A compression method for data transmission based on shipborne satellite communication

Abstract

The invention relates to the field of shipborne satellite communication, and in particular to a compression method for data transmission based on shipborne satellite communication; the compression method provided by the invention comprises the following steps: respectively obtaining channel characteristics of a first communication channel and a second communication channel at a sampling moment; setting a communication data compression ratio according to the channel characteristics at a sampling moment, compressing the first communication data based on the communication data compression ratio, and restoring the compressed first communication data; adjusting the communication data compression ratio of a first shipborne communication node in combination with the restored first communication data and the channel characteristics at the next sampling moment, and compressing the second communication data transmitted by the first shipborne communication node based on the adjusted communication data compression ratio; the invention dynamically adjusts the data compression ratio by using the communication channel characteristics, solves the problems of limited bandwidth and low data transmission efficiency in shipborne satellite communication, and can meet the requirements of ships for data transmission efficiency and stability in maritime communication.

Description

Technical Field

[0001] The invention relates to the field of shipborne satellite communications, and in particular to a compression method based on shipborne satellite communications data transmission. Background Art

[0002] In the field of modern navigation, shipborne satellite communications, with its long-distance and high-coverage characteristics, have become a key means of achieving communications between ships and ground communication terminals and other ships.

[0003] Due to the limitation of satellite orbit and the attenuation of signal transmission, the bandwidth resources that can be allocated to each ship are very limited. At the same time, with the development of navigation technology, the data types involved in shipborne satellite communications are becoming more and more diverse, and the requirements for data transmission rate and stability are becoming higher and higher. Traditional data transmission and compression methods can no longer meet the needs.

[0004] Therefore, there is an urgent need for an efficient compression method based on shipborne satellite communication data transmission to achieve efficient data compression and transmission, thereby improving bandwidth utilization, reducing communication costs, and meeting the growing data transmission needs in the navigation field. Summary of the invention

[0005] In view of the deficiencies of the prior art and the needs of practical applications, the present invention provides a compression method for data transmission based on shipborne satellite network communication, aiming to meet the growing data transmission needs in the navigation field.

[0006] The compression method for data transmission based on shipborne satellite network communication provided by the present invention comprises the following steps: respectively obtaining channel characteristics of a first communication channel and a second communication channel at a sampling time, wherein the first communication channel is a data transmission channel between a first shipborne communication node and a satellite communication node, and the second communication channel is a data transmission channel between the satellite communication node and a second shipborne communication node; setting a communication data compression ratio of the first shipborne communication node according to the channel characteristics of the first communication channel and the second communication channel at the sampling time, and compressing the first communication data transmitted by the first shipborne communication node based on the communication data compression ratio, and restoring the compressed first communication data on the second shipborne communication node; respectively obtaining the channel characteristics of the first communication channel and the second communication channel at the next sampling time, and adjusting the communication data compression ratio of the first shipborne communication node in combination with the restored first communication data and the channel characteristics at the next sampling time, and compressing the second communication data transmitted by the first shipborne communication node based on the adjusted communication data compression ratio. The compression method for data transmission based on shipborne satellite network communication provided by the present invention has the following advantages: first, the present invention sets the corresponding communication data compression ratio according to the channel characteristics at a sampling moment to ensure the data transmission efficiency of the first communication data; second, the communication data compression ratio is adjusted according to the channel characteristics at the next sampling moment and the quality of the restored first communication data to adapt to the change of the communication channel, thereby ensuring the data transmission efficiency of the second communication data. In summary, the present invention dynamically adjusts the data compression ratio according to the characteristics of the communication channel, which can effectively solve the problems of limited bandwidth and low data transmission efficiency in shipborne satellite communications, and can meet the growing data transmission needs in the field of navigation.

[0007] Optionally, the communication data compression ratio of the first shipborne communication node is set according to the channel characteristics of the first communication channel and the second communication channel at the sampling moment, comprising the following steps: obtaining the channel capacities of the first communication channel and the second communication channel respectively according to the channel characteristics of the first communication channel and the second communication channel at a sampling moment; setting a data transmission volume threshold based on the minimum channel capacity of the channel capacities of the first communication channel and the second communication channel, and setting the communication data compression ratio of the first shipborne communication node by using the data transmission volume threshold. The present invention sets the communication data compression ratio according to the actual capacity of the communication channel, and uses the compressed first communication data to transmit in the communication channel, which not only ensures the stability and reliability of data transmission, but also ensures the utilization rate of bandwidth resources.

