Wireless communication method and system in astronomical telescope

Abstract

This invention relates to the field of wireless communication technology, specifically to a wireless communication method and system for astronomical telescopes. The method includes the following steps: based on the location of the astronomical telescope and the communication environment, assessing the signal strength and interference levels of surrounding wireless channels, recording channel usage and signal quality, and selecting channels with low signal interference to obtain a preferred channel record. In this invention, by refining real-time data stream analysis and channel configuration, communication interference caused by environmental changes is effectively reduced. Simulation tests verify the performance of each channel, ensuring that selected channels can provide stable service under various conditions, thereby improving communication reliability. The application of a particle swarm optimization algorithm achieves optimal channel performance configuration, making communication channel management more flexible and efficient. This enables efficient and secure transmission of communication data even in harsh observation environments, improving the data's usability and observation timeliness, and ensuring high-quality collection and processing of astronomical data.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more particularly to a wireless communication method and system for astronomical telescopes. Background Technology

[0002] Wireless communication technology is a technology that uses electromagnetic waves (such as radio frequencies, microwaves, etc.) to transmit information between devices. This technology does not require physical connections, such as cables or lines, making communication more flexible and faster. Wireless communication technology has a wide range of applications, including mobile phones, wireless networks, satellite communications, radio broadcasting and television, and GPS. With the development of technology, wireless communication can now support high data rate transmission, enabling functions such as high-definition video streaming, large-capacity data packets, and real-time data transmission.

[0003] Wireless communication methods in astronomical telescopes refer to the use of wireless technology in astronomical telescope systems to transmit observational data and control information. In astronomy, telescopes are usually deployed in remote or harsh geographical locations, such as high mountains or deserts. These places have lower light pollution and better observation conditions, but they also bring challenges to data transmission. Traditional wired communication methods are greatly limited by geography and environment, have high installation costs and complex maintenance. Using wireless communication methods can realize real-time data transmission, optimize the efficiency of remote control and data acquisition, and improve the flexibility and real-time nature of astronomical observation.

[0004] Existing technologies are often severely affected by environmental factors in remote areas, such as signal interference and network load issues, which often lead to unstable data transmission. When handling high data rate transmission, especially the real-time transmission requirements of video streams and large data packets, traditional technologies have failed to effectively adapt to channel congestion and rapidly changing environments, resulting in data loss or transmission errors. This affects the accuracy of observation data and the continuity of scientific research, limits the performance of astronomical telescopes under extreme observation conditions, and reduces their effectiveness in scientific research and practical applications. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies by proposing a wireless communication method and system for astronomical telescopes.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a wireless communication method in an astronomical telescope, comprising the following steps:

[0007] S1: Based on the location of the astronomical telescope and the communication environment, assess the signal strength and interference level of surrounding wireless channels, record channel usage and signal quality, and filter channels with low signal interference to obtain the optimal channel record;

[0008] S2: Based on the channel optimization record, continuously monitor the signal quality and network load of the target channel, perform real-time analysis of the data stream, record the analysis results and refine the channel configuration, optimize data transmission efficiency, and obtain refined channel configuration information;

[0009] S3: Perform simulation tests on the detailed channel configuration information to verify the communication performance of the selected channels. Re-evaluate channels that do not meet expectations, revise the channel selection list, and obtain the communication performance evaluation results.

[0010] S4: Based on the communication performance evaluation results, the channel selection logic is optimized using the particle swarm optimization algorithm. The performance of multiple channels is re-sorted and optimized, the communication channel selection is updated, and the real-time effect of the adjustment is evaluated to obtain channel selection verification data.

[0011] S5: Based on the channel selection verification data, process the astronomical telescope data, generate encoded data packets through linear combination, test the transmission effect of the encoded data packets in the network environment, and analyze the encoding efficiency and error rate to obtain the encoding performance analysis set;

[0012] S6: Based on the aforementioned coding performance analysis set, analyze and reconstruct the lost data packets, verify the quality and integrity of the reconstructed data packets through communication tests, evaluate the application effect of the reconstructed data, and obtain the data packet integrity verification results.

[0013] As a further aspect of the present invention, the preferred channel record includes signal reception rate, interference index, and selected channel; the detailed channel configuration information includes network load index, channel stability data, and transmission delay data; the communication performance evaluation results include performance benchmark test, abnormal channel identification results, and preferred channel update results; the channel selection verification data includes the adjusted channel list and performance improvement details; the coding performance analysis set includes coding rate and error occurrence frequency; and the data packet integrity verification results include reconstruction power and reconstruction efficiency evaluation results.

[0014] As a further aspect of the present invention, the steps of evaluating the signal strength and interference level of surrounding wireless channels based on the location of the astronomical telescope and the communication environment, recording channel usage and signal quality, and selecting channels with low signal interference to obtain the preferred channel records are as follows:

[0015] S101: Based on the location of the astronomical telescope and the communication environment, it collects signal strength and interference data of wireless channels in real time, continuously monitors each channel through frequency scanning technology, captures real-time signal changes, and generates signal monitoring data.

