272 results about "Multipath effect" patented technology

The invention provides an unmanned aerial vehicle high-precision autonomous navigation method and system based on GNSS and IMU deep fusion, and aims to solve the problems of insufficient navigation precision and poor robustness in a complex electromagnetic environment. Through a tight coupling architecture, GNSS original observed quantity and IMU pre-integration results are jointly modeled in an observation layer, and multi-source constraints are introduced in combination with factor graph optimization, so that the positioning precision and consistency in weak signal and shielding scenes are remarkably improved. For abnormal observation, a robust kernel function is adopted to dynamically adjust the weight, and the influence of electromagnetic interference and a multipath effect is effectively inhibited. Meanwhile, navigation calculation and model prediction control MPC are combined, and sub-meter hovering and high-precision trajectory tracking are achieved. According to the method, in high-voltage transmission line inspection, dependence on a high-cost sensor is reduced, the engineering application value is high, the method can be widely applied to the fields of electric power inspection, disaster emergency, infrastructure monitoring and the like, and reliable technical support is provided for high-precision autonomous navigation of the unmanned aerial vehicle in a complex environment.

The invention discloses a signal processing method based on deep learning and adaptive filtering fusion. The method comprises the following steps: S1, collecting and preprocessing an original signal; s2, carrying out adaptive filtering; s3, constructing a deep neural network model to perform deep feature extraction on the filtered signal; s4, signal fusion and interference elimination are carried out; S5, a real-time closed-loop feedback mechanism is established, and dynamic parameter adjustment is carried out; s6, performing an end-to-end dynamic optimization process; s7, performing iterative updating and high-confidence sample judgment; and S8, processing a newly collected signal by using the trained adaptive filtering module and the deep neural network model, and generating a reconstructed signal through signal fusion. According to the method, through effective fusion of adaptive filtering and the deep neural network, accurate suppression and high-dimensional feature extraction of a multipath effect, nonlinear noise and transient interference in a complex wireless signal are realized, so that the precision, robustness and real-time performance of signal processing are remarkably improved.

The invention discloses an indoor UWB-IMU fusion trajectory tracking system and method based on factor graph optimization, and belongs to the technical field of UWB indoor positioning. The system adopts a multi-stage processing framework, and specifically comprises the following steps: firstly, collecting channel pulse response and distance information by virtue of a wireless communication system, constructing a dynamic environment sensing mechanism, and evaluating the current channel state and the availability of each base station in real time; secondly, for the ranging values of the available base stations in the NLOS environment, compensating by using historical information, and for the ranging values of the unavailable base stations, estimating and correcting by using a time step length; and finally, collaborative optimization is carried out on UWB ranging data, IMU inertial information and base station state information through an SW-FGO algorithm, so that positioning stability is ensured, and adverse effects of obstacle shielding and a multipath effect on trajectory tracking precision are reduced. The invention provides a fusion positioning system which combines the advantages of UWB and IMU, can realize the tracking of a target motion track, and is suitable for most LOS and NLOS indoor mixed scenes.

The invention relates to the technical field of coal mine telecommunication, and discloses a coal mine underground integrated private network coverage system based on a 5G communication and AR double-transmitting selective-receiving technology, an efficient transmission and baseband processing network is constructed by taking a macro base station as a core on the ground and matching with PTN equipment and a BBU, a 5G micro base station and an RRU are deployed under the ground for a complex environment, and low-loss signal coverage is realized through optical fibers. The AR double-transmitting selective-receiving module ensures that underground data are not lost and have no error through redundant coding and double-link transmission; the edge computing module sinks data processing to the underground, reduces transmission delay and optimizes resource allocation; and the system monitoring and interference suppression unit monitors the operation state in real time, performs multi-stage alarm and resists multipath effect and electromagnetic interference, and finally realizes integration of communication above and under the well, reliability of data transmission, high efficiency of resource utilization and stability of system operation, thereby providing solid communication support for safety production, equipment management and control and personnel scheduling under the coal mine.

