A Method, Device, Electronic Device and Storage Medium for Timing Synchronization of Signals

Abstract

The present application discloses a method, apparatus, electronic device, and storage medium for timing synchronization of signals, belonging to the field of satellite communication technology. The method includes: sampling an acquired test signal to obtain a sampled signal, determining upper and lower threshold values for double-threshold signal acquisition based on the distribution interval of the noise variance of the sampled signal, performing uncertainty estimation on the noise variance in the sampled signal to obtain a lower limit estimate value and an upper limit estimate value of the distribution interval, correcting the upper and lower threshold values based on the lower limit estimate value and the upper limit estimate value, using the corrected upper and lower threshold values for double-threshold signal acquisition, determining a capture error representing the number of sampling points advanced or delayed based on the capture result, and performing timing synchronization on the acquired first signal based on the capture error. In this way, considering the difference between the measurement partition interval and the estimation partition interval of the noise variance, the influence of noise distribution uncertainty on signal capture performance can be eliminated to a certain extent, thereby improving the timing synchronization effect.

Description

Technical Field

[0001] This application relates to the field of satellite communication technologies, and in particular, to a method, apparatus, electronic device, and storage medium for signal timing synchronization. Background Art

[0002] In high-dynamic satellite communication scenarios, accurately capturing signals is of great significance for subsequent receivers to demodulate correct signal data. Energy detection is widely used in signal capture due to its low complexity.

[0003] Generally, the threshold for signal capture based on energy detection depends on the noise variance. In related technologies, the threshold for signal capture based on energy detection is pre-determined by technicians according to the measured noise variance of the signal. However, in actual transceiver links, the noise variance changes with time progression and physical coordinate changes. The resulting uncertainty in noise distribution will directly affect the robustness of signal capture results, making the capture performance less than satisfactory and further affecting subsequent signal timing synchronization. Summary of the Invention

[0004] Embodiments of this application provide a method, apparatus, electronic device, and storage medium for signal timing synchronization to solve the problem in related technologies that the signal capture performance based on energy detection is poor and affects timing synchronization.

[0005] In a first aspect, embodiments of this application provide a method for signal timing synchronization, including:

[0006] Sampling an acquired test signal to obtain a sampled signal;

[0007] Determining upper and lower threshold values for double-threshold signal capture based on the distribution interval of the noise variance of the sampled signal;

[0008] Performing uncertainty estimation on the noise variance in the sampled signal to obtain a lower estimated value and an upper estimated value of the distribution interval;

[0009] Correcting the upper and lower threshold values based on the lower estimated value and the upper estimated value;

[0010] Performing double-threshold signal capture using the corrected upper and lower threshold values, and determining a capture error based on the capture result, where the capture error is used to represent the number of sampling points advanced or delayed;

[0011] Performing timing synchronization on the acquired first signal based on the capture error.

[0012] In some embodiments, performing uncertainty estimation on the noise variance in the sampled signal to obtain a lower estimated value and an upper estimated value of the distribution interval includes:

[0013] Group the sampled signals to obtain K groups of signal samples, where K is an integer greater than 1;

[0014] Perform maximum likelihood estimation on the noise variances of the K groups of signal samples to obtain variance estimation values;

[0015] Based on the variance estimation values of the K groups of signal samples, determine the lower limit estimation value and the upper limit estimation value.

[0016] In some embodiments, determining the lower limit estimation value and the upper limit estimation value based on the variance estimation values of the K groups of signal samples includes:

[0017] Calculate the first mean of the variance estimation values of the K groups of signal samples;

[0018] Calculate the second mean of the variance estimation values of the K groups of signal samples when K approaches infinity;

[0019] Based on the first mean, the second mean, and the noise variance of the sampled signal, determine the lower limit estimation value and the upper limit estimation value.

[0020] In some embodiments, correcting the upper and lower threshold values based on the lower limit estimation value and the upper limit estimation value includes:

[0021] Using the lower limit estimation value as the lower limit of the interval and the upper limit estimation value as the upper limit of the interval to obtain an estimation interval, and determining a first floating value based on the lower limit estimation value and a second floating value based on the upper limit estimation value;

[0022] Use the first floating value to lower the lower limit estimation value, use the second floating value to lower the upper limit estimation value to obtain an estimation interval, and use the first floating value to raise the lower limit estimation value and use the second floating value to raise the upper limit estimation value to obtain an estimation interval;

[0023] Use each estimation interval to correct the upper and lower threshold values respectively.

