1241 results about "Satellite navigation" patented technology

The invention discloses a Beidou strong deception jamming detection processing method and system, and relates to the technical field of satellite navigation anti-jamming. The invention provides a solution based on dynamic gain monitoring and multi-dimensional feature collaborative analysis to solve the problems that a Beidou / GNSS system is prone to being affected by strong deception interference signals in a complex electromagnetic environment to suppress radio frequency link gain, and positioning failure is caused by the fact that deception signals and real signals are difficult to distinguish in a traditional technology. According to the method, radio frequency gain change is tracked in real time through a digital AGC module to generate an interference-to-signal ratio, an equivalent carrier-to-noise ratio is calculated in combination with a signal carrier-to-noise ratio for primary judgment, and accurate recognition is achieved by fusing verification of multi-dimensional characteristics such as code phase consistency, carrier frequency stability and signal strength fluctuation. The system comprises a radio frequency front end, a digital AGC module, a correlator channel and an interference processing module, and precise suppression of strong deception interference is realized through dynamic reference gain learning, interference signal mark elimination and robust positioning resolving mechanisms.

The invention relates to the technical field of high-precision satellite navigation and positioning, and discloses a multi-modal sensor space-time synchronization method for high-precision data acquisition, which comprises the following steps: constructing a hardware delay observation loop to calculate physical response delay in real time; establishing a receiver clock drift model and extracting a clock drift coefficient; generating a phase lead trigger instruction in response to the delay mean value and the clock drift coefficient cumulant based on the GNSS whole-second target moment; according to the method, a feed-forward control closed loop is constructed by using GNSS clock difference parameters, the intrinsic alignment of the heterogeneous sensor physical sampling action and GNSS atomic time is realized, the real-time alignment of the sensor physical sampling action and the GNSS atomic time is realized, and the real-time alignment of the sensor physical sampling action and the GNSS atomic time is realized. And a strict physical time reference is provided for high-dynamic multi-source data fusion.

The invention relates to the technical field of time synchronization, and discloses a hybrid time service method based on Beidou satellite navigation and a TSN, which comprises the following steps: acquiring network topology structure information and historical time service error data of each synchronization node in a target distributed system, and constructing a dynamic time delay state set for jitter identification; based on the dynamic time delay state set, a current global time reference is extracted through a time calibration algorithm, a time difference reference vector sequence is generated, and initial synchronization adjustment is carried out on the TSN main node; constructing an inter-node clock convergence function curve according to the slave node response stability, and judging whether the synchronous network is in a low jitter interval or not based on the time offset rate and the time drift trend change; in combination with the node time state after directional offset suppression, a multi-channel redundant time synchronization mechanism in a time window is applied, a weight adjustment coefficient is extracted, and an unbalanced calibration factor is introduced; and according to a regression correction result, evaluating a time service stability index in real time. The method has the advantage of improving the time service stability.

The invention provides an unmanned aerial vehicle inspection accurate positioning method and device integrating vision and satellite navigation, and relates to the technical field of aerospace information. According to the method, satellite signal quality features reflecting aerospace information reliability and multi-dimensional features such as visual geometric textures reflecting ground environment features are jointly extracted, and the environment state is deeply perceived; based on real-time dynamic generation of a fusion strategy adaptive to the current environment, a data weight and an algorithm model are intelligently adjusted, and the limitation of a traditional fixed parameter fusion mode is broken through; a specific inspection stage and a target object where the unmanned aerial vehicle is located are understood through visual identification, and a corresponding priori task constraint model is loaded, so that the positioning process closely meets the precision and safety requirements of actual operation. And finally, fusion calculation is carried out under the common guidance of a dynamic strategy and task constraints, so that the problem of inaccurate positioning of the unmanned aerial vehicle in a complex environment is solved, and the environmental adaptability, robustness and task guidance accuracy of a positioning system are improved.

