A method for signal quality enhancement in satellite communications

Abstract

The application discloses a kind of signal quality enhancement methods of satellite communication, belong to satellite communication technical field.The application is modulated to satellite demodulation after being sent to satellite with different frequency carrier to the same baseband signal first, and the amplitude of demodulation signal is restored according to satellite receiving signal attenuation ratio.Then the restored signal is sampled, with the eigenvalue of neighborhood of sampling point defining the eigenvalue of center sampling point (eigenvalue contains dispersion, amplitude mean and extreme value).Subsequently, the characteristic bias (including dispersion bias, amplitude bias and extreme value bias) is extracted according to the eigenvalue of sampling point at the same time, and the characteristic bias of each time of the same sampling signal is constructed as sequence.Based on the fusion of each sampling signal of three kinds of characteristic bias sequence, three kinds of fusion signals are obtained, and finally the fusion signal is weighted, so that the signal of signal quality significantly enhanced is obtained, and the signal quality of satellite communication is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and more specifically to a method for enhancing the signal quality of satellite communication. Background Technology

[0002] Satellite communication is widely used in various fields such as military, maritime, aviation, remote area communication, and broadcast television signal transmission. However, satellite communication faces many severe challenges that seriously affect signal quality. Due to the long distance between satellites and ground stations, signals are highly susceptible to interference from atmospheric attenuation, ionospheric scintillation, multipath effects, and space noise during transmission, leading to a decrease in demodulated signal quality, an increase in bit error rate, and a significant reduction in communication reliability.

[0003] Current satellite communication uses spatial diversity technology, which involves deploying multiple antennas on a satellite to simultaneously receive signals from different antennas and coherently combining them using phase information or by combining signals from different antennas through power. However, existing spatial diversity technology does not consider the degree of deformation or local differences in each region, resulting in low combining accuracy and poor quality of the synthesized signal. Summary of the Invention

[0004] In view of the above-mentioned shortcomings in the prior art, the present invention provides a signal quality enhancement method for satellite communication, which solves the problem of low signal quality after synthesis in existing space diversity technology.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by this invention is: a method for enhancing the signal quality of satellite communication, comprising the following steps:

[0006] The same baseband signal is modulated using carriers of different frequencies and sent to a satellite for demodulation processing to obtain a demodulated signal.

[0007] Based on the attenuation ratio of the satellite received signal, the amplitude of the corresponding demodulated signal is restored to obtain the restored signal;

[0008] Each restored signal is sampled and processed to obtain a sampled signal. Taking each sampling point in the sampled signal as the center, the feature values ​​of the neighborhood range are used as the feature values ​​of the center sampling point. The feature values ​​include: dispersion, mean amplitude, and maximum / minimum value.

[0009] Based on the feature values ​​of each sampling point at the same time, feature biases are extracted, and feature biases belonging to the same sampling signal at each time are constructed into a feature bias sequence. The feature biases include: discrete biases, amplitude biases, and extreme value biases.

[0010] Based on the three characteristic bias sequences, the sampled signals are fused to obtain three fused signals;

[0011] The three fused signals are weighted to obtain a signal with enhanced quality.

[0012] Furthermore, the process of obtaining the demodulated signal includes:

[0013] Multiple modulated signals are obtained by modulating the same baseband signal with carriers of different frequencies;

[0014] Each modulated signal is transmitted to the satellite through the uplink of an antenna to obtain the satellite received signal, wherein one modulated signal corresponds to one satellite received signal;

[0015] The satellite received signal is demodulated to obtain the demodulated signal.

[0016] Furthermore, the amplitude restoration process includes:

[0017] The ratio of the average amplitude of the modulated signal to the average amplitude of the satellite-received signal is used as the attenuation ratio;

[0018] The restored signal is obtained by multiplying the amplitude of the demodulated signal at each moment by the attenuation ratio.

[0019] Furthermore, the dispersion is: the variance or standard deviation of each sampling point within the neighborhood of the central sampling point;

[0020] The mean amplitude is the average amplitude of all sampling points within the neighborhood of the central sampling point.

[0021] The maximum or minimum value is the maximum or minimum value of each sampling point within the neighborhood of the central sampling point.

