55 results about "Satellite telemetry" patented technology

The invention discloses an in-orbit satellite intelligent fault diagnosis system based on deep learning, and relates to the technical field of in-orbit satellite intelligent fault diagnosis, and the system comprises the steps: carrying out the data regularization processing of multi-source heterogeneous telemetry data generated in the in-orbit operation process of a satellite; capturing a weak abnormal mode at the early stage of the fault; identifying a fault mode in the operation process of the on-orbit satellite; and fault emergency levels are divided according to the fault emergency degrees. According to the method, efficient regularization of on-orbit satellite telemetry data, automatic mining of on-satellite lightweight depth features, online incremental learning recognition of unknown fault modes and intelligent hierarchical scheduling of diagnosis tasks are realized; the accuracy, timeliness, autonomy and generalization ability of on-orbit satellite fault diagnosis are improved, and the technical bottlenecks that a traditional method depends on manual rules, is difficult to deal with novel composite faults, lacks deep data mining ability, is difficult to deploy on a satellite and the like are effectively solved.

A crop species identification system based on satellite telemetry data is disclosed, which includes: a receiver module, receiving plural telemetric vegetation indexes of a target area; a data cleaning module, cleaning anomalous data in the telemetric vegetation indices, to correspondingly generate cleaned index data; a feature extraction module, including at least two different convolution kernels for mapping the cleaned index data into at least two feature scale mapping data which respectively correspond to the convolution kernels, performing a pooling operation of the feature scale mapping data to generate a pooled data, and concatenating the at least two feature scale mapping data and the pooled data into concatenated data; and a classification module, including a fully-connected layer, for extracting features of the concatenated data, to generate a species classification result for the target area.

The invention provides a multi-task multi-satellite telemetry data efficient processing method and system and electronic equipment, and relates to the technical field of satellite ground telemetry data processing. Comprising the following steps: dynamically allocating a task plug-in to an optimal computing node based on a resource state evaluation result of each computing node in a server cluster; uploading task registration information to a configuration center, and storing telemetering parameter configuration information contained in the information in a memory database in a key-value pair form; according to the distributed task plug-in, task telemetering data is led from a specified information source, and step-by-step subdivision is carried out on the data based on a data shunt model; and extracting a telemetering source packet based on the obtained telemetering data flow of each frequency band, and distributing a telemetering source packet analysis task through a thread pool. And on the basis of the telemetering parameter configuration information, utilizing the parameter resolving virtual thread to resolve all parameters in the source packet in parallel. The defect that high-code-rate telemetry data cannot be efficiently processed in real time in a multi-task and multi-satellite scene is overcome.

The invention belongs to the technical field of ground measurement and control of spacecrafts, and particularly relates to a satellite telemetering monitoring and warning method and system based on an event-driven state machine. Comprising the following steps: modeling a life cycle of a satellite plan arc section as an event-driven finite state machine; acquiring a satellite needing to be monitored, plan time of a plan and corresponding latest telemetry data, and generating a current event; the generated current event is routed to a state processor corresponding to the current state of the satellite needing to be monitored, and the state processor executes corresponding alarm operation based on preset service logic responding to different events in combination with the current state of the satellite and completes state transition of the next state of the satellite. According to the method, an event-driven finite-state machine model is constructed, the life cycle of a satellite plan arc section is abstracted into four states and three types of events, service logic is executed through a state processor mode, and the whole monitoring alarm logic is reconstructed through the states, the events and actions.

The application belongs to the technical field of time series data prediction, and particularly relates to a time series data prediction optimization method and system introducing dynamic error. The method comprises the following steps: preprocessing time series data to be processed; inputting the preprocessed data into a prediction model established and trained in advance to obtain preliminary prediction data; comparing the preliminary prediction data with the preprocessed data to obtain a preliminary error; based on the preliminary error, combining historical data of different time lengths, and according to a time decay function, obtaining long-term error and recent error, and through weighted combination, obtaining a corrected prediction value to realize real-time correction of dynamic error. The application firstly applies the dynamic error correction method to time series prediction of satellite telemetry data, realizes real-time correction of prediction error, and significantly improves prediction accuracy.

This application provides a method, apparatus, and electronic device for detecting outliers in satellite telemetry data. The outlier detection model for telemetry data is trained using a kernel extreme learning machine, which can effectively detect outliers in satellite telemetry data, greatly improving the efficiency and accuracy of outlier detection.