[0008] Optionally, the communication data compression ratio of the first shipborne communication node satisfies the following setting model: , , ,in, represents the communication data compression ratio corresponding to sampling time t, represents the communication data volume of the first communication data before compression corresponding to the sampling time t, represents the data transmission volume threshold corresponding to sampling time t, represents the data transmission volume threshold adjustment coefficient corresponding to sampling time t, represents the minimum channel capacity corresponding to sampling time t, represents the channel bandwidth of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t, The channel signal-to-noise ratio of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t is indicated. The present invention sets the communication data compression ratio according to the actual situation of the communication channel, so that the data transmission volume is always controlled within an acceptable threshold range, which not only ensures the stability and reliability of data transmission, but also ensures the utilization rate of bandwidth resources.

[0009] Further optionally, when the satellite communication node corresponds to a second communication channel, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the second communication channel, Indicates the channel capacity of the first communication channel Channel capacity with the second communication channel The present invention takes into account the actual capacity of the first communication channel and the second communication channel at the same time, and sets an appropriate communication data compression ratio according to the actual capacity of the first communication channel and the second communication channel, thereby ensuring that the compressed first communication data can be applied to different communication channels.

[0010] Further optionally, when the satellite communication node corresponds to multiple second communication channels, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the first second communication channel corresponding to the first communication channel, represents the channel capacity of the second second communication channel corresponding to the first communication channel, Indicates the first communication channel corresponding to the The channel capacity of the second communication channel, Indicates the total number of second communication channels corresponding to the first communication channel, Indicates the channel capacity of the first communication channel , the channel capacity of the first second communication channel, the channel capacity of the second second communication channel, and the The present invention takes into account the actual capacity of the first communication channel and the plurality of second communication channels at the same time, and sets an appropriate communication data compression ratio according to the actual capacity of the first communication channel and the plurality of second communication channels, thereby ensuring that the compressed first communication data can be applied to different communication channels.

[0011] Optionally, compressing the first communication data transmitted by the first shipborne communication node based on the communication data compression ratio, where the first communication data is image data, comprises the following steps: converting the first communication data into a first data matrix, where the element value of the i-th row and j-th column in the first data matrix is ​​the grayscale value of the i-th row and j-th column in the first communication data; obtaining the grayscale mean and grayscale standard deviation in the first communication data, and using the grayscale mean and the grayscale standard deviation to standardize the first data matrix to obtain a second data matrix, where the element value of the i-th row and j-th column in the second data matrix is ​​the quotient of the difference between the element value of the i-th row and j-th column in the first data matrix and the grayscale mean and the grayscale standard deviation; constructing a correlation coefficient matrix using the second data matrix, and obtaining the eigenvalues ​​and eigenvectors of the correlation coefficient matrix, where the correlation coefficient matrix satisfies the following construction model: , where C represents the correlation coefficient matrix, represents the number of rows of the first data matrix, represents the second data matrix, represents the transpose of the second data matrix; based on the communication data compression ratio, the number of feature vectors retained is set, and the number of feature vectors retained satisfies the following setting model: ,in, represents the number of feature vectors retained, represents the number of rows of the first data matrix, Indicates the communication data compression ratio, Express Rounding; arranging the corresponding eigenvectors in descending order according to the size of the eigenvalue, and reserving the eigenvectors starting from the eigenvector corresponding to the maximum eigenvalue according to the number of eigenvectors to be retained, until the number of retained eigenvectors is consistent with the number of retained eigenvectors; constructing an eigenvector matrix using the retained eigenvectors, and obtaining compressed first communication data using the eigenvector matrix and the second data matrix, wherein the compressed first communication data is the product of the transpose of the eigenvector matrix and the second data matrix. The present invention effectively utilizes the characteristics of image data, and realizes efficient compression of communication data through compression of eigenvectors.

[0012] Optionally, restoring the compressed first communication data on the second shipborne communication node comprises the following steps: restoring the second data matrix according to the compressed first communication data and the eigenvector matrix obtained on the second shipborne communication node; restoring the first data matrix based on the restored second data matrix according to the grayscale mean and grayscale standard deviation obtained on the second shipborne communication node; and reconstructing the first communication data using the restored first data matrix. The present invention effectively restores the compressed data through inverse operations, ensuring the integrity and accuracy of the communication data during the entire transmission process.