[0024] In some embodiments, it further includes:

[0025] Determine the timing error of the sampled signal;

[0026] Based on the timing error, determine the interpolation base point and the interpolation coefficient;

[0027] Based on the interpolation coefficient, construct L Lagrange interpolation polynomials, where L is an integer greater than 1;

[0028] Based on the capture error, perform timing synchronization on the acquired first signal, including:

[0029] Extract L groups of signals from the signal after the first signal matched filtering based on the capture error and the interpolation base points;

[0030] Perform Lagrange interpolation processing on the L groups of signals based on the L Lagrange interpolation polynomials to obtain the signal after timing synchronization.

[0031] In a second aspect, an embodiment of the present application provides a timing synchronization device for a signal, including:

[0032] A sampling module, configured to sample an acquired test signal to obtain a sampled signal;

[0033] A determination module, configured to determine upper and lower threshold values for double-threshold signal capture based on the distribution interval of the noise variance of the sampled signal;

[0034] An estimation module, configured to perform uncertainty estimation on the noise variance in the sampled signal to obtain a lower limit estimated value and an upper limit estimated value of the distribution interval;

[0035] A correction module, configured to correct the upper and lower threshold values based on the lower limit estimated value and the upper limit estimated value;

[0036] An analysis module, configured to perform double-threshold signal capture using the corrected upper and lower threshold values, and determine a capture error based on the capture result, where the capture error is used to represent the number of sampling points advanced or delayed;

[0037] A synchronization module, configured to perform timing synchronization on the acquired first signal based on the capture error.

[0038] In some embodiments, the estimation module is specifically configured to:

[0039] Group the sampled signal to obtain K groups of signal samples, where K is an integer greater than 1;

[0040] Perform maximum likelihood estimation on the noise variance of the K groups of signal samples to obtain a variance estimated value;

[0041] Determine the lower limit estimated value and the upper limit estimated value based on the variance estimated values of the K groups of signal samples.

[0042] In some embodiments, the estimation module is specifically configured to:

[0043] Calculate a first mean value of the variance estimated values of the K groups of signal samples;

[0044] Calculate a second mean value of the variance estimated values of the K groups of signal samples when K approaches infinity;

[0045] Determine the lower limit estimate value and the upper limit estimate value based on the first mean value, the second mean value, and the noise variance of the sampling signal.

[0046] In some embodiments, the correction module is specifically configured to:

[0047] Use the lower limit estimate value as the lower limit of the interval and the upper limit estimate value as the upper limit of the interval to obtain an estimated interval, determine a first floating value based on the lower limit estimate value, and determine a second floating value based on the upper limit estimate value;

[0048] Use the first floating value to lower the lower limit estimate value, use the second floating value to lower the upper limit estimate value to obtain an estimated interval, and use the first floating value to raise the lower limit estimate value and use the second floating value to raise the upper limit estimate value to obtain an estimated interval;

[0049] Use each estimated interval to correct the upper and lower threshold values respectively.

[0050] In some embodiments, it further includes:

[0051] A preprocessing module, configured to determine the timing error of the sampling signal; based on the timing error, determine the interpolation base point and the interpolation coefficient; based on the interpolation coefficient, construct L Lagrange interpolation polynomials, where L is an integer greater than 1;

[0052] The synchronization module is specifically configured to extract L groups of signals from the signal after the first signal matched filtering based on the capture error and the interpolation base point; perform Lagrange interpolation processing on the L groups of signals based on the L Lagrange interpolation polynomials to obtain the signal after timing synchronization.

[0053] In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor, and a memory communicatively connected to the at least one processor, where:

[0054] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the above-mentioned signal timing synchronization method.

[0055] In a fourth aspect, an embodiment of the present application provides a storage medium, when the computer program in the storage medium is executed by a processor of an electronic device, the electronic device can execute the above-mentioned signal timing synchronization method.

[0056] In the embodiments of the present application, the acquired test signal is sampled to obtain a sampled signal. Based on the distribution interval of the noise variance of the sampled signal, the upper and lower threshold values for dual-threshold signal capture are determined. The uncertainty of the noise variance in the sampled signal is estimated to obtain the lower and upper estimated values of the distribution interval. Based on the lower and upper estimated values, the upper and lower threshold values are corrected. The corrected upper and lower threshold values are used for dual-threshold signal capture. Based on the capture result, the capture error is determined. Based on the capture error, timing synchronization is performed on the acquired first signal, where the capture error is used to represent the number of sampling points advanced or delayed. In this way, considering the difference between the measured partition interval and the estimated partition interval of the noise variance, the influence of the noise distribution uncertainty on the signal capture performance is eliminated, and thus the timing synchronization effect can be improved. Description of the Drawings

