93 results about "Ambiguity resolution" patented technology

The invention relates to the technical field of natural language processing, in particular to an NLP-based multi-source data fusion system and method.The NLP-based multi-source data fusion system comprises a data collecting and processing unit, an NLP processing unit, a data fusion unit and an output unit.The data collecting and processing unit collects multi-source heterogeneous data and executes standardization processing to obtain preprocessed data; the NLP processing unit extracts entity, relation and emotion features through deep semantic analysis, a context-aware entity relation graph is constructed by adopting a bidirectional attention mechanism model and a graph attention network, and the data fusion unit realizes cross-source entity ambiguity resolution through an iterative graph neural network based on a graph topological structure. The emotion confidence weight is dynamically distributed to generate a fusion vector, a rule feedback reconstruction map is extracted, and the output unit converts the fusion vector into a target format for output, so that the problem of semantic conflict of multi-source data is solved, and semantic coherence and availability of fusion data are improved.

The invention belongs to the technical field of natural language processing and geographic information systems, and particularly relates to a region address standardization method based on knowledge graph enhanced retrieval. Cleaning and preprocessing the original address text input by the user; utilizing a fine-tuned large language model to identify a geographic entity and performing standardized expansion on variant expression to generate a query candidate set; entity linking and context retrieval are carried out based on the knowledge graph, and attributes, hierarchy and spatial topology information of associated entities are obtained; in combination with the original input and the map context, an enhanced retrieval query text is generated through large language model reconstruction; vectorized semantic retrieval is carried out through the fine-tuned embedding model, and a preliminary candidate address set is obtained; carrying out multi-dimensional refined sorting by adopting a resorting model; and generating a structured standard address by using a large language model, and outputting the structured standard address after multi-level verification. According to the method, the problems of ambiguity resolution, alias recognition and context understanding in address processing are solved, and the accuracy and robustness of address standardization are improved.

The invention discloses an intelligent voice question-answering system and a knowledge reasoning method for operation and maintenance of power equipment. The system comprises a knowledge base construction module and a core question and answer engine module, the knowledge base construction module is used for constructing a power equipment knowledge graph and a fault case library, and the core question and answer engine module comprises a natural language understanding unit, a multistage semantic retrieval unit and a voice interaction ambiguity resolution unit. A natural language understanding unit identifies intent categories and power entities. The multi-stage semantic retrieval unit executes the following steps: matching in an ontology layer of the knowledge graph; performing extended query to obtain detailed information; and similar case matching is carried out in the fault case library. The voice interaction ambiguity resolution unit is used for executing disambiguation processing; analyzing the confidence and clarifying the dialogue; and triggering knowledge retrieval and reasoning and generating a sorting answer. The operation and maintenance efficiency is improved, the dependence on experts is reduced, the operation and maintenance quality and safety are improved, knowledge precipitation and sharing are promoted, the field work experience is improved, and scientific decision making is assisted.

The application discloses an improved radar two-dimensional ambiguity resolution method for multi-targets, comprising the following steps: arranging point trail data after radar signal processing according to pulse repetition period from small to large; constructing a reference lookup table for resolving range ambiguity based on the arranged data; constructing a reference lookup table for resolving velocity ambiguity based on the arranged data; traversing all the frequency combinations of radar transmission, selecting N groups from M groups of frequency for multi-target pairing; obtaining a range pairing table based on the reference lookup table for resolving range ambiguity, calculating the standard deviation between rows of the range pairing table, and solving the real range of targets; obtaining a velocity pairing table based on the reference lookup table for resolving velocity ambiguity, calculating the standard deviation between rows of the velocity pairing table, and solving the real velocity of targets; and merging and processing output target data. The application can solve the problem that the traditional one-dimensional set method cannot meet the real-time requirement when the number of targets is large and the ambiguity is large.

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 relates to the field of robot technology and artificial intelligence, and discloses a robot fine operation method and system based on a visual language model and semantic key point characterization, a closed-loop multi-body Agent system is constructed, GPT-4o and Ground DINO are combined to accurately understand and disambiguate a natural language instruction of a user, an innovative bridging layer is introduced, and the robot fine operation method and system based on visual language model and semantic key point characterization are obtained. Abstract decision information is converted into bottom execution parameters represented by three-dimensional semantic key points, the problem of decision transfer distortion is solved, meanwhile, a KMP algorithm is improved, and the stiffness and contact force of trajectory tracking are dynamically optimized by introducing a learning-based time-varying hybrid impedance / force control strategy, so that the accuracy of trajectory tracking is improved. According to the method, the generalization success rate of fine operation tasks of the robot and the stability of physical interaction are remarkably improved, seamless connection from high-level semantic understanding to low-level action generation is achieved, and an efficient and reliable technical scheme is provided for autonomous operation of the robot in a complex scene.