[0013] Optionally, the value of the jth element in the i-th row of the restored first data matrix satisfies the following calculation formula: ,in, represents the element value of the i-th row and j-th column in the restored first data matrix, represents the grayscale standard deviation obtained on the second shipborne communication node, Indicates that the second shipborne communication node obtains the compressed first communication data, represents the transpose of the eigenvector matrix obtained on the second shipborne communication node, The invention can effectively restore the first communication data matrix, thereby ensuring the integrity and accuracy of the communication data in the whole transmission process.

[0014] Optionally, the adjusting the communication data compression ratio of the first shipborne communication node in combination with the restored first communication data and the channel characteristics at the next sampling moment comprises the following steps: evaluating the data quality of the reconstructed first communication data; adjusting the data transmission volume threshold adjustment coefficient according to the data quality of the restored first communication data; obtaining the minimum channel capacity corresponding to the next sampling moment according to the channel characteristics at the next sampling moment; adjusting the data transmission volume threshold based on the minimum channel capacity corresponding to the next sampling moment; and obtaining the adjusted communication data compression ratio in combination with the communication data volume of the second communication data, the adjusted data transmission volume threshold and the adjusted data transmission volume threshold. The present invention can realize the intelligent adjustment of the communication data compression ratio in a dynamic shipborne satellite network environment, which is conducive to the stability and efficiency of data transmission.

[0015] Optionally, adjusting the data transmission volume threshold adjustment coefficient according to the data quality of the first communication data comprises the following steps: when the data quality of the restored first communication data does not meet the expected quality, increasing the data transmission volume threshold adjustment coefficient; when the data quality of the restored first communication data meets the expected quality, maintaining or reducing the data transmission volume threshold adjustment coefficient. The present invention intelligently adjusts the data transmission volume threshold adjustment coefficient according to the data quality of the restored first communication data to optimize the communication quality and data transmission efficiency. The adaptive adjustment strategy provided by the present invention allows the communication data compression ratio to be flexibly optimized under different network conditions to meet real-time communication needs and network performance requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a method for compressing data based on a shipborne satellite network provided by the present invention;

[0017] Figure 2 A schematic diagram of connecting communication nodes in a shipborne satellite network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0019] In one embodiment, see Figure 1 , Figure 1 The flowchart of the method for compressing data based on a shipborne satellite network provided by an embodiment of the present invention is as follows. Figure 1 As shown, the compression method based on shipborne satellite network data includes the following steps:

[0020] S01. Acquire channel characteristics of a first communication channel and a second communication channel at a sampling time respectively, wherein the first communication channel is a data transmission channel between a first shipborne communication node and a satellite communication node, and the second communication channel is a data transmission channel between the satellite communication node and a second shipborne communication node.

[0021] See also Figure 2 , Figure 2 The following is a schematic diagram of the connection of communication nodes in a shipborne satellite network provided by an embodiment of the present invention. Figure 2 As shown, the communication data is transmitted between the first shipborne communication node 11 and the second shipborne communication node 13 with the satellite communication node 12 as a relay station.

[0022] Furthermore, if Figure 2 As shown in the figure (1), in the shipborne satellite network, based on the first communication channel between the first shipborne communication node 11 and the satellite communication node 12, a second communication channel can correspond.

[0023] Furthermore, if Figure 2 (2) As shown in the figure, in the shipborne satellite network, based on the first communication channel between the first shipborne communication node 11 and the satellite communication node 12, multiple second communication channels may also correspond.

[0024] In this embodiment, the first communication channel between the first shipborne communication node 11 and the satellite communication node 12 is not the same communication channel as the second communication channel between the second shipborne communication node 13 and the satellite communication node 12; therefore, the channel characteristics of the first communication channel differ from the channel characteristics of one or more second communication channels.

[0025] Furthermore, the channel characteristics of a communication channel can be characterized by a variety of parameters, such as bandwidth, signal-to-noise ratio, delay, packet loss rate, etc.

[0026] In this embodiment, the channel characteristics of the first communication channel and the one or more second communication channels are characterized by channel bandwidth and channel signal-to-noise ratio.

[0027] The channel bandwidth refers to the maximum frequency range or data rate that a communication channel can transmit data, which characterizes the data transmission capacity of the corresponding communication channel, and is usually measured in bits per second (bit / s) or Hertz (Hz). In this embodiment, the channel bandwidth of the first communication channel or the second communication channel can be obtained by the following steps:

[0028] S0111. Send a test data packet with a known data volume on a first communication channel or a second communication channel, and obtain a transmission time of the test data packet on the corresponding communication channel.