[0016] S102: Based on the signal monitoring data, analyze the channel usage and signal quality, filter channels with low interference, and determine the channel with the best signal through comparative analysis to obtain a channel selection list;

[0017] S103: Based on the channel selection list, record the data transmission efficiency and stability of the selected channels, perform performance evaluation on the selected channels, determine the optimal configuration of the selected channels, and obtain the channel optimization record.

[0018] As a further aspect of the present invention, based on the channel preference record, the steps of continuously monitoring the signal quality and network load of the target channel, performing real-time parsing of the data stream, recording the parsing results and refining the channel configuration, optimizing data transmission efficiency, and obtaining refined channel configuration information are as follows:

[0019] S201: Based on the channel preference record, monitor the signal quality and network load of the target channel, collect communication signal quality data and load data, analyze the collected data trends, and generate load trend records;

[0020] S202: Based on the load trend record, optimize the signal path and data routing according to the real-time parsed data stream, and adjust the channel configuration to match the current network conditions to obtain routing optimization information;

[0021] S203: Based on the routing optimization information, adjust the parameter settings of multiple communication channels to optimize communication efficiency, verify the adjustment results, determine the optimal communication state, and obtain detailed channel configuration information.

[0022] As a further aspect of the present invention, the steps of simulating tests on the refined channel configuration information, verifying the communication performance of the selected channels, re-evaluating channels that do not meet expectations, revising the channel selection list, and obtaining the communication performance evaluation results are as follows:

[0023] S301: Based on the detailed channel configuration information, configure a simulation test environment, simulate the communication performance of multiple channels under extreme conditions, and collect performance data of multiple channels, including signal delay and error rate, to generate a performance test dataset.

[0024] S302: Based on the performance test dataset, compare the communication performance of multiple channels with the standard, quantitatively evaluate the deviation of each channel, mark the substandard channels, and organize the channel performance indicators to obtain a list of channels to be optimized.

[0025] S303: Based on the channel list to be optimized, adjust the channel configuration settings, retest the adjusted channels, verify the adjustment effect, and determine whether the channels have reached or exceeded the performance baseline to obtain the communication performance evaluation results.

[0026] As a further aspect of the present invention, based on the communication performance evaluation results, the channel selection logic is optimized using the particle swarm optimization algorithm, the performance of multiple channels is re-ranked and optimized, the communication channel selection is updated, and the real-time effect of the adjustment is evaluated to obtain channel selection verification data. The specific steps are as follows:

[0027] S401: Based on the communication performance evaluation results, the priority settings of the channels are adjusted using the particle swarm optimization algorithm, channel resources are reallocated, communication network efficiency is optimized, and the performance data after the channel adjustment is recorded to generate a performance ranking set.

[0028] S402: Based on the performance ranking set, continuously refine the transmission parameters of the channels, adjust the signal enhancement and interference suppression settings, re-evaluate the performance changes of the parameter adjustments, verify the optimal configuration of each channel, and obtain the transmission optimization record;

[0029] S403: Based on the transmission optimization record, perform communication channel selection, test the network stability and data transmission efficiency under the new configuration, and verify whether the adjustment results achieve the expected effect, and obtain channel selection verification data.

[0030] As a further aspect of the present invention, the priority setting of the channel is adjusted using the particle swarm optimization algorithm, according to the formula:

[0031] PG i =wP i-1 +c1r1(P best -P i-1 )+c2r2(G best -P i-1 )

[0032] Adjust the channel priority, where PG i P represents the priority of the current channel. i-1 P represents the previous channel priority. best G represents the channel's highest priority to date. best The global optimal priority in the channel is represented by w, the inertia weight is w, c1 and c2 are learning factors, and r1 and r2 are random numbers in the interval 0 and 1.

[0033] As a further aspect of the present invention, based on the channel selection verification data, the astronomical telescope data is processed to generate encoded data packets through linear combination. The transmission effect of the encoded data packets is tested in a network environment, and the encoding efficiency and error rate are analyzed to obtain the encoding performance analysis set. The specific steps are as follows:

[0034] S501: Based on the channel selection verification data, use linear combination to merge the data collected from multiple channels, optimize data integration efficiency and data error, and generate an encoded integration set;

[0035] S502: Based on the aforementioned encoding integration set, simulate the current network conditions, perform data packet transmission tests, record the transmission rate and error occurrences during the transmission process, evaluate the encoding process, and obtain a transmission effect analysis record;

[0036] S503: Based on the transmission effect analysis record, adjust the data packet encoding parameters, perform the transmission test again, verify the effect of parameter adjustment, and verify the improvement effect of data packet transmission to obtain the encoding performance analysis set.