[0022] Furthermore, the process of obtaining the feature bias includes: at the same time, calculating the average value of the feature values ​​of the sampling points in each sampled signal; subtracting the average value from each feature value and taking the absolute value to obtain the feature bias; summing the feature biases to obtain the total feature bias; and subtracting the ratio of the feature bias to the total feature bias from 1 to obtain the feature bias.

[0023] Furthermore, the process of obtaining the discrete bias includes: at the same time, calculating the average value of the dispersion of each sampling point in each sampled signal, subtracting the average value from each dispersion and taking the absolute value to obtain the discrete bias, summing the discrete biases to obtain the total discrete bias, and subtracting the ratio of the discrete bias to the total discrete bias from 1 to obtain the discrete bias.

[0024] The process of obtaining the amplitude deviation includes: at the same time, calculating the average value of the amplitude mean in each sampled signal; subtracting the average value from the amplitude mean of each sampled signal and taking the absolute value to obtain the amplitude deviation; summing the amplitude deviations to obtain the total amplitude deviation; and subtracting the ratio of the amplitude deviation to the total amplitude deviation from 1 to obtain the amplitude deviation.

[0025] The process of obtaining the extreme value deviation includes: at the same time, calculating the average value of the extreme values ​​of each sampled signal; subtracting the average value of the extreme values ​​from the extreme values ​​of each sampled point in the sampled signal and taking the absolute value to obtain the extreme value deviation; summing the extreme value deviations to obtain the total extreme value deviation; and subtracting the ratio of the extreme value deviation to the total extreme value deviation from 1 to obtain the extreme value deviation.

[0026] Furthermore, the process of obtaining the first fused signal includes:

[0027] Each sampled signal is multiplied by the discrete bias sequence of each sampled signal at the same sampling time to obtain the discrete weighted signal;

[0028] The first fused signal is obtained by adding all discrete weighted signals at the same sampling time.

[0029] Furthermore, the process of obtaining the second fused signal includes:

[0030] Each sampled signal is multiplied by the amplitude bias sequence of each sampled signal at the same sampling time to obtain the amplitude-weighted signal;

[0031] All amplitude-weighted signals are summed at the same sampling time to obtain the second fused signal.

[0032] Furthermore, the process of obtaining the third fused signal includes:

[0033] Each sampled signal is multiplied by the sequence of extreme and minimum bias values ​​of each sampled signal at the same sampling time to obtain the extreme and minimum weighted signal;

[0034] The third fused signal is obtained by summing all the extreme value weighted signals at the same sampling time.

[0035] Furthermore, the weighted processing formula is as follows: Where G is the signal quality enhancement signal, ω1 is the first weight, ω2 is the second weight, ω3 is the third weight, g1 is the first fused signal, g2 is the second fused signal, and g3 is the third fused signal.

[0036] In summary, the beneficial effects of this invention are as follows:

[0037] 1. Existing spatial diversity techniques do not consider the degree of deformation and local differences in each region, resulting in low combination accuracy and poor quality of the synthesized signal. This invention, however, uses each sampling point in the sampled signal as the center and takes the feature values ​​(dispersion, mean amplitude, and maximum / minimum values) of the neighborhood range as the feature values ​​of the center sampling point, accurately capturing the local features of the signal. This allows subsequent processing to fully consider the changes in the signal at different local locations, providing a more accurate data foundation for signal fusion and enhancement, thereby effectively improving the accuracy of signal combination.

[0038] 2. Signal amplitude changes during transmission are caused by factors such as atmospheric attenuation. This invention restores the amplitude of the demodulated signal based on the attenuation ratio of the satellite received signal. It recovers the energy lost due to transmission losses, making the signal amplitude closer to the original transmitted signal and reducing signal distortion caused by amplitude changes.

[0039] 3. This invention extracts characteristic biases (discrete biases, amplitude biases, and extreme value biases) and constructs a characteristic bias sequence. These characteristic biases can reflect the relative changes in the characteristics of different sampled signals at the same time. Based on these characteristic bias sequences, the various sampled signals are fused to reduce interference from sampling points with large local deformation, thereby reducing signal distortion and deformation.

[0040] 4. This invention performs weighted processing on the three fused signals, taking into account the deformation effects of the three features, thereby further improving the signal quality. Attached Figure Description

[0041] Figure 1 This is a flowchart of a method for enhancing the signal quality of satellite communications. Detailed Implementation

[0042] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0043] like Figure 1 As shown, a method for enhancing the signal quality of satellite communication includes the following steps:

[0044] The same baseband signal is modulated using carriers of different frequencies and sent to a satellite for demodulation processing to obtain a demodulated signal.