The invention discloses a multi-source navigation data fusion method for an unmanned loader, which comprises the following steps: data acquisition: acquiring environmental perception data of satellite navigation, an inertial measurement unit IMU, a wheel type odometer and a laser radar and camera in real time; performing space-time synchronization preprocessing, realizing multi-source data time synchronization, unifying environment sensing data to a body coordinate system, eliminating abnormal data, and complementing missing data; carrying out dynamic weight calculation, establishing an error model of each sensor, and adjusting a fusion weight by using an error reciprocal exponential weighting method; layering fusion is carried out, a satellite and an IMU are fused through bottom-layer extended Kalman filtering (EKF), a laser radar and a high-precision map are fused through middle-layer ICP, a middle-layer result and a wheel type odometer are integrated through high-layer federated filtering, and high-precision fusion is achieved; and outputting and optimizing a result, outputting navigation data, performing closed-loop optimization, monitoring the health degree of the sensor, and executing redundancy switching when a fault occurs. The system comprises a corresponding processing unit, and a storage medium stores a program for executing the method.

The invention discloses a high-precision positioning method based on combination of a Beidou satellite and 5G-Mesh, and relates to the technical field of satellite positioning, and the method comprises the steps: receiving a navigation signal of the Beidou satellite and a communication signal of a 5G-Mesh network in real time; the topological structure change of the 5G-Mesh network is monitored in real time, and the connection relation between the nodes is dynamically adjusted in combination with network performance indexes; the receiver performs pseudo-range measurement on the signals of the visible satellites; a navigation message is demodulated from the received satellite signal, and the accurate position of each satellite at the current moment is calculated by using a satellite orbit calculation model; constructing a signal intensity fingerprint database; outputting a reference position having the highest similarity with the current signal strength characteristic to carry out error modeling on the Beidou satellite signal and the 5G-Mesh network signal; and fusing the two kinds of position information by adopting a weighted fusion algorithm. By fusing the technical advantages of the two positioning technologies, the positioning precision and reliability are improved, and the requirement for high-precision positioning in a complex scene is met.

The invention discloses a high-precision Beidou satellite navigation and positioning data acquisition method and system, particularly relates to the technical field of satellite navigation and positioning processing, and is used for solving the problem of positioning error increase caused by receiver hardware delay drift in the prior art. Inverting the first dynamic reference value by using carrier phase integral displacement, and extracting a third-order intermodulation component through coherent demodulation to generate a second dynamic reference value; adopting mutual information entropy analysis to select an effective reference value to calculate a residual error; fitting a theoretical value according to the carrier phase change rate to calculate deviation; marking a hardware drift error when the time domain correlation continuously exceeds a threshold value; finally, the ionosphere residual error is dynamically compensated to generate a corrected observation value, effective separation of the hardware drift error and the ionosphere residual error is realized, and the precision and reliability of long-time observation in a dynamic environment are improved.

The invention relates to the cross technical field of satellite navigation and wireless positioning technology, in particular to a real-time dynamic high-precision positioning method based on Beidou and UWB tight coupling, which solves the problem that in the prior art, error coupling in Beidou and UWB observation data is not fully solved, and especially in a high-speed dynamic scene, the positioning accuracy is greatly improved. The mutual influence of the Beidou receiver clock error, the UWB base station clock error and the multi-path error causes the continuous accumulation of the error and the significant reduction of the positioning precision. The invention discloses a real-time dynamic high-precision positioning method based on Beidou and UWB tight coupling. A data preprocessing and space-time alignment module, an error joint estimation model, an ambiguity fast fixing algorithm, a geometric constraint enhanced positioning engine module and a dynamic coordinate conversion and fusion output module are included. According to the mode provided by the invention, a highly integrated multi-model Kalman filtering architecture is adopted, so that synchronous and accurate compensation of the clock error of the Beidou receiver, the time delay of the UWB base station and the multi-path effect is realized.