The invention relates to the technical field of Bluetooth positioning, and discloses a Bluetooth positioning method and system based on multi-beacon RSSI weighted optimization, and the method comprises the steps: sequentially switching and scanning a broadcast signal of a target Bluetooth tag through a plurality of Bluetooth beacons disposed at a fixed position, so as to obtain a plurality of groups of RSSI measurement values from different directions; performing filtering processing on the multiple groups of RSSI measurement values to suppress signal fluctuation; calculating the weight of each beacon based on the filtered RSSI value, and constructing a weighted least square positioning model; and solving the coordinate position of the target Bluetooth tag by using a weighted least square positioning model. According to the invention, through adoption of a multi-beacon rapid switching acquisition and RSSI weighted optimization mechanism, signal quality differences of different beacons can be effectively distinguished, and dynamic weight descending processing is carried out on measurement values which are seriously interfered by a multipath effect and shielding, so that the positioning precision and stability in a complex indoor environment are remarkably improved.

The invention relates to an unmanned aerial vehicle high-precision positioning method based on a satellite-based enhancement system and adaptive Kalman filtering. The method comprises the following steps: acquiring multimode satellite data; analyzing the satellite-based enhanced telegraph text data, and performing error correction on the original observation data; based on the corrected observation data, dynamically adjusting a process noise covariance matrix by using the motion state of the unmanned aerial vehicle, and constructing an adaptive Kalman filtering model; and based on an adaptive Kalman filtering model, fusing the corrected observation data and inertial measurement unit data to obtain unmanned aerial vehicle positioning. The method aims to solve the problems that unmanned aerial vehicle positioning in complex environments (such as urban canyons, electromagnetic interference areas and mountainous areas without ground base stations) is remarkable in multipath effect and has dynamic noise interference, and traditional differential positioning depends on ground base stations. The centimeter-level continuous positioning of the unmanned aerial vehicle in a complex scene is realized through triple technical breakthroughs of satellite-based differential correction, dynamic optimization of environmental perception filtering parameters and multi-source data tight coupling solution.

The invention relates to the technical field of power signals, in particular to a power line broadband carrier signal adaptive enhancement and noise reduction method and system. According to the method, the multi-dimensional interference characteristics of the power line transmission environment are acquired and the initial modulation parameters are pre-adjusted, so that the influence of environmental interference can be reduced at the initial stage of signal transmission, the signal transmission quality is improved, and the multi-path delay inequality of the aggregated signal and the channel attenuation coefficient are acquired in real time and are combined with dynamic channel adjustment, so that the signal transmission efficiency is improved. Signal components can be dynamically adjusted and optimized according to real-time changes of a power line channel, the adaptive capacity of a system is improved, signals can be optimized in real time by means of real-time transmission quality monitoring and optimization of enhanced carrier signals, the lagging influence of signal quality is avoided, and the system performance is improved. The method ensures that the power line communication system has good adaptive enhancement and noise reduction capabilities, improves the overall performance of the communication system, and can effectively overcome the influence of multipath effect, electromagnetic interference, attenuation and other factors on channel estimation in the prior art.

The present application relates to the technical field of speech processing, and particularly relates to a mixed speech processing method, an electronic device and a computer readable medium. The method comprises the following steps: collecting mixed speech and environmental influence parameters; performing bionics frequency domain analysis on the mixed speech to obtain low-frequency attenuation compensation feature data; performing multipath effect propagation analysis on the low-frequency attenuation compensation feature data through the environmental influence parameters to generate channel distortion data; performing time domain-frequency domain joint deconvolution processing on the mixed speech by using the channel distortion data to generate direct sound components and reflected sound components; performing adversarial training based on the direct sound components and the reflected sound components to generate anti-multipath speech enhancement data; and constructing a dynamic frequency compensation filter based on preset environmental acoustic characteristics. The present application improves the output quality of mixed speech through multi-stage signal processing, frequency compensation and real-time optimization technology.

