A method for estimating wireless signal propagation delay

Abstract

The present application relates to a method for estimating wireless signal propagation delay, including: obtaining first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data filtered by fractional delay; performing peak search on the first relevant data and the second relevant data respectively to obtain the first peak maximum value and the second peak maximum value; comparing the first peak maximum value and the second peak maximum value, and performing delay calculation based on the comparison result to obtain a target delay estimate. The delay coefficient of the fractional delay filter in the present application is adjustable, which can realize non-integer multiple delay estimation without increasing the sampling rate, and the delay estimation accuracy can be adjusted in real time according to the delay estimation accuracy requirements to flexibly adapt to the usage scenario.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method for estimating wireless signal propagation delay. Background Art

[0002] The wireless signal propagation delay estimation method usually refers to the process of processing the signal and estimating the parameters after receiving the target radiation source signal at different receiving stations to obtain the estimated delay value, that is, the time difference between the signal reaching different receiving stations. Usually, since it is impossible to predict the time, position, direction and delay value of the radiation source signal, the delay estimation method is required to automatically track the change of the delay value and be real-time and reliable.

[0003] Existing delay estimation methods find it difficult to achieve controllable estimation of non-integer delays without increasing the sampling rate. Summary of the invention

[0004] In order to solve the above technical problems, the embodiments of the present application provide a wireless signal propagation delay estimation method, device, electronic device and storage medium that can achieve non-integer delay and accurately control the delay estimation accuracy. The specific scheme is as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for estimating a wireless signal propagation delay, including:

[0006] Acquire first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering;

[0007] Performing peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value;

[0008] The first peak maximum value and the second peak maximum value are compared, and delay calculation is performed according to the comparison result to obtain a target delay estimation value.

[0009] According to a specific implementation of the embodiment of the present application, obtaining the first relevant data and the second relevant data includes:

[0010] Acquire reception data generated by different receivers receiving the same wireless signal to obtain the first receiving station data and the second receiving station data;

[0011] Performing fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1;

[0012] Perform sliding correlation calculation according to the first receiving station data and the second receiving station data to obtain the first correlation data;

[0013] A sliding correlation calculation is performed according to the first receiving station data and the target delay data to obtain the second correlation data.

[0014] According to a specific implementation of the embodiment of the present application, when performing sliding correlation calculation, the method further includes:

[0015] Determining the correlation length of the sliding correlation calculation according to the type of the wireless signal;

[0016] If the wireless signal is a continuous signal, determining the correlation length according to real-time requirements and performance requirements;

[0017] If the wireless signal is of a pulse type, the correlation length is determined according to real-time requirements.

[0018] According to a specific implementation of the embodiment of the present application, comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimate value includes:

[0019] If the first peak maximum value is greater than or equal to the second peak maximum value, calculating the target delay estimate value according to a first delay calculation method corresponding to the first peak maximum value;

[0020] If the first peak maximum value is less than the second peak maximum value, the target delay estimate value is calculated according to a second delay calculation method corresponding to the second peak maximum value.

[0021] According to a specific implementation of the embodiment of the present application, after performing peak searches on the first related data and the second related data respectively to obtain the first peak maximum value and the second peak maximum value, the method further includes:

[0022] Obtain a first offset position corresponding to the maximum value of the first peak value, and a second offset position corresponding to the maximum value of the second peak value;

[0023] The first delay calculation method includes:

[0024] Determining the first offset position as the target delay estimate;

[0025] The second delay calculation method includes:

[0026] The difference between the second offset position and a preset delay coefficient is determined as the target delay estimation value.

[0027] In a second aspect, an embodiment of the present application provides a wireless signal propagation delay estimation device, including:

[0028] An acquisition module, configured to acquire first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering;

[0029] A peak search module, used to perform peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value;

[0030] A comparison and calculation module is used to compare the first peak maximum value and the second peak maximum value, and perform delay calculation according to the comparison result to obtain a target delay estimation value.

[0031] According to a specific implementation of an embodiment of the present application, the acquisition module is specifically used to acquire the received data generated by different receivers receiving the same wireless signal, and obtain the first receiving station data and the second receiving station data; perform fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1; perform sliding correlation calculation based on the first receiving station data and the second receiving station data to obtain the first correlation data; perform sliding correlation calculation based on the first receiving station data and the target delay data to obtain the second correlation data.

