Wireless communication method and system in astronomical telescope

Abstract

The invention relates to the technical field of wireless communication, in particular to a wireless communication method and system in an astronomical telescope, and the method comprises the following steps: based on the position of the astronomical telescope and a communication environment, evaluating the signal strength and interference level of surrounding wireless channels, recording the channel utilization rate and signal quality, screening channels with low signal interference, and sending the screened channels to the astronomical telescope; and obtaining a channel optimization record. According to the invention, through refining real-time data flow analysis and channel configuration, communication interference caused by environment change is effectively reduced, performance of each channel is verified through simulation testing, and stable service of the selected channel under various conditions is ensured, so that communication reliability is improved, optimal configuration of channel performance is realized by applying a particle swarm algorithm, and the method is suitable for popularization and application. The communication channel management is more flexible and efficient, the communication data can be efficiently and safely transmitted in a severe observation environment, the use value and the observation timeliness of the data are improved, and the high-quality collection and processing of the astronomical data are ensured.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a wireless communication method and system in an astronomical telescope. Background Art

[0002] The field of wireless communication technology is the technology of using electromagnetic waves (such as radio frequency, microwaves, etc.) to transmit information between devices. This technology does not require physical connections, such as cables or lines, making communication more flexible and rapid. The application of wireless communication technology is very extensive, including mobile phones, wireless networks, satellite communications, radio broadcasting and television, and GPS. With the development of technology, wireless communication has been able to support high data rate transmission and realize functions such as high-definition video streaming, large-capacity data packets and real-time data transmission.

[0003] Among them, the wireless communication method in astronomical telescopes refers to the use of wireless technology in astronomical telescope systems to transmit observation data and control information. In astronomy, telescopes are usually deployed in remote or harsh geographical locations, such as mountains or deserts. These places have lower light pollution and better observation conditions, but also bring difficulties to data transmission. Traditional wired communication methods are subject to greater geographical and environmental restrictions, with high installation costs and complex maintenance. The use of 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 performance of astronomical observations.

[0004] Existing technologies are often severely affected by environmental factors in remote areas, such as signal interference and network load problems, which often lead to unstable data transmission. When dealing with high data rate transmission, especially the real-time transmission requirements of video streams and large-capacity data packets, traditional technologies fail to effectively adapt to channel congestion and rapidly changing environments, resulting in data loss or transmission errors, affecting the accuracy of observation data and the continuity of scientific research work, limiting the performance of astronomical telescopes under extreme observation conditions, and reducing the effectiveness of their scientific research and practical applications. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a wireless communication method and system in an astronomical telescope.

[0006] In order to achieve the above object, 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, evaluate the signal strength and interference level of the surrounding wireless channels, record the channel usage rate and signal quality, and select channels with low signal interference to obtain channel optimization records;

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

[0009] S3: Performing simulation test on the channel configuration refinement information to verify the communication performance of the selected channel, re-evaluating the channel that does not meet expectations, correcting the channel selection list, and obtaining a communication performance evaluation result;

[0010] S4: Based on the communication performance evaluation result, the channel selection logic is optimized using a 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;

[0011] S5: Based on the channel selection verification data, the astronomical telescope data is processed, a coded data packet is generated through linear combination, a transmission effect of the coded data packet is tested in a network environment, and the coding efficiency and error rate are analyzed to obtain a coding performance analysis set;

[0012] 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 result.

[0013] As a further solution of the present invention, the channel preference record includes signal reception rate, interference index, and selected channel; the channel configuration detail 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 an adjusted channel list and performance improvement details; the coding performance analysis set includes coding rate and error frequency; the data packet integrity verification results include reconstruction success and reconstruction efficiency evaluation results.

[0014] As a further solution of the present invention, based on the position of the astronomical telescope and the communication environment, the signal strength and interference level of the surrounding wireless channels are evaluated, the channel usage rate and signal quality are recorded, and channels with low signal interference are screened. The specific steps of obtaining the channel optimization record are:

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

[0016] S102: Analyze the usage rate and signal quality of the channels based on the signal monitoring data, select channels with low interference, and determine the channels with the best signals 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 channel, perform performance evaluation on the selected channel, determine the optimal configuration of the selected channel, and obtain a channel optimization record.

