in real time, and to-be-recognized sound wave features about the limbs of the driver are extracted; inputting the to-be-recognized acoustic wave features into the trained action recognition model to obtain an action recognition result; the Doppler effect of the echo signals is analyzed, the motion direction and speed of the motion are obtained, and the motion frequency is determined; performing graded early warning by combining the action recognition result, the motion direction and speed of the action and the action frequency; according to the technical scheme provided by the invention, the defect that the action of the driver is difficult to accurately recognize in the prior art can be effectively overcome.

According to the unmanned aerial vehicle capturing method and device, the electronic equipment and the storage medium, the operation sound and image of the unmanned aerial vehicle are collected, the recognition reliability is improved by using double information sources, and whether the target object is the unmanned aerial vehicle or not can be more accurately judged in combination with the sound features and the image features, so that the recognition accuracy is remarkably improved. In addition, the motion state of the unmanned aerial vehicle is analyzed by using a Doppler effect algorithm, and the operation speed of the unmanned aerial vehicle is identified in combination with an optical flow algorithm, thereby realizing comprehensive monitoring of the motion state of the unmanned aerial vehicle. The multi-dimensional monitoring mode not only improves the accuracy of unmanned aerial vehicle position determination, but also provides powerful data support for subsequent unmanned aerial vehicle capture, so that the accuracy of unmanned aerial vehicle identification and the success rate of capture can be significantly improved.

The present application relates to the technical field of radar detection, and particularly relates to a particle flow multi-parameter detection method based on MIMO-FMCW radar, a medium and equipment, the particle flow multi-parameter detection method based on MIMO-FMCW radar comprises the following steps: S1, arranging a virtual channel array structure of × in a detection area, and obtaining a digital signal matrix of multiple frames of measurement data corresponding to the detection area by using the virtual channel array structure; S2, obtaining multiple parameters of the particle flow in the detection area based on the digital signal matrix.The present application synchronously obtains data in the time, frequency and spatial domain by using the MIMO-FMCW radar system, realizes the joint measurement of the multiple parameters of the particle flow, can extract the speed information by the Doppler effect of the FMCW signal, can form a virtual channel to extract the angle information, and simultaneously combines the signal amplitude to estimate the concentration, so that comprehensive particle flow movement characterization is realized.

The invention discloses a scene adaptive 6G indoor positioning method based on a transfer learning thought, and the method comprises the steps: quantifying environment features through a Gaussian mixture model, designing a multi-objective optimization function, and obtaining a standard scene basic fingerprint database; a transfer learning thought is introduced, and graph structure connection strength is dynamically adjusted through real-time 6G signal quality perception; constructing a multi-source joint compensation function, and optimizing the influence of the multipath effect and the Doppler effect; and finally, based on an error compensation algorithm of inter-domain difference dynamic feedback, quantizing the signal distribution difference of the basic fingerprint database and the real-time positioning scene fingerprint database through maximum mean value difference, taking the quantized signal distribution difference as an optimized weight of a hierarchical fusion environment factor for a positioning result, and performing adaptive correction on the positioning result in combination with a positioning error of a source positioning model to obtain a positioning result. Therefore, an indoor positioning result is obtained. According to the invention, the problem that a single positioning model is reduced in positioning precision or cannot be used due to scene switching is solved, and the positioning precision is high.