A target signal radius ratio determination method, device, equipment and medium

Abstract

The application provides a target signal radius ratio determination method and device, equipment and medium, used in the field of wireless communication technology, comprising: calculating the inner circle probability value and the outer circle probability value corresponding to each signal sample point according to the preset parameter group and the corresponding target amplitude, and classifying the signal sample points to obtain the inner circle radius sample point and the outer circle radius sample point; based on the target amplitude, the inner circle radius sample point and the outer circle radius sample point are sorted respectively, and the corresponding target inner circle radius value and the target outer circle radius value are determined; according to the target inner circle radius value, the target outer circle radius value and the preset parameter group, the radius change value is calculated, and based on the preset convergence radius threshold, the convergence result corresponding to the radius change value is determined; according to the convergence result, the target inner circle radius value and the target outer circle radius value, the corresponding target signal radius ratio is determined; in this way, the calculation efficiency and accuracy of the signal radius ratio under noise interference are improved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a method, apparatus, device and medium for determining the radius ratio of a target signal. Background Technology

[0002] 16APSK is a highly efficient multi-level modulation scheme. Its constellation diagram consists of two concentric circles, with the inner circle having a radius of r1 and the outer circle having a radius of r2. Several phase points are distributed on each circle, with a conventional configuration of 4 points on the inner circle and 12 points on the outer circle. At the receiver, the demodulator needs to accurately obtain the ratio of r1 to r2 in order to complete symbol decision and decoding.

[0003] Existing methods for determining the radius ratio include dividing the inner and outer circle samples by clustering the amplitude histogram and taking the mean of each cluster as the radius estimate; using the known distribution pattern of the sign phase of the inner and outer circles, such as the uniform distribution of 4 points in the inner circle, and estimating the radius of each circle separately after screening the samples; or extracting the distribution features through higher-order moments of the signal amplitude, such as the fourth-order cumulant, and mapping them to r1 and r2.

[0004] However, existing methods for determining the radius ratio are susceptible to noise interference and have low computational efficiency and accuracy under low signal-to-noise ratio conditions. Summary of the Invention

[0005] This application provides a method, apparatus, device, and medium for determining the radius ratio of a target signal, in order to solve the problems of existing radius ratio determination methods being greatly affected by noise interference and having low computational efficiency and accuracy under low signal-to-noise ratio conditions.

[0006] In a first aspect, this application provides a method for determining the radius ratio of a target signal, the method comprising: Based on the preset parameter set and its corresponding target amplitude, the inner circle probability value and outer circle probability value of each signal sample point are calculated. Based on the inner circle probability value, outer circle probability value and preset classification threshold, the signal sample points are classified to obtain inner circle radius sample points and outer circle radius sample points. Among them, the signal sample points are multiple sample points obtained by sampling the target signal. Based on the target amplitude, the inner circle radius sample points and the outer circle radius sample points are sorted respectively, and based on the sorted inner circle radius sequence and outer circle radius sequence, the corresponding target inner circle radius value and target outer circle radius value are determined. Based on the target inner circle radius value, the target outer circle radius value, and the preset parameter set, calculate the radius change value, and determine the convergence result corresponding to the radius change value based on the preset convergence radius threshold. Based on the convergence results, the inner radius value of the target, and the outer radius value of the target, determine the corresponding target signal radius ratio.

[0007] In some embodiments of this application, before calculating the inner circle probability value and outer circle probability value corresponding to each signal sample point based on a preset parameter set and their respective target amplitudes, the method further includes: The target signal is sampled to obtain multiple signal sample points, and the sum of squares of all signal amplitudes is calculated based on the signal amplitudes corresponding to the signal sample points. Based on the sum of squares, the normalized parameter value corresponding to the signal amplitude is determined, and the target amplitude corresponding to each signal sample point is determined according to the ratio of each signal amplitude to the normalized parameter value.

[0008] In some embodiments of this application, the preset parameter set includes a preset inner circle radius value, a preset outer circle radius value, a preset inner circle variance value, a preset outer circle variance value, and a preset weighting coefficient; Based on the preset parameter set and its corresponding target amplitude, calculate the inner circle probability value and outer circle probability value for each signal sample point, including: Substituting the inner circle probability parameter set and the outer circle probability parameter set into the Gaussian probability density function respectively, we obtain the initial inner circle probability value and the initial outer circle probability value corresponding to each signal sample point; wherein, the inner circle probability parameter set includes the target amplitude, the preset inner circle radius value and the preset inner circle variance value, and the outer circle probability parameter set includes the target amplitude, the preset outer circle radius value and the preset outer circle variance value; Based on the preset weighting coefficients, the initial inner circle probability value, and the initial outer circle probability value, calculate the corresponding inner circle probability value and outer circle probability value.

[0009] In some embodiments of this application, determining the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence includes: The target inner circle radius value and the target outer circle radius value are determined based on the median of the inner circle radius sequence and the outer circle radius sequence, respectively.

[0010] In some embodiments of this application, the radius change value is calculated based on the target inner circle radius value, the target outer circle radius value, and a preset parameter set, including: Based on the preset inner circle radius value and preset outer circle radius value in the preset parameter group, calculate the difference between the target inner circle radius value and the preset inner circle radius value, and between the target outer circle radius value and the preset outer circle radius value, respectively, and sum the differences to obtain the target radius difference; Based on the sum of the preset inner circle radius value and the preset outer circle radius value, the ratio between the target radius difference and the sum is calculated to obtain the radius change value.