[0018] As a further solution of the present invention, based on the channel optimization record, the signal quality and network load of the target channel are continuously monitored, the data stream is analyzed in real time, the analysis results are recorded and the channel configuration is refined to optimize the data transmission efficiency. The steps of obtaining the channel configuration refinement information are specifically as follows:

[0019] S201: Based on the channel optimization 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 a load trend record;

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

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

[0022] As a further solution of the present invention, the steps of performing a simulation test on the channel configuration refinement information, verifying the communication performance of the selected channel, re-evaluating the channel that does not meet the expectations, correcting the channel selection list, and obtaining the communication performance evaluation result are specifically as follows:

[0023] S301: Based on the channel configuration refinement 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 data set;

[0024] S302: Based on the performance test data set, compare the communication performance of multiple channels with the standard, quantitatively evaluate the deviation of each channel, mark the channels that do not meet the standard, and organize the performance indicators of the channels to obtain a channel table to be optimized;

[0025] S303: Based on the channel list to be optimized, adjust the configuration settings of the channel, retest the adjusted channel, verify the adjustment effect, and determine whether the channel reaches or exceeds the performance baseline to obtain a communication performance evaluation result.

[0026] As a further solution of the present invention, based on the communication performance evaluation result, the channel selection logic is optimized using a 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. The steps of obtaining the channel selection verification data are specifically as follows:

[0027] S401: Based on the communication performance evaluation result, using a particle swarm optimization algorithm to adjust the priority setting of the channel, reallocate channel resources, optimize the efficiency of the communication network, and record the performance data of the adjusted channel to generate a performance ranking set;

[0028] S402: Based on the performance ranking set, continuously refine the transmission parameters of the channel, adjust the signal enhancement and interference suppression settings, and re-evaluate the performance changes of the parameter adjustment, verify the optimal configuration of each channel, and obtain a 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 result achieves the expected effect, and obtain channel selection verification data.

[0030] As a further solution of the present invention, the particle swarm optimization algorithm is used to adjust the priority setting of the channel 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 Represents the priority of the current channel, P i-1 Represents the previous channel priority, P best represents the best priority of the channel so far, G best represents the global optimal priority in the channel, w is the inertia weight, c1 and c2 are learning factors, and r1 and r2 are random numbers in the range of 0 and 1.

[0033] As a further solution of the present invention, based on the channel selection verification data, the astronomical telescope data is processed, a coded data packet is generated by linear combination, the transmission effect of the coded data packet is tested in a network environment, and the coding efficiency and error rate are analyzed to obtain the coding performance analysis set. Specifically, the steps are as follows:

[0034] S501: Based on the channel selection verification data, the data collected from multiple channels are merged using linear combination to optimize data integration efficiency and data error, and generate a coding integration set;

[0035] S502: Based on the encoding integration set, simulate the current network conditions, perform data packet transmission test, record the rate and error occurrence during the transmission process, and evaluate the encoding process to 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, check the parameter adjustment effect, and verify the improvement effect of the data packet transmission to obtain the encoding performance analysis set.

[0037] As a further solution of the present invention, 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 testing, and the application effect of the reconstructed data is evaluated. The steps of obtaining the data packet integrity verification result are specifically as follows:

[0038] S601: Based on the 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 a quality test on the reconstructed data packet, compare the consistency of the test result with the original data packet, and evaluate the application effect of the data packet reconstruction to 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 of the data packet to obtain a data packet integrity verification result.

[0041] A wireless communication system in an astronomical telescope, the wireless communication system in the astronomical telescope is used to execute the wireless communication method in the astronomical telescope, the system comprising:

[0042] The signal optimization module evaluates 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 communication channel usage rate and signal quality, selects channels with low interference, and generates channel optimization records;

[0043] 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, refines the channel configuration, and obtains the channel configuration refinement information;

[0044] The performance verification module performs a simulation test on the channel configuration refinement information, verifies the communication performance of multiple channels, re-evaluates the channels that do not meet the performance standards, corrects the channel selection list, and obtains the communication performance evaluation results;

[0045] The selection optimization module uses the communication performance evaluation results to sort and optimize the multi-channel performance using a particle swarm optimization algorithm, updates the channel selection list, and evaluates the adjusted real-time communication effect to establish channel selection verification data;