[0032] According to a specific implementation of an embodiment of the present application, the comparison and calculation module is specifically used to calculate the target delay estimate value according to a first delay calculation method corresponding to the first peak maximum value if the first peak maximum value is greater than or equal to the second peak maximum value; if the first peak maximum value is less than the second peak maximum value, calculate the target delay estimate value according to a second delay calculation method corresponding to the second peak maximum value.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising:

[0034] at least one processor; and,

[0035] a memory communicatively connected to the at least one processor; wherein,

[0036] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the wireless signal propagation delay estimation method in the aforementioned first aspect or any implementation of the first aspect.

[0037] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the wireless signal propagation delay estimation method in the aforementioned first aspect or any implementation of the first aspect.

[0038] In summary, the present embodiment provides a method, device, electronic device and storage medium for estimating the propagation delay of a wireless signal, including: obtaining first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data filtered by a fractional delay; performing peak searches on the first relevant data and the second relevant data respectively to obtain a first peak maximum value and a second peak maximum value; comparing the first peak maximum value and the second peak maximum value, and performing delay calculation based on the comparison result to obtain a target delay estimate. The delay coefficient of the fractional delay filter in the present application is adjustable, and non-integer multiple delay estimation can be achieved without increasing the sampling rate, and the delay estimation accuracy can be adjusted in real time according to the delay estimation accuracy requirements to flexibly adapt to the usage scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 A schematic diagram of a data processing flow of a delay estimation method in the prior art;

[0041] Figure 2 A schematic diagram of a data processing flow of a wireless signal propagation delay estimation method provided in an embodiment of the present application;

[0042] Figure 3 A flowchart of a method for estimating wireless signal propagation delay provided in an embodiment of the present application;

[0043] Figure 4 A schematic diagram of the steps for obtaining relevant data provided in an embodiment of the present application;

[0044] Figure 5 A schematic diagram of the steps for determining the correlation length provided in an embodiment of the present application;

[0045] Figure 6 A schematic diagram of the steps for determining an offset value provided in an embodiment of the present application;

[0046] Figure 7 One of the experimental simulation schematic diagrams provided in the embodiment of the present application;

[0047] Figure 8 The second experimental simulation schematic diagram provided for the embodiment of the present application;

[0048] Fig. 9 A schematic diagram of device modules of a wireless signal propagation delay estimation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0050] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0051] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0052] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0053] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, one skilled in the art will appreciate that aspects may be practiced without these specific details.

[0054] As mentioned in the background technology section above, the existing delay estimation algorithms cannot effectively meet the real-time requirements of delay estimation and the requirements for estimating non-integer multiples of delay values. For example, the basic delay estimation algorithms mainly include generalized correlation delay estimation, generalized phase spectrum delay estimation, high-order statistics delay estimation, and adaptive delay estimation algorithms.

[0055] Among them, the generalized correlation delay estimation method mainly calculates the delay value of the signal by calculating the extreme point of the cross-correlation function between the reference signal and the delayed signal. The advantages of the generalized correlation delay estimation method are small amount of calculation and relatively simple algorithm, but the generalized correlation delay estimation method cannot effectively estimate non-integer delay values.

[0056] The generalized phase spectrum method delay estimation method mainly calculates the phase of the cross-correlation function of the reference signal and the delayed signal to calculate the delay value of the signal, and uses the corresponding frequency domain weighted function processing to improve the measurement accuracy and improve the measurement effect. The generalized phase spectrum method delay estimation method can estimate non-integer delay values ​​to a certain extent after being combined with the interpolation method. However, after interpolation, the generalized phase spectrum method delay estimation method will lead to an increase in the sampling rate and higher requirements for data processing capabilities.

[0057] The delay estimation method based on high-order statistics mainly estimates the delay value by solving the maximum value of the transverse filter. Since the high-order cumulants are not sensitive to Gaussian noise, the cumulants of Gaussian processes higher than the second order are always zero, so the delay estimation method based on high-order statistics can use the correlation properties to suppress the correlated noise. However, the delay estimation method based on high-order statistics will greatly increase the difficulty of delay calculation and greatly reduce the real-time performance.