The invention belongs to the technical field of indoor positioning, and discloses a Bluetooth path loss model parameter adaptive calibration method and system. According to the method, the historical learning mechanism and the hybrid optimization strategy are fused, so that the global search capability and the local optimization precision are considered while the dynamic updating of the path loss model parameters is realized. Compared with an existing calibration method of a fixed parameter or a single optimization algorithm, the method can automatically correct the model parameters according to the environment change, and solves the problem that the precision of a traditional model is reduced under the conditions of multipath effect, shielding interference and environment sudden change. A hybrid optimization framework of a genetic algorithm and a particle swarm algorithm is introduced, so that a parameter optimization process obtains a high-quality initial value in a global search stage, rapid convergence is realized in a local fine adjustment stage, and the calibration efficiency and precision are remarkably improved. And meanwhile, a historical learning mechanism is added, so that the model has a time memory characteristic, smooth mutation of historical parameter information can be fused, and the stability and robustness of the method in a complex dynamic environment are improved.

The invention provides a wind power tower monitoring data dynamic compensation and fusion method for Beidou positioning, and relates to the technical field of data processing and signal processing. The method comprises the steps of obtaining original positioning data of a wind power tower, and performing data preprocessing; performing real-time analysis on the preprocessed original positioning sequence, and extracting characteristic values reflecting a multipath effect and an ionosphere delay degree; constructing a state space model, designing an adaptive module based on characteristic values, adjusting a filtering process noise matrix and an observation noise matrix in real time, and filtering the positioning data to obtain preliminary filtering data; establishing a lightweight neural network model, predicting the error compensation amount at the current moment, and compensating the preliminary filtering data; and carrying out tight coupling fusion on the compensated Beidou positioning result and high-frequency attitude data output by the IMU, and outputting a final displacement sequence. According to the method, a stable, reliable and high-precision tower drum deformation data sequence can be output.

The invention relates to the technical field of radio navigation and countering, and particularly discloses an unmanned aerial vehicle interference system and device based on phased array radar direction finding. The system comprises a phased array radar direction finding module, an environment electromagnetic propagation characteristic modeling module, an interference beam dynamic planning module and a digital beam forming interference module. Through constructing a three-dimensional electromagnetic propagation model and based on propagation loss and a multipath effect predicted by the model, a beamforming weight used for pre-compensating environmental influence is optimized and calculated, and finally an interference antenna array is driven to radiate an intelligent beam subjected to environmental pre-compensation, so that high-intensity interference is formed at an actual physical position of a target unmanned aerial vehicle, and the target unmanned aerial vehicle is subjected to environmental pre-compensation. Direction finding errors are overcome, and interference efficiency and electromagnetic compatibility are improved.

The invention relates to the technical field of computer vision, and discloses a precise medicine delivery method and system, and the method effectively strips illumination artifacts through the construction of a local gradient structure tensor field and an anisotropic screening mechanism, remarkably improves the robustness of a visual front end in a light and dark alternating environment, and improves the accuracy of medicine delivery. Rigid body motion constraint and Lie algebra continuous modeling are utilized, high-precision space-time alignment between heterogeneous sensors is realized on the premise that scene depth does not need to be recovered, hardware delay errors are eliminated, a physical-driven probability weight dynamic allocation mechanism is constructed by introducing a multipath scattering index and a structural information entropy flux, and a dynamic space-time alignment algorithm is established. Environment degradation is sensed in real time, the observation weight is adjusted in a self-adaptive mode, the influence of the non-line-of-sight multipath effect and visual texture missing is effectively restrained, high-precision inertial dead reckoning can still be maintained in a blind area where a sensor is in full failure in combination with momentum prior information generated through Schel complement marginalization operation, and the method has the advantages of being high in precision and high in precision. And the navigation continuity and reliability of the distribution robot in a complex scene are ensured.