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

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

[0048] In the present invention, by refining the real-time data flow analysis and channel configuration, the communication interference caused by environmental changes is effectively reduced, the performance of each channel is verified by simulation test, and it is ensured that the selected channel can provide stable services under various conditions, thereby improving the reliability of communication. The particle swarm algorithm is applied to achieve the optimal configuration of channel performance, making the communication channel management more flexible and efficient, and enabling the communication data to be transmitted efficiently and safely in harsh observation environments, thereby improving the use value of the data and the timeliness of observation, and ensuring the high-quality collection and processing of astronomical data. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

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

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

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] Embodiment 1

[0060] See also Figure 1 The present 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, evaluate the signal strength and interference level of the surrounding wireless channels, record the channel usage rate and signal quality, and select the channel with the lowest signal interference to obtain the channel optimization record;

[0062] S2: Based on the channel optimization record, the signal quality and network load of the target channel are continuously monitored, the data stream is analyzed in real time, the analysis results are recorded and the channel configuration is refined to optimize the data transmission efficiency and obtain the channel configuration refinement information;

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

[0064] S4: Based on the communication performance evaluation results, the particle swarm optimization algorithm is used to optimize the channel selection logic, 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 the channel selection verification data;

[0065] S5: Based on the channel selection verification data, the astronomical telescope data is processed, and a coded data packet is generated through linear combination. The transmission effect of the coded data packet is tested in the network environment, and the coding efficiency and error rate are analyzed to obtain a coding 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] Channel optimization records include signal reception rate, interference index, and selected channels. Channel configuration details include 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. The coding performance analysis set includes coding rate and error frequency. Data packet integrity verification results include reconstruction success and reconstruction efficiency evaluation results.

[0068] See also Figure 2 Based on the location of the astronomical telescope and the communication environment, the signal strength and interference level of the surrounding wireless channels are evaluated, the channel usage rate and signal quality are recorded, and the channels with the lowest signal interference are selected. The specific steps for obtaining the channel optimization record are as follows:

[0069] S101: Based on the location of the astronomical telescope and the communication environment, it collects the signal strength and interference data of the wireless channel 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 the astronomical telescope needs to be updated in real time through global positioning GPS to ensure the accuracy of the data. The monitoring of the communication environment involves the strength and quality of the signal, and multiple frequency detections are required. The intensity changes and interference levels of each signal in the channel are recorded in real time through scanning technology. For each channel, a time series data is generated to record any slight changes in the signal, and the data is subjected to noise filtering and signal enhancement processing to ensure the purity and availability of the data. Through this continuous monitoring and real-time recording, the signal changes within the channel can be captured and signal monitoring data can be generated.

[0071] S102: Analyze the usage rate and signal quality of the channels based on the signal monitoring data, select the channels with the lowest interference, and determine the channels with the best signals through comparative analysis to obtain a channel selection list;

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

[0073]

[0074] Calculate the channel with the lowest interference, where I d represents the interference degree, γ irepresents the interference value of the ith channel, and N represents 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 each channel γ i For example, the interference value of channel 1 is 30, the interference value of channel 2 is 40, and the interference value of 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, γ3

[0075] =20, then the total interference I of channel 3 d =20 is the lowest, this process ensures that the selected channel has the best signal quality, because lower interference generally means better signal quality.

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

[0077] Based on the channel selection list, record the data transmission efficiency and stability of the selected channels, including the evaluation of the channels. The data transmission efficiency of each selected channel is obtained through actual transmission tests, including multiple transmissions of the same data packet in different time periods to evaluate the average success rate and transmission speed of the data on the channel. At the same time, the stability evaluation involves testing the channel under different environmental conditions, such as testing under different weather conditions and different network loads, to ensure that the channel can maintain good performance under various conditions. In addition, the performance evaluation of the selected channel also needs to take into account the response time and error rate of the channel under high load conditions. Through comprehensive performance evaluation, the optimal configuration of the selected channel is determined.

[0078] See also Figure 3 , based on the channel optimization record, continuously monitor the signal quality and network load of the target channel, perform real-time analysis on the data stream, record the analysis results and refine the channel configuration, optimize the data transmission efficiency, and obtain the detailed information of the channel configuration in the following steps:

[0079] S201: Based on the channel optimization 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;

[0080] Based on the channel optimization record, the signal quality and network load of the target channel are monitored, and the communication signal quality and load data are collected. It is necessary to set the signal quality threshold and the monitoring parameters of the network load to ensure that the actual needs of the current network environment are reflected. The signal strength and network load data are captured in real time. The data is obtained through signal quality sensors and analysis of network traffic. The collected data will be recorded according to timestamps for trend analysis. By performing regression analysis and trend prediction on data in continuous time, load trend records can be generated. The records provide decision support for network management. The generated trend records provide a dynamic view, showing the evolution of network conditions and pressure points.