[0057] The drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0058] Figure 1 It is a flowchart of a method for timing synchronization of a signal provided by an embodiment of the present application;

[0059] Figure 2 It is a flowchart of a method for determining the lower and upper estimated values of the distribution interval provided by an embodiment of the present application;

[0060] Figure 3 It is a flowchart of another method for timing synchronization of a signal provided by an embodiment of the present application;

[0061] Figure 4 It is a schematic structural diagram of a device for timing synchronization of a signal provided by an embodiment of the present application;

[0062] Figure 5 It is a schematic hardware structure diagram of an electronic device for implementing the method for timing synchronization of a signal provided by an embodiment of the present application. Detailed Embodiments

[0063] To solve the problem in the related art that the signal capture performance based on energy detection is poor and affects timing synchronization, the embodiments of the present application provide a method, a device, an electronic device, and a storage medium for timing synchronization of a signal.

[0064] The following describes the preferred embodiments of the present application with reference to the accompanying drawings of the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application. And without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0065] For the convenience of understanding the present application, in the technical terms related to the present application:

[0066] False alarm probability: Since noise always objectively exists, when the amplitude of the noise signal exceeds the detection threshold, the detection device or system will be misjudged as detecting a target, and this error is called a false alarm, and the probability of its occurrence is called the false alarm probability.

[0067] In the related art, the threshold of signal capture based on energy detection is pre-determined by a technician according to the noise variance of the signal. It does not consider the difference between the estimated value and the measured value of the noise, nor does it adaptively correct the decision threshold. Therefore, there is still room for optimization in improving the performance of signal capture based on energy detection. In addition, the feedforward timing method based on interpolation filtering usually has fewer interpolation points and lower reliability of interpolation coefficients, resulting in difficulty in obtaining the optimal sampling point after timing processing.

[0068] In view of this, the embodiments of the present application provide a multi-threshold capture and non-linear interpolation timing synchronization method based on noise distribution estimation, aiming to improve the robustness and reliability of signal capture, and obtaining the optimal sampling point in symbol timing synchronization by means of multi-point interpolation of Lagrange cubic interpolation coefficients.

[0069] Specifically, the multi-threshold capture and non-linear interpolation timing synchronization method based on noise distribution estimation provided by the embodiments of the present application includes the following steps:

[0070] Step 1: Assume that the short-time burst signal received by the receiver can be expressed as:

[0071]

[0072] where solution1 represents the scenario with an effective signal, solution2 represents the scenario with only noise, s(n) is the effective signal, and in the case of non-coherent detection, it can be regarded as a Gaussian process with a mean of λ(n) is the channel noise, which can be regarded as a Gaussian process with a mean of 0 and a variance of n = 1,..., N, and N is the number of sampling points.

[0073] Based on this, the signal energy can be obtained as:

[0074] Step 2: Since the number of sampling points of the short-time burst signal by the receiver is usually large, according to the central limit theorem, s(n) approximately follows a Gaussian distribution, that is where is the signal-to-noise ratio of the received signal.

[0075] Step 3. Based on the signal distribution in Step 2, calculate the false alarm probability P f which is:

[0076]

[0077] where is the non-integral function of normal Gaussian, and η is the decision threshold.

[0078] Step 4. Calculate the upper and lower threshold values of the signal catcher based on the distribution interval of the noise variance . Specifically, it includes the following steps:

[0079] Step 4(1). Assume that the channel noise variance Define the uncertainty of the noise as where is the variance of λ(n), is the minimum variance of λ(n), is the maximum variance of λ(n). Based on this, we can get

[0080] Step 4(2). Based on the value range, the upper and lower threshold values of the double-threshold signal catcher can be calculated as follows:

[0081]

[0082] where is 's inverse function.

[0083] Step 5. Calculate the uncertainty estimation interval of the noise variance based on the grouped signal sample variance. Specifically, it includes the following steps:

[0084] Step 5(1). Assume that the noise variance is uniformly distributed in the interval . Input the received signal x(n) (n = 1,..., N) into a K×M (K*M = N) grouper to obtain K groups of signal samples. Each group of signal samples contains M signal samples, where x ij (i = 1,..., K; j = 1,..., M) represents the jth sampling point in the ith group of signal samples.