[0037] As a further aspect of the present invention, based on the aforementioned coding performance analysis set, lost data packets are analyzed and reconstructed. The quality and integrity of the reconstructed data packets are verified through communication tests, and the application effect of the reconstructed data is evaluated to obtain the data packet integrity verification result. The specific steps are as follows:

[0038] S601: Based on the aforementioned coding performance analysis set, identify lost data packets during transmission, reconstruct lost data packets, monitor reconstruction success and data packet integrity, and generate data recovery records;

[0039] S602: Based on the data recovery record, perform quality testing on the reconstructed data packet, compare the consistency of the test results with the original data packet, evaluate the application effect of the data packet reconstruction, and obtain communication quality verification information;

[0040] S603: Based on the communication quality verification information, verify whether the reconstructed data packet meets the quality standard of the original data, and perform application testing on the data packet to obtain the data packet integrity verification result.

[0041] A wireless communication system for an astronomical telescope, the wireless communication system for performing the wireless communication method described above in the astronomical telescope, the system comprising:

[0042] The signal optimization module assesses the signal strength of surrounding wireless channels based on the location of the astronomical telescope and the communication environment, analyzes the interference level of multiple channels, records the usage rate and signal quality of communication channels, filters channels with low interference, and generates channel optimization records.

[0043] Based on the channel optimization record, the channel monitoring module monitors the signal quality and network load of the target channel in real time, parses the communication data stream, refines the channel configuration, and obtains refined channel configuration information.

[0044] The performance verification module performs simulation tests on the detailed channel configuration information to verify the communication performance of multiple channels. Channels that fail to meet the performance standards are re-evaluated, the channel selection list is corrected, and the communication performance evaluation results are obtained.

[0045] The optimization module uses the communication performance evaluation results to sort and optimize the performance of multiple channels using the particle swarm optimization algorithm, updates the channel selection list, evaluates the adjusted real-time communication effect, and establishes channel selection verification data.

[0046] The data encoding module selects verification data according to the channel, generates encoded data packets through linear combination, tests the transmission effect in the network environment, analyzes the encoding efficiency and error rate, reconstructs lost data packets, tests the quality and integrity of the reconstructed data packets, and obtains the data packet integrity verification results.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In this invention, by refining real-time data stream analysis and channel configuration, communication interference caused by environmental changes is effectively reduced. Simulation tests verify the performance of each channel, ensuring that the selected channels can provide stable services under various conditions, thereby improving the reliability of communication. The particle swarm optimization algorithm is applied to achieve the optimal configuration of channel performance, making communication channel management more flexible and efficient. This enables communication data to be transmitted efficiently and securely even in harsh observation environments, improving the usability of data and the timeliness of observation, and ensuring the high-quality collection and processing of astronomical data. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flowchart of S1 of the present invention;

[0051] Figure 3 This is a detailed flowchart of the S2 process of the present invention;

[0052] Figure 4 This is a detailed flowchart of the S3 process of the present invention;

[0053] Figure 5 This is a detailed flowchart of the S4 process of the present invention;

[0054] Figure 6 This is a detailed flowchart of S5 of the present invention;

[0055] Figure 7 This is a detailed flowchart of S6 of the present invention;

[0056] Figure 8 This is a system flowchart of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0059] Example 1

[0060] Please see Figure 1 This invention provides a technical solution: a wireless communication method in an astronomical telescope, comprising the following steps:

[0061] S1: Based on the location of the astronomical telescope and the communication environment, assess the signal strength and interference level of surrounding wireless channels, record channel usage and signal quality, and select the channel with the lowest signal interference to obtain the channel optimization record;

[0062] S2: Based on channel optimization records, continuously monitor the signal quality and network load of the target channel, perform real-time analysis of the data stream, record the analysis results and refine the channel configuration, optimize data transmission efficiency, and obtain refined channel configuration information;

[0063] S3: Perform simulation tests on the detailed channel configuration information to verify the communication performance of the selected channels. Re-evaluate channels that do not meet expectations, revise the channel selection list, and obtain the communication performance evaluation results.

[0064] S4: Based on the communication performance evaluation results, the channel selection logic is optimized using the particle swarm optimization algorithm. The performance of multiple channels is re-ranked and optimized, the communication channel selection is updated, and the real-time effect of the adjustment is evaluated to obtain channel selection verification data.

[0065] S5: Based on channel selection verification data, process astronomical telescope data, generate encoded data packets through linear combination, test the transmission effect of encoded data packets in a network environment, and analyze encoding efficiency and error rate to obtain an encoding performance analysis set;

[0066] S6: Based on the coding performance analysis set, the lost data packets are analyzed and reconstructed. The quality and integrity of the reconstructed data packets are verified through communication tests, and the application effect of the reconstructed data is evaluated to obtain the data packet integrity verification results.

[0067] The channel selection record includes signal reception rate, interference index, and selected channel. Detailed channel configuration information includes network load indicators, channel stability data, and transmission delay data. Communication performance evaluation results include performance benchmark tests, abnormal channel identification results, and preferred channel update results. Channel selection verification data includes the adjusted channel list and performance improvement details. Coding performance analysis set includes coding rate and error occurrence frequency. Data packet integrity verification results include reconstruction power and reconstruction efficiency evaluation results.