[0081] S202: Based on the load trend record, the signal path and data routing are optimized according to the real-time parsing data stream, and the channel configuration is adjusted to match the current network status to obtain routing optimization information;

[0082] Based on the load trend record, the signal path and data routing are optimized according to the formula:

[0083]

[0084] Calculate the routing optimization information, where P opt represents the optimized path efficiency, x i represents the selection variable of the i-th routing point (0 or 1, indicating whether this routing point is selected), d i represents the data transmission efficiency of the i-th routing point, N q 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, apply the formula, and we get:

[0085] P opt =1×0.5+0×0.8+1×0.6=1.1

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

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

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

[0089] See also Figure 4 , simulate the channel configuration details, verify the communication performance of the selected channel, re-evaluate the channels that do not meet expectations, and correct the channel selection list. The specific steps to obtain the communication performance evaluation results are as follows:

[0090] S301: Based on the detailed information of the channel configuration, 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, is collected to generate a performance test data set;

[0091] Based on the detailed information of channel configuration, a simulation 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, interference source type and strength, to ensure that the test environment can simulate the most extreme conditions encountered. Performance data collection includes monitoring of signal delay and error rate. Monitoring indicators are automatically recorded through data collection, and the accuracy and consistency of the data are ensured. Through simulation and data collection, a comprehensive data set reflecting the actual communication performance can be generated. This data set includes the performance of each channel under different test conditions, providing a basis for further analysis and optimization.

[0092] S302: Based on the performance test data set, compare the communication performance of multiple channels with the standard, quantitatively evaluate the deviation of each channel, mark the channels that do not meet the standard, and organize the performance indicators of the channels to obtain a channel table to be optimized;

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

[0094]

[0095] Calculate the deviation of each channel, where D i represents the performance deviation percentage of the i-th channel, O i represents the observed channel performance, S iRepresents 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 is used to calculate:

[0096]

[0097] It means that the performance of the channel is 5% below the standard. Through this method, you can quickly identify channels whose performance does not meet the expected standards and then perform targeted optimization.

[0098] S303: Based on the channel list to be optimized, adjust the configuration settings of the channel, retest the adjusted channel, verify the adjustment effect, and determine whether the channel reaches or exceeds the performance baseline to obtain a communication performance evaluation result;

[0099] Based on the channel table to be optimized, adjust the configuration settings of the channel and retest the adjusted channel. First, select the adjustment parameters based on the performance deviation data. The parameters include transmission power, bandwidth adjustment or coding strategy. Each adjustment is based on the specific deficiencies and optimization goals of the channel. Then, test the effect of the adjustment by implementing a series of control experiments, including comparative analysis of the channel performance before and after the adjustment under the same test conditions. Through this comparison, the actual impact of each adjustment on the performance can be verified. If the performance of the channel 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] See also Figure 5 Based on the communication performance evaluation results, the particle swarm optimization algorithm is used to optimize the channel selection logic, 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. The specific steps to obtain the channel selection verification data are as follows:

[0101] S401: Based on the communication performance evaluation results, the particle swarm optimization algorithm is used to adjust the priority setting of the channel, 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 particle swarm optimization algorithm is used to adjust the channel priority setting 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 iRepresents the priority of the current channel, P i-1 Represents the previous channel priority, P best Represents the best priority of the channel so far, G best represents the global optimal priority among all channels, w is the inertia weight, c1 and c2 are learning factors, r1 and r2 are random numbers in the interval of 0 and 1;

[0105] According to the actual situation of channel priority, the priority P of a channel at a certain moment i-1 is 0.5, the historical optimal priority P of the channel best is 0.7, and the global optimal G in all channels best is 0.9, the inertia weight w is 0.8, the learning factor c1 is 0.2, c2 is 0.2, the random number r1 is 0.5, r2 is 0.3, 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 through the particle swarm algorithm, channel resource allocation can be optimized according to changes in the communication environment and the efficiency of the communication network can be improved.

