185 results about "Ambiguity resolution" patented technology

The invention relates to the technical field of natural language processing, in particular to an intelligent customer service system based on natural language processing, which comprises a dynamic term ambiguity resolution module, a context intention chain construction module, a domain emotion vectorization module, a compliance response decision module and an aging knowledge injection module. Wherein the dynamic term ambiguity resolution module is used for receiving an original statement of a user and generating a standard term set; the context intention chain construction module is used for generating a structured intention chain; the domain emotion vectorization module is used for generating a three-dimensional emotion vector; the compliance response decision module is used for generating a to-be-verified response scheme; and the timeliness knowledge injection module is used for verifying the timeliness of legal provisions in the response scheme to be verified. According to the method, through fusion of dynamic term disambiguation, context intention chain modeling, emotion vector quantization and law and regulation aging verification, accurate semantic understanding and compliance response generation of the intelligent customer service system in multiple rounds of dialogues are realized.

A partial ambiguity resolving method suitable for a complex dynamic environment belongs to the field of high-precision dynamic satellite navigation relative positioning, and comprises the following steps: constructing a single-epoch carrier phase double-difference difference observation equation; and calculating a weight factor corresponding to each satellite through a standardized residual error and an IGG3 method, and substituting the weight factors into the double-difference factor matrix to obtain a corrected observation value. And resolving the updated observation equation through a weighted iterative least square method. And carrying out partial ambiguity fixation on the corrected ambiguity floating point solution to obtain a whole cycle ambiguity fixed solution. And carrying out Ratio-based posteriori consistency traversal detection, monitoring the number of satellites participating in calculation in a traversal search process, and if the number of the satellites is smaller than a threshold value, outputting a floating point solution. And if the number of satellites after traversal search is greater than or equal to And substituting the fixed solution of the integer ambiguity into the updated observation equation to obtain a fixed solution of a three-dimensional relative position vector and a covariance matrix of the three-dimensional relative position vector.

The invention provides a multi-language cross-culture communication assisting method and system based on a large model. The method comprises the following steps: receiving a source language audio stream during a call, calling a multi-language sound frequency harmonic modulation feature library to extract fundamental frequency harmonic intensity distribution and tone turning features, and generating a cultural acoustic fingerprint vector; based on the vector, controlling a microphone array phase difference, directionally enhancing a fundamental frequency harmonic component of a speaker and suppressing noise, and outputting a high signal-to-noise ratio spectrogram; analyzing the pronunciation rhythm and tone turning characteristics of the spectrogram, capturing the pitch jump and duration of the syllable boundary, and generating an acoustic culture label; associating the spectrogram with a target semantic library, matching harmonic distribution and a cultural context rule based on a large model, and outputting a cultural interpretation prompt containing an ambiguity resolution suggestion; and generating a calibration result according to the acoustic tag and the semantic prompt, and overlapping the dynamic floating subtitles to the face area of the speaker in the video conference picture. According to the invention, cultural tone ambiguity in multi-language communication is eliminated.

The invention discloses a method for enhancing geographical name and address translation precision by using context awareness and a geographic library, relates to the technical field of intelligent translation, and constructs a dynamic collaborative ambiguity resolution framework by fusing a context awareness mechanism and multi-dimensional attributes of a geographic knowledge base so as to break through semantic limitation of traditional geographical name and address translation. Specifically, firstly, dynamic association information implied in an address text is captured by utilizing context semantic coding of a non-geographical name text fragment, and structured feature embedding is performed on candidate entities in combination with a geographic knowledge base to extract multi-dimensional attributes of the candidate entities, so that cross-modal disambiguation decision is realized in a semantic aggregation stage; through a geographic feature cross validation mechanism guided by context semantics, the problem of translation ambiguity caused by static rule dependence and geographic attribute segmentation in the prior art is effectively solved, so that a more accurate multi-language address translation effect is achieved.