The invention relates to the technical field of satellite navigation and precision positioning, in particular to a Beidou large-area sea area millimeter-level high-precision positioning method. The method comprises the specific implementation steps that marine environment state data and Beidou observation data are collected and preprocessed, and environment influence parameters are extracted; establishing a quantitative model based on the environment state data, the satellite signal propagation data and the antenna phase center data, and obtaining propagation path delay data and antenna phase center change data; processing the observation data and the self-adaptive reference network information based on a Beidou cooperative satellite positioning algorithm to obtain a preliminary positioning result; constructing a satellite signal error model to analyze environmental influence parameters and data, obtaining a positioning error value, and adjusting a preliminary positioning result; and calculating and judging the positioning result, dividing the positioning result into a first type of working condition and a second type of working condition, switching the second type of working condition to an emergency mode, and performing enhanced compensation on the Beidou signal error. According to the invention, the positioning precision, reliability and adaptive capability of the Beidou system in a marine environment are improved.

The invention provides a train attitude precision keeping method and system based on inertial quaternion modeling, and belongs to the technical field of train operation positioning. Through a quaternion modeling train attitude feedback compensation model, auxiliary calibration of a gyroscope is realized by using an accelerometer, and calculation of an inertial attitude is realized; converting the acquired wheel speed sensor information into three-dimensional speed under a navigation coordinate system through attitude information resolved by a quaternion modeling train attitude feedback compensation model, and further integrating to obtain a position; and fusing the speed and position information of the wheel speed sensor after attitude conversion with the speed and position information obtained by inertial navigation dead reckoning to realize error correction of the inertial navigation system. According to the method, the problem that the train state sensing precision is degraded due to the fact that a satellite navigation / inertial navigation system positioning model is difficult to overcome inertial device error accumulation when a satellite fails is solved, the train attitude precision is kept, and then error divergence of a combined positioning system during satellite signal denial is effectively restrained.

The invention provides a high-precision satellite navigation positioning method based on Android, and relates to the technical field of positioning navigation and dead reckoning, the compatibility and adaptability of a system are improved by constructing an abstraction intermediate communication interface between an application layer and an Android kernel layer; asynchronous processing is carried out through monitoring callback, so that deep dependence on a kernel is reduced; batch acquisition is realized by adopting an annular buffer area, and the acquisition frequency and the task priority are adjusted in real time according to the motion state of terminal equipment in combination with a dynamic sampling frequency and scheduling mechanism; the method comprises the following steps: constructing a multi-source data fusion model, fusing multi-source data, and synchronously aligning with timestamps to generate accurate position information; the CPU occupancy rate and the energy consumption in the fusion process are monitored in real time, and the sampling frequency and the scheduling mechanism are dynamically optimized in combination with terminal feedback and a preset threshold value, so that the positioning precision and the equipment load are balanced, and high efficiency and high reliability of the system are realized.

The invention discloses a foundation pit support deformation real-time monitoring method based on edge calculation, and aims to solve the problems of multi-node time synchronization and clock drift compensation caused by unavailability or poor quality of satellite navigation and precise time protocols in an underground or shielded environment. According to the method, through event dictionary learning, partition time slot scheduling and safety coding micro excitation time synchronization, matched filtering decoding, multi-scale arrival time estimation, paired time difference robust fusion, frequency priority and phase speed limit correction and network disconnection time holding, the time synchronization efficiency is improved; the technical effects that multi-source data alignment, deformation field reconstruction and graded early warning are completed on the unified virtual reference time scale, and high-precision synchronization and online drift compensation are obtained without depending on the external time service condition are achieved.

The invention relates to the technical field of satellite navigation signal processing, and discloses a signal noise suppression method in a Beidou navigation system, which comprises the following steps of: performing three-dimensional modeling on navigation signals, and extracting time-frequency characteristics to generate a signal model; constructing an interference heat prediction map, and dynamically updating and identifying a high-interference area; analyzing a signal phase change, calculating a phase rate, and identifying abrupt change interference; adopting adaptive filtering and L1 norm sparsification to remove multi-source interference; correcting deviation in signal modeling by using a redundant navigation module; and adjusting a signal processing strategy based on a real-time control and scheduling mechanism. According to the method, a signal modeling guide mechanism based on an interference heat prediction map is introduced, and the dynamic change of electromagnetic environment interference is combined with a signal modeling process, so that an interference sensitive area is recognized in advance, and structural sparse constraint is applied; and a blind area lacking sensing of interference at the initial modeling stage in the traditional technology is eliminated.