[0011] In some embodiments of this application, the convergence result corresponding to the radius change value is determined based on a preset convergence radius threshold, including: By comparing the radius change value with the preset convergence radius threshold value, the corresponding comparison result is obtained; If the comparison result shows that the radius change value is less than the preset convergence radius threshold, then the corresponding convergence result is determined to be the radius change value convergence. If the comparison result shows that the radius change value is not less than the preset convergence radius threshold, then the corresponding convergence result is determined to be that the radius change value does not converge.

[0012] In some embodiments of this application, the corresponding target signal radius ratio is determined based on the convergence result, the target inner radius value, and the target outer radius value, including: Determine the convergence result; If the convergence result is that the radius change value converges, then the target signal radius ratio is determined based on the ratio of the inner radius value to the outer radius value of the target. If the convergence result indicates that the radius change value does not converge, then the target inner circle radius value is determined as the updated inner circle radius value, and the target outer circle radius value is determined as the updated outer circle radius value. Based on the updated inner circle radius value, the updated outer circle radius value, and the target amplitude, the updated inner circle variance value, the updated outer circle variance value, and the updated weight coefficient are calculated to obtain the corresponding updated parameter set. Based on the updated parameter set, the corresponding updated radius change value is iteratively calculated to obtain the target radius change value, and based on the target radius change value, the target signal radius ratio is calculated. Among these, the target radius change value is the converged updated radius change value.

[0013] Secondly, this application provides a device for determining the radius ratio of a target signal, the device comprising: The classification module is used to calculate the inner circle probability value and outer circle probability value corresponding to each signal sample point according to the preset parameter group and their respective target amplitude, and classify the signal sample points based on the inner circle probability value, outer circle probability value and preset classification threshold to obtain inner circle radius sample points and outer circle radius sample points; wherein, the signal sample point is multiple sample points obtained by sampling the target signal; The sorting module is used to sort the inner circle radius sample points and the outer circle radius sample points based on the target amplitude, and to determine the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence. The calculation module is used to calculate the radius change value based on the target inner circle radius value, the target outer circle radius value and the preset parameter set, and determine the convergence result corresponding to the radius change value based on the preset convergence radius threshold. The determination module is used to determine the corresponding target signal radius ratio based on the convergence result, the target inner circle radius value, and the target outer circle radius value.

[0014] Thirdly, this application provides a computer device, including: a processor, and a memory communicatively connected to the processor; The memory stores instructions that the computer executes; The processor executes computer execution instructions stored in memory to implement the method of this application.

[0015] Fourthly, this application provides a computer-readable storage medium storing program code, which, when executed by a processor, is used to implement the method of this application.

[0016] Compared with existing technologies, the method of this application calculates the inner and outer circle probability values ​​corresponding to each signal sample point based on a preset parameter set and a target amplitude, and classifies the samples by combining a classification threshold. This achieves accurate segmentation of inner and outer circle signal samples even when noise causes overlapping signal amplitude distributions. Furthermore, sorting the inner and outer circle sample points separately based on the target amplitude and determining the target inner and outer circle radii suppresses the influence of noise and outliers, improving the accuracy and stability of radius estimation. Calculating the radius change value based on the target radius value and the preset parameter set, and judging the convergence result by combining a convergence threshold, allows iterative optimization to continuously approach the true radius parameters, ensuring the accuracy of parameter estimation. Convergence and computational efficiency: By combining the convergence result with the inner and outer radius values ​​of the target signal, the ratio of the target signal radius is determined. This allows for the output of a relative radius parameter that is unaffected by channel gain, providing the demodulator with an accurate basis for symbol decision. This effectively improves the overall performance of 16APSK signal reception and demodulation under low signal-to-noise ratio conditions, thus avoiding information loss caused by preprocessing. Statistical robustness optimization is performed using the Expectation-Maximization Algorithm (EM optimization algorithm), and robust statistics such as the median and corrected estimators are introduced in the parameter estimation to suppress the influence of noise. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] Figure 1 A flowchart illustrating a method for determining the radius ratio of a target signal, provided in an embodiment of this application; Figure 2 A schematic diagram illustrating a method for determining the radius ratio of a target signal according to an embodiment of this application; Figure 3 A schematic diagram of a target signal radius ratio determination device provided in an embodiment of this application; Figure 4 This is a structural block diagram of an apparatus for performing a method for determining the radius ratio of a target signal according to an embodiment of this application. Detailed Implementation

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0020] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0021] In existing technologies, amplitude clustering divides samples into inner and outer circles by clustering amplitude histograms and takes the mean of each cluster as the radius estimate. However, at low SNR, noise causes sample overlap, making it difficult to accurately segment cluster centers (e.g., the k-means algorithm is sensitive to initial values). It relies on noise reduction preprocessing (e.g., filters or nonlinear enhancement), but noise reduction may introduce signal distortion or computational delay.

[0022] Phase-assisted screening utilizes the known distribution pattern of the phase of the inner and outer circle symbols (e.g., uniform distribution of 4 points on the inner circle) to screen samples and then estimate the radius of each circle separately. Its drawback is that when the signal-to-noise ratio is extremely low, the phase error is too large (e.g., phase noise or frequency offset interference), and the screening accuracy drops sharply; it is not suitable for dynamic channel conditions (e.g., instantaneous phase jumps caused by moving satellite scenarios).

