160 results about "Satellite telemetry" patented technology

The invention relates to the technical field of data processing, in particular to a multi-source target trajectory fusion method and system based on deep learning. Comprising the following steps: constructing a space-time alignment training set containing radar echo data, satellite telemetry data and truth value trajectory data; designing a multi-channel deep learning network architecture which comprises a radar echo data feature extraction channel and a satellite telemetry data feature extraction channel, and establishing dual-channel feature association through an attention mechanism; optimizing network parameters through back propagation to obtain a weight prediction model; radar echo data and satellite telemetry data are received in real time, and space-time alignment of sampling data is achieved through a sliding window mechanism and coordinate system conversion; inputting the preprocessed double-source features into the trained weight prediction model, and generating a radar-telemetering fusion weight coefficient; and performing weighting processing and optimization on the double-source trajectory coordinates, and outputting a fused target motion trajectory. The problem that a traditional single-source track measurement system is insufficient in precision in a complex environment is solved.

The invention relates to the technical field of satellite telemetering and remote control, and discloses a port task processing method for a satellite measurement, operation and control system, which comprises the following steps of: 1, detecting all available network interfaces through a port scanner, and establishing a multi-path communication channel comprising a public network, a private network and a satellite link; step 2, acquiring packet loss rate, delay, 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; and step 3, generating a comprehensive score of each path according to the packet loss rate, the delay, the bandwidth and the jitter parameters. According to the method and the device, the technical scheme of dynamic scoring and switching of the multi-path communication channel is adopted, and the technical effect of automatically selecting the optimal path according to the real-time network performance is achieved; the problems of high transmission delay, large packet loss rate and incapability of adaptive adjustment caused by network fluctuation are solved.

A system and method for cross-domain knowledge transfer in federated compression networks. The system enables efficient lossless data compression across diverse data types by intelligently sharing compression strategies between domains. A cross-domain knowledge transfer system identifies relationships between different data domains, adapts compression parameters accordingly, and optimizes learning processes to maximize knowledge reuse. The architecture may include a knowledge repository for storing domain features and compression patterns, domain mapping components that identify similarities, and transfer learning optimization that enables efficient adaptation with minimal examples. This approach significantly accelerates model training for new domains while improving compression performance. Applications include satellite telemetry systems where efficient compression is critical for transmitting large information sets between distant locations. The system may employ probability prediction driven arithmetic coding paired with long short-term memory networks, enhanced by cross-domain knowledge sharing that adapts successful compression strategies from one domain to another while preserving domain-specific optimization.

The invention discloses a multi-modal enhanced satellite telemetry data multi-task processing system and method. The system comprises an input embedding module, a knowledge-driven prompt enhancement module, a fusion perception module, a large language model processing module, a feature enhancement module, a time sequence model processing module and a task execution and optimization module. The method comprises the following steps: performing knowledge graph enhancement on an initial instruction of a natural language mode by utilizing a knowledge-driven prompt enhancement module to generate an optimized instruction; fusing the natural language mode of the optimized instruction and the time sequence mode of the satellite telemetry data by using a fusion sensing module; mining mixed features in the fused data by using a large language model processing module; a final prediction result is deduced by using a time sequence model processing module, and prediction and anomaly detection of the satellite telemetry data are realized; according to the method, under the technical framework of fusing the large language model, the large time sequence model and the knowledge graph, efficient processing and accurate analysis of the satellite telemetry data are realized.

The invention provides a real-time telemetry data multivariate presentation and comparative analysis system for batch production satellites. The system comprises a front end and a rear end, the front end comprises a page management module and a corresponding control, and obtains telemetering data according to the selected satellite code and telemetering channel code through multiple types of controls so as to realize real-time telemetering data multivariate presentation and comparative analysis of mass-produced satellites; and the rear end is responsible for receiving and storing multi-satellite telemetering data, maintaining the latest real-time telemetering information table, triggering all controls to update the displayed telemetering data, and carrying out basic processing and interpretation on the telemetering data. According to the method, under the trend that satellite batch production and satellite telemetry data interpretation requirements are improved, a single person carries out conventional monitoring on multiple satellites at the same time, and when the multiple satellites in batch production cooperatively test or work cooperatively, the requirements for telemetry data joint monitoring and comparative analysis of the multiple satellites are met.