[0045] Based on the attenuation ratio of the satellite received signal, the amplitude of the corresponding demodulated signal is restored to obtain the restored signal;

[0046] Each restored signal is sampled and processed to obtain a sampled signal. Taking each sampling point in the sampled signal as the center, the feature values ​​of the neighborhood range are used as the feature values ​​of the center sampling point. The feature values ​​include: dispersion, mean amplitude, and maximum and minimum values. One restored signal corresponds to one sampled signal.

[0047] Based on the feature values ​​of each sampling point at the same time, feature biases are extracted, and feature biases belonging to the same sampling signal at each time are constructed into a feature bias sequence. The feature biases include: discrete biases, amplitude biases, and extreme value biases.

[0048] Based on the three characteristic bias sequences, the sampled signals are fused to obtain three fused signals;

[0049] The three fused signals are weighted to obtain a signal with enhanced quality.

[0050] In this embodiment, the process of obtaining the demodulated signal includes:

[0051] Multiple modulated signals are obtained by modulating the same baseband signal with carriers of different frequencies;

[0052] Each modulated signal is transmitted to the satellite through the uplink of an antenna to obtain the satellite received signal, wherein one modulated signal corresponds to one satellite received signal;

[0053] The satellite received signal is demodulated to obtain the demodulated signal.

[0054] In this embodiment, the expression for modulating the same baseband signal using carriers of different frequencies is: , Let S be the k-th modulation signal, and w be the baseband signal. k Let cos(w) be the frequency of the k-th carrier. k t) represents the carrier signal, k is a positive integer, and τ is time. For example, for the C band (5.925-6.425GHz for uplink), the carrier frequencies that can be set include: 5.95GHz, 6.0GHz, 6.12GHz, 6.25GHz, 6.38GHz, and 6.4GHz. During the uplink process, there is varying degrees of interference in space for signals of different frequencies. Therefore, multiple frequencies are set to resist spatial interference.

[0055] In this embodiment, when transmitting multiple modulated signals, they can be transmitted in time intervals or simultaneously.

[0056] In this embodiment, the amplitude restoration process includes:

[0057] The ratio of the average amplitude of the modulated signal to the average amplitude of the satellite-received signal is used as the attenuation ratio;

[0058] The restored signal is obtained by multiplying the amplitude of the demodulated signal at each moment by the attenuation ratio.

[0059] Since the attenuation of signals of different frequencies varies in space, this invention restores the amplitude of each demodulated signal to the same scale.

[0060] In this embodiment, the dispersion is: the variance or standard deviation of each sampling point within the neighborhood of the central sampling point;

[0061] The mean amplitude is the average amplitude of all sampling points within the neighborhood of the central sampling point.

[0062] The maximum or minimum value is the maximum or minimum value of each sampling point within the neighborhood of the central sampling point.

[0063] This invention takes each sampling point as the center and uses the dispersion, mean amplitude, and maximum / minimum values ​​of the neighborhood range as feature values ​​to comprehensively reflect the signal characteristics at that center.

[0064] In this embodiment, the neighborhood range length is set to 3, 4, 5, etc. For example, when the neighborhood range length is set to 3, with the addition of the center sampling point, there are 7 sampling points in the neighborhood range of the center sampling point.

[0065] In this embodiment, the process of obtaining the feature bias includes: at the same time, calculating the average value of the feature values ​​of the sampling points in each sampling signal, subtracting the average value from each feature value and taking the absolute value to obtain the feature bias, summing the feature biases to obtain the total feature bias, and subtracting the ratio of the feature bias to the total feature bias from 1 to obtain the feature bias.

[0066] In this embodiment, the process of obtaining the discrete bias includes: calculating the average value of the dispersion of each sampling point in each sampled signal at the same time; subtracting the average value from each dispersion and taking the absolute value to obtain the discrete bias; summing the discrete biases to obtain the total discrete bias; and subtracting the ratio of the discrete bias to the total discrete bias from 1 to obtain the discrete bias. , where γ σ,i,t Let σ be the discrete bias of the sampling point at time t in the i-th sampled signal, || is the absolute value operation, and σ is the discrete bias of the sampling point at time t in the i-th sampled signal. i,t Let N be the discreteness of the sampling point at time t in the i-th sampled signal, N be the number of sampled signals, t be the sampling time number, and i be a positive integer.