[0023] Higher-order statistics extract distribution features from higher-order moments (such as fourth-order cumulants) of the signal amplitude and map them to r1 and r2. However, higher-order statistics are sensitive to noise, and the estimation variance increases significantly at low SNR; they also have high computational complexity, making them difficult to apply to real-time systems.

[0024] The common problem with the above methods is that they fail to effectively balance noise robustness and computational efficiency under low signal-to-noise ratio conditions, and most of them rely on preprocessing operations (such as noise reduction or phase compensation), which leads to increased system complexity or introduces additional errors.

[0025] Figure 1 This is a flowchart illustrating a method for determining the radius ratio of a target signal, provided in an embodiment of this application. Figure 1 As shown, the method for determining the radius ratio of this type of target signal may include the following steps: S110. Based on the preset parameter group and their respective target amplitudes, calculate the inner circle probability value and outer circle probability value corresponding to each signal sample point, and classify the signal sample points based on the inner circle probability value, outer circle probability value and preset classification threshold to obtain inner circle radius sample points and outer circle radius sample points; wherein, the signal sample points are multiple sample points obtained by sampling the target signal.

[0026] The target signal refers to the signal whose corresponding constellation diagram is composed of multiple concentric circles, such as the 16APSK signal. 16APSK is an efficient multi-level modulation method. Its constellation diagram is composed of two concentric circles (corresponding to radii r1 and r2 respectively). Several phase points are distributed on each circle (the conventional configuration is 4 points on the inner circle and 12 points on the outer circle). At the receiving end, the demodulator needs to accurately obtain the r1 and r2 values ​​to complete the symbol decision and decoding.

[0027] The preset parameter set is a pre-determined set of initial parameters, including preset inner circle radius values, preset outer circle radius values, preset inner circle variance values, preset outer circle variance values, and preset weighting coefficients. It can be understood as the initial parameter values ​​for radius estimation, so that the radius ratio of the target signal can be iteratively calculated based on the given preset parameter set. In practical applications, a set of initial parameters that is most reasonable, closest to the true distribution, and easiest to converge iteratively can be determined as the preset parameter set according to the prior structure of the 16APSK constellation and the general initialization rules of the Gaussian Mixture Model (GMM).

[0028] The target amplitude is the relative amplitude value obtained after sampling, amplitude extraction and normalization of the target signal. It is obtained by dividing the amplitude of the original signal sample points by the normalization parameter to eliminate the influence of absolute amplitude such as channel gain, transmission attenuation and transmit power, and only retain the relative magnitude relationship between sample points.

[0029] The inner circle probability value is the posterior probability that a single signal sample point belongs to the inner circle symbol of the 16APSK constellation. The larger the value, the higher the confidence that the sample point belongs to the inner circle. The outer circle probability value is the posterior probability that a single signal sample point belongs to the outer circle symbol of the 16APSK constellation. The larger the value, the higher the confidence that the sample point belongs to the outer circle. The sum of the inner circle probability value and the outer circle probability value is always equal to 1.

[0030] The preset classification threshold is a pre-defined probability critical value used to convert continuous probability values ​​into definite sample assignments. It is usually fixed at 0.5. In practical applications, the inner circle probability value and the outer circle probability value are compared with the preset classification threshold respectively. If the inner circle probability value corresponding to the signal sample point is greater than the threshold, it is determined to be an inner circle radius sample point. If the outer circle probability value is greater than the threshold, it is determined to be an outer circle radius sample point. In this way, only high-confidence samples with a probability greater than the threshold are retained, while low-probability and heavily noise-contaminated ambiguous samples are removed, thereby improving the accuracy of radius statistics.

[0031] Based on this, multiple signal sample points are obtained by sampling the target signal, and the target amplitude corresponding to each signal sample point is determined. In order to calculate the inner circle probability value and outer circle probability value corresponding to each signal sample point according to the preset parameter group and their respective target amplitude, the signal sample points are classified based on the inner circle probability value, outer circle probability value and preset classification threshold, thereby obtaining inner circle radius sample points with inner circle probability value greater than preset classification threshold and outer circle radius sample points with outer circle probability value greater than preset classification threshold.

[0032] S120. Based on the target amplitude, sort the inner circle radius sample points and the outer circle radius sample points respectively, and determine the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence.

[0033] The target inner circle radius value refers to the statistical characteristic value used to characterize the ideal amplitude of the inner circle symbols in the 16APSK constellation diagram. This value is calculated using a robust statistical method based on all the inner circle radius sample points obtained through probability classification, sorted according to their corresponding target amplitudes from small to large or from large to small, forming an ordered inner circle radius sequence. It represents the center value of the inner circle symbol amplitude extracted most robustly and reliably from the noisy signal in the current iteration round, serving as the radius corresponding to the inner circle of the signal.

[0034] The target outer radius value is obtained by sorting all the outer radius sample points obtained through probability classification according to their corresponding target amplitude from small to large or from large to small, forming an ordered outer radius sequence. Then, the center value of the outer circle symbol amplitude is further determined as the radius corresponding to the signal outer circle.

[0035] Based on this, by sorting the inner and outer radius sample points respectively, an ordered inner radius sequence and an outer radius sequence are obtained. Then, the center value of the amplitude distribution corresponding to the sequence is further determined, thereby obtaining the target inner radius value and the target outer radius value.