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 remote sensing satellite proximity search subsystem testing system and method relates to the field of remote sensing satellite ground testing, and comprises a satellite platform and a ground testing system, and the ground testing system comprises a server, a general control system and interpretation analysis software; the satellite platform comprises an on-satellite comprehensive electronic subsystem and a distributor; the master control system sends a remote control instruction to the server, obtains satellite telemetry information and satellite data from the server and sends the satellite telemetry information and the satellite data to the interpretation analysis software; the server sends a remote control instruction to the comprehensive electronic subsystem, and satellite telemetry information and satellite data are obtained from the comprehensive electronic subsystem; the comprehensive electronic subsystem sends a remote control instruction to the proximity search subsystem and receives satellite telemetry information and satellite data of the proximity search subsystem; the proximity search subsystem carries out state setting according to the remote control instruction and feeds satellite telemetry information and satellite data back to the comprehensive electronic subsystem. The method is suitable for ground testing of the remote sensing satellite proximity search subsystem.

The invention discloses a method and a system for detecting time sequence anomaly of satellite telemetry data. The method comprises the following steps: normalizing satellite telemetry time sequence data X; dividing the normalized X into a plurality of window data Xw with the length of w by adopting a sliding window strategy; inputting each Xw into a generator G of the generative adversarial network for mask interpolation, and generating covered data with the length of w; comparing Xw with concealed data bit by bit, and if a difference value of a certain bit exceeds a threshold value, determining that the window data is abnormal; the generative adversarial network further comprises a discriminator D in the training stage, the input of the D is window data and concealed data, the output of the D is the probability of whether the concealed data is real data, and the data generated by the G better conforms to the distribution characteristics of the X through training. According to the method, the accuracy, the robustness and the adaptive capacity of anomaly detection are improved, and a new technical scheme is provided for the anomaly detection of the satellite telemetry parameters.

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.

A system and method for federated two-stage compression with federated joint learning. The system and method proposed allow for fast and efficient lossless data compression of a large variety of data types. The system and method have a variety of real-world applications, including deep learning solutions for telemetry, tracking, and command subsystems for satellites. Satellites and their control centers are incredibly spaced apart which makes data compression an extremely important process to transmit large sets of information in a low-latency, high-efficiency environment. The proposed system and method utilize probability prediction driven arithmetic coding which provides faster encoding times and higher compression ratios when paired with a long short-term memory system for data compression.

The invention discloses a time sequence data fault root cause diagnosis method and a related device for causal discovery, and relates to the technical field of fault identification, and the method comprises the steps: obtaining to-be-processed satellite telemetering time sequence data; calculating a Hotelling T2 statistic of each data sample by using a principal component analysis algorithm, and determining a fault sample according to a comparison result of the Hotelling T2 statistic and a Hotelling T2 statistic control limit; for each fault sample, screening out a fault candidate variable corresponding to the fault sample by using an LASSO-based fault isolation method; applying a channel attention sparse causal network model to the fault candidate variables of each fault sample to obtain a causal matrix between the fault candidate variables; and determining a causal topology among the fault candidate variables according to the causal matrix so as to realize identification of a fault propagation path and positioning of a fault root cause. The method can effectively identify the propagation path of the associated fault and accurately position the root cause.

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 provides an inter-satellite laser communication system based on visual positioning assisted link establishment and a link establishment method. The system comprises a laser communication machine which comprises a processor and an optical head and is used for realizing laser link establishment and laser communication; the optical detection camera, the rotary table and the sensing positioning module form a visual positioning subsystem which is used for observing and positioning a passive end target, namely a communication opposite end satellite; the measurement and control data transmission module is used for receiving data and instructions from the ground and sending satellite telemetry data; and the satellite service management module is used for realizing task management and control management of a load single machine. The inter-satellite laser communication link establishment method is suitable for inter-satellite laser communication link establishment of satellites in orbit, especially inter-satellite laser communication link establishment in under-communication and high-dynamic scenes. By using visual positioning assistance, the dependence on a ground station and external data can be reduced, the laser link establishment time is shortened, the use scene is expanded, and the stability and robustness of a satellite laser communication system are enhanced.