[0109] S402: Based on the performance ranking set, continuously refine the transmission parameters of the channel, adjust the signal enhancement and interference suppression settings, and re-evaluate the performance changes of the parameter adjustment, 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 channel are continuously refined, and the signal enhancement and interference suppression settings are adjusted. In this process, the adjustment of the transmission parameters is based on the refined performance analysis results, including the optimization of power regulation, frequency band selection and modulation technology. The refinement of the parameters enables the communication system to adapt to different network environments and needs more effectively. After the adjustment, the impact of the adjustment is evaluated by running the performance test again to ensure that the configuration of each channel is optimal. The method allows continuous adaptation to new communication conditions, ensuring maximum transmission efficiency of the signal and minimizing 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 result achieves the expected effect, and obtain channel selection verification data;

[0112] Based on the 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 indicators, such as data transmission speed, latency and error rate. The purpose of testing the new configuration is to verify whether the adjusted channel meets 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 can perform best 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, and the information helps make more accurate channel configuration and resource allocation decisions.

[0113] See also Figure 6 , based on the channel selection verification data, the astronomical telescope data is processed, the coded data packet is generated by linear combination, the transmission effect of the coded data packet is tested in the network environment, and the coding efficiency and error rate are analyzed. The specific steps of obtaining the coding performance analysis set are:

[0114] S501: Based on the channel selection verification data, the data collected from multiple channels are merged using linear combination to optimize the data integration efficiency and data error, and generate a coded integration set;

[0115] Based on the channel selection verification data, linear combination is used to merge the data collected from multiple channels. The key is the optimization of data integration efficiency and errors. First, the weight of each channel data is determined. The weight is based on the historical performance and current status of each channel to ensure that errors are reduced during data integration. The weighted data is merged into a unified data set through the mathematical model of linear combination. The signal strength and interference level of each channel are taken into account to optimize the overall data quality. The integrated data set is processed by an algorithm to identify and correct any errors or deviations to ensure the high quality and availability of the data set. The generated coded integration set provides a data basis for subsequent network optimization and decision-making.

[0116] S502: Based on the coding integration set, simulate the current network conditions, perform data packet transmission test, record the rate and error occurrence during the transmission process, and evaluate the coding process to obtain a transmission effect analysis record;

[0117] Based on the encoding integration set, perform packet transmission test according to the formula:

[0118]

[0119] Calculate the transmission rate, where RS represents the data transmission rate and TR s Represents the amount of data successfully transmitted, TR t Represents the total transmission time, TR e Represents the time for retransmission due to errors; used to evaluate the actual transmission efficiency of the network. Taking into account the errors and retransmissions that occur during the transmission of data packets, in a test, 1000MB of data was successfully transmitted, the total transmission time was 10 seconds, and the retransmission consumed 2 seconds. The transmission rate is calculated as:

[0120]

[0121] The result 83.33MB / 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, check the parameter adjustment effect, and verify the improvement effect of the data packet transmission, and obtain the encoding performance analysis set;

[0123] Based on the transmission effect analysis records, the packet coding parameters are adjusted, the packet transmission performance provided in the records is analyzed, and those parameters that need to be adjusted, such as coding rate, power, etc., are identified. The adjustment parameters are aimed at reducing the error rate and improving transmission efficiency. Afterwards, a second round of transmission tests is implemented to verify the effect of the adjustments. The success rate and failure rate of each transmission, as well as any type of data errors that occur, are recorded in detail in the test. By comparing the test results before and after, the actual impact of the parameter adjustment can be quantified, so as to determine 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] See also Figure 7 , 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. The specific steps to obtain the data packet integrity verification results are as follows:

[0125] S601: Based on the coding performance analysis set, identify the lost data packets in the transmission process, try to reconstruct the lost data packets, monitor the reconstruction success rate and data packet integrity, and generate a data recovery record;

[0126] Based on the coding performance analysis set, identify the lost packets during transmission and try to reconstruct the lost packets according to the formula:

[0127]

[0128] Calculate the reconstruction success rate, where RV represents the reconstruction success rate, S recRepresents the number of successfully reconstructed packets, S tot Represents the total number of lost packets; in one communication, 50 packets were lost and 45 were successfully reconstructed. The reconstruction success rate is:

[0129]

[0130] This shows that most of the data packets are successfully recovered through reconstruction measures, which shows the effectiveness of the reconstruction strategy. Through this formula, the performance of data recovery technology can be quantitatively analyzed, providing a basis for further improving the technology.