[0036] S130. Calculate the radius change value based on the target inner circle radius value, the target outer circle radius value, and the preset parameter set, and determine the convergence result corresponding to the radius change value based on the preset convergence radius threshold.

[0037] The radius change value refers to the quantitative index obtained by calculating the relative difference between the newly calculated target inner circle radius value and the target outer circle radius value in the current iteration and the preset inner circle radius value and the preset outer circle radius value in the preset parameter group used in the previous iteration. It is used to quantitatively characterize the change of the radius parameter between two iterations. That is, the radius change value is the sum of the relative deviations between the radius of this iteration and the radius of the previous iteration. It is a dimensionless and non-negative value. The smaller the value, the more stable the radius parameter is, and the closer it is to the true value.

[0038] The preset convergence radius threshold is a fixed critical value set in advance to determine whether the radius change value has reached a stable state. It is an extremely small dimensionless positive number that represents the maximum relative fluctuation range of the parameter. When the radius change value is less than this threshold, it is considered that the radius parameter no longer changes significantly, and the iteration has reached a stable convergence state. The smaller the threshold, the smaller the radius change is required, and the higher the accuracy of the output radius ratio.

[0039] The convergence result is the iterative state judgment conclusion obtained by comparing the radius change value with the preset convergence radius threshold. The convergence result includes the radius change value convergence and the radius change value non-convergence. Convergence means that the inner circle radius value and outer circle radius value of the target in this round are sufficiently stable and the difference from the parameters in the previous round is minimal, which can be used as the optimal estimate of the final true radius; non-convergence means that the radius parameter is still in the process of optimization iteration and has not yet reached a stable state, and it is necessary to continue to update the parameters and execute the next round of calculation.

[0040] Based on this, the calculated target inner circle radius value and target outer circle radius value are compared with the preset inner circle radius value and preset outer circle radius value in the preset parameter group to perform a quantitative calculation of the radius change value, and the radius change value is obtained. Based on the preset convergence radius threshold, the convergence result corresponding to the radius change value is judged.

[0041] S140. Based on the convergence results, the inner radius value of the target, and the outer radius value of the target, determine the corresponding target signal radius ratio.

[0042] The target signal radius ratio refers to the dimensionless relative proportion parameter obtained by calculating the ratio of the final stable inner circle radius value to the final stable outer circle radius value after the iterative estimation algorithm reaches the convergence state. That is, the target signal radius ratio = target inner circle radius value ÷ target outer circle radius value, which represents the true relative magnitude relationship between the inner circle symbol amplitude and the outer circle symbol amplitude in the 16APSK constellation diagram.

[0043] Based on this, during the iteration process, the non-converged inner circle radius value and outer circle radius value are still in the state of optimization fluctuation, with large numerical deviations and strong noise influence, and cannot represent the true radius. Only when the convergence result is that the radius change value converges, the radius change between the two iterations is extremely small, the parameters have become stable and close to the true value, and the calculated ratio is accurate and reliable.

[0044] Based on the feasible implementation of S110 described above, this application further provides a method that, before calculating the inner circle probability value and outer circle probability value corresponding to each signal sample point according to the preset parameter set and their respective corresponding target amplitude, includes: The target signal is sampled to obtain multiple signal sample points, and the sum of squares of all signal amplitudes is calculated based on the signal amplitudes corresponding to the signal sample points. Based on the sum of squares, the normalized parameter value corresponding to the signal amplitude is determined, and the target amplitude corresponding to each signal sample point is determined according to the ratio of each signal amplitude to the normalized parameter value.

[0045] The signal amplitude refers to the instantaneous amplitude value corresponding to each signal sample point obtained after discrete sampling of the target signal. It represents the absolute strength of the signal sample point under the current channel conditions and is affected by external factors such as channel gain, transmission attenuation, noise superposition, and transmission power fluctuation. It is the raw amplitude data without any processing.

[0046] The normalization parameter value is a global amplitude normalization coefficient calculated based on the signal amplitude of all signal sample points. It represents the average amplitude of the entire signal segment and is a global scalar coefficient. This enables the uniform mapping of all original signal amplitudes to a standard amplitude space that is independent of absolute intensity and only retains the relative proportion, so as to unify the amplitude of all sample points to the standard amplitude range.

[0047] Therefore, in practical applications, in order to eliminate the effect of channel gain on the amplitude of signal sample points... The influence of the inner circle Outer radius The estimation is independent of the absolute amplitude and can be obtained by analyzing the baseband signal. Calculate the normalization coefficient C: ; Where N is the baseband signal The number of points, k is the sample point number.

[0048] The normalized amplitude of the signal is then: ; This allows us to determine the target amplitude corresponding to each signal sample point.

[0049] Based on the feasible implementation of S110 described above, this application further provides a preset parameter set including a preset inner circle radius value, a preset outer circle radius value, a preset inner circle variance value, a preset outer circle variance value, and a preset weight coefficient. Based on the preset parameter set and its corresponding target amplitude, calculate the inner circle probability value and outer circle probability value for each signal sample point, including: Substituting the inner circle probability parameter set and the outer circle probability parameter set into the Gaussian probability density function respectively, we obtain the initial inner circle probability value and the initial outer circle probability value corresponding to each signal sample point; wherein, the inner circle probability parameter set includes the target amplitude, the preset inner circle radius value and the preset inner circle variance value, and the outer circle probability parameter set includes the target amplitude, the preset outer circle radius value and the preset outer circle variance value; Based on the preset weighting coefficients, the initial inner circle probability value, and the initial outer circle probability value, calculate the corresponding inner circle probability value and outer circle probability value.