[0068] Please see Figure 2 Based on the location of the astronomical telescope and the communication environment, the specific steps for evaluating the signal strength and interference level of surrounding wireless channels, recording channel usage and signal quality, and selecting the channel with the lowest signal interference to obtain the optimal channel record are as follows:

[0069] S101: Based on the location of the astronomical telescope and the communication environment, it collects signal strength and interference data of wireless channels in real time, continuously monitors each channel through frequency scanning technology, captures real-time signal changes, and generates signal monitoring data.

[0070] The location data of astronomical telescopes needs to be updated in real time via GPS to ensure data accuracy. Monitoring the communication environment involves signal strength and quality, requiring multiple frequency tests. Scanning technology is used to record the strength changes and interference levels of each signal in the channel in real time. For each channel, a time series data is generated, recording any minute changes in the signal. Noise filtering and signal enhancement processing are performed on the data to ensure its purity and usability. Through this continuous monitoring and real-time recording, signal changes within the channel can be captured, generating signal monitoring data.

[0071] S102: Based on signal monitoring data, analyze channel usage and signal quality, filter channels with the lowest interference, and determine the channels with the best signal through comparative analysis to obtain a channel selection list;

[0072] Based on signal monitoring data, the channel with the lowest interference is selected according to the formula:

[0073]

[0074] Calculate the channel with the lowest interference, where I d Represents the degree of interference, γ iLet γ represent the interference value of channel i, and N represent the number of channels. This formula is used to determine which channel has the lowest total interference among all available channels. First, the interference value of each channel is measured in real time to obtain γ for each channel. i The values ​​are given, for example, the interference value for channel 1 is 30, the interference value for channel 2 is 40, and the interference value for channel 3 is 20. Then, the sum of the interference values ​​is calculated, and the channel with the smallest sum of interference is selected. For example, if γ1 = 30, γ2 = 40, and γ3 = 20, then the channel with the smallest sum of interference is selected.

[0075] =20, then the total interference I of channel 3 is d =20 is the minimum. This process ensures that the selected channel has optimal signal quality, because lower interference usually means better signal quality.

[0076] S103: Based on the channel selection list, record the data transmission efficiency and stability of the selected channels, perform performance evaluation on the selected channels, determine the optimal configuration of the selected channels, and obtain the channel optimization record;

[0077] Based on the channel selection list, the data transmission efficiency and stability of the selected channels are recorded. This includes channel evaluation, with the data transmission efficiency of each selected channel obtained through actual transmission tests, including multiple transmissions of the same data packet within different time periods, to evaluate the average success rate and transmission speed of the data on that channel. Simultaneously, stability evaluation involves testing the channel under different environmental conditions, such as different weather conditions and different network loads, to ensure that the channel maintains good performance under various conditions. Furthermore, the performance evaluation of the selected channels also needs to consider the response time and error rate under high load conditions. Through comprehensive performance evaluation, the optimal configuration of the selected channels is determined.

[0078] Please see Figure 3 Based on channel optimization records, the specific steps for continuously monitoring the signal quality and network load of the target channel, performing real-time parsing of the data stream, recording the parsing results, refining the channel configuration, optimizing data transmission efficiency, and obtaining refined channel configuration information are as follows:

[0079] S201: Based on channel optimization records, monitor the signal quality and network load of the target channel, collect communication signal quality data and load data, analyze the collected data trends, and generate load trend records;

[0080] Based on channel optimization records, the system monitors the signal quality and network load of target channels, collects communication signal quality and load data, and requires setting signal quality thresholds and network load monitoring parameters to ensure that the actual needs of the current network environment are reflected. Signal strength and network load data are captured in real time, obtained through signal quality sensors and network traffic analysis. The collected data is recorded according to timestamps for trend analysis. By performing regression analysis and trend prediction on data over a continuous period, load trend records can be generated. These records provide decision support for network management, and the generated trend records provide a dynamic view showing the evolution of network conditions and stress points.

[0081] S202: Based on load trend records, optimize signal paths and data routes according to real-time parsed data streams, adjust channel configurations, match the current network conditions, and obtain routing optimization information;

[0082] Based on load trend records, optimize signal paths and data routing according to the formula:

[0083]

[0084] Calculate the route optimization information, where P opt x represents the optimized path efficiency. i The selection variable for the i-th routing point (0 or 1, representing whether to select this routing point), d i N represents the data transmission efficiency of the i-th routing point. q This represents the total number of selectable routing points in the network; there are three routing points with efficiency values ​​of 0.5, 0.8, and 0.6 respectively. If the first and third routing points are selected, then... =1, applying the formula, we get:

[0085] P opt =1×0.5+0×0.8+1×0.6=1.1

[0086] The result value represents the overall efficiency after selecting a routing point, ensuring maximum efficiency in data transmission while taking into account the performance variations of different routing points under different network conditions.