[0085] Step 5(2). Perform maximum likelihood estimation on the ith group of signal samples, and its variance can be obtained as Traverse the K groups of signal samples to obtain the variance set of the signal samples which are independent of each other and follow a uniform distribution;

[0086] Step 5(3). Calculate the mathematical expectation E K of the variances of the K groups of sample signals, By the weak law of large numbers, we have: where ε is an arbitrary real number greater than 0, Based on this, when K → +∞,

[0087] Step Five (Four): On the basis of Step Five (Three), according to the uncertainty of the noise we can obtain and combining we can calculate the interval upper and lower limit estimates of the noise variance as:

[0088]

[0089] where and are respectively and the estimates of.

[0090] Step Six: Based on and obtain 3 groups of decision threshold boundary values of the double-threshold signal capturer. Specifically, it includes the following steps:

[0091] Step Six (One): The difference between the measured noise variance boundary value and the estimated boundary value of the noise variance is:

[0092]

[0093] Step Six (Two): On the basis of Step Six (One), by the central limit theorem, we know that can be regarded as a normal process, and

[0094] Step Six (Three): On the basis of Step Six (Two), respectively take 3 groups of noise variance noise uncertainty intervals, that is and

[0095] Step Six (Four): On the basis of Step Six (Three), combining the calculation formulas of threshold L and threshold H we can obtain the following three groups of decision thresholds:

[0096]

[0097] Step 7: Input the decision thresholds Ω1, Ω2, and Ω3 into the dual-threshold signal capturer based on energy detection to obtain three decision results. Then, fuse the three decision results through the majority criterion to obtain the final capture result, denoted as toa, representing the number of sampling points by which the received signal is advanced / delayed.

[0098] Step 8: Calculate the timing error σ time , where L is the number of symbols in x(n), and x * (n) is the conjugate operation of x(n). On this basis, determine the interpolation base points mk and interpolation coefficients uk according to the O&M algorithm.

[0099] Step 9: Calculate the Lagrange cubic interpolator coefficients Coe f (f = 1, …, 4) as follows:

[0100]

[0101] Step 10: Assume that the output signal after the matched filter is rx_match_sig, and extract four groups of signals from rx_match_sig in sequence according to the following rules:

[0102]

[0103] where is the h-th group of sub-signal data extracted, interp is the interpolation multiple, and len is the length of the signal data after removing the guard interval.

[0104] Step 11: Based on Step 10, perform Lagrange interpolation on every four extracted signals to obtain the output signal sig_out after timing synchronization.

[0105] In the embodiment of the present application, in the signal capturer based on dual-threshold energy detection, the decision threshold is adaptively set by calculating the difference between the estimated value and the measured value of the noise distribution to improve the robustness and reliability of the decision. In the subsequent symbol timing synchronization, the designed Lagrange multi-point cubic interpolator is also used to overcome the problem of inaccurate acquisition of the optimal sampling point in traditional symbol synchronization.

[0106] Figure 1 This is a flowchart of a method for timing synchronization of a signal provided by an embodiment of the present application. This method is applied to a receiver, and the method includes the following steps.

[0107] In step 101, sample the acquired test signal to obtain a sampled signal.

[0108] Among them, the test signal can be a short-time burst signal or not a short-time burst signal.

[0109] Assume that the test signal is represented after sampling as:

[0110]

[0111] Among them, solution1 represents the scenario where there is a valid signal, solution2 represents the scenario with only noise, s(n) is the valid signal, and in the case of non-coherent detection, it can be regarded as a Gaussian process with a mean of and λ(n) is the channel noise, which can be regarded as a Gaussian process with a mean of 0 and a variance of , where n = 1, …, N and N is the number of sampling points.

[0112] Based on this, the signal energy can be obtained as:

[0113] In step 102, based on the distribution interval of the noise variance of the sampled signal, determine the upper and lower threshold values for double-threshold signal acquisition.

[0114] For example, determine the upper and lower threshold values for double-threshold signal acquisition according to the following formula:

[0115]

[0116]

[0117] where threshold L is the lower threshold value, threshold H is the upper threshold value, is the distribution interval of the noise variance, which can be obtained by measuring the sampled signal, is the non-integral function of the normal Gaussian, is 's inverse function, P f is the false alarm probability, and η is the decision threshold.

[0118] In step 103, perform uncertainty estimation on the noise variance in the sampled signal to obtain the lower and upper estimated values of the distribution interval.

[0119] In some embodiments, the lower and upper estimated values of the distribution interval can be determined according to the process shown in Figure 2 , including the following steps:

[0120] In step 1031, group the sampled signal to obtain K groups of signal samples, where K is an integer greater than 1.