[0029] S0112. Divide the data volume of the test data packet by the transmission time to obtain the channel bandwidth of the corresponding communication channel.

[0030] In one or some other embodiments, the channel bandwidth of the first communication channel or the second communication channel may also be obtained by other existing bandwidth detection methods, such as spectrum analysis methods, network performance testing tools, etc.

[0031] The channel signal-to-noise ratio refers to the ratio of the transmitted signal to the noise power in the channel, which is used to measure the communication quality of the channel. In this embodiment, the channel signal-to-noise ratio of the first communication channel or the second communication channel can be obtained by the following steps:

[0032] S0121. Obtain signal power and noise power in the first communication channel or the second communication channel respectively.

[0033] S0122. Utilize a signal-to-noise ratio calculation model to combine signal power and noise power to obtain a channel signal-to-noise ratio of a corresponding communication channel.

[0034] Furthermore, the signal-to-noise ratio calculation model satisfies the following calculation formula: ,in, represents the channel signal-to-noise ratio, represents the signal power in the communication channel, Represents the noise power in the communication channel.

[0035] S02. According to the channel characteristics of the first communication channel and the second communication channel at the sampling time, a communication data compression ratio of the first shipborne communication node is set, and based on the communication data compression ratio, the first communication data transmitted by the first shipborne communication node is compressed, and the compressed first communication data is restored on the second shipborne communication node.

[0036] In this embodiment, the communication data compression ratio represents the ratio of the communication data volume before compression to the communication data volume after compression.

[0037] Specifically, the communication data compression ratio satisfies the following calculation formula: ,in, Indicates the communication data compression ratio, Indicates the amount of communication data before compression, Indicates the amount of compressed communication data; further, to ensure the quality of data reconstructed by the receiving end, the initial setting and subsequent adjustment of the communication data compression ratio are not less than 0.5. In one or more other embodiments, the minimum threshold of the communication data compression ratio can also be set according to actual conditions.

[0038] It is understandable that in a channel with a specific channel bandwidth and channel signal-to-noise ratio, the greater the communication data compression ratio, the smaller the amount of compressed communication data. Furthermore, during the communication channel transmission process, when the channel signal-to-noise ratio is determined, the higher the channel bandwidth, the greater the communication data compression ratio, and the higher the data transmission rate; when the channel bandwidth is determined, the higher the channel signal-to-noise ratio, the greater the communication data compression ratio, and the better the data transmission quality.

[0039] In this embodiment, the step S02 of setting the communication data compression ratio of the first shipborne communication node according to the channel characteristics of the first communication channel and the second communication channel at the sampling time includes the following steps:

[0040] S0211. Obtain channel capacities of the first communication channel and the second communication channel respectively according to channel characteristics of the first communication channel and the second communication channel at a sampling time.

[0041] Furthermore, the communication capacity in the communication channel satisfies the following calculation formula: ,in, Indicates communication capacity, represents the channel bandwidth, Represents the channel signal-to-noise ratio.

[0042] S0212. Based on the minimum channel capacity of the first communication channel and the second communication channel, a data transmission volume threshold is set, and by using the data transmission volume threshold, a communication data compression ratio of the first shipborne communication node is set.

[0043] Further, when the satellite communication node corresponds to a second communication channel, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the second communication channel, Indicates the channel capacity of the first communication channel Channel capacity with the second communication channel The minimum value in .

[0044] Furthermore, when the satellite communication node corresponds to multiple second communication channels, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the first second communication channel corresponding to the first communication channel, represents the channel capacity of the second second communication channel corresponding to the first communication channel, Indicates the first communication channel corresponding to the The channel capacity of the second communication channel, Indicates the total number of second communication channels corresponding to the first communication channel, Indicates the channel capacity of the first communication channel , the channel capacity of the first second communication channel, the channel capacity of the second second communication channel, …, and the channel capacity of the The minimum value of the channel capacity of the second communication channels.

[0045] It can be understood that the data transmission volume threshold is a limit value of the communication quantity, which is used to control the amount of communication data transmitted per unit time on the communication channel to ensure data transmission efficiency. In this embodiment, the data transmission volume threshold satisfies the following setting model: ,in, Indicates the data transfer volume threshold. Indicates the data transmission volume threshold adjustment coefficient, The value range of is usually 0.5 to 1.2. represents the minimum channel capacity. Furthermore, The value of can be determined according to the amount of communication data before compression.