[0050] The preset inner radius value refers to a fixed initial value set in advance, which is used to represent the ideal amplitude center of the inner circle symbol of the 16APSK constellation diagram. It is the initial mean value of the Gaussian component of the inner circle in the Gaussian mixture model. This value is set in advance according to the standard 16APSK constellation structure. The preset outer radius value is the ideal amplitude center of the outer circle symbol of the 16APSK constellation diagram.

[0051] The preset inner circle variance value is a quantitative representation of the initial dispersion of the inner circle Gaussian components, which is used to describe the distribution width of the inner circle symbol amplitude near the ideal mean, reflecting the initial assumption strength of noise and disturbance, and thus serving as the inner circle variance input of the Gaussian probability density function to control the steepness of the inner circle probability distribution; while the preset outer circle variance value is a quantitative representation of the initial dispersion of the outer circle Gaussian components, which is also predetermined.

[0052] The preset weight coefficient refers to the pre-set proportion of the inner circle symbol in all 16 APSK symbols. In practical applications, the standard 16 APSK has 4 points in the inner circle and 12 points in the outer circle, so the weight is usually preset to 0.25.

[0053] The Gaussian probability density function is the standard probability function that describes the normal distribution of a continuous random variable around its mean. It is used to model the noise distribution of the sample amplitude under a given radius.

[0054] The initial inner circle probability value is the likelihood probability obtained by substituting the target amplitude, preset inner circle radius, and preset inner circle variance into the Gaussian probability density function. It represents the probability of a sample point appearing when only the inner circle distribution is considered, without weight normalization.

[0055] The initial outer circle probability value is the likelihood probability obtained by substituting the target amplitude, preset outer circle radius, and preset outer circle variance into the Gaussian probability density function. It represents the probability of a sample point appearing when only the outer circle distribution is considered, without weight normalization.

[0056] Based on this, in practical applications, the posterior probability of each sample belonging to the inner or outer circle component can be calculated. , :

[0057]

[0058] in, This indicates that the mean is u and the variance is calculated. The normal probability distribution function value at signal sample point A; inner radius. Outer radius Inner circle variance outer circle variance Weighting coefficient .

[0059] Based on the feasible implementation of S120 described above, this application further provides a method for determining the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence, including: The target inner circle radius value and the target outer circle radius value are determined based on the median of the inner circle radius sequence and the outer circle radius sequence, respectively.

[0060] Based on this, by sorting the inner and outer radius sample points according to the target amplitude from smallest to largest or from largest to smallest, an ordered sequence is formed. The median value of the middle position of this sequence is taken as the sequence median. The median of the inner radius sequence is determined as the target inner radius value, and the median of the outer radius sequence is determined as the target outer radius value. The sequence median is a statistic specifically used to robustly extract the radius center from noisy and disturbed samples. It is different from the mean, which is easily affected by noise, and has the ability to resist outliers.

[0061] Based on the feasible implementation of S130 described above, this application further provides a method for calculating the radius change value based on the target inner circle radius value, the target outer circle radius value, and a preset parameter set, including: Based on the preset inner circle radius value and preset outer circle radius value in the preset parameter group, calculate the difference between the target inner circle radius value and the preset inner circle radius value, and between the target outer circle radius value and the preset outer circle radius value, respectively, and sum the differences to obtain the target radius difference; Based on the sum of the preset inner circle radius value and the preset outer circle radius value, the ratio between the target radius difference and the sum is calculated to obtain the radius change value.

[0062] Therefore, in practical applications, the radius change value can be expressed as follows: This indicates that the preset inner circle radius is r1, the preset outer circle radius is r2, and the target inner circle radius is r1. The target outer radius value is ,but:

[0063] Thus, the radius change value can be calculated.

[0064] Based on the feasible implementation of S130 described above, this application further provides a method for determining the convergence result corresponding to the radius change value based on a preset convergence radius threshold, including: By comparing the radius change value with the preset convergence radius threshold value, the corresponding comparison result is obtained; If the comparison result shows that the radius change value is less than the preset convergence radius threshold, then the corresponding convergence result is determined to be the radius change value convergence. If the comparison result shows that the radius change value is not less than the preset convergence radius threshold, then the corresponding convergence result is determined to be that the radius change value does not converge.

[0065] Based on this, by quantifying and comparing the numerical relationship between the radius change value and the convergence threshold, it can be determined whether the iterative optimization process has reached a stable state, that is, whether the radius change value has converged. During the iteration process, the radius value is constantly being optimized and changing. Only when the change is small enough to be ignored, that is, less than the threshold, can it be said that the parameter no longer jumps, is no longer affected by noise, and has approached the true value.

[0066] Based on the feasible implementation of S140 described above, this application further provides a method for determining the corresponding target signal radius ratio based on the convergence result, the target inner radius value, and the target outer radius value, including: Determine the convergence result; If the convergence result is that the radius change value converges, then the target signal radius ratio is determined based on the ratio of the inner radius value to the outer radius value of the target. If the convergence result indicates that the radius change value does not converge, then the target inner circle radius value is determined as the updated inner circle radius value, and the target outer circle radius value is determined as the updated outer circle radius value. Based on the updated inner circle radius value, the updated outer circle radius value, and the target amplitude, the updated inner circle variance value, the updated outer circle variance value, and the updated weight coefficient are calculated to obtain the corresponding updated parameter set. Based on the updated parameter set, the corresponding updated radius change value is iteratively calculated to obtain the target radius change value, and based on the target radius change value, the target signal radius ratio is calculated. Among these, the target radius change value is the converged updated radius change value.