This invention discloses a product classification and recognition method and system based on AI technology, belonging to the field of AI recognition technology. By constructing a semantic alignment master vector Edis, the system achieves structured extraction and ambiguity resolution of the overall semantic representation of the product. On this basis, the system introduces the construction of a product classification label semantic vector set Gvec and a semantic similarity score set Sset, enabling the system to perform fine-grained matching of multiple classification labels based on contextual semantic features. This constructs a confidence score Conf reflecting the classification credibility, which is then compared with a preset classification judgment threshold Thrs to ensure that product labels are output only when the classification judgment credibility is sufficient. Through the connection of the above processes and the linkage of output results, this method not only significantly reduces the probability of misjudgment caused by expression ambiguity and word order reversal, but also provides a reliable rejection mechanism when accurate classification is not possible, effectively improving the overall robustness and practical value of the classification system.

The invention provides a PPPRTK / LiDAR / INS fusion positioning method based on hierarchical optimization. The PPPRTK / LiDAR / INS fusion positioning method comprises the following steps: firstly, constructing a front-end tight coupling module of LiDAR and INS, extracting point cloud geometric constraints, and combining the point cloud geometric constraints with IMU pre-integration to form LIO odometer factors; then obtaining multi-system multi-frequency GNSS original observation, unifying time, coordinates and antenna reference, and carrying out multi-stage correction on the observation; a PPP-RTK / INS tight coupling observation model is established under an SRIF framework, linearization and residual construction are carried out on a non-difference and non-combination equation, a joint state is constructed, and a floating point-fixed two-stage ambiguity resolving and quality control method is adopted; and finally, performing joint optimization on the front-end LIO factor and the PPP-RTK / INS factor by utilizing a factor graph, eliminating abnormal observation in combination with a robust kernel and a residual error threshold, and outputting a continuous and accurate vehicle pose. The method can effectively improve the continuity, convergence speed and precision of positioning in complex scenes such as urban canyons and elevated interchange, and is suitable for the fields of navigation, automatic driving, free flow charging and the like.

This invention relates to an inter-satellite laser multi-standard signal fusion time-frequency synchronization method and system. It integrates frequency synchronization, time synchronization, and communication functions by using a single laser source to carry a frequency signal, a single-frequency signal, a low-pass filtered signal, and a pseudo-random code signal with communication data via spectrum shifting. The three signal spectra are separated and do not interfere with each other. The frequency signal is used for inter-satellite frequency synchronization; the single-frequency signal is used for high-precision time delay measurement to achieve inter-satellite time synchronization; and the pseudo-random code signal serves both communication and time delay measurement ambiguity resolution. This invention employs a bidirectional time delay measurement and joint calculation method, combined with frequency signal link jitter compensation, to achieve parallel and collaborative operation of the three functions. Compared with existing technologies, this invention improves system integration, reduces the number of modules and external interfaces, and effectively reduces the weight, power consumption, and volume of onboard equipment. It is suitable for high-precision time-frequency synchronization applications such as satellite navigation, deep space exploration, and integrated space-ground networks.

The invention provides a lightweight anaphora ambiguity resolution multi-task learning method, and relates to the technical field of intelligent language processing of a power system, and the method comprises the steps: S1, collecting power production command related documents to construct a lightweight power semantic knowledge base; s2, on the basis of the lightweight electric power semantic knowledge base, constructing an ultra-lightweight semantic analysis model through double-layer knowledge distillation; s3, performing lightweight deployment on the ultra-lightweight semantic analysis model based on an INT8 quantification technology to obtain a quantification model capable of running on edge equipment; s4, inputting the electric power semantic analysis task into a quantitative model obtained by lightweight deployment by adopting an end-side collaborative reasoning strategy, performing complexity evaluation and intelligent shunting processing, and outputting a semantic analysis result with high confidence; according to the method, high-precision semantic understanding under the condition of extremely low computing resources can be realized, and a practical and reliable intelligent language analysis capability is provided for a power production command system.