The invention provides a high-reliability lamp mutual positioning method, system and device and a medium. The method comprises the following steps: determining a mutual influence relationship between lamps through reference parameters of the lamps with a visible light communication function in a target shopping mall during installation and working state parameters of visible light signals of the lamps; determining an interference feature vector of each lamp in the positioning process according to the mutual influence relationship, the multipath effect of the visible light signal and the interference superposition feature; determining a positioning constraint condition of each lamp, and determining a cooperative positioning parameter of each lamp through all the positioning constraint conditions and all the interference feature vectors; and determining relative positioning information of each lamp in the target shopping mall according to the anti-interference configuration parameter of the visible light signal of each lamp in the positioning process and all the cooperative positioning parameters. By adopting the scheme of the invention, the influence of the multipath effect and signal attenuation between the lamps on mutual positioning of the lamps can be reduced, so that high-reliability mutual positioning of the lamps is realized.

The invention relates to the technical field of indoor positioning, in particular to a millimeter wave CSI (Channel State Information) indoor positioning method and system based on a generative adversarial network, and millimeter waves are large in bandwidth, narrow in beam, high in time resolution and space angle resolution and capable of reducing the influence of a multipath effect. Position estimation is directly obtained from CSI data directly obtained in the millimeter wave communication process, complex signal processing and filtering steps of obtaining other parameters from CSI are avoided, and the system calculation complexity is greatly reduced. The information of the AP position is extracted from the high-dimensional observation vector by using the generative adversarial network, so that complex positioning algorithms such as Kalman filtering or graph optimization are avoided, and the calculation complexity is reduced; according to the method, AP position estimation is obtained through confrontation training of the generator and the discriminator, position coordinates of reference points do not need to serve as labels, input data are all label-free data, dependence on marked data is avoided, and prior knowledge such as the AP or the reference points is not needed.

The invention relates to the technical field of satellite navigation positioning, in particular to a Beidou robust Kalman filtering positioning method based on a non-Gaussian noise model. According to the method, non-Gaussian noise generated by shielding and a multipath effect in Beidou positioning is accurately represented by constructing a Gaussian mixture model and a student t distribution model, model parameters are updated online by an expectation maximization algorithm, and the problem that a traditional Gaussian hypothesis model cannot adapt to noise statistical characteristics is solved; the non-Gaussian noise model is fused with robust filtering, a self-adaptive robust weight matrix is constructed through a Huber cost function, an IGGIII scheme or noise probability density, an observation covariance matrix is dynamically adjusted, the influence of abnormal observation values is suppressed, the defects that classical robust filtering lacks noise modeling and weight adjustment fails under continuous strong interference are overcome, and the robustness of the robust filtering is improved. And meanwhile, the problem of complex particle filtering calculation is avoided.

The invention provides an ultrasonic positioning method and electronic equipment, and relates to the technical field of ultrasonic localization, and the method comprises the steps: installing an ultrasonic device on a to-be-positioned object, and arranging a plurality of radio devices in a working space of the to-be-positioned object; obtaining an ultrasonic time difference corresponding to each radio device; and determining the position of the to-be-positioned object based on each ultrasonic time difference and the sound velocity of the ultrasonic signal. According to the invention, the plurality of sound receiving devices are arranged in the working space, and the ultrasonic time difference corresponding to each sound receiving device is obtained according to the fact that the time when the ultrasonic device sends the ultrasonic signal to each sound receiving device is different; therefore, by comprehensively analyzing the sound velocity of the ultrasonic signal and the ultrasonic time difference corresponding to each radio device, the influence of a multipath effect during positioning is avoided, and the positioning precision is improved.