[0121] For example, when x(n) (n = 1, …, N) is input into a K×M (K*M = N) grouper, K groups of signal samples can be obtained, and each group of signal samples contains M signal samples. Among them, x ij (i = 1, …, K; j = 1, …, M) represents the j-th sampling point in the i-th group of signal samples.

[0122] In step 1032, perform maximum likelihood estimation on the noise variances of the K groups of signal samples to obtain variance estimation values.

[0123] That is, perform maximum likelihood estimation on the noise variance of each group of signal samples among the K groups of signal samples to obtain the variance estimation value of this group of signal samples. For example, performing maximum likelihood estimation on the i-th group of signal samples, its variance can be obtained as Traversing the K groups of signal samples can obtain the variance set of the signal samples and they are independent of each other and follow a uniform distribution.

[0124] In step 1033, based on the variance estimation values of the K groups of signal samples, determine the lower limit estimation value and the upper limit estimation value.

[0125] In specific implementation, the first mean of the variance estimation values of the K groups of signal samples can be calculated, and the second mean of the variance estimation values of the K groups of signal samples when K approaches infinity can be calculated. Then, based on the first mean, the second mean, and the noise variance of the sampling signal, determine the lower limit estimation value and the upper limit estimation value.

[0126] For example, calculate the noise variance according to the following formula The interval upper and lower limit estimation values of are:

[0127]

[0128] Among them, and are respectively and 's estimation values, is the variance of λ(n).

[0129] In step 104, based on the lower limit estimation value and the upper limit estimation value, correct the upper and lower threshold values.

[0130] For example, using the lower limit estimation value as the interval lower limit and the upper limit estimation value as the interval upper limit, an estimation interval can be obtained, and the first floating value can be determined based on the lower limit estimation value. For example, the first floating value The second floating value is determined based on the upper limit estimation value, such as the second floating value Then, use the first floating value to lower the lower limit estimation value, and use the second floating value to lower the upper limit estimation value to obtain an estimation interval And the lower limit estimated value is increased using the first floating value, and the upper limit estimated value is increased using the second floating value to obtain an estimated interval

[0131] After that, the upper and lower threshold values can be corrected using each estimated interval respectively. For example, using each estimated interval, the upper and lower threshold values during double-threshold signal capture are recalculated to obtain the corrected upper and lower threshold values

[0132] In step 105, double-threshold signal capture is performed using the corrected upper and lower threshold values, and the capture error is determined based on the capture result. The capture error is used to represent the number of sampling points advanced or delayed

[0133] For example, double-threshold signal capture is performed using each corrected upper and lower threshold, and the capture result is obtained. Then, the capture results corresponding to multiple corrected upper and lower thresholds are fused through the majority criterion to obtain the capture error toa representing the number of sampling points advanced or delayed

[0134] In step 106, timing synchronization is performed on the subsequently acquired first signal based on the capture error

[0135] Among them, the first signal and the sampling signal are different signals

[0136] Figure 3 It is a flowchart of another signal timing synchronization method provided by the embodiments of the present application. This method is applied to a receiver, and the method includes the following steps

[0137] In step 301, the acquired test signal is sampled to obtain a sampling signal

[0138] In step 302, based on the distribution interval of the noise variance of the measured sampling signal, the upper and lower threshold values for double-threshold signal capture are determined

[0139] In step 303, uncertainty estimation is performed on the noise variance in the sampling signal to obtain the lower limit estimated value and the upper limit estimated value of the distribution interval

[0140] In step 304, the upper and lower threshold values are corrected based on the lower limit estimated value and the upper limit estimated value

[0141] In step 305, double-threshold signal capture is performed using the corrected upper and lower threshold values, and the capture error is determined based on the capture result. The capture error is used to represent the number of sampling points advanced or delayed

[0142] In step 306, the timing error of the sampling signal is determined

[0143] For example, the timing error Among them, L is the number of symbols in the sampling signal x(n), x * (n) is the conjugate operation of x(n), and N is the number of sampling points.

[0144] In step 307, based on the timing error, the interpolation base point and the interpolation coefficient are determined.

[0145] Based on the timing error, the interpolation base point mk and the interpolation coefficient uk are determined according to the O&M algorithm.

[0146] In step 308, based on the interpolation coefficient, L Lagrange interpolation polynomials are constructed, where L is an integer greater than 1.