[0046] Specifically, when the ratio of the communication data volume before compression to the minimum channel capacity is less than or equal to 1, the value range of the data transmission volume threshold adjustment coefficient is [0.7, 1]; when the ratio of the communication data volume before compression to the minimum channel capacity is greater than 1, the value range of the data transmission volume threshold adjustment coefficient is (1, 2].

[0047] In this embodiment, the communication data compression ratio of the first shipborne communication node satisfies the following setting model: , , ,in, represents the communication data compression ratio corresponding to sampling time t, represents the communication data volume of the first communication data before compression corresponding to the sampling time t, represents the data transmission volume threshold corresponding to sampling time t, , represents the data transmission volume threshold adjustment coefficient corresponding to sampling time t, represents the minimum channel capacity corresponding to sampling time t, represents the channel bandwidth of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t, Represents the channel signal-to-noise ratio of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t.

[0048] In this embodiment, the first communication data is image data. Further, the step S02 of compressing the first communication data transmitted by the first shipborne communication node based on the communication data compression ratio, wherein the first communication data is image data, comprises the following steps:

[0049] S0221. Convert the first communication data into a first data matrix, wherein the element value of the i-th row and j-th column in the first data matrix is ​​the grayscale value of the i-th row and j-th column in the first communication data.

[0050] For example, when the first communication data is an image of size m×n, the corresponding first data matrix is a matrix of size m×n, the first data matrix The element value in is consistent with the pixel grayscale value of the corresponding position in the first communication data.

[0051] S0222. Obtain the grayscale mean and grayscale standard deviation in the first communication data, and use the grayscale mean and the grayscale standard deviation to standardize the first data matrix to obtain a second data matrix, wherein the element value of the i-th row and j-th column in the second data matrix is ​​the quotient of the difference between the element value of the i-th row and j-th column in the first data matrix and the grayscale mean and the grayscale standard deviation.

[0052] Furthermore, the element value of the i-th row and j-th column in the second data matrix satisfies the following calculation formula: , , ,in, represents the element value of the i-th row and j-th column in the second data matrix, represents the element value of the i-th row and j-th column in the first data matrix, represents the grayscale mean, Represents the grayscale variance.

[0053] S0223. Use the second data matrix to construct a correlation coefficient matrix, and obtain the eigenvalues ​​and eigenvectors of the correlation coefficient matrix, wherein the correlation coefficient matrix satisfies the following construction model: , where C represents the correlation coefficient matrix, represents the number of rows of the first data matrix, represents the second data matrix, represents the transpose of the second data matrix.

[0054] Furthermore, at least m eigenvalues ​​and corresponding eigenvectors can be obtained based on the correlation coefficient matrix.

[0055] S0224. Based on the communication data compression ratio, set the number of feature vectors to be retained, and the number of feature vectors to be retained satisfies the following setting model: ,in, represents the number of feature vectors retained, represents the number of rows of the first data matrix, Indicates the communication data compression ratio, Express Round up.

[0056] S0225. Arrange the corresponding eigenvectors in descending order according to the sizes of the eigenvalues, and according to the number of retained eigenvectors, retain the eigenvectors starting from the eigenvector corresponding to the maximum eigenvalue until the number of retained eigenvectors is consistent with the number of retained eigenvectors.

[0057] Furthermore, the eigenvalues ​​are sorted from large to small to obtain the following sequence: ,in, represents the first eigenvalue corresponding to the correlation coefficient matrix, represents the second eigenvalue corresponding to the correlation coefficient matrix, The correlation coefficient matrix corresponds to eigenvalues, represents the total number of eigenvalues, The smaller the subscript corresponding to the eigenvalue, the larger the corresponding eigenvalue.

[0058] According to the descending order of the eigenvalues, the corresponding eigenvectors are arranged in a corresponding descending order, and the first s eigenvectors are retained according to the number s of eigenvectors obtained in step S0224.

[0059] S0226 constructs an eigenvector matrix using the retained eigenvectors, and uses the eigenvector matrix and the second data matrix to obtain compressed first communication data, where the compressed first communication data is the product of the transpose of the eigenvector matrix and the second data matrix.