The invention discloses an intelligent auditing method and system based on a multi-modal large model, and relates to the field of artificial intelligence, and the method comprises the following steps: a field adaptive model is constructed by injecting financial and accounting field corpora into an LLaMA-3 architecture, accounting criteria, policies and regulations can be automatically analyzed, executable auditing rules can be generated, the system adopts a multi-channel structure, and the auditing efficiency is improved. According to the method, key entity extraction, logic relation identification and ambiguity resolution are synchronously completed, the accuracy and robustness of rules are ensured, multi-source heterogeneous data are integrated by constructing a finance and accounting knowledge graph, generated SPARQL query is executed to realize automatic auditing testing, block chain anchoring rule hash and a three-dimensional evidence matrix are innovatively introduced, and the auditing efficiency is improved. And the traceable and non-tampering decision traceability of the whole process is realized. According to the method, the auditing efficiency, the coverage and the automation level are remarkably improved, the auditing risk is effectively avoided, and a highly credible solution is provided for intelligent auditing of man-machine cooperation.

The invention relates to a work order material intelligent tracking and dynamic updating system based on multi-source data fusion. The system comprises an acquisition module, a tracking module, an updating module, a man-machine interaction module and a storage module, the acquisition module is used for acquiring work order information from a bill of material, scheduling information and inventory and supplier data, and constructing a material data model; the tracking module monitors material inventory, consumption and material shortage risks based on the model, and realizes automatic state updating and graphical path recording in combination with bar code recognition and ambiguity analysis; the updating module predicts material requirements through a machine learning algorithm, optimizes a distribution plan and outputs a dynamic report; the interaction module supports multi-format data import, unstructured field classification and interrupted operation control; the storage module ensures credible synchronization and tamper-proofing performance of data among different systems through a block chain technology; according to the invention, high-efficiency management and dynamic allocation of work order materials can be realized in an environment without an MES system, and the production transparency and the resource utilization efficiency are improved.

The invention discloses an ambiguity determination method for satellite positioning, a terminal and a medium in the field of satellite navigation and positioning, and the method comprises the steps: obtaining observation data of a base station and a mobile station, eliminating errors through employing a double-difference technology, and carrying out the cycle slip correction, and obtaining the corrected observation data; preliminarily estimating the speed and position of the mobile station; based on the corrected observation data, extracting an optimal ambiguity subset through satellite-level and ambiguity-level screening; constructing a factor graph model by using the optimal ambiguity subset, taking the preliminarily estimated speed and position of the mobile station as initial values, minimizing an error function in a factor graph, and optimizing to obtain a floating solution of ambiguity; obtaining an integer ambiguity solution based on the floating point solution; and verifying the stability of an ambiguity resolving result through consistency, and finally obtaining an ambiguity fixed solution. According to the method provided by the invention, high precision, high efficiency and high stability of ambiguity calculation are realized, and the method is suitable for a high-precision satellite positioning system in a complex environment.

Aspects of the invention provide a method, system, and computer program product for retrieval augmented generation. In one aspect, the method includes receiving a query. The method further includes classifying the query to a first domain within a plurality of domains. The method additionally includes determining an ambiguity associated with classifying the query. The method also includes retrieving an index of domain-specific vector embeddings corresponding to the domains when the ambiguity does not exceed a threshold for ambiguity. The method further includes prompting a large language model with the query and the domain-specific vector embeddings. The method also includes receiving a query response from the large language model as grounded with the most relevant index results. The method further includes forwarding the query response.

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 invention relates to a mine monitoring method based on millimeter-wave radar multi-feature fusion, and the method comprises the steps: transmitting an FMCW signal through a millimeter-wave radar, receiving a target echo, sequentially carrying out the signal preprocessing, 1DFFT distance measurement, 2DFFT speed measurement, velocity ambiguity resolution and DOA estimation angle measurement, and extracting the distance, velocity, angle and energy variation features of a target point cloud; then millimeter-level deformation is obtained through phase analysis; obtaining a vibration frequency through band-pass filtering and spectrum analysis; fusing the six types of features of the target point cloud, adopting a confidence counter weighting decision mechanism, and triggering early warning when a fusion score exceeds a preset threshold value; according to the invention, through the advantages of high reliability, strong anti-interference performance and high non-contact safety of multi-feature fusion decision, the false alarm rate is significantly reduced, and the real-time accurate early warning capability of the mine dangerous state is improved.