This invention discloses a method and system for anomaly detection in satellite on-orbit telemetry data. The method involves acquiring the on-orbit telemetry time-series data of the satellite to be tested; decomposing the data into multiple approximate and detail sequences using the time-frequency characteristics of multi-scale wavelet transform; assigning weights to each approximate and detail sequence, calculating attention weights for each sequence by calculating similarity scores; weighted summing of the hidden states of neurons in the coding layer and their corresponding attention weights within each approximate and detail sequence to calculate a content vector, which is then combined with the current hidden state of neurons in the decoding layer, and so on, to obtain a reconstructed sequence of the on-orbit telemetry time-series data; and outputting anomaly data by comparing the difference between the reconstructed sequence and the on-orbit telemetry time-series data of the satellite to be tested. This method effectively processes the spatiotemporal information of satellite telemetry data, improving the accuracy and robustness of anomaly detection.

The invention discloses a measurement and control system for a deep space satellite formation. The measurement and control system comprises a spread spectrum forwarding subsystem arranged on a primary satellite in the satellite formation and a spread spectrum measurement and control subsystem arranged on a secondary satellite in the satellite formation. Wherein the spread spectrum forwarding subsystem adopts the same communication system as the S-frequency-band ground station to communicate with child satellites in the satellite formation, and the frequency point of the spread spectrum forwarding subsystem is connected with the spread spectrum measurement and control subsystem. The spread spectrum forwarding subsystem is used for broadcasting and sending remote control information of the X-frequency-band ground station to all the sub-satellites, receiving remote measurement information of the sub-satellites and carrying out distance measurement and speed measurement on the sub-satellites by the main satellite; and the spread spectrum measurement and control subsystem receives remote control information of the primary satellite and the S-band ground station on the secondary satellite, sends remote measurement information to the primary satellite and the S-band ground station, and carries out distance measurement and speed measurement on the primary satellite or the S-band ground station by the secondary satellite. By constructing the inter-satellite telemetering and remote control forwarding link, the sub-satellites reuse the frequency resources of the main satellite, and the spectrum utilization rate can be improved.

The invention discloses a satellite-ground time difference monitoring method, system, product and equipment based on a ground station and a narrow-band communication terminal and a storage medium, belongs to the technical field of remote sensing satellite measurement and control, and solves the problems of data loss, orbit measurement and calculation misalignment and imaging position offset caused by the fact that satellite-ground time difference cannot be obtained in time in the prior art. And the ground station is limited in receiving range and poor in timeliness. The method comprises the following steps: 1, acquiring satellite telemetry by using a ground station or a ground narrowband communication terminal; 2, carrying out system conversion on satellite telemetering and ground time respectively; and step 3, obtaining the satellite-ground time difference based on the satellite telemetry after the system conversion and the ground time after the system conversion. The satellite-ground time difference monitoring method is used for realizing real-time and accurate satellite-ground time difference monitoring.

This invention relates to the field of satellite telemetry, tracking, and command (TT&C) technology, and provides a satellite orbit prediction method, system, equipment, and medium for a multi-coordinate system. The method includes the following steps: S1: Receiving prediction request parameters input by the user, the prediction request parameters including satellite identifier and prediction type; S2: Obtaining the satellite orbit status based on the satellite identifier; S3: Identifying the prediction algorithm to be used based on the prediction type; S4: Performing prediction based on the satellite orbit status and the prediction algorithm; S5: Outputting the prediction result. This solution can unify the multi-coordinate system prediction interface, improve prediction efficiency, simplify the operation process, ensure data consistency, optimize coordinate transformation, and enhance system scalability.

A massive telemetering data characteristic value processing method based on time fragmentation and double compression comprises the following steps: receiving satellite telemetering original stream data in real time, performing formatting analysis, extracting a baseband timestamp, a telemetering code and an engineering value field, and generating a standardized telemetering engineering value frame; fragmenting the telemetering engineering value frame based on a timestamp, determining a triple composed of the timestamp, a date to which the timestamp belongs and a telemetering code as a storage sub-partition key, and dynamically allocating data to a corresponding storage partition according to the key for storage in a disk; carrying out historical archiving on the stored telemetering engineering value frames by adopting double-compression processing; constructing a shared bulletin board task model, and registering all to-be-calculated feature tasks to a shared bulletin board queue by taking a combination of a telemetering code, a processing time slice and a processing identifier as a bulletin board key value; and the thread pool obtains task entries in the shared bulletin board queue in parallel based on a shared lock queue mechanism, and reads satellite telemetering point information from the shared memory.