[0058] The adaptive delay estimation method mainly processes the reference signal by using an adaptive filter, and dynamically adjusts the tap coefficients of the filter under a certain criterion (such as the minimum mean square error criterion), so that the reference signal is equal to the corresponding delayed signal after filtering, and the delay estimation value is obtained. The adaptive delay estimation method can achieve high-precision delay estimation under correlated noise conditions. However, due to the high filter order and increased computational complexity of the adaptive delay estimation method, the time difference will increase as the signal-to-noise ratio and filter length decrease.

[0059] like Figure 1As shown in the figure, the correlation delay estimation algorithm is used as an example to illustrate that the same wireless signal is transmitted through different paths to the received signals at different receivers, and then the peak of the obtained cross-correlation is searched to obtain the time difference between the signals. This algorithm is applicable to the conditions where the signal and noise and the noise are uncorrelated.

[0060] The baseband discrete-time signal received by two spatially separated receivers is:

[0061]

[0062]

[0063] Among them, the source signal Zero-mean Gaussian white noise and Not related to each other. is the reference signal observation, is the delayed signal observation. , is the number of signal samples. is the time difference between the two baseband discrete-time signals.

[0064] Calculating discrete signals and The cross-correlation function is:

[0065]

[0066]

[0067]

[0068] in, represents the mean calculation, and are all noise signals, is the corresponding reference signal observation The source signal, is the corresponding delayed signal observation The source signal, express and Cross-correlation value at delay m;

[0069]

[0070]

[0071]

[0072]

[0073] Based on the above formula, we can further deduce:

[0074]

[0075] Since the signal and noise are uncorrelated, and the noise is uncorrelated, , as well as The actual value compared to The actual value of can be ignored, so we can further deduce:

[0076]

[0077] And by the related property function It is known that when When the cross-correlation function It can take the maximum value. In practical applications, the correlation function of a stationary random process is estimated using time averaging, and the formula is as follows:

[0078]

[0079] in, , is the order of the cross-correlation, In actual application, Need to be greater than , Indicates the time difference value rounded up. Since the actual time difference value cannot be known during the application process , The value of needs to be larger. Through the peak search step, based on The function calculates the time difference between the reference signal and the delayed signal.

[0080] From the above calculation steps, it can be seen that the traditional correlation delay estimation algorithm can only calculate the time difference estimation value of the integer multiple of the sampling time, which cannot meet the delay estimation requirements for non-integer multiples of the wireless signal propagation process in actual application scenarios.

[0081] The wireless signal propagation delay estimation method provided in the embodiment of the present application proposes a new algorithm structure, such as Figure 2 As shown, the wireless signal propagation delay estimation method provided by this embodiment adds a fractional delay filter to the delay estimation algorithm, performs fractional delay filtering on the delayed signal part, and calculates the time difference estimation value of the fractional multiple of the sampling time, thereby effectively meeting the delay estimation requirements for non-integer multiples of the wireless signal propagation process. In addition, the wireless signal propagation delay estimation method provided by this embodiment can also flexibly adjust the algorithm according to the requirements of the delay estimation accuracy, and can adapt to various application conditions.

[0082] refer to Figure 3 The present invention provides a method for estimating the propagation delay of a wireless signal. Figure 2 The algorithm structure shown is used as an example to illustrate, including the following steps:

[0083] S301, obtaining first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering.

[0084] In this embodiment, for the reception data generated by different receiving stations receiving the same wireless signal, such as Figure 2 As shown, the received data includes the first receiving station data and the second receiving station data. It should be noted that the first receiving station data and the second receiving station data in this embodiment are data generated after two receivers set at different positions receive the same wireless signal, and this embodiment does not specifically limit the setting position and setting number of the receivers. In the corresponding usage scenario, the number of receiving station data and related data can be adaptively changed according to changes in the observation situation.

[0085] After obtaining the first receiving station data and the second receiving station data, this embodiment will respectively use a preset correlation algorithm to perform two correlation calculations. In the first correlation calculation, the first receiving station data and the second receiving station data are directly used to calculate the first correlation data. In the second correlation calculation, the second correlation data is calculated based on the first receiving station data and the second receiving station data after fractional delay filtering.