The invention relates to the field of radar distance ambiguity resolution processing, in particular to a radar distance ambiguity resolution implementation method based on a GPU. According to the technical scheme, the method comprises the steps of obtaining echo data sets under multiple groups of different PRFs, extracting a target distance ambiguity solution set corresponding to each group of PRFs from the echo data sets, performing extension calculation on target ambiguity distances under each PRF, generating all possible physical distance sets, forming a two-dimensional data structure, and obtaining a target distance ambiguity solution set; the two-dimensional data structure is stored in a shared table of a GPU global memory, sliding window statistics of a plurality of distance units are calculated in parallel through threads in the GPU, then sliding window clustering judgment is carried out, and if the windows are judged to be consistent, all distance values in the sliding windows are averaged to serve as a target real distance estimated value. The method is suitable for radar distance ambiguity resolution processing.

A multiple-pulses-in-air (MPiA) laser scanning system configured for measuring the time-of-flight of laser pulses, wherein the computing unit is configured for triggering the transmitter to transmit the send pulses with a varying pulse frequency, wherein the transmitter is configured to have a dead mode, wherein in the dead mode an increase in pulse frequency is effected, wherein in the course of increasing the pulse frequency, a reduction in pulse energy per individual send pulse of the send pulses is provided such that the pulse energy of the resulting return pulses is reduced such that it is below a detection threshold, and a measurement mode, wherein in the measurement mode a reduction in pulse frequency compared to the dead mode is effected.

The present application relates to the technical field of database construction, and particularly relates to a construction method of a foraminifera morphological feature database, comprising the following steps: S1, collecting foraminifera images from multiple sources, identifying scale drift and shooting deviation based on principal axis normalization and local vorticity field, performing structure-preserving image enhancement, and outputting an enhanced image set consistent in shell substance, shell arrangement, shell opening, suture line and micro-pore features; S2, extracting a multi-scale shell structure atlas, constructing a structure-semantic coupled label nested tree, performing polysemy recognition and ambiguity resolution, and generating a structured annotation set; S3, fusing the image set and the annotation set, and constructing a three-layer database model containing a part layer, an attribute layer and a variation layer according to the label nested tree. Through image structure enhancement, semantic ambiguity resolution and three-layer database construction, the present application effectively improves the recognition accuracy of foraminifera morphological features, the label organization logicality and the information retrieval efficiency.

The application discloses an online medical intelligent doctor guiding system based on text graph embedding and belongs to the technical field of medical doctor guiding. Through fine-grained medical entity recognition and ambiguity resolution on online medical consultation texts, fine-grained entities can be accurately recognized, and the problem of fine semantic granularity can be solved. Through matching of a medical dictionary and context, the ambiguity generated by the entity can be effectively eliminated. Through a dynamic updating mechanism, the latest medical knowledge can be ensured to be incorporated into the graph, and the knowledge can be prevented from being outdated. From text preprocessing to graph construction, a complete link is formed, which can provide a high-quality knowledge base for subsequent graph embedding and doctor guiding reasoning. The entity vector obtained through processing contains graph structure, deep semantics and clinical logic, and can effectively solve the defects of single mode of traditional embedding. Through a constraint loss function, the vector can be ensured to conform to the path rules of authoritative clinical guidelines, clinical logic consistency can be realized, and vectors that violate medical common sense can be avoided.

The application discloses a dual-polarization weather radar speed ambiguity resolution method based on lag-1 cross-correlation, which utilizes lag-1 cross-correlation of adjacent radial directions instead of radial velocity of the adjacent radial directions in a traditional algorithm to calculate an ambiguity resolution reference speed. This makes the ambiguity resolution speed range of the ATAR mode expand to twice that of the traditional algorithm, so that the speed measurement range is consistent with that of the single-polarization mode. Application of the algorithm improves the reliability of speed data of the ATAT mode weather radar in severe weather detection.

The application discloses a satellite-ground communication time offset and Doppler frequency offset pre-compensation device, which has high estimation accuracy and can complete wide-range time offset and frequency offset estimation and pre-compensation without acquiring satellite ephemeris information of a terminal. The application is realized by the following technical scheme: a DoA estimation unit estimates the arrival angle DoA of a satellite signal by using an array signal processing algorithm; the estimation unit estimates the arrival angle DoA of a satellite signal; the acquired satellite azimuth angle and elevation angle information is divided into two paths, one path is sent to a distance calculation unit, a time offset calculation unit and a time offset pre-compensation unit, the propagation time delay between the satellite and the terminal is calculated and time offset pre-compensation is performed; the other path is output to a velocity vector calculation unit, a Doppler frequency offset calculation unit, a Doppler ambiguity resolution unit and a frequency offset pre-compensation unit, the Doppler frequency offset caused by satellite movement is calculated and frequency offset pre-compensation is performed, the residual time offset and frequency offset are estimated, and the residual time offset and frequency offset are accurately adjusted.