The invention discloses a low-altitude aircraft airway meteorological data acquisition and processing method, and relates to the technical field of airway meteorological data acquisition, and the method comprises the following steps: obtaining a carrier phase observation value of a target satellite from a GNSS receiver, recording a corresponding timestamp, and carrying out the original turnover ambiguity resolution of the obtained carrier phase observation value; carrying out first-order differential processing on carrier phase observation values of the same satellite at two continuous time points, and constructing an instantaneous carrier phase variation sequence reflecting the phase change rate; according to the invention, through carrier phase disturbance feature extraction and deep learning multipath risk prediction, dynamic weight adjustment of multipath interference satellites is realized, the system anti-interference capability and the data processing robustness are improved, the space mismatching and meteorological misjudgment risks are significantly reduced, and the positioning precision and the track sensing reliability in a complex environment are guaranteed.

The invention relates to a sparse cloth double-array-element phase comparison and double-frequency phase solution ambiguity radar angle measurement method and device, and belongs to the technical field of radar measurement. The method specifically comprises the following steps of: 1, performing phase comparison measurement on sparse cloth double array elements at a dual-carrier frequency and a lower dual-channel to obtain a phase difference between the array elements so as to obtain a fuzzy coefficient containing a phase error; according to the fuzzy coefficient, determining constraint conditions of dual-frequency and carrier wave values; step 2, under the constraint condition determined in the step 1, selecting a radar signal working frequency, and constructing a virtual short baseline according to the dual-array-element phase difference under different frequencies; and step 3, based on a virtual baseline ambiguity resolution method, calculating to obtain a non-ambiguity high-precision one-dimensional angle measurement angle.

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.

Aspects of the invention provide a method, system, and computer program product for retrieval augmented generation. In one aspect, the method includes receiving a query. The method further includes classifying the query to a first domain within a plurality of domains. The method additionally includes determining an ambiguity associated with classifying the query. The method also includes retrieving an index of domain-specific vector embeddings corresponding to the domains when the ambiguity does not exceed a threshold for ambiguity. The method further includes prompting a large language model with the query and the domain-specific vector embeddings. The method also includes receiving a query response from the large language model as grounded with the most relevant index results. The method further includes forwarding the query response.

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 technical field of navigation positioning, and discloses an INS-assisted positioning system and method under a GNSS / INS positioning system, and a medium, and the system comprises a prediction pseudo-range confirmation module, a floating point solution calculation module, a first optimal fixed solution calculation module, a second optimal fixed solution calculation module, and a fusion solution module. According to the scheme, the floating point ambiguity resolving and fixing process is optimized by correcting inertial information in real time, specifically, inertial prior information is corrected by using a combined positioning high-precision result, a traditional GNSS pseudo-range estimation method is replaced, an improved partial ambiguity fixing strategy is introduced, the fixing efficiency of non-optimal subset ambiguity is improved, and the positioning accuracy of the GNSS pseudo-range estimation method is improved. According to the method, the positioning precision, the stability and the real-time performance can be remarkably improved in a complex urban environment.

The invention relates to the technical field of GNSS high-precision positioning, and provides a BIE-based real-time dynamic positioning integer ambiguity resolving method and system, and the method comprises the steps: obtaining a preliminary ambiguity subset through the screening of a satellite elevation angle and a carrier-to-noise ratio, and carrying out the correlation reduction processing; a multi-level screening mechanism is adopted and comprises three stages of dynamic optimization of coarse screening, fine screening and candidate group generation; a weight distribution model is improved based on Laplacian distribution to calculate candidate solution weights and probability weighted fusion is carried out; in combination with an ILS and BIE mixed fixing strategy, BIE weighted averaging is adopted when ILS fixing fails; a positioning result is optimized through dynamic satellite screening and multi-system data fusion, and a jump detection threshold value is set to realize abnormal recalculation. The method improves the reliability of real-time dynamic positioning, and guarantees the continuous and stable operation of the system in a signal shielding or multi-path interference scene through a jump detection and recalculation mechanism.

The invention discloses a partial ambiguity resolving method and device, a medium and equipment, and relates to the technical field of satellite navigation and positioning. Based on the concept that in the partial ambiguity resolving process, after multiple-dimensional ambiguity corresponding parameters are removed, the more accurate the whole-cycle ambiguity resolving based on the remaining ambiguity related parameters is, the more stable the resolving of partial parameters corresponding to partial-dimensional ambiguity subsets is, the invention proposes that in each round of partial ambiguity resolving process, the more accurate the whole-cycle ambiguity resolving is, and the more accurate the whole-cycle ambiguity resolving is, the more stable the resolving of partial parameters corresponding to partial-dimensional ambiguity subsets is. According to the current ambiguity related parameters and the integer ambiguity, and different parameter parts corresponding to ambiguity subsets of different dimensions in the current ambiguity related parameters and the integer ambiguity, respectively solving baseline fixed solutions for multiple times to obtain multiple groups of baseline fixed solutions; the difference between the maximum value and the minimum value in the multiple groups of baseline fixed solutions is compared with the preset threshold value, the stability of the integer ambiguity solution is judged, and the accuracy and the reliability of the partial ambiguity solution are improved by utilizing the statistical characteristics of the ambiguity integer solution.