[0060] Furthermore, the first s eigenvectors can be used to construct an m×s eigenvector matrix , the eigenvector matrix satisfies the following expression: ,in, represents the eigenvector matrix, Represents eigenvalue The corresponding eigenvector, Represents eigenvalue The corresponding eigenvector, Represents eigenvalue The corresponding feature vector.

[0061] Then, the transpose of the eigenvector matrix is ​​multiplied by the second data matrix to obtain the compressed first communication data. The compressed first communication data satisfies the following calculation model: ,in, represents the compressed first communication data, represents the transpose of the eigenvector matrix, represents the second data matrix.

[0062] Based on the compression method described in step S0221 to step S0223 in this embodiment, the step S02 of restoring the compressed first communication data on the second shipborne communication node includes the following steps:

[0063] S0231. Restore the second data matrix according to the compressed first communication data and the eigenvector matrix obtained on the second shipborne communication node.

[0064] Furthermore, the restored second vector satisfies the following expression model: ,in, represents the restored second vector, represents the eigenvector matrix obtained on the second shipborne communication node, The first communication data obtained by the second shipborne communication node.

[0065] S0232. Restore the first data matrix based on the restored second data matrix according to the grayscale mean and grayscale standard deviation obtained on the second shipborne communication node.

[0066] Furthermore, the value of the jth element in the i-th row of the restored first data matrix satisfies the following calculation formula: ,in, represents the element value of the i-th row and j-th column in the restored first data matrix, represents the grayscale standard deviation obtained on the second shipborne communication node, Indicates that the second shipborne communication node obtains the compressed first communication data, represents the transpose of the eigenvector matrix obtained on the second shipborne communication node, Represents the grayscale mean obtained on the second shipborne communication node.

[0067] S0233 reconstructs the first communication data using the restored first data matrix.

[0068] In the present invention, the value of the jth element in the i-th row in the restored first data matrix is ​​the grayscale value of the jth image in the i-th row in the reconstructed first communication data.

[0069] S03. Acquire the channel characteristics of the first communication channel and the second communication channel at the next sampling moment respectively, and adjust the communication data compression ratio of the first shipborne communication node in combination with the restored first communication data and the channel characteristics at the next sampling moment, and compress the second communication data transmitted by the first shipborne communication node based on the adjusted communication data compression ratio.

[0070] Furthermore, the adjusting the communication data compression ratio of the first shipborne communication node by combining the restored first communication data and the channel characteristics at the next sampling moment comprises the following steps:

[0071] S031. Evaluate data quality of the reconstructed first communication data.

[0072] In this embodiment, the first communication data before and after compression are both pixel grayscale matrices.

[0073] Furthermore, the data quality of the restored first communication data can be evaluated by the mean square error of the corresponding point pixels between the first communication data before and after restoration; specifically, the higher the mean square error, the worse the quality of the reconstruction result, and the lower the mean square error, the better the quality of the reconstruction result.

[0074] In one or some other embodiments, the data quality of the restored first communication data can also be evaluated by calculating the peak signal-to-noise ratio between the first communication data before and after restoration; specifically, the higher the peak signal-to-noise ratio, the better the quality of the reconstruction result, and the lower the peak signal-to-noise ratio, the worse the quality of the reconstruction result.

[0075] In one or some other embodiments, the data quality of the restored first communication data can also be evaluated by calculating the structural similarity index between the first communication data before and after restoration; specifically, the closer the structural similarity index is to 1, the better the quality of the reconstruction result, and the closer the structural similarity index is to 0, the worse the quality of the reconstruction result.

[0076] In one or some other embodiments, the data quality of the restored first communication data can also be evaluated by manual observation and perception to evaluate the visual quality of the reconstructed image; further, subjective evaluation results can be obtained through experiments, surveys or user feedback to understand the observer's acceptance of the reconstructed image; specifically, the higher the acceptance level, the better the quality of the reconstruction result, and the lower the acceptance level, the worse the quality of the reconstruction result.

[0077] S032. Adjust the data transmission volume threshold adjustment coefficient according to the data quality of the restored first communication data.

[0078] Further, when the data quality of the restored first communication data does not meet the expected quality, the data transmission threshold adjustment coefficient is increased; when the data quality of the restored first communication data meets the expected quality, the data transmission threshold adjustment coefficient is maintained or reduced.

[0079] It is understandable that if the quality of the restored communication data does not reach the expected level, the data transmission volume threshold adjustment coefficient will be increased to improve the transmission quality and accuracy. On the contrary, if the data quality has met expectations, the data transmission volume threshold adjustment coefficient can be maintained or reduced to maintain the efficiency and stability of communication data transmission.