[0147] For example, according to the interpolation coefficient uk, the Lagrange cubic interpolator coefficient Coe f (f = 1,..., 4) is as follows:

[0148]

[0149] Among them, each Lagrange cubic interpolator coefficient is a Lagrange interpolation polynomial.

[0150] In step 309, based on the capture error and the interpolation base point, L groups of signals are extracted from the signal after the first signal is matched filtered.

[0151] Taking L = 4 as an example, assuming that the output signal of the first signal after matched filtering is rx_match_sig, then L groups of signals can be sequentially extracted from rx_match_sig according to the following rules:

[0152]

[0153] Among them, is the hth group of sub-signal data extracted, interp is the interpolation multiple, and len is the length of the signal data after removing the guard interval.

[0154] In step 310, based on the L Lagrange interpolation polynomials, Lagrange interpolation processing is performed on the L groups of signals to obtain the signal after timing synchronization.

[0155] For example, the output signal after timing synchronization

[0156] In the embodiments of the present application, by calculating the difference between the estimated value and the measured value of the noise distribution, the upper and lower threshold values during double-threshold signal capture are adaptively set, which can improve the robustness and reliability of signal capture, and moreover, multi-point interpolation based on the Lagrange cubic interpolation coefficient can be performed on the first signal to obtain the optimal sampling point, improving the timing synchronization effect.

[0157] Based on the same inventive concept, an embodiment of the present application further provides a signal timing synchronization device. The principle of the signal timing synchronization device for solving problems is similar to that of the above-mentioned signal timing synchronization method. Therefore, for the implementation of the signal timing synchronization device, reference can be made to the implementation of the signal timing synchronization method, and repeated parts will not be elaborated.

[0158] Figure 4 FIG. 4 is a schematic structural diagram of a signal timing synchronization device provided by an embodiment of the present application, including a sampling module 401, a determination module 402, an estimation module 403, a correction module 404, an analysis module 405, and a synchronization module 406.

[0159] The sampling module 401 is configured to sample the acquired test signal to obtain a sampled signal;

[0160] The determination module 402 is configured to determine upper and lower threshold values for double-threshold signal capture based on the distribution interval of the noise variance of the sampled signal;

[0161] The estimation module 403 is configured to perform uncertainty estimation on the noise variance in the sampled signal to obtain a lower limit estimated value and an upper limit estimated value of the distribution interval;

[0162] The correction module 404 is configured to correct the upper and lower threshold values based on the lower limit estimated value and the upper limit estimated value;

[0163] The analysis module 405 is configured to perform double-threshold signal capture using the corrected upper and lower threshold values, and determine a capture error based on the capture result. The capture error is used to represent the number of sampling points advanced or delayed;

[0164] The synchronization module 406 is configured to perform timing synchronization on the acquired first signal based on the capture error.

[0165] In some embodiments, the estimation module 403 is specifically configured to:

[0166] Group the sampled signal to obtain K groups of signal samples, where K is an integer greater than 1;

[0167] Perform maximum likelihood estimation on the noise variance of the K groups of signal samples to obtain a variance estimated value;

[0168] Determine the lower limit estimated value and the upper limit estimated value based on the variance estimated values of the K groups of signal samples.

[0169] In some embodiments, the estimation module 403 is specifically configured to:

[0170] Calculate a first mean value of the variance estimated values of the K groups of signal samples;

[0171] Calculate the second mean of the variance estimates of K groups of signal samples when K approaches infinity;

[0172] Based on the first mean, the second mean, and the noise variance of the sampled signal, determine the lower limit estimate and the upper limit estimate.

[0173] In some embodiments, the correction module 404 is specifically configured to:

[0174] Using the lower limit estimate as the lower limit of the interval and the upper limit estimate as the upper limit of the interval, obtain an estimation interval, and determine a first floating value based on the lower limit estimate and a second floating value based on the upper limit estimate;

[0175] Use the first floating value to lower the lower limit estimate, use the second floating value to lower the upper limit estimate, obtain an estimation interval, and use the first floating value to raise the lower limit estimate and use the second floating value to raise the upper limit estimate to obtain an estimation interval;

[0176] Use each estimation interval to correct the upper and lower threshold values respectively.

[0177] In some embodiments, it further includes:

[0178] A preprocessing module 407, configured to determine the timing error of the sampled signal; based on the timing error, determine the interpolation base point and the interpolation coefficient; based on the interpolation coefficient, construct L Lagrange interpolation polynomials, where L is an integer greater than 1;

[0179] The synchronization module 406 is specifically configured to extract L groups of signals from the signal after the first signal matched filtering based on the capture error and the interpolation base point; perform Lagrange interpolation processing on the L groups of signals based on the L Lagrange interpolation polynomials to obtain the signal after timing synchronization.