The invention discloses a Beidou-based high-precision differential positioning adjustment system and method, and relates to the technical field of satellite navigation and high-precision localization. Time-frequency analysis is carried out on a multi-frequency carrier phase observation sequence, signal-to-noise ratio monitoring is combined, and a flicker identifier and a noise weight are constructed; the system can identify frequency points and observation sections which are seriously polluted by flicker at an epoch level, and the weight of the system is actively reduced at a combination stage; secondly, under the constraint of maintaining ambiguity integer characteristics, the coefficient combination takes equivalent noise variance and residual ionosphere high-order term error sensitivity as optimization targets, and considers the observation noise level and the suppression capability for high-order ionosphere residual errors, so that on one hand, the reliability of carrier phase integer ambiguity calculation is maintained, and on the other hand, the reliability of carrier phase integer ambiguity calculation is improved; and on the other hand, the sensitivity degree of combined observation to high-order ionosphere residual errors is reduced, so that high-precision differential positioning of a low-latitude region has higher robustness.

The invention provides a deformation monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of positioning. The method comprises the following steps: acquiring reference coordinates, initial observed quantity data and ephemeris data at the current moment; the reference coordinate is used for indicating the accurate position of the monitoring station in a historical time period; the initial observed quantity data comprises the observed quantity of the monitoring station at the current moment and the observed quantity of the reference station at the current moment; performing double-difference ambiguity calculation based on the reference coordinates, the initial observed quantity data and the ephemeris data to obtain a plurality of double-difference ambiguity values; determining one or more error ambiguity values from the plurality of double-difference ambiguity values; eliminating the observed quantity corresponding to the error ambiguity value in the initial observed quantity data to obtain final observed quantity data; according to the final observed quantity data, the ephemeris data and the reference coordinates, the deformation quantity is calculated, the deformation quantity is used for indicating the deformation of the accurate position of the monitoring station at the current moment relative to the reference coordinates, and therefore the deformation monitoring accuracy is improved.

The invention provides an ambiguity resolving method for hybrid differential evolution and improved particle swarm optimization. And determining various parameters of the algorithm according to the ambiguity resolving space range determined by the floating point solution. And the global search capability of the particles is enhanced according to the set inertia weight, so that local optimum is avoided. In order to solve the problem of population homogenization in the later stage of the particle swarm optimization algorithm, a variation-crossover-selection mechanism of differential evolution is integrated, and particle positions are optimized. And adjusting particle positions according to a particle swarm optimization algorithm position updating formula to obtain a new candidate ambiguity solution. And through boundary processing and calculation of weighted least square cost of each particle position, individual optimum and global optimum are updated. And when the number of iterations reaches a set threshold value, outputting global optimum. Compared with a traditional particle swarm optimization algorithm, the method has the advantages that local optimum is avoided, the convergence speed is increased, and the method is more suitable for fast and reliable ambiguity fixing requirements in GNSS high-precision positioning.

The application provides a time difference positioning ambiguity method based on multi-station direction finding positioning, a medium and a device, the method comprising: a central positioning station collecting original data sets of each auxiliary positioning station, and performing data grouping on the original data; according to the signal conditions of each positioning station, selecting a positioning station with a longer baseline for cross positioning; calculating the time difference based on the position of the cross positioning; estimating the time difference error according to the deployment conditions and direction finding accuracy of each positioning station; generating a time difference threshold based on the calculated time difference and the time difference error; after data grouping, the time difference positioning branch performs pulse-by-pulse time difference pairing; filtering the time difference pairing results according to the time difference threshold; and performing point track calculation and track association based on the filtered time difference pairing results. Through the application, the baseline of the time difference positioning can be further extended under the prerequisite of meeting the target common view requirement, which is conducive to improving the time difference positioning accuracy.