[0087] S203: Based on routing optimization information, adjust the parameter settings of multiple communication channels to optimize communication efficiency, verify the adjustment results, determine the optimal communication state, and obtain detailed channel configuration information;

[0088] Based on routing optimization information, the parameter settings of multiple communication channels are adjusted to optimize communication efficiency. First, the bandwidth, power, and modulation scheme of the channels are adjusted according to the routing optimization information. The parameter adjustments are based on the data transmission efficiency requirements and network load. The parameter settings are verified through actual network testing and simulation models to ensure the accuracy of the optimal configuration. During the adjustment process, the performance of various parameter configurations is automatically tested, communication efficiency is compared, and the optimal configuration is selected. After multiple rounds of testing and adjustment, the optimal parameter configuration for each communication channel is recorded. This detailed information helps to further optimize network performance. The obtained detailed channel configuration information provides technical support for management and maintenance, ensuring the stable operation and efficient transmission of the communication network.

[0089] Please see Figure 4 The specific steps for simulating and testing the detailed channel configuration information, verifying the communication performance of the selected channels, re-evaluating channels that do not meet expectations, revising the channel selection list, and obtaining the communication performance evaluation results are as follows:

[0090] S301: Based on detailed channel configuration information, configure a simulation test environment, simulate the communication performance of multiple channels under extreme conditions, and collect performance data of multiple channels, including signal delay and error rate, to generate a performance test dataset.

[0091] Based on detailed channel configuration information, a simulated test environment is configured to simulate the communication performance of multiple channels under extreme conditions. This process involves setting simulation environment parameters, including simulated network load, types and intensities of interference sources, to ensure that the test environment can simulate the most extreme conditions encountered. Performance data collection includes monitoring signal delay and error rate. Monitoring indicators are automatically recorded through data collection, ensuring the accuracy and consistency of the data. Through simulation and data collection, a comprehensive dataset reflecting real communication performance can be generated. This dataset includes the performance of each channel under different test conditions, providing a foundation for further analysis and optimization.

[0092] S302: Based on the performance test dataset, compare the communication performance of multiple channels with the standard, quantitatively evaluate the deviation of each channel, mark the substandard channels, and organize the channel performance indicators to obtain a list of channels to be optimized.

[0093] Based on performance test datasets, the communication performance of multiple channels is compared with the standard, according to the formula:

[0094]

[0095] Calculate the deviation for each channel, where D i O represents the percentage of performance deviation for channel i. i S represents the observed channel performance. iThis represents the performance standard; the formula is used to calculate the percentage deviation of each channel from the preset standard. For example, if the measured performance O1 of channel 1 is 95, and the standard S1 is 100, the formula will calculate:

[0096]

[0097] This indicates that the channel's performance is 5% below the standard. This method can quickly identify channels that do not meet the expected standards, and then carry out targeted optimization.

[0098] S303: Based on the channel list to be optimized, adjust the channel configuration settings, retest the adjusted channels, verify the adjustment effect, and determine whether the channels have reached or exceeded the performance baseline to obtain the communication performance evaluation results.

[0099] Based on the channel list to be optimized, the channel configuration settings are adjusted, and the adjusted channels are retested. First, adjustment parameters are selected based on performance deviation data. These parameters include transmission power, bandwidth adjustment, or coding strategy. Each adjustment is based on the specific shortcomings and optimization goals of the channel. Then, a series of control experiments are conducted to test the effect of the adjustment, including comparing and analyzing the channel performance before and after the adjustment under the same test conditions. This comparison verifies the actual impact of each adjustment on performance. If the channel performance reaches or exceeds the set baseline, it will be recorded in the communication performance evaluation results, ensuring that the performance of the communication system meets the design requirements and user expectations.

[0100] Please see Figure 5 Based on the communication performance evaluation results, the channel selection logic is optimized using the particle swarm optimization algorithm. The performance of multiple channels is re-ranked and optimized, the communication channel selection is updated, and the real-time effect of the adjustment is evaluated to obtain channel selection verification data. The specific steps are as follows:

[0101] S401: Based on the communication performance evaluation results, the particle swarm optimization algorithm is used to adjust the channel priority settings, reallocate channel resources, optimize the communication network efficiency, and record the performance data after the channel adjustment to generate a performance ranking set.