[0086] It should be noted that the preset correlation algorithm in this embodiment can select a suitable calculation method according to the needs of the actual application scenario. For example, the preset correlation algorithm can be a sliding correlation algorithm or a cross-correlation algorithm. Preferably, the preset correlation algorithm in this embodiment is a sliding correlation algorithm, which simplifies the algorithm execution steps and facilitates the delay estimation method to meet the requirements of real-time performance and estimation accuracy.

[0087] This embodiment adds an extra step of calculating the relevant data and interpolates the second receiving station data through a fractional delay filter, thereby effectively calculating and obtaining a time difference estimation value that is a fractional multiple of the sampling time without changing the sampling rate.

[0088] S302, performing peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value.

[0089] According to the correlation principle, the delay estimation value corresponding to the peak maximum value is the optimal value. In the previous step, this embodiment calculates multiple related data, performs peak search on each related data, and compares the peak maximum values ​​of each related data. The maximum value among the peak maximum values ​​of all related data is selected to obtain the optimal delay estimation value calculation path.

[0090] S303 , comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimation value.

[0091] In this embodiment, a peak search is performed on the first related data to obtain the first peak maximum value, and a peak search is performed on the second related data to obtain the second peak maximum value. The maximum values ​​of the first peak maximum value and the second peak maximum value are then compared, and the delay offset value corresponding to the largest peak maximum value is selected for delay calculation to obtain the optimal delay estimate value.

[0092] In summary, this embodiment provides a method for estimating the propagation delay of a wireless signal. By adding a fractional delay filter and performing fractional delay filtering on the receiving station data corresponding to the delayed signal in the delay estimation algorithm, it is possible to break through the limitation of the sampling rate and obtain a time difference estimation value of a fractional multiple of the sampling time, thereby meeting the non-integer multiple delay estimation requirements of the wireless signal propagation delay estimation. In addition, this embodiment can adjust the accuracy of the delay estimation algorithm by adjusting the delay filter coefficient of the fractional delay filter.

[0093] According to a specific implementation of the embodiment of the present application, Figure 4 As shown, the step of obtaining the first relevant data and the second relevant data in S301 includes:

[0094] S401, acquiring reception data generated by different receivers receiving the same wireless signal to obtain first receiving station data and second receiving station data.

[0095] In this embodiment, the first receiving station data is assumed to be the first receiving data generated by the receiving station 1 receiving the target wireless signal. The second receiving station data is assumed to be the second receiving data generated by receiving the target wireless signal from the receiving station 2 , wherein receiving station 1 and receiving station 2 are receivers arranged at different spatial locations.

[0096] S402, performing fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1.

[0097] In this embodiment, the wireless signal propagation delay estimation method configures a fractional delay filter on the calculation path of the second related data, and the fractional delay filter is used to calculate the second receiving station data. Perform fractional delay filtering to obtain target delay data .

[0098] In this embodiment, the preset delay coefficient is configured as a decimal, that is, configured as a fraction and the preset delay coefficient is less than 1. For example, the preset delay coefficient may be configured as 0.5.

[0099] In practical applications, the coefficients of the N-order fractional delay filter can be designed as:

[0100]

[0101] in, The superscript indicates that the center frequency of the filter is When the signal center frequency is When the filter center frequency is modulated to The modulated filter coefficients are:

[0102]

[0103] According to the above modulated filter coefficients, the weight coefficients of the delay filter can be constructed by combining the sinc function and Lagrange interpolation, that is, .

[0104] By configuring different delay values , different filter coefficients, namely preset delay coefficients, can be obtained. This embodiment can achieve regulation of different delay configurations by configuring different preset delay coefficients, effectively improving the flexibility and controllability of the wireless signal communication delay estimation step.

[0105] S403, performing sliding correlation calculation according to the first receiving station data and the second receiving station data to obtain first correlation data.

[0106] S404, performing sliding correlation calculation according to the first receiving station data and the target delay data to obtain second correlation data.

[0107] In this embodiment, the data sliding correlation operation in S403 and S404 is performed respectively to obtain the first correlation data and second related data Among them, according to the first receiving station data and the second receiving station data Perform sliding correlation calculation to obtain the first correlation data , according to the first receiving station data and target latency data Perform sliding correlation calculation to obtain the second correlation data .

[0108] The corresponding expression for sliding is:

[0109]

[0110]

[0111] in, , represents the sliding window length, represents the correlation length, for and The correlation value after sliding correlation operation, for and Correlation value after sliding correlation operation.