[0067] The discreteness of this invention reflects the fluctuation of a signal. In scenarios such as satellite communication, signal transmission is susceptible to interference from various factors, leading to differences in stability. Calculating the discrete deviation allows comparison of the discreteness of each sampled signal with the average discreteness, clearly showing the degree of deviation of the fluctuation of each signal point from the overall average level. The larger the ratio of discrete deviation to total discrete deviation, the further the discreteness at that sampling point deviates from the average level, and the smaller the discrete deviation at that sampling point. In the subsequent signal fusion process, reducing the weight of its amplitude in the fusion can effectively reduce the interference of local abnormal signals on the fusion result.

[0068] In this invention, the same sampling frequency is used for each restored signal, and the same number of sampling points are extracted.

[0069] In this embodiment, the process of obtaining the amplitude deviation includes: calculating the average value of the amplitude mean in each sampled signal at the same time; subtracting the average value from the amplitude mean of each sampled signal and taking the absolute value to obtain the amplitude deviation; summing the amplitude deviations to obtain the total amplitude deviation; and subtracting the ratio of the amplitude deviation to the total amplitude deviation from 1 to obtain the amplitude deviation. , where γ s,i,t Let s be the amplitude deviation of the sampling point at time t in the i-th sampled signal. i,t Let s be the mean amplitude of the sampling points at time t in the i-th sampled signal. t,avg Let be the average of the magnitudes at time t, and || be the absolute value.

[0070] The amplitude mean of this invention reflects the overall amplitude level within the neighborhood of a sampling point. Calculating the amplitude deviation allows comparison of the amplitude mean of each sampling point with the overall average amplitude, clearly showing the degree of deviation of the amplitude range of each signal point from the overall average level. The larger the ratio of amplitude deviation to total amplitude deviation, the further the amplitude at that sampling point deviates from the average level, and the smaller the amplitude deviation at that sampling point. In subsequent signal fusion processes, reducing the weight of its amplitude in the fusion can effectively reduce the interference of local abnormal signals on the fusion result.

[0071] In this embodiment, the process of obtaining the extreme value deviation includes: at the same time, calculating the average of the extreme values ​​of each sampled signal; subtracting the average extreme value from the extreme value of each sampled point in the sampled signal and taking the absolute value to obtain the extreme value deviation; summing the extreme value deviations to obtain the total extreme value deviation; and subtracting the ratio of the extreme value deviation to the total extreme value deviation from 1 to obtain the extreme value deviation. , where γ M,i,t M represents the extreme value bias of the sampling point at time t in the i-th sampled signal. i,t M represents the maximum and minimum values ​​of the sampling points at time t in the i-th sampled signal. t,avg Let be the mean of the extreme values ​​at time t.

[0072] Extreme values ​​reflect the extreme state of a signal at a certain moment. By calculating the extreme value deviation and comparing the extreme value of each sampling point with the mean extreme value, the degree of deviation of the extreme values ​​in each sampled signal can be accurately measured. The larger the ratio of the extreme value deviation to the total extreme value deviation, the further the extreme value at that sampling point deviates from the average level, and the smaller the extreme value deviation at that sampling point. In the subsequent signal fusion process, reducing the weight of its amplitude in the fusion can effectively reduce the interference of local abnormal signals on the fusion result.

[0073] In this embodiment, the process of obtaining the first fused signal includes:

[0074] Each sampled signal is multiplied by the discrete bias sequence of each sampled signal at the same sampling time to obtain the discrete weighted signal;

[0075] The first fused signal is obtained by adding all discrete weighted signals at the same sampling time.

[0076] In this embodiment, the process of obtaining the second fused signal includes:

[0077] Each sampled signal is multiplied by the amplitude bias sequence of each sampled signal at the same sampling time to obtain the amplitude-weighted signal;

[0078] All amplitude-weighted signals are summed at the same sampling time to obtain the second fused signal.

[0079] In this embodiment, the process of obtaining the third fused signal includes:

[0080] Each sampled signal is multiplied by the sequence of extreme and minimum bias values ​​of each sampled signal at the same sampling time to obtain the extreme and minimum weighted signal;

[0081] The third fused signal is obtained by summing all the extreme value weighted signals at the same sampling time.