[0180] The division of modules in the embodiments of the present application is illustrative. It is only a logical function division. In actual implementation, there may be other division methods. In addition, each functional module in the embodiments of the present application can be integrated in a processor, or can exist separately physically, or two or more modules can be integrated in one module. The coupling between each module can be realized through some interfaces, and these interfaces are usually electrical communication interfaces, but it does not exclude the possibility of being mechanical interfaces or other forms of interfaces. Therefore, the modules described as separate components may or may not be physically separated, and can be located in one place, or distributed to different positions of the same or different devices. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0181] After introducing the signal timing synchronization method and apparatus according to the exemplary embodiments of the present application, next, an electronic device according to another exemplary embodiment of the present application will be introduced.

[0182] Next, reference will be made to Figure 5 to describe the electronic device 130 implemented according to this embodiment of the present application. Figure 5 The illustrated electronic device 130 is merely an example and should not impose any limitation on the functions and scope of use of the embodiments of the present application.

[0183] As Figure 5 shown, the electronic device 130 is presented in the form of a general-purpose electronic device. The components of the electronic device 130 may include, but are not limited to: at least one of the above-mentioned processors 131, at least one of the above-mentioned memories 132, and a bus 133 connecting different system components (including the memory 132 and the processor 131).

[0184] The bus 133 represents one or more of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, a processor, or a local bus using any of the multiple bus architectures.

[0185] The memory 132 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 1321 and / or a cache memory 1322, and may further include a read-only memory (ROM) 1323.

[0186] The memory 132 may further include a program / utility 1325 having a set (at least one) of program modules 1324. Such program modules 1324 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. The implementation of a network environment may be included in each or some combination of these examples.

[0187] The electronic device 130 can also communicate with one or more external devices 134 (such as a keyboard, a pointing device, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 130, and / or communicate with any device that enables the electronic device 130 to communicate with one or more other electronic devices (such as a router, a modem, etc.). Such communication can be carried out through the input / output (I / O) interface 135. Moreover, the electronic device 130 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 136. As shown in the figure, the network adapter 136 communicates with other modules for the electronic device 130 through the bus 133. It should be understood that although not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 130, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0188] In an exemplary embodiment, a storage medium is also provided. When the computer program in the storage medium is executed by the processor of the electronic device, the electronic device can execute the above-mentioned signal timing synchronization method. Optionally, the storage medium can be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0189] In an exemplary embodiment, the electronic device of the present application can at least include at least one processor and a memory communicatively connected to the at least one processor. Among them, the memory stores a computer program executable by the at least one processor. When the computer program is executed by the at least one processor, the at least one processor can execute the steps of any signal timing synchronization method provided by the embodiments of the present application.

[0190] In an exemplary embodiment, a computer program product is also provided. When the computer program product is executed by the electronic device, the electronic device can implement any exemplary method provided by the present application.

[0191] Moreover, the computer program product can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, RAM, ROM, an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0192] In the embodiments of the present application, the program product for signal timing synchronization can adopt a CD-ROM and include program code, and can run on a computing device. However, the program product of the present application is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

[0193] The readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which the readable program code is carried. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable signal medium can also be any readable medium other than the readable storage medium, and the readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0194] The program code contained on the readable medium can be transmitted by any appropriate medium, including but not limited to wireless, wired, optical cable, radio frequency (RF), etc., or any suitable combination of the above.

[0195] The program code for performing the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network such as a local area network (LAN) or a wide area network (WAN), or, it can be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0196] It should be noted that although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0197] In addition, although the operations of the method of the present application are described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution.

[0198] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0199] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0200] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0201] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operating steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0202] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0203] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also includes these changes and modifications.

Claims

1. A method for timing synchronization of signals, characterized in that including: Sampling the acquired test signal to obtain a sampled signal; Determining upper and lower threshold values for double-threshold signal capture based on the distribution interval of the noise variance of the sampled signal; Grouping the sampled signal to obtain K groups of signal samples, where K is an integer greater than 1; Performing maximum likelihood estimation on the noise variances of the K groups of signal samples to obtain variance estimation values; Determining a lower limit estimation value and an upper limit estimation value based on the variance estimation values of the K groups of signal samples; Taking the lower limit estimation value as the lower limit of the interval and the upper limit estimation value as the upper limit of the interval to obtain an estimation interval, and determining a first floating value based on the lower limit estimation value and a second floating value based on the upper limit estimation value; Using the first floating value to lower the lower limit estimation value, using the second floating value to lower the upper limit estimation value to obtain an estimation interval, and using the first floating value to raise the lower limit estimation value, using the second floating value to raise the upper limit estimation value to obtain an estimation interval; Using each estimation interval to correct the upper and lower threshold values respectively; Performing double-threshold signal capture using the corrected upper and lower threshold values, and determining a capture error based on the capture result, where the capture error is used to represent the number of sampling points advanced or delayed; Performing timing synchronization on the acquired first signal based on the capture error.