Embodiments of the present application disclose a satellite telemetry data feature selection method and device based on a multi-objective optimization algorithm and a medium; the method can include: splicing the original telemetry data of the satellite, and screening out constant values in numerical data and time alignment, and based on the Rayleigh criterion, the 53H algorithm and the median filtering algorithm, removing outliers and noise in the original telemetry data to obtain preprocessed telemetry data; improving the traditional fast non-dominated sorting genetic algorithm NSGA-II according to the non-uniform arithmetic crossover operator and the mutation operator based on the fitness level; determining the objective function for feature selection according to the feature quantity, the root mean square error and the correlation function; based on the objective function, selecting feature data for data completion, satellite state prediction and fault diagnosis from the preprocessed telemetry data by using the improved NSGA-II algorithm.

This invention relates to the field of satellite telemetry and remote control technology, and discloses a port task processing method for a satellite telemetry, tracking, and command (TT&C) system, comprising: Step 1, probing all available network interfaces using a port scanner and establishing a multi-path communication channel including public network, private network, and satellite link; Step 2, collecting packet loss rate, latency, bandwidth, and jitter parameters of each path in the multi-path communication channel in real time, and updating the parameters based on a preset period; Step 3, generating a comprehensive score for each path based on the packet loss rate, latency, bandwidth, and jitter parameters. This invention employs a dynamic scoring and switching technology scheme for multi-path communication channels, achieving the technical effect of automatically selecting the optimal path based on real-time network performance. Compared to existing technologies that rely on fixed paths or manually configured switching thresholds, this solves the problems of high transmission latency, high packet loss rate, and inability to adaptively adjust due to network fluctuations.

This invention relates to the field of satellite telemetry, tracking, and command (TT&C) technology, and provides a method, system, device, and medium for satellite IoT TT&C mission planning. The method includes: S1: obtaining the set of observable arc segments for each ground station; S2: dividing the mission planning time period into m time segments; S3: first solving the mission planning result for the first time segment; S4: removing observable arc segments in the current time segment that intersect with the previous time segment, completing the mission planning for the current time segment; S5: taking the current time segment as the previous time segment and the next time segment as the current time segment, repeating step S4 until the mission planning for the second to the mth time segments is completed; S6: combining the mission plans of the m time segments to form the satellite IoT TT&C mission plan. This scheme can plan all actions within the planning time period at once, designing a reasonable planning scheme and reducing the complexity of the mission planning algorithm.

The application relates to the technical field of satellite telemetry data transmission, and provides a fast backhaul method and a fast backhaul system for overseas remote sensing satellite data, the fast backhaul method comprising the following steps: S1, acquiring overseas remote sensing satellite telemetry data; S2, carrying out fragmentation processing on the overseas remote sensing satellite telemetry data to form fragmented files and metadata; the metadata records the fragmentation condition; S3, successively uploading the fragmented files and the metadata to the cloud; and S4, receiving the fragmented files and the metadata from the cloud in the country, and combining multiple fragmented files into a complete file according to the metadata. The scheme can adapt to the characteristics of large-volume data, combine the advantages of cloud services, and is a new transmission method for breaking through the cross-border link restriction, improving data utilization, and reducing comprehensive cost.

This invention provides an automated testing and interpretation system and method for the downlink radio frequency performance of regenerative processing payloads on communication satellites, including a hardware platform and a control unit. The hardware platform is used to construct a satellite-to-ground radio frequency link and supports remote control. The control unit carries main control software to control the hardware platform to perform the following functions: loading and executing predefined test sequences to initiate the test process; sending remote control commands to set the satellite payload status via power supply control equipment or requesting command permissions from the satellite platform; receiving and parsing satellite telemetry to confirm whether the status meets the requirements; remotely controlling general-purpose test instruments to perform automatic testing, acquiring test data, and automatically interpreting and recording it based on predefined templates; and automatically storing remote control commands, telemetry data, and test data in a time sequence to a database. Thus, this invention achieves one-click automated testing and interpretation of the downlink radio frequency performance of satellite processing payloads, improving efficiency, reducing cost and error rate, and possessing versatility and scalability.

