13 results about "Multipath propagation" patented technology

An information display device is a device worn on a user's head. Here, the information display device includes a processor and an antenna capable of receiving multipath propagating radio waves. The processor analyzes the multipath propagation information of the radio waves received by the antenna. If the processor detects the presence of a moving object based on the analysis results, it alerts the user.

Embodiments of the disclosure describe a method for dynamically configured beam forming that mitigates remote interference experienced by a second base station (200) while scheduling at least one of uplink and downlink transmission for a plurality of UEs (201) associated with the second base station (200). The method includes receiving a plurality of Radio Frequency (RF) signals from a first base station (100). The plurality of RF signals is traversed through a multipath propagation channel and has been interfered by the atmospheric ducting propagation. The method includes determining a multipath channel impulse response (Hij) corresponding to each path and scatterer associated with the plurality of received RF signals. The method includes dynamically configuring beam forming for the plurality of UEs (201) associated with the second base station (200). The beamforming is dynamically configured based on the multipath channel impulse response (Hij).

The application discloses a kind of Buddha jumps over the wall flow circulation traceability system, specifically relates to supply chain management technical field;It is by obtaining the radio frequency identification tag data and corresponding cold-chain storage metal shelf space coordinate data set on Buddha jumps over the wall package, the main path signal feature sequence and reflection path signal feature sequence are formed to radio frequency identification tag read-write signal is carried out multipath propagation decomposition;The main path signal feature sequence and reflection path signal feature sequence are carried out time delay difference value matching, obtain the radio frequency identification tag effective identification sequence that satisfies preset time delay stability condition;Based on radio frequency identification tag effective identification sequence, Buddha jumps over the wall freeze-drying processing batch data and cold-chain storage batch data are carried out batch mapping verification, and flow batch association data is generated;Flow batch association data is carried out continuous time window consistency verification, and forms cold-chain flow effective traceability data;According to cold-chain flow effective traceability data, update Buddha jumps over the wall flow circulation traceability database and output real-time traceability record.

This invention belongs to the field of wireless communication and relates to a machine learning-based method for wireless communication channel estimation. The method includes: acquiring pilot signals, antenna array geometric parameters, and multipath propagation parameters from the transceiver end of a millimeter-wave massive MIMO system to construct a three-dimensional propagation structure model; determining candidate regions for the channel sparse support set and generating a prior constraint matrix for the channel sparse support; inputting the prior constraint matrix and pilot observation data into a sparse reconstruction algorithm for channel sparse feature extraction and dimensionality reduction; performing super-oscillatory feature enhancement on the dimensionality-reduced channel sparse features to form an enhanced channel feature vector; inputting the enhanced channel feature vector and the prior support vector matrix into a complex domain deep expansion network to output the channel estimation result; and outputting the final beamforming weights. Its beneficial effects are improved sparse support set matching accuracy and channel estimation precision with low pilot overhead, and enhanced system throughput and interference suppression capabilities.

The application discloses a UAV beam tracking method based on deep learning and layered scanning cooperation, which comprises the following steps: S1, signal receiving and preprocessing; S2, deep learning intelligent sensing and routing decision; S3, layered codebook scanning; S4, time domain smoothing and trajectory tracking; and S5, beamforming execution. The application introduces a deep network to replace a complex matrix decomposition operation, realizes fast and stable tracking of a phased array antenna beam of a UAV under complex channel conditions such as multipath propagation and low signal-to-noise ratio, solves the problems of poor timeliness and insufficient robustness of a traditional algorithm under a limited computing power platform, has extremely high system reliability, dynamic tracking stability, and also considers speed and accuracy.

This invention relates to the field of underwater weld technology and discloses a method and system for forward modeling of nonlinear ultrasonic scattering in the early stage of underwater welds. The method includes: obtaining material nonlinear parameters based on the ratio of second harmonic to fundamental wave amplitude; obtaining interface contact nonlinear parameters through the second harmonic amplitude in the reflected wave from the crack interface; establishing water-solid interface propagation conditions and constructing a sound velocity model; combining the sound pressure superposition relationship under multipath propagation and array excitation conditions to obtain the total fundamental wave sound pressure at any receiving point within the weld; and constructing a unified nonlinear ultrasonic forward scattering model by introducing equivalent local nonlinear parameters for unified characterization. This invention, by constructing a unified characterization model of material nonlinearity and contact acoustic nonlinearity, and combining the water-solid coupling propagation mechanism with Green's function forward modeling, can improve the completeness of the description of nonlinear ultrasonic scattering mechanisms and the accuracy and stability of the quantitative characterization of early-stage micro-damage in underwater welds.