The invention discloses an ambiguity adaptive resolving method and system based on ILS and BIE estimation. The method comprises the following steps: acquiring GNSS original observed quantity; constructing a pseudo-range and carrier phase double-difference observation equation, and calculating a floating point solution of an ambiguity parameter by using extended Kalman filtering; performing ambiguity fixation on the ambiguity subset through an ILS algorithm to obtain an ILS fixed solution, performing ambiguity fixed check on the ILS fixed solution, if the check is passed, obtaining a final solution, and if the check is not passed, performing ambiguity fixation through a BIE algorithm to obtain a BIE fixed solution: performing multiple screening on the ambiguity subset based on an observation value domain and a state domain to obtain an optimal ambiguity subset; searching the optimal ambiguity subset by using an improved SEVB algorithm to obtain a BIE multi-ambiguity candidate solution; and calculating a BIE fixed solution, and performing reliability verification on the BIE fixed solution to obtain a final fixed solution. According to the method, the ambiguity fixing success rate can be improved, meanwhile, the precision of a fixed solution is remarkably improved, and the ambiguity resolving efficiency is effectively optimized.

The invention discloses a domestic PC terminal cross-modal natural interaction method and system fused with generative AI, and relates to the technical field of man-machine interaction, and the method comprises the steps: obtaining multi-modal data, and carrying out the preprocessing and feature extraction; constructing a modal adapter, mapping the extracted multi-modal features to a shared semantic space, and generating a multi-modal semantic vector; calculating a dynamic weight coefficient of each mode according to the current scene features; fusing the multi-modal semantic vectors to generate cross-modal fusion features, and carrying out ambiguity resolution processing on the fusion features; inputting the disambiguated fusion features into a lightweight domestic generative AI model, carrying out intention understanding, and generating a multi-modal response; and the generated multi-mode response is adapted to domestic PC terminal hardware and an operating system, and natural interaction is completed. According to the method, intention understanding and response generation are performed by introducing the generative AI domestic large model, so that the accuracy and naturalness of cross-modal interaction of the domestic PC terminal are improved.

The invention discloses a real-time PPP whole-cycle ionosphere elimination combination ambiguity fixing method and device based on PPP-B2b, terminal equipment and a storage medium, and belongs to the technical field of GNSS positioning and navigation, and the method comprises the steps: obtaining original observation data of a plurality of satellites and PPP-B2b correction information; according to the original observation data and the correction information of each row, generating wide lane and narrow lane floating point ambiguity resolution; calculating wide lane and narrow lane FCB of each satellite according to the wide lane and narrow lane floating point ambiguity resolution; and according to the wide-lane floating point ambiguity resolution, the wide-lane FCB, the narrow-lane floating point ambiguity resolution and the narrow-lane FCB, generating the whole-cycle ionosphere elimination combined ambiguity. According to the method, the PPP-B2b service broadcasted in real time is used for resolving, the method does not depend on post precision products, and the real-time performance can be guaranteed. By implementing the invention, the problem that the whole-cycle ionosphere elimination combination ambiguity cannot be solved in real time in the prior art can be solved.

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 disclosure provides a signal processing method and apparatus. The method includes: obtaining Nr1×M1 signals, where the Nr1×M1 signals are echo signals of M1 signals that are sent by a radar to a target in a SIMO mode; obtaining Nt×Nr2×M2 signals, where the Nt×Nr2×M2 signals are echo signals of M2 signals that are sent by the radar to the target in a MIMO mode; performing first signal processing on the Nr1×M1 signals to obtain first processing data, where the first signal processing includes sequentially performing range FFT analysis, linear prediction, and Doppler FFT analysis; performing second signal processing on the Nt×Nr2×M2 signals to obtain second processing data, where the second signal processing includes range FFT analysis and Doppler FFT analysis; and performing velocity matching ambiguity resolution processing based on the first processing data and the second processing data.