[0082] In this invention, since each sampling point in the sampled signal calculates a discrete bias, an amplitude bias, and an extremum bias, and each sampled signal corresponds to a discrete bias sequence, an amplitude bias sequence, and an extremum bias sequence, each sampled signal is element-wise multiplied with its corresponding discrete bias sequence, and then the multiplied signals are element-wise summed to obtain a fused signal, thus configuring fusion weights according to discrete conditions. Alternatively, each sampled signal is element-wise multiplied with its corresponding amplitude bias sequence, and then the multiplied signals are element-wise summed to obtain a fused signal, thus configuring fusion weights according to amplitude conditions. Finally, each sampled signal is element-wise multiplied with its corresponding extremum bias sequence, and then the multiplied signals are element-wise summed to obtain a fused signal, thus configuring fusion weights according to extremum conditions.

[0083] In this embodiment, the weighted processing formula is: Where G is the signal quality enhancement signal, ω1 is the first weight, ω2 is the second weight, ω3 is the third weight, g1 is the first fused signal, g2 is the second fused signal, and g3 is the third fused signal.

[0084] In this embodiment, the values ​​of ω1, ω2, and ω3 can all be set to 1 / 3 to evenly consider the influence of the three features on the signal. More preferably, the optimal values ​​of ω1, ω2, and ω3 can be found through an optimization method that minimizes the error. The initial values ​​of ω1, ω2, and ω3 are set to 1. The first fused signal, the second fused signal, and the third fused signal are used as samples. The nth sample is input into the weighting formula to obtain the signal quality enhancement signal of the nth iteration. Based on the difference between the signal quality enhancement signal of the nth iteration and the corresponding baseband signal, each weight is updated. When the number of iterations meets a threshold, the iteration stops, and the weight corresponding to the smallest difference among all iterations is taken as the optimal value. The difference between the signal quality enhancement signal of the nth iteration and the corresponding baseband signal can be calculated using mean square error (MSE). The threshold can be set to 2000. The formula for updating the weights is: , where J n ω represents the difference in the nth iteration. m,n+1 Let ω be the weight of the m-th weight in the (n+1)-th iteration. m,n Let m be the weight of the m-th weight in the nth iteration, where m takes the values ​​1, 2, or 3. Let ω1 be the partial derivative and 'a' be the step size. The step size 'a' is usually set between 0.001 and 1, and can be tried from values ​​such as 0.01 and 0.1. The method for finding the optimal values ​​of ω1, ω2, and ω3 is not limited to the method described in this embodiment; genetic algorithms, particle swarm optimization algorithms, etc., can also be used to find the optimal weights.

[0085] Existing spatial diversity techniques fail to consider the degree of deformation and local differences in each region, resulting in low combination accuracy and poor quality of the synthesized signal. This invention, however, uses each sampling point in the sampled signal as the center and employs the feature values ​​(dispersion, mean amplitude, and maximum / minimum values) of the neighborhood range as the feature values ​​of the central sampling point, accurately capturing the local features of the signal. This allows subsequent processing to fully consider the changes in the signal at different local locations, providing a more accurate data foundation for signal fusion and enhancement, thereby effectively improving the accuracy of signal combination.

[0086] Signal amplitude changes during transmission due to factors such as atmospheric attenuation. This invention restores the amplitude of the demodulated signal based on the attenuation ratio of the satellite received signal. It recovers the energy lost due to transmission losses, making the signal amplitude closer to the original transmitted signal and reducing signal distortion caused by amplitude variations.

[0087] This invention extracts characteristic biases (discrete biases, amplitude biases, and extreme value biases) and constructs a sequence of characteristic biases. These characteristic biases reflect the relative changes in the characteristics of different sampled signals at the same time. Based on these characteristic bias sequences, the various sampled signals are fused to reduce interference from sampling points with large local deformations, thereby reducing signal distortion and deformation.

[0088] This invention performs weighted processing on three fused signals, taking into account the deformation effects of the three features, thereby further improving signal quality.