The invention belongs to the technical field of time series data prediction, and particularly relates to a dynamic error introduced time series data prediction optimization method and system. The method comprises the following steps: preprocessing to-be-processed time sequence data; inputting the preprocessed data into a pre-established and trained prediction model to obtain preliminary prediction data; comparing the preliminary prediction data with the preprocessed data to obtain a preliminary error; and based on the initial error, combining historical data of different time durations, obtaining a long-term error and a recent error according to a time decay function, and obtaining a corrected predicted value through weighted combination, thereby realizing real-time correction of the dynamic error. According to the method, the dynamic error correction method is applied to the time sequence prediction of the satellite telemetry data for the first time, the real-time correction of the prediction error is realized, and the prediction precision is remarkably improved.

The invention provides a satellite telemetry data injection attack anomaly detection method and system, and the method comprises the steps: carrying out the multi-source data collection of each satellite subsystem, obtaining satellite telemetry data, obtaining a preset satellite telemetry data physical constraint library, and constructing a satellite ecological stability model in combination with the satellite telemetry data; performing primary screening on the satellite telemetry data based on a primary satellite data screening mechanism, generating an initial satellite ecological early warning group, calculating the ecological stability of the initial satellite ecological early warning group based on a satellite ecological stability model, and obtaining an ecological stability result; performing secondary screening on the initial satellite ecological early warning group based on a secondary satellite data screening mechanism and an ecological stability result to obtain a satellite ecological early warning group; performing ecological intrusion verification on the satellite ecological early warning group to obtain a satellite ecological damage score; performing intrusion cleaning decision generation based on the satellite ecological damage score to obtain an intrusion cleaning decision; through the method, the efficiency and accuracy of attack anomaly detection in satellite telemetry data can be improved.

The invention provides a satellite irregular telemetry data self-adaptive reconstruction method for continuous time modeling, belongs to the technical field of aerospace, and aims to solve the problems that the precision of nonlinear data reconstruction is reduced, the output dimension is fixed, and the reconstruction precision is low due to the fact that detailed information of data change is easy to lose in traditional satellite telemetry data reconstruction. The method comprises the following steps: calculating an abnormal threshold value of the telemetry data based on the telemetry data; constructing a satellite telemetry data adaptive reconstruction window based on the abnormal threshold, and recording a missing position and missing time; dividing the telemetry data into a training data set and a test data set according to a missing detection result, and establishing a satellite telemetry data reconstruction model based on NODE; inputting the test data set, the missing position and the missing time into the trained satellite telemetry data reconstruction model for data adaptive reconstruction to obtain normally sampled satellite telemetry data; and the calculation is repeated until the maximum number of iterations is reached, and a reconstructed data set of the satellite telemetry data is obtained.

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.

The invention discloses a flexible and adjustable satellite telemetering quantity acquisition and downloading system and method, and the system comprises a telemetering acquisition unit which is used for periodically acquiring telemetering quantity generated by each module in a load subsystem when a feed link is provided; the acquisition table storage unit is used for storing a telemetering acquisition table uploaded by a ground operation and control system; when the telemetering quantity needs to be downloaded through the measurement and control link, the telemetering acquisition unit is used for screening the telemetering quantity required by the ground operation and control system according to the telemetering acquisition table, and the telemetering quantity is the telemetering quantity required by telemetering downloading of the measurement and control link; the telemetering processing unit is used for receiving the telemetering quantity acquired by the telemetering acquisition unit, storing the telemetering quantity on a satellite to form a telemetering quantity set of a load subsystem, and performing health monitoring on the required telemetering quantity; and the telemetering downloading unit is used for downloading the screened telemetering quantity required by the ground operation and control system to the ground operation and control system. The reliability of in-orbit operation of a satellite system is improved, and fine management of satellite in-orbit control is achieved.