The invention belongs to the crossing field of space geodetics, satellite navigation positioning technology and atmospheric science, and discloses a real-time troposphere delay modeling method for enhancing a global forecasting system. The method comprises the following specific steps: firstly, acquiring zenith fluid static delay and zenith wet delay predicted by earth surface GFS, and constructing a regional grid difference time sequence by taking a fusion result of ERA5 data and a GNSS troposphere delay product as a reference; secondly, fitting the difference to form a GFS enhanced core model; meanwhile, a troposphere delay correction model from the grid height to the target site height is constructed based on ERA5 stratified atmosphere data, time sequence modeling is carried out on model coefficients, and finally refined troposphere delay output at different heights is achieved. The method has the advantages that (1) the real-time troposphere model is high in precision; (2) real-time application can keep robust performance without depending on a GNSS network; (3) expansion and deployment are facilitated; and (4) the real-time performance is strong, and seamless integration precision positioning application can be realized.

The invention discloses a satellite navigation positioning method and device based on scene recognition, electronic equipment and a storage medium, and belongs to the technical field of satellite navigation positioning, and the method comprises the steps: determining the geometric space characteristics of each satellite according to the observation time, the satellite number of each satellite and preset satellite ephemeris information; according to the observation time, the satellite pseudo-range of each satellite and the satellite distance change rate of each satellite, determining the signal quality characteristics of each satellite; determining a satellite observation feature set based on the geometric space features of the satellites and the signal quality features of the satellites; inputting the satellite observation feature set and the satellite signal-to-noise ratio of each satellite into a preset scene recognition model to generate a scene category; and determining the positioning coordinate of the satellite navigation receiver according to the scene category in combination with the satellite signal-to-noise ratio of each satellite and the satellite pseudo-range of each satellite. According to the invention, the problem that satellite navigation positioning is not accurate enough in the prior art can be solved.

The invention belongs to the technical field of crossing of satellite navigation and edge computing, and relates to a differential data broadcasting method based on edge computing, which comprises the following steps: accessing multi-source data through a dynamic data acquisition processing module, reducing noise, scheduling computing power through an edge node cooperative computing module, and fusing data to generate a differential factor; the spatio-temporal characteristic difference generation module generates adaptive difference data in combination with spatio-temporal and environmental parameters, then the intelligent broadcast resource management and control module selects channels and performs layered coding broadcast, the system health degree management module guarantees stability, the cross-domain collaborative application interface module adapts to multiple scenes, and after the system is started, all the modules operate in sequence, data are collected and processed firstly, and then the data are transmitted to the intelligent broadcast resource management and control module. And then generating factors through cooperative calculation, generating adaptive differential data, intelligently broadcasting the adaptive differential data, monitoring and maintaining the adaptive differential data by a health degree module, and finally docking each application scene through an interface module to realize high-precision positioning service.

The invention discloses an image analysis method and system for quality control traceability of a satellite navigation board, and relates to the technical field of image processing. The method comprises the following steps: synchronously acquiring an image and three-dimensional point cloud data of a radio frequency transmission line area through a high-resolution area array CCD camera and a laser contourgraph; acquiring a transmission line contour based on image identification, and constructing a three-dimensional radio frequency line model through point cloud fitting; detecting the line width and the distance to the ground plane by using the model, and calculating the impedance prediction complexity in combination with a data acquisition error; dynamically calling a characteristic impedance prediction engine based on the complexity to obtain a predicted characteristic impedance sequence; and quality defect judgment is carried out, and traceability control is carried out on defective products. According to the method, a complete technical chain from geometric dimension detection to electrical performance evaluation is established, hidden defects which are difficult to find by a traditional method can be effectively identified, and the quality control precision and the product yield of the satellite navigation board are improved.