The invention provides a method for supporting batch satellite data analysis in a batch production satellite manufacturing process, and the method comprises the steps: automatically generating a satellite test matrix table according to a satellite test station, a satellite SN serial number and test feature data; collecting batch-produced satellite telemetry data of the listed test item lines based on the satellite test matrix table; analyzing the satellite telemetry data, and judging whether the data is normal or abnormal; calculating the maximum value, the minimum value, the average value and the range value according to the important telemetering parameters with the data in the normal value range in the test matrix time range of each satellite; and performing data analysis on the calculation result to obtain an evaluation result of the current batch of satellites. The analysis method mainly has an integration and analysis process for the data of the batch-produced satellites, the analysis of the data of the satellites is further carried out in the stages of average value, maximum value and minimum value, further comparison of telemetering parameters is realized through software, and the data deviation condition of the current batch-produced satellites is obtained through data analysis.

The invention provides a dynamic closed-loop test system and method for satellite task planning. The method comprises the steps of satellite telemetering dynamic feedback simulation, result pre-evaluation before satellite remote control uploading and satellite remote control execution closed verification. A simulation module establishes and operates dynamic feedback simulation test software, a comprehensive management and expansion unit is connected through analog quantity, temperature quantity, a serial communication interface and a bus communication interface, and satellite telemetering dynamic feedback simulation needs to set a telemetering data format. And dynamically updating and feeding back the telemetry data. According to the method, a complete test system is formed, satellite task planning can be tested more accurately and comprehensively through links such as telemetering dynamic feedback, evaluation before remote control uploading and satellite remote control execution closed verification, a powerful guarantee is provided for smooth development of satellite tasks, and the test efficiency is improved. Therefore, multi-type satellite task planning and whole-satellite closed-loop test requirements are met.

The invention discloses a satellite telemetering anomaly detection method and system based on a multi-scale time domain convolutional network, belongs to the technical field of time sequence anomaly detection, and solves the problems that an existing space-time fusion method is insufficient in single-scale time feature capture capability and simple in multi-scale feature fusion mode. The method comprises the steps of collecting satellite telemetry data, constructing a data sequence and a sample matrix, and performing preprocessing and feature extraction to obtain a spatial feature vector; constructing a multi-layer MSTCN network, and performing time evolution feature extraction and feature fusion on the spatial feature vector to obtain a fused feature vector; activating the fusion feature vector to obtain feature output of the telemetry data; calculating residual statistical magnitude of the actual data and the predicted data, calculating a mean value and a standard deviation of the residual statistical magnitude, and setting an abnormal threshold value and a range thereof; and calculating an anomaly score of the satellite telemetry data, comparing the anomaly score with a preset threshold value, and judging anomaly. The method is suitable for anomaly detection scenes with different dimensions and different types of telemetry data.

The application relates to a satellite fault prediction model training and fault prediction method based on confidence estimation, and belongs to the field of satellite fault prediction, which comprises the following steps: acquiring original satellite telemetry data and performing data preprocessing; inputting the original satellite telemetry data into a satellite fault prediction model trained by an unknown satellite fault prediction model training method based on confidence estimation, calculating an output feature vector and a bias vector; calculating the harmonic mean of each dimension of the bias vector to obtain a confidence estimation value of the input data; judging whether the confidence estimation value is greater than a confidence threshold value; if the confidence estimation value is less than the confidence threshold value, the satellite state is determined as unknown fault; if the confidence estimation value is greater than or equal to the confidence threshold value, the satellite state is determined as no fault or known fault. The application can simultaneously predict the known faults and unknown faults of a satellite platform and a load according to satellite telemetry data, reduces the influence of data noise on a satellite fault prediction model, and improves the reliability of the fault prediction model.