[0112] According to a specific implementation of the embodiment of the present application, Figure 5 As shown, when performing sliding correlation calculation, the wireless signal propagation delay estimation method also includes:

[0113] S501, determining a correlation length of a sliding correlation calculation according to a type of a wireless signal;

[0114] S502, if the wireless signal is a continuous signal, determining a correlation length according to real-time requirements and performance requirements;

[0115] S503: If the wireless signal is of a pulse type, determine the relevant length according to real-time requirements.

[0116] In this embodiment, if the wireless signal is a continuous signal, the larger the correlation length N is, the longer the integral operation time is, the larger the amount of calculation is, and the better the performance is. However, when the correlation length N is too large, the real-time performance of the delay estimation method will be affected. Therefore, when the wireless signal received by the receiving station is a continuous signal, the correlation length N of the sliding correlation calculation needs to be determined according to the real-time requirements and performance requirements. The correlation length N can be taken as large as possible without affecting the real-time requirements.

[0117] If the wireless signal is a pulse signal, the larger the correlation length N, the worse the performance. Therefore, when the wireless signal received by the receiving station is a pulse signal, it is only necessary to determine the correlation length N of the sliding correlation calculation according to the real-time requirements. The correlation length N is taken as the minimum value that meets the calculation requirements as much as possible.

[0118] According to a specific implementation of the embodiment of the present application, comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimation value includes:

[0119] If the first peak maximum value is greater than or equal to the second peak maximum value, the target delay estimate is calculated according to the first delay calculation method corresponding to the first peak maximum value.

[0120] If the first peak maximum value is less than the second peak maximum value, the target delay estimation value is calculated according to the second delay calculation method corresponding to the second peak maximum value.

[0121] In this embodiment, the results after sliding correlation are searched for peak values, and the maximum values ​​of the peak values ​​of the two paths are found, that is, the maximum values ​​of the first peak values. and the second peak maximum .

[0122] exist When , the first delay calculation method is used for calculation, and the first delay calculation method is to determine the first offset position as the target delay estimation value. The specific formula is as follows:

[0123]

[0124] exist When the second delay calculation method is used, the second delay calculation method is to determine the difference between the second offset position and the preset delay coefficient as the target delay estimation value. The specific formula is as follows:

[0125]

[0126] in, is the target delay estimate, is the first offset position corresponding to the first peak maximum value, is the second offset position corresponding to the second peak maximum value, The set delay value.

[0127] According to a specific implementation of the embodiment of the present application, after performing peak searches on the first related data and the second related data respectively to obtain the first peak maximum value and the second peak maximum value, the method further includes:

[0128] A first offset position corresponding to the maximum value of the first peak value and a second offset position corresponding to the maximum value of the second peak value are obtained.

[0129] In this embodiment, the first offset position corresponding to the maximum value of the first peak value needs to be collected according to the corresponding relationship between the peak starting position and the delay position. and a second offset position corresponding to the second peak maximum value. It should be noted that the first offset position and the second offset position The calculation method is as follows Figure 6 shown.

[0130] In this embodiment, after sliding correlation is performed on the first receiving station data and the second receiving station data to obtain the first correlation data, the first peak maximum value in the first correlation data is further searched, such as Figure 6 As shown, the corresponding first offset position can be determined based on the first peak maximum value .

[0131] The first receiving station data and the fixed delay The second receiving station data subjected to fractional delay filtering is subjected to sliding correlation to obtain second correlation data, and then the second peak maximum value in the second correlation data is further searched, such as Figure 6 As shown, the corresponding second offset position can be determined based on the second peak maximum value It should be noted that the first offset position and the second offset position are the corresponding delay estimates.

[0132] In summary, this embodiment provides a method for estimating the propagation delay of a wireless signal. Under a fixed sampling rate, by configuring a fixed fractional delay filter, the decimal multiple data delay can be effectively realized, breaking through the limitation of the sampling rate, completing the delay of the decimal sampling point of the data, and completing the delay estimation through the correlation operation. The algorithm is simple and has high real-time performance. In addition, the wireless signal propagation delay estimation can be flexibly controlled by adjusting the preset delay coefficient.