[0067] The updated inner circle radius value is the inner circle radius parameter used in the new iteration when the convergence result of the current round of the iterative estimation algorithm is non-convergent. It is the target inner circle radius value obtained by the sequence median statistics in this round, which is directly assigned to the new round of iteration. It is an optimization and replacement of the preset inner circle radius value in the previous round, and represents a better and closer estimation result to the true value of the inner circle radius of 16APSK after this round of iteration.

[0068] Updating the outer radius value means that when the convergence result is non-convergence, the target outer radius value obtained in this round of statistics is used as the outer radius parameter for the next round of iteration.

[0069] The updated inner circle variance value refers to the new variance parameter used to describe the dispersion of the inner circle amplitude distribution when the convergence result fails to converge. It is obtained by recalculating the updated inner circle radius value, target amplitude, and inner circle probability value of each sample point. It is the new variance of the inner circle Gaussian distribution in the next round. The updated outer circle variance value is the new variance of the outer circle distribution obtained by recalculating the updated outer circle radius value, target amplitude, and outer circle probability value.

[0070] Furthermore, in practical applications, the inner circle variance outer circle variance ,but:

[0071]

[0072] The updated weighting coefficients refer to the new prior proportion coefficients recalculated based on the probability weighting ratio of the inner and outer circle samples in this round. These coefficients reflect the actual proportions of inner and outer circle symbols in the current signal and replace the original preset weighting coefficients. In practical applications, the weighting coefficients... ,but:

[0073] N is the baseband signal. The number of points, k is the sample point number.

[0074] The updated parameter set is a complete new set of parameters for the next round of iteration, consisting of updated inner circle radius values, updated outer circle radius values, updated inner circle variance values, updated outer circle variance values, and updated weight coefficients, when the convergence result is non-convergence.

[0075] Iterative calculation refers to the process of repeatedly calculating the change value of the updated radius when the convergence result is non-convergence, using the updated parameter set as the new given parameter set. When the change value of the updated radius satisfies the convergence iteration, that is, when the change value of the updated radius converges, the target inner circle radius value and the target outer circle radius value corresponding to the target radius change value that meets the convergence condition are used to calculate the corresponding target signal radius ratio.

[0076] Based on this, if the convergence result is that the radius change value converges, the target signal radius ratio can be determined directly based on the ratio of the inner radius value to the outer radius value. If the convergence result is that the radius change value does not converge, the corresponding update parameter set is determined by the inner and outer radius values ​​of the target, so as to recalculate the radius change value and judge convergence until the radius change value reaches the convergence state, and finally output the target signal radius ratio.

[0077] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a method for determining the radius ratio of a target signal according to an embodiment of this application; as shown. Figure 2 As shown, the target signal is amplitude normalized to eliminate the influence of channel gain. The GMM model parameters, including inner and outer circle radii, variance, and weights, are initialized. Then, the EM iteration loop is entered. In the E step, the posterior probability of each signal sample point belonging to the inner and outer circles is calculated. In the M step, the radius, variance, and weight parameters are updated based on the probability, and it is determined whether the parameters converge. If they do not converge, the iteration returns to the E step. If they converge, the final ratio of the two radii is output.

[0078] Based on the above steps, it can be seen that this application calculates the inner and outer circle probability values ​​corresponding to each signal sample point based on the preset parameter set and the target amplitude, and classifies the samples in combination with the classification threshold, thereby achieving accurate division of inner and outer circle signal samples when noise causes the signal amplitude distribution to overlap. Furthermore, sorting the inner and outer circle sample points separately based on the target amplitude and determining the target inner and outer circle radius values ​​can suppress the influence of noise and outliers, improving the accuracy and stability of radius estimation. Calculating the radius change value based on the target radius value and the preset parameter set, and judging the convergence result in combination with the convergence threshold, can continuously approximate the true radius parameter through iterative optimization, ensuring the convergence and computational efficiency of parameter estimation. Determining the target signal radius ratio by combining the convergence result with the target inner and outer circle radius values ​​can output a relative radius parameter unaffected by channel gain, providing the demodulator with accurate symbol decision criteria and effectively improving the overall performance of 16APSK signal reception and demodulation under low signal-to-noise ratio conditions. This avoids information loss caused by preprocessing, utilizes the EM optimization algorithm for statistical robustness optimization, and introduces robust statistics such as the median and corrected estimators in parameter estimation to suppress the influence of noise.

[0079] Figure 3 This is a schematic diagram of a target signal radius ratio determination device provided in an embodiment of this application. Figure 3 As shown, the target signal radius ratio determination device includes: a classification module, a sorting module, a calculation module, and a determination module; wherein: The classification module is used to calculate the inner circle probability value and outer circle probability value corresponding to each signal sample point according to the preset parameter group and their respective target amplitude, and classify the signal sample points based on the inner circle probability value, outer circle probability value and preset classification threshold to obtain inner circle radius sample points and outer circle radius sample points; wherein, the signal sample point is multiple sample points obtained by sampling the target signal; The sorting module is used to sort the inner circle radius sample points and the outer circle radius sample points based on the target amplitude, and to determine the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence. The calculation module is used to calculate the radius change value based on the target inner circle radius value, the target outer circle radius value and the preset parameter set, and determine the convergence result corresponding to the radius change value based on the preset convergence radius threshold. The determination module is used to determine the corresponding target signal radius ratio based on the convergence result, the target inner circle radius value, and the target outer circle radius value.