The invention provides an inertia / satellite / vision adaptive integrated navigation method and system. The method comprises the following steps: carrying out inertia measurement and navigation calculation to obtain inertia data; calculating satellite navigation observed quantity according to the satellite navigation data and the inertial data, and constructing a satellite observation model; calculating visual navigation observed quantity according to the visual navigation data and the inertial data, and constructing a visual observation model; aiming at a satellite and a visual observation model, respectively adopting an innovation-based adaptive covariance estimation method to obtain satellite and visual observation noise covariance updated values; constructing a satellite and visual navigation health degree, and calculating a satellite and visual fusion weight according to the satellite and visual navigation health degree; controlling updating of satellite and visual navigation observed quantity according to the satellite and visual fusion weight; and calculating a weighted equivalent observation matrix and a noise covariance, and carrying out filtering estimation. According to the method, an adaptive noise estimation and sensor health degree evaluation mechanism is introduced, dynamic weighted fusion of multi-sensor data is realized, and the robustness and precision of a navigation system in complex environments such as satellite signal lock losing and visual feature missing are improved.

The invention discloses an ionospheric scintillation monitoring method based on a geodetic measurement receiver, which belongs to the technical field of satellite navigation, and comprises the following steps of: accurately eliminating non-scintillation errors by constructing an inter-station single-difference function model and an inter-station single-difference random model, extracting carrier phase residual errors by using a single epoch ambiguity fixing technology, and finally obtaining an ionospheric scintillation monitoring result. Establishing a reliable ionospheric scintillation monitoring index; according to the ionospheric scintillation monitoring method based on the geodetic measurement type receiver, high-precision real-time monitoring of ionospheric scintillation can be realized through a single-epoch ambiguity fixing technology under the condition of not depending on an external precision product, and reliable technical support is provided for space weather monitoring.

The invention provides a portable mobile base station data service and management method and system, and relates to the technical field of satellite navigation and high-precision positioning, and the method comprises the steps: analyzing broadcast ephemeris and clock error parameters according to an interface control file protocol; an RTCM SSR data stream is obtained; decoding the RTCM SSR data stream to obtain an SSR correction number; based on the GNSS observation value, the satellite navigation message and the SSR correction number, calculating to obtain an accurate coordinate of the base station; the convergence state of the accurate coordinates of the reference station is evaluated in real time, and parameter configuration is carried out; the GNSS observation value is packaged into an RTCM MSM4 telegraph text, and the RTCM MSM4 telegraph text and an RTCM 1005 telegraph text packaged by the accurate coordinates of the reference station are combined and coded to generate a real-time RTCM differential data stream; and according to the NTRIP protocol, the RTCM differential data stream is broadcasted to each terminal through a TCP / IP interface. According to the invention, high-precision reference station positioning and multi-terminal service are realized.

The invention relates to the technical field of satellite navigation and intelligent positioning, and discloses an indoor positioning method and system based on Beidou double-frequency signals, and the method comprises the steps: receiving Beidou B1I and B1C double-frequency signals through adaptive signal enhancement and preprocessing; the double-frequency differential carrier phase extraction technology is adopted to form ionosphere-independent combined observed quantity, and ionosphere delay errors are eliminated. Multipath interference is identified and suppressed through a multipath suppression method based on statistical characteristics, and an extended Kalman filtering algorithm is adopted to fuse Beidou double-frequency observed quantity and IMU inertial data to realize multi-sensor information fusion positioning; according to the method, a soft constraint condition is established by utilizing geometric features of a building to optimize a positioning result, a multi-dimensional precision evaluation model is established to predict the positioning precision, and the result is adaptively output, so that sub-meter positioning precision and millisecond response time can be realized in a complex indoor environment, and an effective solution is provided for an indoor positioning technology.

The invention discloses a traffic drainage signal management method and system based on a Beidou system, and relates to the technical field of Beidou satellite navigation, and the method comprises the steps: obtaining the real-time traffic data of the position and speed of a vehicle at each intersection based on the Beidou system, and transmitting the real-time traffic data to a traffic management platform; carrying out feature matching on the accident identification model trained based on historical emergency data and a deep learning algorithm and real-time traffic data, and identifying an emergency; and constructing a real-time traffic situation map in combination with the identified emergency information and the traffic condition information of the intersections. The vehicle position and speed data are obtained in real time through the Beidou system, emergencies are rapidly recognized and signal lamp timing is dynamically adjusted in combination with a deep learning algorithm, and compared with a traditional fixed timing scheme, traffic flow changes can be responded in real time, frequent start and stop of vehicles are reduced, the road passing efficiency is improved, and the traffic safety is improved. And particularly, in a sudden traffic accident or construction scene, a signal strategy can be quickly optimized, and traffic congestion aggravation is avoided.