[0102] Based on the communication performance evaluation results, the channel priority settings are adjusted using the particle swarm optimization algorithm, according to the formula:

[0103] PG i =wP i-1 +c1r1(P best -P i-1 )+c2r2(G best -P i-1 )

[0104] Adjust the channel priority, where PG iP represents the priority of the current channel. i-1 P represents the previous channel priority. best G represents the channel's highest priority to date. best Represents the global optimal priority among all channels, w is the inertia weight, c1 and c2 are learning factors, and r1 and r2 are random numbers in the interval 0 and 1;

[0105] Based on the actual situation of channel priority, the priority P of a certain channel at a certain moment i-1 The highest historical priority P for this channel is 0.5. best The value is 0.7, while the globally optimal G across all channels is... best Given an inertia weight w of 0.8, learning factors c1 and c2 of 0.2, and random numbers r1 and r2 of 0.5, calculate the new priority P. i :

[0106] PG i = 0.8 × 0.5 + 0.2 × 0.5 × (0.7 - 0.5) + 0.2 × 0.3 × (0.9 - 0.5)

[0107] PG i =0.4 + 0.02 + 0.024 = 0.444

[0108] The results show that by dynamically adjusting channel priorities using the particle swarm optimization algorithm, channel resource allocation can be optimized according to changes in the communication environment, thereby improving the efficiency of the communication network.

[0109] S402: Based on the performance ranking set, continuously refine the transmission parameters of the channel, adjust the signal enhancement and interference suppression settings, re-evaluate the performance changes of parameter adjustments, verify the optimal configuration of each channel, and obtain the transmission optimization record;

[0110] Based on the performance ranking set, the transmission parameters of the channels are continuously refined, and signal enhancement and interference suppression settings are adjusted. In this process, the adjustment of transmission parameters is based on the results of refined performance analysis, including optimization of power regulation, frequency band selection, and modulation techniques. The refinement of parameters enables the communication system to more effectively adapt to different network environments and needs. After adjustment, the impact of the adjustment is evaluated by running performance tests again to ensure that the configuration of each channel reaches the optimal state. The method allows for continuous adaptation to new communication conditions, ensuring maximum signal transmission efficiency and minimum interference. The continuous optimization and verification of performance forms an iterative process. Through continuous testing and adjustment, the communication quality and network stability can be continuously improved.

[0111] S403: Based on the transmission optimization record, perform communication channel selection, test the network stability and data transmission efficiency under the new configuration, and verify whether the adjustment results achieve the expected effect, and obtain channel selection verification data;

[0112] Based on transmission optimization records, communication channel selection is performed to test network stability and data transmission efficiency under the new configuration. This process involves selecting the optimal channel suitable for the current network conditions. Channel selection is based on a series of performance evaluation metrics, such as data transmission speed, latency, and error rate. The purpose of testing the new configuration is to verify whether the adjusted channels meet the expected communication standards and user needs. The test results are used to further fine-tune the channel settings to ensure that each selected channel performs optimally in its operating environment, thereby maximizing the efficiency and reliability of the communication network. The channel selection verification data provides information about the performance of each channel, which helps to make more accurate channel configuration and resource allocation decisions.

[0113] Please see Figure 6 Based on channel selection verification data, astronomical telescope data is processed, encoded data packets are generated through linear combination, the transmission effect of the encoded data packets is tested in a network environment, and the encoding efficiency and error rate are analyzed to obtain the encoding performance analysis set. The specific steps are as follows:

[0114] S501: Based on channel selection verification data, use linear combination to merge data collected from multiple channels, optimize data integration efficiency and data error, and generate an encoded integration set;

[0115] Based on channel selection verification data, linear combination is used to merge data collected from multiple channels. Optimizing the efficiency and error of this data integration is crucial. First, the weights of each channel's data are determined, based on the historical performance and current state of each channel, to ensure reduced errors during data integration. Through a mathematical model of linear combination, the weighted data is merged into a unified dataset, taking into account the signal strength and interference levels of each channel to optimize overall data quality. The integrated dataset is then processed by an algorithm to identify and correct any errors or deviations, ensuring high quality and usability of the dataset. The generated coded integrated set provides a data foundation for subsequent network optimization and decision-making.

[0116] S502: Based on the encoding integration set, simulate the current network conditions, perform data packet transmission tests, record the rate and error occurrences during transmission, evaluate the encoding process, and obtain transmission effect analysis records;

[0117] Based on the encoded assembly set, perform packet transmission tests according to the formula:

[0118]

[0119] Calculate the transmission rate, where RS represents the data transmission rate, and TR... s TR represents the amount of data successfully transmitted. t TR represents the total transmission time. e This represents the time spent retransmitting due to errors; it's used to evaluate the actual transmission efficiency of a network. Considering errors and retransmissions that occur during data packet transmission, in a test, 1000MB of data was successfully transmitted in 10 seconds, with 2 seconds spent on retransmissions. The transmission rate is then calculated as follows:

[0120]

[0121] The result of 83.33 MB / s reflects the actual performance of the network under the current configuration, which helps to identify bottlenecks and optimize network configuration.