[0080] In this embodiment of the application, other modules of the target signal radius ratio determination device may also be specifically used for: The target signal is sampled to obtain multiple signal sample points, and the sum of squares of all signal amplitudes is calculated based on the signal amplitudes corresponding to the signal sample points. Based on the sum of squares, the normalized parameter value corresponding to the signal amplitude is determined, and the target amplitude corresponding to each signal sample point is determined according to the ratio of each signal amplitude to the normalized parameter value.

[0081] In this embodiment of the application, the classification module can also be specifically used for: Substituting the inner circle probability parameter set and the outer circle probability parameter set into the Gaussian probability density function respectively, we obtain the initial inner circle probability value and the initial outer circle probability value corresponding to each signal sample point; wherein, the inner circle probability parameter set includes the target amplitude, the preset inner circle radius value and the preset inner circle variance value, and the outer circle probability parameter set includes the target amplitude, the preset outer circle radius value and the preset outer circle variance value; Based on the preset weighting coefficients, the initial inner circle probability value, and the initial outer circle probability value, calculate the corresponding inner circle probability value and outer circle probability value.

[0082] In this embodiment of the application, the sorting module can also be specifically used for: The target inner circle radius value and the target outer circle radius value are determined based on the median of the inner circle radius sequence and the outer circle radius sequence, respectively.

[0083] In this embodiment of the application, the calculation module can also be specifically used for: Based on the preset inner circle radius value and preset outer circle radius value in the preset parameter group, calculate the difference between the target inner circle radius value and the preset inner circle radius value, and between the target outer circle radius value and the preset outer circle radius value, respectively, and sum the differences to obtain the target radius difference; Based on the sum of the preset inner circle radius value and the preset outer circle radius value, the ratio between the target radius difference and the sum is calculated to obtain the radius change value.

[0084] In this embodiment of the application, the calculation module can also be specifically used for: By comparing the radius change value with the preset convergence radius threshold value, the corresponding comparison result is obtained; If the comparison result shows that the radius change value is less than the preset convergence radius threshold, then the corresponding convergence result is determined to be the radius change value convergence. If the comparison result shows that the radius change value is not less than the preset convergence radius threshold, then the corresponding convergence result is determined to be that the radius change value does not converge.

[0085] In this embodiment of the application, the determining module can also be specifically used for: Determine the convergence result; If the convergence result is that the radius change value converges, then the target signal radius ratio is determined based on the ratio of the inner radius value to the outer radius value of the target. If the convergence result indicates that the radius change value does not converge, then the target inner circle radius value is determined as the updated inner circle radius value, and the target outer circle radius value is determined as the updated outer circle radius value. Based on the updated inner circle radius value, the updated outer circle radius value, and the target amplitude, the updated inner circle variance value, the updated outer circle variance value, and the updated weight coefficient are calculated to obtain the corresponding updated parameter set. Based on the updated parameter set, the corresponding updated radius change value is iteratively calculated to obtain the target radius change value, and based on the target radius change value, the target signal radius ratio is calculated. Among these, the target radius change value is the converged updated radius change value.

[0086] Figure 4 This is a schematic diagram of the structure of an apparatus for performing a method for determining the radius ratio of a target signal according to an embodiment of this application. Figure 4 As shown, the device includes: The device may include one or more processors with processing cores, one or more computer-readable storage media such as memory, communication components, etc. The processor, memory, and communication components are connected via a bus.

[0087] In the specific implementation process, at least one processor executes computer execution instructions stored in memory, causing at least one processor to execute the above-described method for determining the radius ratio of a target signal.

[0088] The specific implementation process of the processor can be found in the above method embodiments, and its implementation principle and technical effect are similar, so it will not be repeated here.

[0089] Furthermore, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0090] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0091] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0092] In some embodiments, a computer program product is also provided, comprising a computer program or instructions that, when executed by a processor, implement the steps in the method for determining the radius ratio of any of the target signals described above.

[0093] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0094] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0095] Therefore, embodiments of this application provide a computer-readable storage medium storing a plurality of program codes that can be loaded by a processor to execute the steps in any of the target signal radius ratio determination methods provided in embodiments of this application.

[0096] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0097] According to one aspect of this application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium.

[0098] Since the instructions stored in the storage medium can execute the steps in any of the target signal radius ratio determination methods provided in the embodiments of this application, the beneficial effects that any of the target signal radius ratio determination methods provided in the embodiments of this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0099] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope of this application is indicated by the appended claims.

[0100] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for determining the radius ratio of a target signal, characterized in that, The method includes: Based on the preset parameter set and its corresponding target amplitude, the inner circle probability value and outer circle probability value corresponding to each signal sample point are calculated. Based on the inner circle probability value, the outer circle probability value and the preset classification threshold, the signal sample points are classified to obtain inner circle radius sample points and outer circle radius sample points; wherein, the signal sample points are multiple sample points obtained by sampling the target signal. Based on the target amplitude, the inner circle radius sample points and the outer circle radius sample points are sorted respectively, and based on the sorted inner circle radius sequence and outer circle radius sequence, the corresponding target inner circle radius value and target outer circle radius value are determined. Based on the target inner circle radius value, the target outer circle radius value, and the preset parameter set, the radius change value is calculated, and based on the preset convergence radius threshold, the convergence result corresponding to the radius change value is determined; Based on the convergence result, the inner radius value of the target, and the outer radius value of the target, the corresponding target signal radius ratio is determined.