This invention relates to the field of satellite telemetry, tracking, and command (TT&C) technology, specifically a rapid switching relay tracking method for densely packed satellite formations. Applied to the antenna servo embedded system of ground-based TT&C equipment for densely packed satellite formations, it solves the problems of response lag, high computational overhead, and low pointing accuracy inherent in traditional methods for tracking densely packed satellite formations. This method generates acceleration / deceleration planning sequences through ephemeris analysis, combines link indicators and preset times to achieve dual-trigger judgment for acceleration and deceleration, preloads dedicated parameter templates and adapts to the FPGA+MCU dual-core hardware architecture, employs a simplified three-stage acceleration / deceleration execution to compensate for orbital drift, verifies the status after motion and dynamically adapts parameters, and activates a backup plan in case of anomalies. This invention achieves proactive predictive planning, significantly reducing the computational overhead of the embedded system, achieving satellite switching tracking time ≤20s, controllable pointing accuracy, and constructing a complete acceleration / deceleration control system without requiring large-scale hardware modifications, making it highly practical for engineering applications.

This invention provides a satellite telemetry scheduling and processing method and system suitable for spread spectrum hopping mode, comprising: collecting telemetry source packets from various satellite subsystems; performing secondary screening on all telemetry source packets and recombining important telemetry parameter packets in spread spectrum hopping mode; grouping important telemetry parameter packets in spread spectrum hopping mode into virtual channel data units according to the virtual channel identifier of spread spectrum hopping mode; scrambling the virtual channel data units according to the selected scrambling polynomial and initial phase; adding frame synchronization words to group channel access data units; performing frame selection processing under different modes according to different telemetry rate switching modes; dividing the selected telemetry frames into equal parts and inserting the equally divided telemetry data into different spread spectrum hopping downlink measurement frames for transmission. This invention effectively meets the compatibility processing requirements of integrated electronic computers for conventional noncoherent spread spectrum mode and spread spectrum hopping mode, ensures the transmission of important telemetry in spread spectrum hopping mode, and facilitates ground processing.

This invention discloses a method and system for anomaly detection in satellite telemetry data based on reinforcement learning, comprising: acquiring telemetry orbit mission data to generate a basic sequence; generating phase index mission labels and rearranging the sequence; inputting the rearranged sequence into an improved Autoformer model to output trend periodic residuals; performing secondary forward correction through residual convolution feedback; recursively inferring long-range imagined sequences based on DreamerV3 hierarchical imagination; performing latent variable decomposition on the long-range imagined sequences to extract differential latent variables; outputting the current anomaly detection result by a policyr; and updating and fine-tuning the improved Autoformer model based on the feedback reward value. This invention combines phase rearrangement, kernelized delay coding, residual self-correction, and hierarchical imagination recursion mechanisms to distinguish between mission switching fluctuations and genuine anomalies, improving the capabilities of satellite telemetry anomaly identification, early warning, delayed anomaly judgment, and closed-loop adaptive updating.

The invention relates to a multi-satellite multi-telemetry data query method and system, and relates to the technical field of satellite in-orbit flight control and multi-satellite telemetry data processing, and the multi-satellite multi-telemetry data query method comprises the following steps: S1, multi-satellite telemetry data acquisition and preprocessing; s2, carrying out structured analysis and lightweight processing; s3, full life cycle data storage and management; s4, heterogeneous communication and bidirectional interaction; and S5, performing dynamic visualization and user interaction. The method has the advantages that the technical problems of low multi-satellite telemetry data parallel processing efficiency, difficulty in cross-dimension telemetry parameter association analysis and inconvenience in historical telemetry data tracing are solved; according to the invention, a modular system design method is utilized to construct a complete link from telemetry data receiving, analysis and distribution to user-defined configuration and visual presentation, so that the real-time performance and accuracy of satellite state monitoring are effectively improved; effective technical support is provided for flight control, long-term health management and stability and reliability of state monitoring of an on-orbit satellite.

This application discloses a satellite anomaly detection method, device, medium, and program product to reduce the false alarm rate and missed alarm rate of satellite anomaly detection and improve the accuracy of satellite anomaly detection. The method includes: acquiring satellite telemetry data; preprocessing the satellite telemetry data to obtain data to be detected; converting the data to be detected into a vector to be detected using a pre-trained vector embedding model, wherein the vector embedding model is trained using a metric learning algorithm based on satellite telemetry data samples and their corresponding labels; and detecting satellite anomalies based on the vector to be detected.