[0089] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for enhancing the signal quality of satellite communication, characterized in that, Includes the following steps: The same baseband signal is modulated using carriers of different frequencies and sent to a satellite for demodulation processing to obtain a demodulated signal. Based on the attenuation ratio of the satellite received signal, the amplitude of the corresponding demodulated signal is restored to obtain the restored signal; Each restored signal is sampled and processed to obtain a sampled signal. Taking each sampling point in the sampled signal as the center, the feature values ​​of the neighborhood range are used as the feature values ​​of the center sampling point. The feature values ​​include: dispersion, mean amplitude, and maximum / minimum value. Based on the feature values ​​of each sampling point at the same time, feature biases are extracted. The feature biases of each time point belonging to the same sampling signal are constructed into a feature bias sequence. The feature biases include: discrete bias, amplitude bias, and extreme value bias. The process of obtaining the feature biases includes: at the same time, calculating the average value of the feature values ​​of each sampling point in each sampling signal; subtracting the average value from each feature value and taking the absolute value to obtain the feature deviation; summing the feature deviations to obtain the total feature deviation; and subtracting the ratio of the feature deviation to the total feature deviation from 1 to obtain the feature bias. Based on the three characteristic bias sequences, the sampled signals are fused to obtain three fused signals; The three fused signals are weighted to obtain a signal with enhanced quality.

2. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The process of obtaining the demodulated signal includes: Multiple modulated signals are obtained by modulating the same baseband signal with carriers of different frequencies; Each modulated signal is transmitted to the satellite through the uplink of an antenna to obtain the satellite received signal, wherein one modulated signal corresponds to one satellite received signal; The satellite received signal is demodulated to obtain the demodulated signal.

3. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The amplitude restoration process includes: The ratio of the average amplitude of the modulated signal to the average amplitude of the satellite-received signal is used as the attenuation ratio; The restored signal is obtained by multiplying the amplitude of the demodulated signal at each moment by the attenuation ratio.

4. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The dispersion is the variance or standard deviation of each sampling point within the neighborhood of the central sampling point. The mean amplitude is the average amplitude of all sampling points within the neighborhood of the central sampling point. The maximum or minimum value is the maximum or minimum value of each sampling point within the neighborhood of the central sampling point.

5. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The process of obtaining the discrete bias includes: at the same time, calculating the average value of the dispersion of each sampling point in each sampled signal, subtracting the average value from each dispersion and taking the absolute value to obtain the discrete bias, summing the discrete biases to obtain the total discrete bias, and subtracting the ratio of the discrete bias to the total discrete bias from 1 to obtain the discrete bias. The process of obtaining the amplitude deviation includes: at the same time, calculating the average value of the amplitude mean in each sampled signal; subtracting the average value from the amplitude mean of each sampled signal and taking the absolute value to obtain the amplitude deviation; summing the amplitude deviations to obtain the total amplitude deviation; and subtracting the ratio of the amplitude deviation to the total amplitude deviation from 1 to obtain the amplitude deviation. The process of obtaining the extreme value deviation includes: at the same time, calculating the average value of the extreme values ​​of each sampled signal; subtracting the average value of the extreme values ​​from the extreme values ​​of each sampled point in the sampled signal and taking the absolute value to obtain the extreme value deviation; summing the extreme value deviations to obtain the total extreme value deviation; and subtracting the ratio of the extreme value deviation to the total extreme value deviation from 1 to obtain the extreme value deviation.

6. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The process of obtaining the first fused signal includes: Each sampled signal is multiplied by the discrete bias sequence of each sampled signal at the same sampling time to obtain the discrete weighted signal; The first fused signal is obtained by adding all discrete weighted signals at the same sampling time.

7. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The process of obtaining the second fused signal includes: Each sampled signal is multiplied by the amplitude bias sequence of each sampled signal at the same sampling time to obtain the amplitude-weighted signal; All amplitude-weighted signals are summed at the same sampling time to obtain the second fused signal.

8. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The process of obtaining the third fused signal includes: Multiply each sampled signal by the sequence of extreme and minimum bias values ​​of each sampled signal at the same sampling time to obtain the extreme and minimum weighted signal; The third fused signal is obtained by summing all the extreme value weighted signals at the same sampling time.

9. The signal quality enhancement method for satellite communication according to claim 1, characterized in that, The weighted processing formula is: Where G is the signal quality enhancement signal, ω1 is the first weight, ω2 is the second weight, ω3 is the third weight, g1 is the first fused signal, g2 is the second fused signal, and g3 is the third fused signal.

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