[0133] In a more detailed embodiment, it is assumed that the sampling rate is 25MHz when receiving the signal and 100MHz when transmitting the signal. To analyze the sampling error between the transmitted signal and the received signal, it is necessary to configure four consecutive delays at the sampling rate of 100MHz for the transmitted signal, and confirm whether the delay estimation accuracy of 20ns can be achieved at the sampling rate of 25MHz based on the wireless signal propagation delay estimation method provided in this embodiment.

[0134] The delay estimation is performed by using the common delay estimation method without configuring the fractional delay filter and the wireless signal propagation delay estimation method provided by this embodiment. The simulation results are as follows: Figure 7 and Figure 8 As shown in FIG. 1 , the correlation value is the actual value of the correlation data obtained after the sliding correlation operation, and the delay estimation value is the number of sampling points.

[0135] From the simulation results, it is clear that when the sampling rate is 100MHz, the oversampling multiple is 1, the delay reference value is 162 sampling points, and the delay value is 162. When 10ns=1620ns, the calculation result of the wireless signal propagation delay estimation method provided in this embodiment, that is, the delay estimation value after the fractional delay filter is 41 sampling points, but the actual offset position needs to subtract the delay D value, so the target delay estimation value is 40.5 sampling points.

[0136] The calculation result of the common delay estimation method, that is, the delay estimation value without passing through the fractional delay filter is 40 sampling points.

[0137] The oversampling multiple of the received signal is 4, the sampling rate is 25MHz, and the final delay value is calculated as T = number of sampling points The target delay estimation value calculated based on the wireless signal propagation delay estimation method provided in this embodiment is used to calculate the final delay value T1, and the delay estimation value calculated by the common delay estimation method without the fractional delay filter is used to calculate the final delay value T2. The specific formula is as follows:

[0138]

[0139]

[0140] In summary, it can be clearly seen that the target delay estimation value calculated based on the wireless signal propagation delay estimation method provided in this embodiment can achieve a delay estimation accuracy of 20ns by calculating the final delay value. The calculation result of the wireless signal propagation delay estimation method provided in this embodiment can effectively achieve a higher-precision delay estimation and meet the non-integer delay estimation requirements.

[0141] Based on the same inventive concept, the embodiment of the present application also provides a wireless signal propagation delay estimation device for implementing the wireless signal propagation delay estimation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more wireless signal propagation delay estimation device embodiments provided below can refer to the limitations of the wireless signal propagation delay estimation method above, and will not be repeated here.

[0142] In one embodiment, reference Fig. 9 This embodiment further provides a wireless signal propagation delay estimation device 900, including: an acquisition module 910, a peak search module 920 and a comparison calculation module 930, wherein:

[0143] An acquisition module 910 is used to acquire first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering;

[0144] A peak search module 920, configured to perform peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value;

[0145] The comparison and calculation module 930 is used to compare the first peak maximum value and the second peak maximum value, and perform delay calculation according to the comparison result to obtain a target delay estimation value.

[0146] In one embodiment, the acquisition module 910 is specifically used to acquire the received data generated by different receivers receiving the same wireless signal to obtain the first receiving station data and the second receiving station data; perform fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1; perform sliding correlation calculation based on the first receiving station data and the second receiving station data to obtain the first correlation data; perform sliding correlation calculation based on the first receiving station data and the target delay data to obtain the second correlation data.

[0147] In one embodiment, the comparison calculation module 930 is specifically used to calculate the target delay estimate value according to the first delay calculation method corresponding to the first peak maximum value if the first peak maximum value is greater than or equal to the second peak maximum value; if the first peak maximum value is less than the second peak maximum value, calculate the target delay estimate value according to the second delay calculation method corresponding to the second peak maximum value.

[0148] In summary, this embodiment provides a wireless signal propagation delay estimation device. Under a fixed sampling rate, by configuring a fixed fractional delay filter, decimal multiple data delay can be effectively achieved, breaking through the limitation of the sampling rate, completing the delay of the decimal sampling point of the data, and completing the delay estimation through correlation operations. The algorithm is simple and has high real-time performance. Flexible control of wireless signal propagation delay estimation can be achieved by adjusting the preset delay coefficient.

[0149] Fig. 9 The specific implementation of the device shown can refer to the specific implementation of the aforementioned method embodiment, which will not be repeated here.