The application discloses a speech data processing method and system based on a large language model, relates to the technical field of speech data processing, and comprises the following steps: performing multi-channel feature decomposition on a received original speech signal, and constructing an acoustic state representation tensor; constructing a semantic candidate distribution space, generating multiple sets of semantic hypothesis vectors, and constructing a semantic evolution path graph; generating a semantic uncertainty function representing semantic ambiguity and speech disturbance sensitivity; dynamically constructing a reasoning depth control parameter and inputting the same to a multi-layer reasoning path scheduling unit of the large language model, constructing an intention structure vector, and mapping the intention structure vector into a structured semantic output. The technical problems that in the prior art, under a complex acoustic environment, it is difficult to accurately and effectively separate acoustic features, leading to low speech understanding accuracy of high ambiguity, and lacking dynamic reasoning ability to cope with semantic uncertainty risks are solved, and the technical effects of improving semantic understanding precision, ambiguity resolution ability of speech interaction, and reducing business misjudgment rate and risk are achieved.

The invention discloses a distributed coherent aperture radar angle ambiguity resolution method based on maximum likelihood estimation in the technical field of radar signal processing. Aiming at the problem of angle ambiguity of the distributed coherent aperture radar caused by transmitting beam grating lobes, the method comprises the following steps: firstly, transmitting a group of carrier frequency linear stepping pulse sequences; then carrying out beam forming on received echoes, and carrying out coherent accumulation on beam output of a plurality of pulses by utilizing the characteristic that main lobe response does not deviate along with the frequency and grating lobe response deviates along with the frequency, so as to suppress grating lobes and enhance the main lobe on the aspect of energy; and finally, modeling is carried out on the accumulated signals, and unambiguous angle estimation is realized by solving a conditional maximum likelihood estimator of a target direction. The method can effectively solve the problem of angle measurement ambiguity caused by transmitting grating lobes under the condition that the beam coverage range is not lost, and particularly has the advantages of high precision and high robustness in a low signal-to-noise ratio environment.

One or more embodiments of the present disclosure provide a Beidou satellite-based positioning method, device, electronic equipment and storage medium. The method comprises: acquiring carrier phase measurement data, pseudo-range measurement data and Doppler observation values of multiple frequency bands of multiple satellites through a mobile receiver and a fixed base station; obtaining double-difference pseudo-range observations and an initial rough coordinate of the mobile receiver according to the pseudo-range measurement data and an inter-station double-difference model; calculating single-frequency ambiguity of a B1 frequency point of the satellite using a three-frequency carrier ambiguity resolution algorithm according to the carrier phase measurement data, and verifying the fixed state of the single-frequency ambiguity of each satellite; constructing a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudo-range measurement data and the Doppler observation values; and obtaining a target positioning coordinate of the mobile receiver using a sliding window estimator, with the sum of all residual squares in a preset sliding window being the minimum as an objective function.

The invention discloses a multi-channel frequency hopping communication method based on a broadside array of an underwater unmanned vehicle, and aims to solve the problem that the communication performance of the broadside array is reduced due to correlation and intensity inconsistency of array element noise of the broadside array caused by over-strong platform self-noise of the underwater unmanned vehicle. According to signal energy of array elements in a broadside array, starboard and starboard ambiguity resolution is carried out to determine a signal incidence side, direction of arrival estimation is carried out on the array elements of the signal incidence side, delay inequality of adjacent array element signals is obtained, then the array element signals are compensated, multiple array elements after delay inequality compensation are sequentially weighted and merged, multiple merging results are obtained, and the multiple merging results are obtained. The number of array elements which are finally required to be combined is selected to form an array element subset; the output signal-to-noise ratio of the array element subset and the weighting coefficient of each array element are solved to obtain a unique weighting coefficient, all array element signals in the array element subset are combined, the signal arrival time in the combined signals is calculated, Doppler estimation compensation is carried out, the compensated combined signals are solved through an iteration receiver, and original bit information is obtained.

An apparatus comprising an interface and a processor. The interface may be configured to present a probe signal and receive raw radar data generated in response to a reflection of the probe signal. The processor may be configured to generate a plurality of profile configurations, interleave the plurality of profile configurations into the probe signal, and reconstruct a radar output based on the plurality of profile configurations in response to the raw radar data. Interleaving the profile configurations into the probe signal may enable the raw radar data to be received comprising information about an environment corresponding to each of the profile configurations at one time frame. Interleaving the profile configurations may enable the processor to extract the information about the environment corresponding to each of the profile configurations independent from each other. The radar output may comprise the information about the environment.