[0122] S503: Based on the transmission effect analysis record, adjust the data packet encoding parameters, perform the transmission test again, verify the effect of parameter adjustment, and verify the improvement effect of data packet transmission to obtain the encoding performance analysis set;

[0123] Based on the transmission performance analysis records, packet encoding parameters are adjusted. The packet transmission performance provided in the records is analyzed to identify parameters that need adjustment, such as coding rate and power. The adjustment aims to reduce the error rate and improve transmission efficiency. Then, a second round of transmission tests is conducted to verify the effect of the adjustment. The success rate and failure rate of each transmission, as well as any types of data errors that occur, are recorded in detail during the test. By comparing the test results before and after, the actual impact of the parameter adjustment can be quantified, thereby determining whether the expected improvement effect has been achieved. The coding performance analysis set summarizes the results to provide a basis for further network optimization.

[0124] Please see Figure 7 Based on the coding performance analysis set, lost data packets are analyzed and reconstructed. The quality and integrity of the reconstructed data packets are verified through communication tests, and the application effect of the reconstructed data is evaluated. The specific steps to obtain the data packet integrity verification results are as follows:

[0125] S601: Based on the coding performance analysis set, identify lost data packets during transmission, attempt to reconstruct the lost data packets, monitor reconstruction success and data packet integrity, and generate data recovery records;

[0126] Based on the coding performance analysis set, lost data packets during transmission are identified, and attempts are made to reconstruct the lost data packets according to the formula:

[0127]

[0128] Calculate the reconstruction power, where RV represents the reconstruction power, S recS represents the number of packets successfully reconstructed. tot This represents the total number of lost data packets. If 50 data packets are lost in a single communication and 45 are successfully reconstructed, then the reconstruction success rate is:

[0129]

[0130] This indicates that most data packets were successfully recovered through reconstruction measures, demonstrating the effectiveness of the reconstruction strategy. This formula allows for quantitative analysis of the performance of data recovery techniques, providing a basis for further improvements.

[0131] S602: Based on the data recovery record, perform quality testing on the reconstructed data packet, compare the consistency of the test results with the original data packet, evaluate the application effect of the data packet reconstruction, and obtain communication quality verification information;

[0132] Based on the data recovery records, quality tests are conducted on the reconstructed data packets. The core task in this process is to compare the test results with the original data packets. By simulating the network environment, the accuracy and consistency of the tests are ensured. A series of quality tests are performed on the reconstructed data packets, including data integrity verification and error rate analysis. The test results show that the consistency between the reconstructed data packets and the original data packets meets the predetermined standards. The application effect of data packet reconstruction is evaluated, ensuring the actual usability and reliability of the reconstruction technology. This evaluation provides empirical support for the maintenance and optimization of communication networks.

[0133] S603: Based on communication quality verification information, verify whether the reconstructed data packet meets the quality standards of the original data, and perform application tests on the data packet to obtain the data packet integrity verification result;

[0134] Based on communication quality verification information, it is verified whether the reconstructed data packets meet the quality standards of the original data, and application tests of the data packets are performed, including simulation tests of actual application scenarios, as well as detailed inspections of data packet transmission efficiency and integrity. Through testing, the performance stability of the data packets under various network conditions can be ensured. The data packet integrity verification results show that the reconstructed data packets meet or exceed the original standards in all performance indicators, verifying the effectiveness of data reconstruction and providing data support for its application in a wider range of communication systems.

[0135] Please see Figure 8 A wireless communication system for an astronomical telescope, the system comprising:

[0136] The signal optimization module assesses the signal strength of surrounding wireless channels based on the location of the astronomical telescope and the communication environment, analyzes the interference level of multiple channels, records the usage rate and signal quality of communication channels, filters the channels with the least interference, and generates channel optimization records.

[0137] The channel monitoring module monitors the signal quality and network load of the target channel in real time based on the channel optimization record, analyzes the communication data stream, and refines the channel configuration to obtain detailed channel configuration information.

[0138] The performance verification module performs simulation tests on the detailed channel configuration information to verify the communication performance of multiple channels. Channels that fail to meet the performance standards are re-evaluated, the channel selection list is revised, and the communication performance evaluation results are obtained.

[0139] The optimization module utilizes the communication performance evaluation results, employs the particle swarm optimization algorithm to sort and optimize the performance of multiple channels, updates the channel selection list, evaluates the adjusted real-time communication effect, and establishes channel selection verification data.

[0140] The data encoding module selects verification data based on the channel, generates encoded data packets through linear combination, tests the transmission effect under the network environment, analyzes the encoding efficiency and error rate, reconstructs lost data packets, tests the quality and integrity of the reconstructed data packets, and obtains the data packet integrity verification results.