The invention belongs to the technical field of pavement detection, and discloses a highway pavement roadbed detection method and system based on laser three-dimensional scanning. By establishing an analytic optical or radar scattering physical model, a distance measurement deviation initial value conforming to a multi-path reflection physical mechanism is provided for each laser measurement point, and then refined correction is performed on the initial value through a residual error regression network fusing local point cloud context information, so that advantage complementation of physical prior and data driving is realized, and the accuracy of distance measurement is improved. And finally, in combination with adaptive filtering based on a confidence map, ranging errors caused by a multi-path effect can be effectively distinguished and corrected in the presence of complex road surface conditions such as slippery road surface, greasy dirt or thin water film, and meanwhile, geometric details such as real road surface pits, textures and the like are completely reserved. Therefore, the reconstruction error and the disease false alarm rate of the pavement digital elevation model are obviously reduced, and the precision and the reliability of highway pavement roadbed detection are improved.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle positioning and orienting method, which comprises the steps of data acquisition and space-time alignment, environment feature fingerprint extraction, adaptive robust factor graph construction and dynamic covariance reweighted optimization. According to the method, the environment feature fingerprints are introduced as a prior diagnosis mechanism, GNSS non-line-of-sight propagation and visual feature depletion areas can be identified in real time, dynamic reweighting is carried out by utilizing the environment feature fingerprints on the factor graph optimization level, GNSS observation values polluted by a multipath effect or visual features with poor quality are automatically inhibited, and the accuracy and the reliability of the GNSS non-line-of-sight propagation and visual feature depletion areas are improved. Therefore, smooth seamless switching from loose coupling to tight coupling is achieved in urban canyons or indoor and outdoor transition areas, posture sudden change caused by traditional fixed threshold switching is avoided, and the positioning reliability of the system in complex electromagnetic and light environments is remarkably improved.

The invention discloses an indoor positioning track tracing and area early warning method and system, and relates to the technical field of indoor positioning, the method comprises the following steps: receiving a positioning signal, and synchronously collecting inertial navigation data of an inertial measurement unit; filtering processing is carried out on the positioning signal, non-line-of-sight interference and multipath effect interference components are identified, and interference compensation parameters are generated; after a positioning signal is calibrated by combining the parameters, real-time position coordinates are calculated; running a pedestrian dead reckoning algorithm on the basis of inertial navigation data to obtain continuous relative position coordinates, and correcting by taking the real-time position coordinates as reference to form initial movement track data; presetting an early warning area boundary and a triggering condition, and if the condition is met, starting an early warning response and recording an early warning event; and integrating the continuous real-time position coordinates, the initial movement track data and the early warning event records, and constructing a complete movement track file to realize track tracing. The system is matched with the method, the positioning reliability in the indoor complex environment can be improved, and continuous track tracing and accurate area early warning are supported.

The invention relates to the technical field of semiconductor radio frequency signal processing, and discloses a narrowband signal receiving system and method, and the system comprises a coarse frequency offset value capturing module, a carrier phase locking module, a digital domain carrier tracking module, a timing synchronization and multipath correction module, and a vector amplitude phase correction and equalization module. In the prior art, the technical problems of lock losing, judgment errors and high bit error rate caused by serious multipath interference and frequency offset drifting of narrow-band signals are difficult to solve in complex environments with multipath effect and high frequency offset, such as urban canyons, basements and warehouses. According to the invention, by introducing analog phase locking, digital fine tuning, dual-correlation symbol synchronization based on multi-path sensing and vector amplitude-phase combined compensation overall architecture with cooperation of analog and digital, the problems of synchronization failure and demodulation performance reduction caused by multi-path distortion in the prior art are avoided; and the sensitivity and the overall reliability of radio frequency signal receiving are remarkably improved.

The invention relates to the technical field of power transmission line state monitoring, and particularly provides a power transmission line dynamic dance positioning detection method and system, and the method comprises the following steps: collecting Beidou positioning data, pose data and environment parameter data of a power transmission line in real time; correcting the Beidou positioning data according to the coordinate error component and the pose data of the base station, and filtering a multipath effect deviation signal to obtain absolute coordinate data; calculating galloping parameter data of the power transmission line according to the absolute coordinate data; and dynamically fusing the galloping parameter data and the environment parameter data to obtain comprehensive detection data. The problems of large dancing posture detection error and high time delay of the power transmission line in the prior art are solved.