The invention belongs to the technical field of communication interference cancellation, and discloses an electromagnetic interference real-time monitoring and cancellation method based on a multi-antenna technology, which can realize comprehensive perception of an electromagnetic environment from a spatial dimension by utilizing the multi-antenna technology and through cooperative work of a main antenna and an auxiliary antenna. And an accurate basis is provided for timely coping with electromagnetic interference. Besides, an interference identification model is further constructed and is suitable for monitoring various different types of electromagnetic interferences, interference cancellation parameters and strategies are dynamically adjusted according to the interference types, high adaptability and flexibility are achieved, a cancellation algorithm is matched for the interference types, signals with the same amplitude and opposite phases as interference signals are generated, and the interference cancellation accuracy is improved. Therefore, the interference is quickly and effectively counteracted, and the normal operation of a satellite navigation communication system is ensured. In addition, according to the method disclosed by the invention, the anti-interference capability of the satellite navigation communication system in a complex electromagnetic environment can be remarkably enhanced, and the anti-interference tolerance is greatly improved.

The invention discloses a GNSS anti-interference closed-loop phase self-correction method based on deep learning, and relates to the technical field of satellite navigation and artificial intelligence, and the method comprises the steps: obtaining an anti-interference array output signal and weight information through an array antenna and space-time adaptive processing; extracting a carrier-to-noise ratio, a weight phase feature and historical positioning quality, and constructing a deep learning feature vector; reasoning an array element-level phase correction reference quantity by using a multi-layer perceptron model, and realizing accurate phase compensation of an array output signal by combining phase error layered modeling, quick-change disturbance prediction and weight sensitivity estimation; an anti-interference perception observation covariance dynamic scaling mechanism is introduced into RTK positioning calculation; on-line learning and model updating are triggered through a positioning quality evaluation result, so that the system has an adaptive evolution capability. According to the method, the GNSS carrier phase quality and the positioning precision under the strong interference condition can be remarkably improved, deep fusion of anti-interference processing and high-precision positioning is realized, and the method has important engineering application value.

The invention discloses a comprehensive quality evaluation method and system for Beidou deformation monitoring observation data in a complex environment, and relates to the technical field of satellite navigation positioning, and the method comprises the steps: carrying out the comprehensive evaluation of an elevating angle, a signal-to-noise ratio, an epoch difference and an environment model of the observation data of a Beidou single station, and determining the initial quality of the data; based on the double-difference observation values among the multiple stations, the data quality evaluation precision is further improved by combining a double-difference ambiguity resolving method; according to the method, ionosphere delay, three-difference errors and inter-epoch difference errors are used for data fusion, a more accurate quality evaluation result is obtained, and finally, the data are optimized through comprehensive analysis based on the quality evaluation results of various types of data so as to ensure accurate positioning and deformation monitoring. The technology aims at improving the accuracy and reliability of data quality evaluation by comprehensively analyzing influence factors of Beidou observation data in a complex environment, and provides support for geological disaster monitoring, smart city construction and other high-precision application scenes.

The invention discloses a positioning and attitude determination method and device integrating Beidou navigation and inertial navigation, and relates to the technical field of attitude measurement, the method comprises the following steps: correcting a gyroscope error by using an accelerometer error and a magnetometer error based on proportional integral operation to obtain a gyroscope output after error correction; using the gyroscope output after error correction to update the quaternion of the moving object, using the quaternion to calculate the attitude, and obtaining the attitude angle of the moving object under the carrier coordinate system calculated through inertial navigation; moving object positioning and attitude determination calculation is carried out by using the time difference of the satellite carrier phase double differences between the double BDS receivers and the different groups of satellites, and the attitude angle of the moving object under a carrier coordinate system calculated through Beidou satellite navigation is obtained; and performing Kalman filtering fusion on the attitude angle calculated by inertial navigation and the attitude angle calculated by Beidou satellite navigation to obtain a final attitude angle. The method can adapt to a dynamic environment, and the attitude measurement precision is improved.