[0141] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A wireless communication method in an astronomical telescope, characterized in that, Includes the following steps: Based on the location of the astronomical telescope and the communication environment, the signal strength and interference data of the wireless channel are collected in real time. The frequency scanning technology is used to continuously monitor each channel, capture real-time signal changes, and generate signal monitoring data. Based on the signal monitoring data, the channel usage rate and signal quality are analyzed, channels with low interference are screened, and the channel with the best signal is determined through comparative analysis to obtain a channel selection list. Based on the channel selection list, the data transmission efficiency and stability of the selected channels are recorded, the performance of the selected channels is evaluated, the optimal configuration of the selected channels is determined, and the channel optimization record is obtained. Based on the channel preference record, monitor the signal quality and network load of the target channel, collect communication signal quality data and load data, analyze the collected data trends, and generate load trend records; Based on the load trend records, the signal path and data routing are optimized according to the real-time parsed data stream, and the channel configuration is adjusted to match the current network conditions to obtain routing optimization information; Based on the routing optimization information, the parameter settings of multiple communication channels are adjusted to optimize communication efficiency, and the adjustment results are verified to determine the optimal communication state and obtain detailed channel configuration information. Based on the detailed channel configuration information, a simulation test environment is configured to simulate the communication performance of multiple channels under extreme conditions, and performance data of multiple channels, including signal delay and error rate, are collected to generate a performance test dataset. Based on the performance test dataset, the communication performance of multiple channels is compared with the standard, the deviation of each channel is quantitatively evaluated, the substandard channels are marked, and the performance indicators of the channels are compiled to obtain a list of channels to be optimized. Based on the channel list to be optimized, adjust the channel configuration settings, retest the adjusted channels, verify the adjustment effect, and determine whether the channels have reached or exceeded the performance baseline to obtain the communication performance evaluation results. Based on the communication performance evaluation results, the priority settings of the channels are adjusted using the particle swarm optimization algorithm, channel resources are reallocated, communication network efficiency is optimized, and the performance data after the channel adjustment is recorded to generate a performance ranking set. Based on the performance ranking set, the transmission parameters of the channels are continuously refined, the signal enhancement and interference suppression settings are adjusted, and the performance changes of the parameter adjustments are re-evaluated to verify the optimal configuration of each channel and obtain the transmission optimization record. Based on the transmission optimization record, communication channel selection is performed to test the network stability and data transmission efficiency under the new configuration, and to verify whether the adjustment results achieve the expected effect, thereby obtaining channel selection verification data. Based on the channel selection verification data, linear combination is used to merge the data collected from multiple channels, optimize the data integration efficiency and data error, and generate an encoded integration set; Based on the aforementioned encoding set, simulate the current network conditions, perform data packet transmission tests, record the transmission rate and error occurrences during the transmission process, evaluate the encoding process, and obtain a transmission effect analysis record. Based on the transmission effect analysis records, the data packet encoding parameters are adjusted, and the transmission test is performed again to verify the effect of the parameter adjustment and to verify the improvement effect of data packet transmission, thus obtaining the encoding performance analysis set. Based on the aforementioned coding performance analysis set, lost data packets during transmission are identified, lost data packets are reconstructed, and reconstruction success and data packet integrity are monitored to generate data recovery records. Based on the data recovery record, the reconstructed data packet is subjected to quality testing. The consistency between the test results and the original data packet is compared, and the application effect of the data packet reconstruction is evaluated to obtain communication quality verification information. Based on the communication quality verification information, the reconstructed data packet is verified to meet the quality standards of the original data, and application tests of the data packet are performed to obtain the data packet integrity verification result.

2. The wireless communication method in an astronomical telescope according to claim 1, characterized in that, The channel preference record includes signal reception rate, interference index, and selected channel. The detailed channel configuration information includes network load indicators, channel stability data, and transmission delay data. The communication performance evaluation results include performance benchmark tests, abnormal channel identification results, and preferred channel update results. The channel selection verification data includes an adjusted channel list and performance improvement details. The coding performance analysis set includes coding rate and error occurrence frequency. The data packet integrity verification results include reconstruction success rate and reconstruction efficiency evaluation results.

3. A wireless communication system in an astronomical telescope, characterized in that, The wireless communication method in an astronomical telescope according to any one of claims 1-2, wherein the system comprises: The signal optimization module, based on the location of the astronomical telescope and the communication environment, evaluates the signal strength of surrounding wireless channels, analyzes the interference level of multiple channels, records the usage rate and signal quality of communication channels, filters channels with low interference, and generates channel optimization records. The channel monitoring module, based on the channel optimization record, monitors the signal quality and network load of the target channel in real time, parses the communication data stream, refines the channel configuration, and obtains refined channel configuration information. The performance verification module performs simulation tests on the detailed channel configuration information to verify the communication performance of multiple channels, re-evaluates channels that fail to meet performance standards, corrects the channel selection list, and obtains the communication performance evaluation results. The optimization module is selected, and using the communication performance evaluation results, the particle swarm optimization algorithm is used to sort and optimize the performance of multiple channels, update the channel selection list, evaluate the real-time communication effect after adjustment, and establish channel selection verification data. The data encoding module selects verification data according to the channel, generates encoded data packets through linear combination, tests the transmission effect in the network environment, analyzes the encoding efficiency and error rate, reconstructs lost data packets, tests the quality and integrity of the reconstructed data packets, and obtains the data packet integrity verification results.

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