The invention relates to the field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle autonomous fixed-point landing control method based on an ultrasonic array algorithm, and the method comprises the steps: dividing the landing process of an unmanned aerial vehicle into a normal flight stage, a deceleration approaching stage and a near-ground landing stage, starting an ultrasonic beacon array in the approaching flight stage, and confirming the availability of a landing point; a horizontal azimuth angle, a yaw angle and a relative distance are calculated in real time in a deceleration approach stage to perform landing guidance, direct waves and multi-path reflection signals are analyzed in a near-earth landing stage, characteristic parameters such as time delay inequality and phase offset are extracted, an environment reflection space model is reversely constructed, then positioning correction is calculated, a pose fine adjustment instruction is generated, and the attitude fine adjustment instruction is subjected to attitude fine adjustment. And precise fixed-point landing of the unmanned aerial vehicle is realized. According to the method, high-precision positioning is kept under complex environment disturbance, and the stability, accuracy and efficiency of fixed-point landing of the unmanned aerial vehicle in a complex environment are improved by converting the multipath effect from an interference source to available positioning information.

The invention discloses a UWB indoor positioning method based on an RTK difference thought, and relates to the technical field of indoor positioning. Comprising a base station, reference stations and a mobile station, and specifically comprises the following steps that 1, UWB signals are sent through the base station, a plurality of reference stations with known accurate coordinates are deployed indoors, the reference stations are UWB anchor points, and the positions of the reference stations are calibrated in advance through laser surveying and mapping; according to the method, the base station with the known accurate position is deployed indoors, the base station is used for calculating the error in the UWB signal propagation process, the error correction information is sent to the mobile station, and the mobile station corrects the distance measurement result of the mobile station according to the correction information, so that the precision and the stability of UWB indoor positioning are improved. The UWB indoor positioning method effectively solves the problem of positioning errors caused by factors such as multipath effect, non-line-of-sight and clock drift in UWB indoor positioning, and is suitable for various indoor scenes such as industrial storage, medical care for the aged and emergency rescue.

The invention discloses a DAS high-precision positioning method, system and device based on deep learning, and a medium, belongs to the technical field of optical fiber sensing, and aims to solve the technical problem of low positioning precision when an existing DAS optical fiber sensing array performs vibration source positioning in complex environments with environmental noise, multipath effect and the like. The method comprises the following steps: arranging optical fibers on the ground, and acquiring vibration signals at different positions by using a distributed optical fiber sound wave sensing system to obtain a two-dimensional space-time signal sample; carrying out time delay estimation by utilizing a self-adaptive short-time energy method based on a signal-to-noise ratio, and eliminating an abnormal time delay value through a multi-sample joint method; in order to reduce the data acquisition cost, a time delay data set is constructed by simulating a time delay array at a known position and combining a small amount of measured data; a time delay data set is adopted to train the constructed vibration source signal positioning prediction network; and efficient and accurate vibration source positioning is realized.

The invention discloses a self-supervised ultra-wideband positioning method based on an improved double-delay depth deterministic strategy. The method comprises the following steps: acquiring channel impulse response data CIR and performing preprocessing; an improved double-delay depth deterministic strategy model is constructed to carry out UWB ranging error correction, the improved double-delay depth deterministic strategy model is based on a double-delay depth deterministic strategy gradient model, a double-commentator network structure is designed, a spatial-temporal feature coding layer based on a self-attention mechanism is introduced, and UWB ranging error correction is carried out. Capturing a long-range dependency relationship through a dynamic weight distribution mechanism, and establishing cross-timestamp time-space association feature mapping; a target network delay updating mechanism is introduced, so that the updating frequency of a target network is lower than that of a commentator network and an actor network, and action noise generated by a strategy is regularized; and generating a pseudo tag by adopting extended Kalman filtering, and carrying out iterative optimization to obtain a positioning result. The method is particularly suitable for processing noise and multipath effect in CIR data, and high-precision UWB positioning is realized.

The invention belongs to the field of bridge main cable structure health monitoring, and provides a GNSS-based long and large bridge main cable self-driven high-precision sensing method and device, and the method comprises the steps: collecting GNSS original displacement data, and carrying out the timing preprocessing through a median absolute deviation (MAD) algorithm; using a CNN-LSTM hybrid model to filter out non-structural noise such as a multipath effect; a reference response model is constructed by adopting an adversarial space-time Transform network, and abnormal signals are accurately separated; the sampling and communication frequency is adaptively adjusted according to the environment state; online optimization of the model is realized by an abnormal driving incremental learning mechanism; the device comprises a data acquisition and preprocessing module, an edge intelligent calculation module, an energy-saving management module and an incremental learning module. Millimeter-level high-precision sensing, low-power-consumption self-driven operation and long-term evolution capability are realized, and the intelligent level of bridge safety monitoring is remarkably improved.