2. The method according to claim 1, characterized in that, Determining the lower limit estimation value and the upper limit estimation value based on the variance estimation values of the K groups of signal samples includes: Calculating a first mean of the variance estimation values of the K groups of signal samples; Calculating a second mean of the variance estimation values of the K groups of signal samples when K approaches infinity; Determining the lower limit estimation value and the upper limit estimation value based on the first mean, the second mean, and the noise variance of the sampled signal.

3. The method according to claim 1 or 2, characterized in that, It further includes: Determining the timing error of the sampled signal; Determining an interpolation base point and an interpolation coefficient based on the timing error; Constructing L Lagrange interpolation polynomials based on the interpolation coefficient, where L is an integer greater than 1; Performing timing synchronization on the acquired first signal based on the capture error includes: Extracting L groups of signals from the signal after matched filtering of the first signal based on the capture error and the interpolation base point; Performing Lagrange interpolation processing on the L groups of signals based on the L Lagrange interpolation polynomials to obtain a timing synchronized signal.

4. A timing synchronization device for a signal, characterized in that, including: A sampling module for sampling the acquired test signal to obtain a sampled signal; A determining module for determining upper and lower threshold values for double-threshold signal capture based on the distribution interval of the noise variance of the sampled signal; An estimating module for performing uncertainty estimation on the noise variance in the sampled signal to obtain a lower limit estimation value and an upper limit estimation value of the distribution interval; A correcting module for correcting the upper and lower threshold values based on the lower limit estimation value and the upper limit estimation value; An analyzing module for performing double-threshold signal capture using the corrected upper and lower threshold values and determining a capture error based on the capture result, where the capture error is used to represent the number of sampling points advanced or delayed; A synchronization module for performing timing synchronization on the acquired first signal based on the capture error; The estimation module is specifically configured to: Group the sampled signals to obtain K groups of signal samples, where K is an integer greater than 1; Perform maximum likelihood estimation on the noise variances of the K groups of signal samples to obtain variance estimation values; Determine the lower limit estimation value and the upper limit estimation value based on the variance estimation values of the K groups of signal samples; The correction module is specifically configured to: Use the lower limit estimation value as the lower limit of the interval and the upper limit estimation value as the upper limit of the interval to obtain an estimation interval, determine a first floating value based on the lower limit estimation value, and determine a second floating value based on the upper limit estimation value; Use the first floating value to lower the lower limit estimation value, use the second floating value to lower the upper limit estimation value to obtain an estimation interval, and use the first floating value to raise the lower limit estimation value, use the second floating value to raise the upper limit estimation value to obtain an estimation interval; Use each estimation interval to correct the upper and lower threshold values.

5. The device according to claim 4, characterized in that, The estimation module is specifically configured to: Calculate a first mean of the variance estimation values of the K groups of signal samples; Calculate a second mean of the variance estimation values of the K groups of signal samples when K approaches infinity; Determine the lower limit estimation value and the upper limit estimation value based on the first mean, the second mean, and the noise variance of the sampled signal.

6. The device according to claim 4 or 5, characterized in that It further includes: A preprocessing module, configured to determine the timing error of the sampled signal; based on the timing error, determine an interpolation base point and an interpolation coefficient; based on the interpolation coefficient, construct L Lagrange interpolation polynomials, where L is an integer greater than 1; The synchronization module is specifically configured to extract L groups of signals from the signal after the first signal matched filtering based on the capture error and the interpolation base point; perform Lagrange interpolation processing on the L groups of signals based on the L Lagrange interpolation polynomials to obtain a timing synchronized signal.

7. An electronic device, characterized in that, It includes: At least one processor, and a memory communicatively connected to the at least one processor, wherein: The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the method according to any one of claims 1-3.

8. A storage medium, characterized in that, When the computer program in the storage medium is executed by the processor of the electronic device, the electronic device is enabled to execute the method according to any one of claims 1-3.

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