The invention discloses a frame synchronization method and device based on soft information filtering and dephasing ambiguity. Frame synchronization is performed by using demodulated soft information, and new strategies such as soft information filtering, phase ambiguity resolution, Doppler frequency estimation and compensation, dynamic frame header adjustment, multi-frame joint detection and adaptive judgment threshold are combined, so that the accuracy and robustness of frame synchronization are remarkably improved; the method is suitable for processing the frame synchronization problem of a long frame header in a low signal-to-noise ratio environment, and effectively solves the problem of phase ambiguity under the condition that the Doppler frequency change rate is large.

An embodiment provides convergent tracking for Global Navigation Satellite System (GNSS) signals (e.g., binary offset carrier (BOC), etc.) in GNSS applications, such as positioning, navigation, timing, and guidance. The embodiment employs a situation-aware two-dimensional (2D) routing algorithm that provides fast convergence to stable tracking. Further, an embodiment may provide subcarrier phase ambiguity resolution that resolves carrier phase with assurance to support high integrity navigation, including high integrity real-time kinematic (RTK) applications. Moreover, an embodiment may provide tracking to more accurate subcarrier phase estimates. This may provide up to four times better ranging accuracy. Accordingly, an embodiment provides robust tracking performance of BOC signals under varying levels of dynamics, high jamming tolerance, more ranging accuracy, support for high integrity navigation, and support for high integrity RTK based positioning and high precision navigation and automatic landing.

The invention discloses a GPU two-stage parallel implementation method for multi-target distance and speed ambiguity resolution, and relates to the technical field of radar ambiguity resolution, and the method comprises the steps: obtaining multiple repetition frequencies, randomly selecting the multiple repetition frequencies each time, and generating multiple repetition frequency groups; each repetition frequency corresponds to a plurality of plots, one plot is selected from the plots corresponding to each repetition frequency in the repetition frequency group each time to form a plot combination, a plurality of plot combinations corresponding to the repetition frequency group are generated, and identifiers of the plots in each plot combination are obtained; allocating a group of thread blocks to each trace point combination, and allocating a plurality of threads to each trace point; for the plurality of trace point combinations, performing coarse-grained parallel processing to obtain a minimum variance corresponding to each trace point combination; and for any trace point combination, performing fine-grained parallel processing to obtain a minimum variance corresponding to the trace point combination. According to the invention, the real-time performance of the defuzzification algorithm can be enhanced.

The invention discloses a circular array interferometer ambiguity resolution method based on adaptive angle clustering, and the method comprises the steps: firstly constructing a two-dimensional uniform circular array interferometer model, and calculating the position of each antenna array element; secondly, two units are randomly selected from the uniform circular array to form base lines, the fuzzy phase difference and the maximum fuzzy number of each base line are calculated, two base lines are randomly selected to form double-base-line combinations, each double-base-line combination is traversed, the azimuth angle and the pitch angle are calculated, and an angle matrix is formed; then, a neighborhood radius parameter of a DBSCAN clustering algorithm is set according to the input frequency, clustering analysis is carried out on the angle matrix, and a cluster with the maximum density is selected; and finally, calculating the average value of the data in the maximum density cluster to obtain the azimuth angle and the pitch angle of the target. According to the method, the correct ambiguity resolution probability and the direction finding precision of the two-dimensional circular array interferometer can be effectively improved.

The present invention relates to a method and device for measuring the attitude of an array antenna, comprising obtaining a solution baseline vector through satellite observation of array elements on the array antenna to be measured, inputting the solution baseline vector into a three-dimensional attitude solution algorithm to obtain the previous three-dimensional attitude angle, obtaining the attitude matrix of the array antenna to be measured based on the previous three-dimensional attitude angle, eliminating the phase center error using the attitude matrix and phase direction diagram, using the three-dimensional attitude solution algorithm to obtain the current three-dimensional attitude angle of the array antenna to be measured, determining whether the current three-dimensional attitude angle has converged based on the current three-dimensional attitude angle and the previous three-dimensional attitude angle, and using the current three-dimensional attitude angle as the attitude angle solution result. The present invention eliminates the influence of the phase center error, improves the accuracy of the attitude solution result, improves the success rate of ambiguity solution and the reliability of the attitude measurement result, and improves the accuracy of the roll angle solution. The present invention also relates to a device and a storage medium.