This invention discloses a high-precision RTK positioning method based on an improved adaptive genetic algorithm-based satellite selection strategy, belonging to the field of satellite navigation and positioning technology. A subset of satellites with a specified number of satellites is selected to minimize the loss of the Position Accuracy Factor (PDOP) and satellite geometric volume. The satellite selection problem is transformed into a combinatorial optimization problem. A fitness function is designed with the reciprocal of PDOP and geometric volume as its core, and adaptive crossover and mutation probabilities are introduced. The genetic operation parameters are dynamically adjusted according to the population evolutionary state to balance global search and local convergence capabilities. Iterative evolution is performed under the condition of satisfying subset size constraints. When the convergence condition is met, the subset of satellites with locally optimal PDOP values ​​is output for subsequent RTK ambiguity resolution and positioning. This invention can quickly converge to a near-globally optimal satellite geometry configuration in polynomial time while also considering satellite quality, significantly reducing computational complexity and improving the real-time performance and reliability of RTK positioning.

The application discloses a BDS-2 / 3 precise point positioning tight combination ambiguity resolution method, which comprises the following steps: S1: fixing station coordinates, using international GNSS service (IGS) analysis center satellite orbit and clock error products, performing (MW) combination calculation and ionosphere-free (IF) floating point PPP resolution, and outputting station channel floating point wide lane ambiguity and pseudo-range OMC residual error; and S2: selecting a reference station and a BDS-3 reference star, and using the result of step S1 to calculate wide lane phase correction deviation and ionosphere-free combination signal distortion deviation correction number. The BDS-2 / 3 precise point positioning tight combination ambiguity resolution method has better model strength. Compared with a PPP-AR loose combination mode, the application adopts a tight combination mode, has better model strength, can fully play the advantages of BDS-2 and BDS-3 fusion processing, can eliminate the phase deviation between wide lane systems and the pseudo-range system deviation and the signal distortion deviation between channels of BDS-2 and BDS-3, and significantly improves the precise positioning performance of the Beidou system.

This invention discloses a high-frequency RTK positioning method and system for RTK terminals. The method includes the following steps: setting up two threads, high-frequency and low-frequency; estimating carrier phase ambiguity using the low-frequency thread based on the time-varying characteristics of the parameters to be estimated; correcting the observation model using the high-frequency thread based on the low-frequency thread's solution results to obtain the terminal's position parameters; detecting data update events of the low-frequency thread's solution results and issuing corresponding control signals to schedule the high-frequency and low-frequency threads. This invention, through a high / low-frequency dual-thread solution approach, with the high-frequency thread responsible for position parameter calculation and the low-frequency thread responsible for ambiguity calculation, achieves high-frequency RTK positioning result updates. By separating the estimation methods for time-varying and time-invariant parameters, it reduces the computation time of single-epoch RTK, lowers the frequency of full parameter estimation, improves solution efficiency, and reduces hardware load.

The application provides a RTK and INS combined positioning ambiguity solution method, comprising: obtaining a baseline vector float solution and its variance-covariance matrix, a float ambiguity and its variance-covariance matrix, and a mutual covariance matrix between the float ambiguity and the baseline vector float solution of a RTK and INS combined positioning system; determining integer ambiguity and its weight by using the float ambiguity and its variance-covariance matrix, and determining a predetermined number of integer ambiguity candidate solutions according to the weight; solving the residual error of the receiver position coordinate and the receiver position coordinate predicted by the INS by using the screened ambiguity candidate value, and updating the weight of the integer ambiguity candidate solution by using the residual error; weighting and fusing the predetermined number of integer candidate solutions obtained by using the updated ambiguity candidate value weight to obtain an ambiguity estimation value and a baseline vector estimation value; and determining a final solution according to the ambiguity estimation value and the baseline vector estimation value.

A geolocation system for efficiently reconstructing and geolocating signals collected in multiple spatially-distributed sensors using a plurality of different Nyquist-folding samplers operating at sub-Nyquist rates. The sensors use Nyquist-folding with a plurality of sampling rates and patterns to reduce the volume of data transmitted off the sensor while retaining the ability to detect weak signals, and produce high-quality signal reconstructions and geolocations. The ambiguities in signal reconstruction introduced by sub-Nyquist sampling are addressed by using spatial consistency computed from sub-Nyquist geo-observables to assist in RF ambiguity resolution.