[0150] In addition, an embodiment of the present application further provides an electronic device, the electronic device comprising:

[0151] at least one processor; and,

[0152] a memory communicatively connected to the at least one processor; wherein,

[0153] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the wireless signal propagation delay estimation method in the aforementioned method embodiment.

[0154] It should be noted that the electronic device in this embodiment may be a compound eye detector device, or may be other electronic devices equipped with or connected to the compound eye detector device.

[0155] An embodiment of the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the wireless signal propagation delay estimation method in the aforementioned method embodiment.

[0156] The electronic devices in the embodiments of the present application may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0157] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. Examples of computer-readable storage media may be, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0158] In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0159] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0160] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains first related data and second related data, wherein the first related data is calculated from the first receiving station data and the second receiving station data, and the second related data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering; performs peak search on the first related data and the second related data respectively to obtain the first peak maximum value and the second peak maximum value; compares the first peak maximum value and the second peak maximum value, and performs delay calculation based on the comparison result to obtain the target delay estimation value.

[0161] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0162] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0163] The units involved in the embodiments described in this application can be implemented by software or hardware. It should be understood that each part of the present disclosure can be implemented by hardware, software, firmware or a combination thereof.

[0164] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for estimating wireless signal propagation delay, characterized in that: include: Acquire first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering; Performing peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value; Comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimation value; The obtaining of the first relevant data and the second relevant data comprises: Acquire reception data generated by different receivers receiving the same wireless signal to obtain the first receiving station data and the second receiving station data; Performing fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1; Perform sliding correlation calculation according to the first receiving station data and the second receiving station data to obtain the first correlation data; A sliding correlation calculation is performed according to the first receiving station data and the target delay data to obtain the second correlation data.

2. The method according to claim 1, characterized in that When performing sliding related calculations, the method further includes: Determining the correlation length of the sliding correlation calculation according to the type of the wireless signal; If the wireless signal is a continuous signal, determining the correlation length according to real-time requirements and performance requirements; If the wireless signal is of a pulse type, the correlation length is determined according to real-time requirements.

3. The method according to claim 1, characterized in that The comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimation value, includes: If the first peak maximum value is greater than or equal to the second peak maximum value, calculating the target delay estimate value according to a first delay calculation method corresponding to the first peak maximum value; If the first peak maximum value is less than the second peak maximum value, the target delay estimate value is calculated according to a second delay calculation method corresponding to the second peak maximum value.

4. The method according to claim 3, characterized in that After performing peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value, the method further includes: Obtaining a first offset position corresponding to the maximum value of the first peak value, and a second offset position corresponding to the maximum value of the second peak value; The first delay calculation method includes: Determining the first offset position as the target delay estimate; The second delay calculation method includes: The difference between the second offset position and a preset delay coefficient is determined as the target delay estimation value.

5. A wireless signal propagation delay estimation device, characterized in that: include: An acquisition module, configured to acquire first relevant data and second relevant data, wherein the first relevant data is calculated from the first receiving station data and the second receiving station data, and the second relevant data is calculated from the first receiving station data and the second receiving station data after fractional delay filtering; A peak search module, used to perform peak searches on the first correlation data and the second correlation data respectively to obtain a first peak maximum value and a second peak maximum value; A comparison and calculation module, used for comparing the first peak maximum value and the second peak maximum value, and performing delay calculation according to the comparison result to obtain a target delay estimation value; The acquisition module is specifically used to acquire the received data generated by different receivers receiving the same wireless signal, and obtain the first receiving station data and the second receiving station data; perform fractional delay filtering on the second receiving station data according to a preset delay coefficient to obtain target delay data, wherein the preset delay coefficient is a fraction and the preset delay coefficient is less than 1; perform sliding correlation calculation based on the first receiving station data and the second receiving station data to obtain the first correlation data; perform sliding correlation calculation based on the first receiving station data and the target delay data to obtain the second correlation data.

6. The device according to claim 5, characterized in that The comparison and calculation module is specifically configured to calculate the target delay estimate value according to a first delay calculation method corresponding to the first peak maximum value if the first peak maximum value is greater than or equal to the second peak maximum value; If the first peak maximum value is less than the second peak maximum value, the target delay estimate value is calculated according to a second delay calculation method corresponding to the second peak maximum value.

7. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of the preceding claims 1 to 4.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the method of any one of the preceding claims 1-4.

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