The embodiment of the invention discloses a deviation angle-considered integrated navigation system attitude estimation method, and relates to the technical field of inertial navigation / satellite navigation integrated navigation, the method is applied to a carrier, and the method comprises the following steps: obtaining observation data through a GNSS receiver to obtain first attitude measurement data; obtaining second attitude measurement data according to the measurement data of the inertial navigation unit in combination with the motion state; constructing an integrated navigation system state equation considering the deviation angle, constructing an integrated navigation system measurement equation based on the first attitude measurement data and the second attitude measurement data, and obtaining an attitude estimation model; initial parameters are obtained based on the observation data and the measurement data, the attitude estimation model is recurred through Kalman filtering, and the attitude angle of the carrier is output. According to the method, by means of the assistance of the speed information provided by the GNSS, the influence of the radial acceleration and the centripetal acceleration to the ground is considered, the method for determining the accelerometer attitude and estimating the deviation angle in real time in the dynamic environment is realized, and the system error of attitude determination is reduced.

The application discloses a fusion positioning algorithm based on low-orbit satellite Doppler measurement, DME and VOR, relates to the technical field of satellite navigation, and comprises the following steps: acquiring the Doppler frequency shift of a low-orbit satellite, the slant range information of a DME and the azimuth angle data of a VOR, constructing a combined observation equation, and obtaining a corresponding Jacobian matrix; based on a geometric dilution of precision, selecting stations and stars through a genetic algorithm, optimizing the selection of the DME, the VOR and the low-orbit satellite, and obtaining an optimal navigation source combination; constructing a motion model under different flight modes, and dynamically estimating the state of an aircraft by using an interactive multiple model Kalman filter, and updating the position information in real time. Therefore, the real-time positioning of the aircraft under complex conditions is realized, the anti-interference capability of the system is improved, and the overall positioning precision and stability of the system are improved.

The invention relates to the technical field of satellite navigation and ionosphere detection, in particular to a low-latitude ionosphere disturbance and non-uniform body multi-means collaborative detection and classification method. A multi-network cooperation-multi-source fusion observation mode is adopted, full space-time coverage of low-latitude ionosphere disturbance is achieved, in addition, a data fusion method based on physical constraints is applied, an ionosphere-middle atmosphere-troposphere multi-physics field coupling constraint mechanism is constructed, space-time consistency of data obtained through different observation means is optimized, and the low-latitude ionosphere disturbance is obtained. And finally, key characteristic parameters are extracted by using a multi-scale signal processing method, a disturbance characteristic matrix is constructed in combination with radar observation data (such as drift speed and spectral width), a'three-axis nine-element 'disturbance / non-uniform body classification standard is proposed firstly, then deep learning classification is used, accurate classification of low-latitude ionosphere disturbance is realized, and GNSS signal anomaly recognition capability is improved.

The invention provides a multi-source information fusion positioning method for air refueling, which relates to the technical field of information fusion, collects original visual data, global navigation satellite system (GNSS) data and inertial navigation system (INS) data, overcomes the limitation of a single sensor, and improves the positioning accuracy. A differential satellite navigation algorithm based on a mobile base station is used for accurately calculating the relative position and speed between an oiling machine and an oil receiving machine, and the problems that the updating frequency is low and the system is prone to being interfered by the atmosphere are solved. When information fusion is carried out, the difference of output frequencies of different sensors is considered, data of an IMU, a GNSS and a visual sensor are fused at the closest time point, the effectiveness and timeliness of information are guaranteed, and meanwhile, through the mode of automatically adjusting the size of a measured noise variance matrix, the accuracy of information fusion is improved. All observation information is effectively utilized, appropriate weight adjustment measures are taken for suspicious or abnormal data, and the positioning precision is improved.