This invention discloses a method for 3D environmental feature extraction and electromagnetic propagation path modeling based on neural networks, belonging to the field of channel modeling technology. The method includes: S1: acquiring wireless channel data of the target scene and corresponding 3D spatial point cloud environmental data; S2: obtaining a physical environment feature dataset for neural network training; S3: constructing a 3D environmental feature extraction model to generate implicit environmental feature representations reflecting the relationship between environmental spatial distribution and material properties; S4: constructing an electromagnetic propagation direction prediction model and a power prediction model to predict the step-by-step evolution of the electromagnetic propagation path and output electromagnetic propagation path-level characteristics. This invention solves the problems of complex and inefficient existing modeling processes, difficulty in directly utilizing measured point cloud data, and difficulty in efficiently generating multipath propagation paths. This invention improves modeling efficiency and reduces labor costs, enabling direct modeling of point cloud geometry and material properties while reducing the computational complexity of multipath path inference.

This invention discloses a wireless channel multipath prediction method based on point cloud deep learning, involving the cross-application technology of deep learning and wireless channel modeling. The method includes: 1) acquiring 3D point cloud data of a communication scene and preprocessing it to obtain standardized 3D point cloud data; 2) generating Gaussian scattering primitives (GSPs) representing the scene's geometric structure and scatterer distribution using the proposed construction and optimization algorithm, and saving the spatial location and shape information of the GSPs as GSP features; 3) combining the GSP features with the spatial location information of the transmitter (Tx) and receiver (Rx), inputting them into a RayFormer model for training, and optimizing the model to predict multipath information; 4) filtering the interaction point coordinates predicted by the RayFormer model using a physical confidence calculation algorithm, ultimately obtaining geometrically reasonable prediction points. This invention can mine environmental geometric information in 3D point clouds, achieving accurate prediction of multipath propagation paths in complex scenes.

The present application relates to the technical field of device testing, solves the problem that there is no RTK differential positioning device testing scheme capable of truly and controllably reproducing multipath propagation effect in a vehicle application scenario in the prior art, and provides a vehicle-mounted RTK differential positioning device testing method, system and storage medium, a virtual physical environment is constructed according to a testing plan; signal simulation is performed according to vehicle motion parameters and environment parameters, to obtain direct signals and synthetic signals; differential correction is performed according to the direct signals, to obtain correction data; the synthetic signals and the correction data are input into a to-be-tested vehicle-mounted RTK differential positioning device for positioning calculation, to obtain calculated vehicle motion parameters; and a testing result of the to-be-tested vehicle-mounted RTK differential positioning device is obtained according to the calculated vehicle motion parameters and the vehicle motion parameters. The embodiment of the present application improves testing accuracy by constructing a virtual physical environment, simulating an actual driving scenario, and taking vehicle motion parameters and environment parameters into account.

The present application relates to the technical field of unmanned aerial vehicle countermeasure, in particular to an unmanned aerial vehicle countermeasure method optimized by genetic algorithm; the present application realizes accurate prediction of the flight trajectory of the unmanned aerial vehicle by fusing multi-source data through Kalman filtering algorithm, solves the interference problem caused by the multipath propagation effect by optimizing the antenna parameter combination using the genetic algorithm, and significantly improves the directivity and stability of the interference beam by coordinating the multipath path compensation through the particle swarm optimization algorithm; combined with the minimum injury distribution and the real-time environment feedback mechanism, the present method can dynamically adjust the countermeasure strategy, minimize the injury risk to the surrounding equipment, and at the same time ensure the continuous optimization of the interference effect.

The application provides a buoy cooperative underwater positioning system based on multipath suppression and sound velocity profile correction, and has the characteristics that the system comprises an intelligent buoy network module, a sound velocity measurement module, a signal suppression module and a cooperative positioning module; the intelligent buoy network module is used for constructing a positioning reference network through a plurality of buoys distributed in space in a target water area; the sound velocity measurement module is used for obtaining sound velocity distribution information of an underwater environment; the signal suppression module is used for identifying and suppressing multipath propagation interference in an underwater acoustic channel; and the positioning solution module is used for obtaining an accurate three-dimensional space position of an underwater target; through the cooperative positioning mechanism of multipath inversion suppression and trajectory prediction constraint, the underwater target positioning system achieves the technical effects of high positioning accuracy, strong stability and good robustness in a complex underwater acoustic environment.