2. The method according to claim 1, characterized in that, Before calculating the inner circle probability value and outer circle probability value corresponding to each signal sample point based on the preset parameter set and their respective target amplitudes, the method further includes: The target signal is sampled to obtain multiple signal sample points, and the sum of squares of all signal amplitudes is calculated based on the signal amplitudes corresponding to the signal sample points. Based on the sum of squares, the normalized parameter value corresponding to the signal amplitude is determined, and the target amplitude corresponding to each signal sample point is determined according to the ratio of each signal amplitude to the normalized parameter value.

3. The method according to claim 1, characterized in that, The preset parameter set includes a preset inner circle radius value, a preset outer circle radius value, a preset inner circle variance value, a preset outer circle variance value, and a preset weighting coefficient; The step of calculating the inner circle probability value and outer circle probability value corresponding to each signal sample point based on the preset parameter set and their corresponding target amplitude includes: Substituting the inner circle probability parameter set and the outer circle probability parameter set into the Gaussian probability density function respectively, the initial inner circle probability value and the initial outer circle probability value corresponding to each of the signal sample points are obtained; wherein, the inner circle probability parameter set includes the target amplitude, the preset inner circle radius value and the preset inner circle variance value, and the outer circle probability parameter set includes the target amplitude, the preset outer circle radius value and the preset outer circle variance value; Based on the preset weighting coefficient, the initial inner circle probability value, and the initial outer circle probability value, the corresponding inner circle probability value and outer circle probability value are calculated.

4. The method according to claim 1, characterized in that, The determination of the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence includes: The target inner radius value and the target outer radius value are determined based on the median of the inner radius sequence and the outer radius sequence, respectively.

5. The method according to claim 1, characterized in that, The step of calculating the radius change value based on the target inner radius value, the target outer radius value, and the preset parameter set includes: Based on the preset inner circle radius value and preset outer circle radius value in the preset parameter group, calculate the difference between the target inner circle radius value and the preset inner circle radius value, and between the target outer circle radius value and the preset outer circle radius value, respectively, and sum the differences to obtain the target radius difference; Based on the sum of the preset inner radius value and the preset outer radius value, the ratio between the target radius difference and the sum is calculated to obtain the radius change value.

6. The method according to claim 1, characterized in that, The step of determining the convergence result corresponding to the radius change value based on a preset convergence radius threshold includes: By comparing the value of the radius change with the value of the preset convergence radius threshold, the corresponding comparison result is obtained; If the comparison result is that the radius change value is less than the preset convergence radius threshold, then the corresponding convergence result is determined to be that the radius change value has converged. If the comparison result indicates that the radius change value is not less than the preset convergence radius threshold, then the corresponding convergence result is determined to be that the radius change value does not converge.

7. The method according to claim 1, characterized in that, The step of determining the corresponding target signal radius ratio based on the convergence result, the target inner radius value, and the target outer radius value includes: Determine the convergence result; If the convergence result is that the radius change value converges, then the target signal radius ratio is determined according to the ratio of the inner radius value of the target to the outer radius value of the target; If the convergence result indicates that the radius change value does not converge, then the target inner circle radius value is determined to be the updated inner circle radius value, and the target outer circle radius value is determined to be the updated outer circle radius value. Based on the updated inner circle radius value, the updated outer circle radius value, and the target amplitude, the updated inner circle variance value, the updated outer circle variance value, and the updated weight coefficient are calculated to obtain the corresponding updated parameter set. Based on the updated parameter set, the corresponding updated radius change value is iteratively calculated to obtain the target radius change value, and the target signal radius ratio is calculated based on the target radius change value. Wherein, the target radius change value is the converged updated radius change value.

8. A device for determining the radius ratio of a target signal, characterized in that, The device includes: The classification module is used to calculate the inner circle probability value and outer circle probability value corresponding to each signal sample point according to the preset parameter group and their respective target amplitude, and classify the signal sample points based on the inner circle probability value, the outer circle probability value and the preset classification threshold to obtain inner circle radius sample points and outer circle radius sample points; wherein, the signal sample points are multiple sample points obtained by sampling the target signal; The sorting module is used to sort the inner circle radius sample points and the outer circle radius sample points respectively based on the target amplitude, and determine the corresponding target inner circle radius value and target outer circle radius value based on the sorted inner circle radius sequence and outer circle radius sequence; The calculation module is used to calculate the radius change value based on the target inner circle radius value, the target outer circle radius value and the preset parameter set, and determine the convergence result corresponding to the radius change value based on the preset convergence radius threshold. The determination module is used to determine the corresponding target signal radius ratio based on the convergence result, the target inner circle radius value, and the target outer circle radius value.

9. A computer device, characterized in that, include: One or more processors; Memory; One or more programs, wherein the one or more programs are stored in memory and configured to be executed by one or more processors, the one or more programs being configured to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program code that can be called by a processor to perform the method as described in any one of claims 1 to 7.

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