[0080] S033. Obtain the minimum channel capacity corresponding to the next sampling moment according to the channel characteristics at the next sampling moment.

[0081] Furthermore, the minimum channel capacity corresponding to the next sampling moment can be obtained according to the implementation steps of step S0212 in combination with the channel characteristics at the next sampling moment.

[0082] In this embodiment, the second communication channel at the next sampling moment is the original second communication channel.

[0083] In one or some other embodiments, the second communication channel at the next sampling moment includes the original second communication channel.

[0084] In still another or some other embodiments, the second communication channel at the next sampling moment does not include the original second communication channel.

[0085] S034. Adjust the data transmission volume threshold based on the minimum channel capacity corresponding to the next sampling moment.

[0086] Furthermore, the adjusted data transmission volume threshold can be obtained according to the implementation steps of step S0212 in combination with the minimum channel capacity at the next sampling moment.

[0087] S035. Obtain an adjusted communication data compression ratio by combining the communication data volume of the second communication data, the adjusted data transmission volume threshold, and the adjusted data transmission volume threshold.

[0088] Furthermore, the communication data compression ratio after adjustment by the first shipborne communication node satisfies the following setting model: , , ,in, represents the communication data compression ratio corresponding to the sampling time t+1, represents the communication data volume of the first communication data before compression corresponding to the sampling time t+1, represents the data transmission volume threshold corresponding to the sampling time t+1, , represents the data transmission volume threshold adjustment coefficient corresponding to the sampling time t+1, represents the minimum channel capacity corresponding to sampling time t+1, represents the channel bandwidth of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t+1, Indicates the channel signal-to-noise ratio of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t+1.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A compression method based on shipborne satellite network communication data transmission, characterized in that: The steps include: Respectively acquiring channel characteristics of a first communication channel and a second communication channel at a sampling time, wherein the first communication channel is a data transmission channel between a first shipborne communication node and a satellite communication node, and the second communication channel is a data transmission channel between the satellite communication node and a second shipborne communication node; setting a communication data compression ratio of the first shipborne communication node according to channel characteristics of the first communication channel and the second communication channel at the sampling time, compressing first communication data transmitted by the first shipborne communication node based on the communication data compression ratio, and restoring the compressed first communication data on the second shipborne communication node; respectively acquiring channel characteristics of the first communication channel and the second communication channel at the next sampling moment, and adjusting the communication data compression ratio of the first shipborne communication node in combination with the restored first communication data and the channel characteristics at the next sampling moment, and compressing the second communication data transmitted by the first shipborne communication node based on the adjusted communication data compression ratio; The step of setting the communication data compression ratio of the first shipborne communication node according to the channel characteristics of the first communication channel and the second communication channel at the sampling time comprises the following steps: Obtaining the channel capacities of the first communication channel and the second communication channel respectively according to the channel characteristics of the first communication channel and the second communication channel at a sampling time; A data transmission volume threshold is set based on the minimum channel capacity of the channel capacities of the first communication channel and the second communication channel, and a communication data compression ratio of the first shipborne communication node is set by using the data transmission volume threshold. The communication data compression ratio of the first shipborne communication node satisfies the following setting model: , , ,in, represents the communication data compression ratio corresponding to sampling time t, represents the communication data volume of the first communication data before compression corresponding to the sampling time t, represents the data transmission volume threshold corresponding to sampling time t, It represents the data transmission volume threshold adjustment coefficient corresponding to the sampling time t, represents the minimum channel capacity corresponding to sampling time t, represents the channel bandwidth of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t, Represents the channel signal-to-noise ratio of the communication channel corresponding to the minimum channel capacity corresponding to the sampling time t.

2. The compression method based on shipborne satellite network communication data transmission according to claim 1 is characterized in that: When the satellite communication node corresponds to a second communication channel, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the second communication channel, Indicates the channel capacity of the first communication channel Channel capacity with the second communication channel The minimum value in .

3. The compression method based on shipborne satellite network communication data transmission according to claim 1 is characterized in that: When the satellite communication node corresponds to multiple second communication channels, the minimum channel capacity satisfies the following characterization model: ,in, represents the minimum channel capacity, represents the channel capacity of the first communication channel, represents the channel capacity of the first second communication channel corresponding to the first communication channel, represents the channel capacity of the second second communication channel corresponding to the first communication channel, Indicates the first communication channel corresponding to the The channel capacity of the second communication channel, Indicates the total number of second communication channels corresponding to the first communication channel, Indicates the channel capacity of the first communication channel , the channel capacity of the first second communication channel, the channel capacity of the second second communication channel, and the The minimum value of the channel capacities of the second communication channels.