The invention relates to the technical field of radar target detection, in particular to a low glancing angle multipath effect real-time compensation method, system and device and a medium, and the method comprises the steps: building an augmented state vector which comprises a target motion state parameter and a pitch angle error oscillation characteristic parameter; establishing a state transition model and a nonlinear measurement model of the augmented state vector, wherein the nonlinear measurement model represents the pitch angle observed quantity as the sum of error terms formed by the target real pitch angle and the pitch angle error oscillation characteristic parameters; predicting a state prediction vector and a prediction covariance matrix at the current moment according to the state transition model and the state estimation value at the previous moment; and filtering and updating the state prediction vector and the prediction covariance matrix based on the nonlinear measurement model and the actual observed quantity of the radar at the current moment, and outputting a target state estimated value and a multipath oscillation characteristic parameter estimated value after multipath error compensation. The objective of the invention is to realize low-delay and high-precision pitch angle error compensation.

The invention discloses a Beidou pseudo satellite fusion positioning method and system in a tunnel. The method comprises the steps that a tunnel is divided into multiple sections of visible sub-areas, a relative coordinate system is established, Beidou signals are introduced into the tunnel through Beidou pseudo satellites, a common commercial receiver can still have the Beidou signal positioning capacity in the tunnel, meanwhile, according to the environment in the tunnel, a directional antenna is adopted, the multipath effect is reduced, and the positioning accuracy of the Beidou signals is improved. An infrared distance measuring device is arranged in a specific area, the vehicle driving direction and Doppler errors are judged, single pseudo satellite positioning is achieved through Doppler, and final coordinate output is achieved through the relation between relative coordinates and map coordinates.

The invention relates to the technical field of geodetic surveying instruments and geological disaster monitoring, and discloses a geological environment displacement surveying system based on a GNSS multipath effect, and the system comprises a signal collection unit which is used for receiving a satellite signal and extracting a signal-to-noise ratio sequence; the interference feature separation unit is used for stripping a direct signal power component and generating a residual oscillation sequence; the geometric inversion calculation unit is used for generating a reference interferometric phase template in a height search domain, and generating a height-correlation map to lock the current vertical height by calculating and superposing correlation coefficients between the residual oscillation sequence and the reference interferometric phase template; according to the invention, through a spatial domain geometric matching mechanism, high-precision distance measurement is realized in a complex environment in which a satellite visual segmental arc is broken, dependence of a traditional spectral analysis method on observation duration is broken through, and signal-to-noise ratio data endogenesis is utilized to decouple observation station attitudes and environmental medium attributes. And the stability and the multi-dimensional perception capability are improved.

The invention relates to the technical field of radar signal processing, and discloses an anti-multipath interference vehicle-mounted millimeter wave radar signal processing method, and the method comprises the steps: obtaining a radar echo signal, and decomposing the radar echo signal into a plurality of overlapped sub-band signals in a frequency domain; constructing a static environment Doppler manifold curved surface by using self-vehicle motion data, and calculating a theoretical phase evolution model according to the static environment Doppler manifold curved surface; extracting an actual measurement phase difference between the sub-bands, and carrying out coherent accumulation on the actual measurement phase difference and the theoretical model to generate a manifold consistency coherence coefficient; direction-of-arrival estimation is carried out on each sub-band signal, and the spatial spectrum drift statistical dispersion of an angle estimation value is calculated; and generating a target multipath confidence score according to the manifold consistency coherence coefficient and the spatial spectrum drift statistical dispersion, and executing a suppression decision on a radar detection target. According to the invention, by introducing a kinematics physical constraint and broadband space stability detection mechanism, false targets generated by a multipath effect are effectively identified and eliminated, and the environmental perception precision and robustness of the vehicle-mounted radar are improved.