The application discloses a system for reducing radio frequency interference in satellite and ground TT&C system docking test, which uses a fixed attenuator to reduce the multipath interference of satellite telemetry signals on telemetry signals through a telemetry and remote control common branch, uses a first isolator to reduce the multipath interference of satellite telemetry signals on telemetry signals through a telemetry branch, and uses a second isolator to reduce the multipath interference of satellite telemetry signals on telemetry signals through a telemetry branch, so as to achieve the purpose of suppressing radio frequency multipath interference, thereby ensuring the accuracy of ranging and speed random error index testing in satellite and ground TT&C system docking test.

The invention provides a satellite telemetry earth magnetic field anomaly detection method based on a periodic sensing structure time sequence feature fusion network. Aiming at the defects of the traditional detection method in the existing pre-earthquake magnetic field anomaly research, such as limited analyzed remote sensing parameters, insufficient positioning precision of an anomaly position, insufficient reliability of a detection result and the like, the method takes a potential periodic characteristic of data as a priori; performing deep analysis on the geomagnetic data from two dimensions of structural features and time sequence evolution, and systematically extracting key features; a jump connection mechanism is introduced into a network structure, efficient multiplexing of deep and shallow layer features is realized, and the information fusion and gradient conduction capability of the model is enhanced; and finally, accurately identifying and positioning the abnormal data of the magnetic field through a dynamic threshold self-adaptive judgment mechanism. The method has better comprehensive performance in a satellite telemetering geomagnetic anomaly detection task, and more reliable and accurate data support can be provided for pre-earthquake magnetic field anomaly behavior analysis and relevance research between the pre-earthquake magnetic field anomaly behavior analysis and earthquake activity.

The present application aims to provide a satellite two-line element generation method based on telemetry data. The method comprises the following steps: S1, satellite telemetry data processing; S2, setting two-line element initial value; S3, preliminary determination of two-line element; S4, optimization estimation of drag coefficient term; S5, generating final satellite two-line element according to two-line element rule; the generated two-line element can be connected to an internet collaborative manufacturing platform and an internet intelligent manufacturing service platform, and is suitable for industrial data integration service and industrial internet basic environment operation service demand, which not only solves the contradiction between satellite two-line element autonomy and universality, but also provides technical support for high-quality industrial internet service in the field of satellite measurement and control, and is suitable for remote sensing satellite measurement and control technical field and industrial internet related scene. The present application relates to the field of remote sensing satellite measurement and control technology, and is also applied to the field of industrial internet technology system service and industrial big data resource service.

The invention discloses a multi-satellite fault detection method based on a constellation auto-encoder and comprehensive diagnosis, and belongs to the technical field of constellation diagnosis. The invention aims to solve the problems of model learning offset and diagnosis result distortion caused by fault samples mixed in training data of an existing auto-encoder for multi-satellite fault diagnosis. Comprising the following steps: preliminarily determining normally operating healthy satellites according to basic knowledge in the satellite field, and taking other satellites as satellites to be diagnosed; distinguishing the working mode of the telemetering data; training the healthy satellite data to obtain fault diagnosis auto-encoders in different modes; a fault diagnosis auto-encoder is adopted to obtain model reconstruction features of telemetry data of each satellite, and low-dimensional features are obtained; and calculating the tail abnormal strength, the overall offset degree and the diffusivity of the to-be-diagnosed satellite, obtaining a comprehensive score, comparing the comprehensive score with a preset comprehensive score threshold, and determining a fault satellite. The method is used for whole satellite fault diagnosis.

The invention relates to the technical field of health management of satellite-borne products with performance degradation characteristics, and discloses a time sequence anomaly detection method for satellite segmented telemetry based on deep learning, which comprises the following steps: firstly, acquiring satellite telemetry data, and performing segmentation and standardization processing to obtain physically continuous data segments; performing point-by-point reconstruction on the data by using a pre-trained time sequence auto-encoder model, calculating a reconstruction error and performing in-segment limited sliding window smoothing to generate an abnormal score; then determining an anomaly judgment threshold based on normal sample distribution, and defining a boundary exclusion region according to the physical boundary of the data segment; and finally, performing classification judgment on each time step by combining a threshold value and the exclusion region, and outputting a detection result. According to the method, by introducing a segmentation constraint mechanism and a boundary elimination strategy, the problem of false alarm caused by data discontinuity and equipment start-stop transition is effectively solved, and the accuracy and stability of satellite telemetry data anomaly detection are remarkably improved.