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

[0132] Based on the data recovery records, the reconstructed data packets are quality tested. During this process, comparing the test results with the original data packets for consistency is the core task. By simulating the network environment to ensure the accuracy and consistency of the test, 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 to ensure the actual availability and reliability of the reconstruction technology. This evaluation provides empirical support for the maintenance and optimization of communication networks.

[0133] 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 of the data packet to obtain a data packet integrity verification result;

[0134] Based on the communication quality verification information, it is verified whether the reconstructed data packet meets the quality standards of the original data, and application testing of the data packet is performed, including simulation testing of actual application scenarios and detailed inspection of data packet transmission efficiency and integrity. Through testing, the performance stability of the data packet under various network conditions can be ensured. The obtained data packet integrity verification results show that the reconstructed data packet meets or exceeds the original standards in various performance indicators, which verifies the effectiveness of data reconstruction and provides data support for its application in a wider range of communication systems.

[0135] See also Figure 8 , a wireless communication system in an astronomical telescope, the system comprising:

[0136] The signal optimization module evaluates 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 communication channel usage rate and signal quality, selects the channel with the lowest 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, refines the channel configuration, and obtains the channel configuration refinement information;

[0138] The performance verification module simulates and tests the detailed information of channel configuration, verifies the communication performance of multiple channels, re-evaluates the channels that do not meet the performance standards, corrects the channel selection list, and obtains the communication performance evaluation results;

[0139] The selection optimization module uses the communication performance evaluation results to sort and optimize the multi-channel performance using the particle swarm optimization algorithm, updates the channel selection list, and evaluates the real-time communication effect after adjustment to establish channel selection verification data;

[0140] The data coding module selects verification data according to the channel, generates coded data packets through linear combination, tests the transmission effect under the network environment, analyzes the coding efficiency and error rate, reconstructs the 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 only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A wireless communication method in an astronomical telescope, characterized in that: The following steps are involved: Based on the location of the astronomical telescope and the communication environment, the signal strength and interference level of the surrounding wireless channels are evaluated, the channel usage rate and signal quality are recorded, and channels with low signal interference are screened to obtain channel optimization records; Based on the channel optimization record, the signal quality and network load of the target channel are continuously monitored, the data stream is analyzed in real time, the analysis results are recorded and the channel configuration is refined, the data transmission efficiency is optimized, and the channel configuration refinement information is obtained; Performing simulation tests on the channel configuration refinement information to verify the communication performance of the selected channels, re-evaluating the channels that do not meet expectations, correcting the channel selection list, and obtaining communication performance evaluation results; Based on the communication performance evaluation results, the channel selection logic is optimized using a 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; Based on the channel selection verification data, the astronomical telescope data is processed, a coded data packet is generated through linear combination, the transmission effect of the coded data packet is tested in a network environment, and the coding efficiency and error rate are analyzed to obtain a coding performance analysis set; 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 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 channel configuration detail 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 adjusted channel list and performance improvement details; the coding performance analysis set includes coding rate and error frequency; the data packet integrity verification results include reconstruction success and reconstruction efficiency evaluation results.

3. A wireless communication system in an astronomical telescope, characterized in that: According to the wireless communication method in an astronomical telescope according to any one of claims 1-2, the system comprises: The signal optimization module evaluates 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 communication channel usage rate and signal quality, selects channels with low interference, and generates channel optimization records; 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, refines the channel configuration, and obtains the channel configuration refinement information; The performance verification module performs a simulation test on the channel configuration refinement information, verifies the communication performance of multiple channels, re-evaluates the channels that do not meet the performance standards, corrects the channel selection list, and obtains the communication performance evaluation results; The selection optimization module uses the communication performance evaluation results to sort and optimize the multi-channel performance using a particle swarm optimization algorithm, updates the channel selection list, and evaluates the adjusted real-time communication effect to establish channel selection verification data; The data coding module selects verification data according to the channel, generates coded data packets through linear combination, tests the transmission effect under the network environment, analyzes the coding efficiency and error rate, reconstructs the lost data packets, tests the quality and integrity of the reconstructed data packets, and obtains the data packet integrity verification result.

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