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.

The invention provides a priori knowledge-based satellite telemetering false alarm identification and processing method and system, and the method comprises the steps: obtaining the working condition, the false alarm influence range and the influence time of the satellite telemetering false alarm based on the priori knowledge accumulated in the early-stage design and acceptance of a satellite and in the development and test process in combination with the analysis and extraction of satellite telemetering data, and carrying out the recognition and processing of the satellite telemetering false alarm. And on the basis, the satellite telemetering false alarm is identified and processed. According to the method, the interference of telemetering false alarm on data interpretation is solved, the data interpretation efficiency and interpretation quality in the satellite test and on-orbit monitoring process are effectively improved, unnecessary treatment measures caused by false alarm are reduced, satellite abnormity can be found timely and accurately, faults can be removed timely and accurately, and the reliability of satellite test and on-orbit monitoring is improved. And guarantee is provided for better organizing satellite management activities and controlling satellites to complete tasks.

This invention belongs to the field of satellite telemetry, tracking, and command (TT&C) technology, and provides a method and system for real-time scheduling of short message resources during overseas orbit control. The method includes: satellite control software constructing a short message frame library and pre-configuring fixed-length normal frames and orbit control-specific frames; attitude and orbit control software monitoring orbit control status in real time, satellite control software identifying orbit control ignition commands and orbit control stage markers, and initiating a dual-queue parallel transmission mechanism; configuring the link for relay satellites according to the dual-queue parallel transmission mechanism and implementing frequency division multiplexing downlink; and entering a transition period after orbit control monitoring ends, performing periodic attenuation control on the orbit control-specific frames. This invention solves the problem of real-time status monitoring failure for geostationary orbit satellites during overseas orbit control, increasing the orbit control anomaly identification rate to over 99%, breaking through monitoring real-time limitations, and significantly improving the safety and controllability of overseas orbit control; optimizing resource utilization, enhancing adaptive capabilities, and achieving second-level on-demand downlink of key parameters and dynamic optimization of channel resources.

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 provides a satellite test interpretation system based on scene recognition and temperature grading. The satellite test interpretation system comprises a data subscription service subsystem and a processing module. The data subscription service subsystem is used for receiving and forwarding satellite telemetry data; the processing module runs fine interpretation software and sequentially executes the following steps: detecting a whole satellite and single machine power-up state and a telemetering interruption state; an actual test scene is intelligently identified in combination with the thermistor mounting state; calling a preset three-level temperature range of storage, work and acceptance according to the scene to carry out grading interpretation; and finally, performing multi-level early warning such as color distinguishing, character prompting and voice alarming according to the interpretation result. Therefore, automatic and precise satellite temperature monitoring and fault early warning are realized.

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.

1. The name of the product of this design: Satellite measurement and transmission integrated machine. 2. Purpose of this design product: This design product is used for satellite measurement and control data transmission communications. It can receive and demodulate ground uplink signals and modulate downlink data and send it to the ground. 3. The design key point of this appearance design product lies in the shape of the product. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

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.

The present invention discloses a satellite telemetry application mode and architecture with a three-level protection mechanism. The application mode includes: the measurement and control subsystem sends normal telemetry when it detects normal telemetry generated by satellite services; sends critical telemetry when there is no normal telemetry and there is critical telemetry generated by the overall circuit subsystem; sends self-telemetry when there is no normal telemetry and no critical telemetry. The satellite architecture includes a measurement and control subsystem that can send self-telemetry, critical telemetry and normal telemetry respectively under different states on the satellite; an overall circuit subsystem that can collect critical telemetry of critical subsystems through dedicated lines; a satellite services subsystem that can collect normal telemetry of all subsystems through a bus; and other subsystems. Based on the idea of telemetry reliability grading, the present invention realizes a multi-level telemetry layered application mode, provides a means of step-by-step analysis and debugging based on telemetry when the satellite is in an on-orbit fault state, improves the safety and reliability of the satellite in orbit, and has important engineering application value.