4. The compression method based on shipborne satellite network communication data transmission according to claim 1 is characterized in that: The step of compressing first communication data transmitted by the first shipborne communication node based on the communication data compression ratio, wherein the first communication data is image data, comprises the following steps: Converting the first communication data into a first data matrix, wherein the element value of the i-th row and j-th column in the first data matrix is ​​the grayscale value of the i-th row and j-th column in the first communication data; Obtaining a grayscale mean and a grayscale standard deviation in the first communication data, and using the grayscale mean and the grayscale standard deviation to standardize the first data matrix to obtain a second data matrix, wherein the element value of the i-th row and j-th column in the second data matrix is ​​the quotient of the difference between the element value of the i-th row and j-th column in the first data matrix and the grayscale mean and the grayscale standard deviation; The correlation coefficient matrix is ​​constructed using the second data matrix, and the eigenvalues ​​and eigenvectors of the correlation coefficient matrix are obtained. The correlation coefficient matrix satisfies the following construction model: , where C represents the correlation coefficient matrix, represents the number of rows of the first data matrix, represents the second data matrix, represents the transpose of the second data matrix; Based on the communication data compression ratio, the number of feature vectors to be retained is set, and the number of feature vectors to be retained satisfies the following setting model: ,in, represents the number of feature vectors retained, represents the number of rows of the first data matrix, Indicates the communication data compression ratio, Express Rounding; Arrange the corresponding eigenvectors in descending order according to the magnitude of the eigenvalues, and according to the number of retained eigenvectors, retain the eigenvectors starting from the eigenvector corresponding to the maximum eigenvalue until the number of retained eigenvectors is consistent with the number of retained eigenvectors; The retained eigenvectors are used to construct an eigenvector matrix, and the eigenvector matrix and the second data matrix are used to obtain compressed first communication data, where the compressed first communication data is the product of the transpose of the eigenvector matrix and the second data matrix.

5. The compression method based on shipborne satellite network communication data transmission according to claim 4 is characterized in that: The restoring the compressed first communication data on the second shipborne communication node comprises the following steps: Restoring a second data matrix according to the compressed first communication data and the eigenvector matrix obtained on the second shipborne communication node; Restore the first data matrix based on the restored second data matrix according to the grayscale mean and grayscale standard deviation obtained on the second shipborne communication node; The first communication data is reconstructed using the restored first data matrix.

6. The compression method based on shipborne satellite network communication data transmission according to claim 1, characterized in that: The value of the jth element in the i-th row of the restored first data matrix satisfies the following calculation formula: ,in, represents the element value of the i-th row and j-th column in the restored first data matrix, represents the grayscale standard deviation obtained on the second shipborne communication node, Indicates that the second shipborne communication node obtains the compressed first communication data, represents the transpose of the eigenvector matrix obtained on the second shipborne communication node, Represents the grayscale mean obtained on the second shipborne communication node.

7. The compression method based on shipborne satellite network communication data transmission according to claim 1 is characterized in that: The method of combining the restored first communication data and the channel characteristics at the next sampling moment to adjust the communication data compression ratio of the first shipborne communication node comprises the following steps: evaluating data quality of the reconstructed first communication data; adjusting the data transmission volume threshold adjustment coefficient according to the data quality of the restored first communication data; According to the channel characteristics at the next sampling moment, the minimum channel capacity corresponding to the next sampling moment is obtained; Adjusting the data transmission volume threshold based on the minimum channel capacity corresponding to the next sampling time; The adjusted communication data compression ratio is obtained by combining the communication data volume of the second communication data, the adjusted data transmission volume threshold, and the adjusted data transmission volume threshold.

8. The compression method based on shipborne satellite network communication data transmission according to claim 7 is characterized in that: The step of adjusting the data transmission volume threshold adjustment coefficient according to the data quality of the restored first communication data comprises the following steps: When the data quality of the restored first communication data does not meet the expected quality, increasing the data transmission volume threshold adjustment coefficient; When the data quality of the restored first communication data meets the expected quality, the data transmission volume threshold adjustment coefficient is maintained or reduced.

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