Method, apparatus, signal receiving device and storage medium for determining arrival time

Abstract

The present application provides a method and apparatus for determining the arrival time, a signal receiving device, and a storage medium. The method generates arrival time correction information based on the leading edge information of the theoretical autocorrelation waveform of positioning signals with different fading values; calculates the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actually received signal; determines target correction information from the arrival time correction information according to the leading edge slope, and determines the arrival time of the actually received signal based on the target correction information.

Description

Technical Field

[0001] The present application relates to a wireless communication system, and for example, relates to a method, apparatus, signal receiving device, and storage medium for determining time of arrival. Background Art

[0002] In a wireless communication system, for high-precision positioning of devices in a communication network, generally the Time Difference of Arrival (TDOA) positioning method is adopted, that is, the distance between the sending end and the receiving end is determined by measuring the time when the signal arrives at the receiving end, and the position of the signal source can be determined according to the distances from the signal source to each receiving end. The TDOA positioning method mainly determines the frame header and delimits the Orthogonal Frequency Division Multiplexing (OFDM) symbol, removes a fixed number of sampling points according to the prefix length from the delimited time point to obtain the symbol time-domain data, and then performs a mathematical sequence correlation operation, and takes the first maximum correlation peak as the Time of Arrival (TOA) of the signal. The detection of TOA is usually based on the theoretical autocorrelation triangular waveform of the signal for detection. However, as the communication network environment becomes more and more complex and changeable, for example, in multipath complex environments such as indoors and dense urban areas, due to the influence of noise and multipath, the slope of the signal correlation waveform is distorted and is no longer an ideal triangular waveform. Therefore, there are very large errors in the slope-based detection method; and in practical applications, the bandwidth is limited. When the bandwidth is strictly restricted, the autocorrelation waveform is no longer a strict triangular waveform. This situation is mixed with the multipath situation, making the signal correlation waveform more complex, and the accuracy and reliability of the slope-based detection method are relatively low. Summary of the Invention

[0003] The present application provides a method, apparatus, signal receiving device, and storage medium for determining time of arrival to improve the accuracy and reliability of time of arrival detection.

[0004] An embodiment of the present application provides a method for determining time of arrival, including:

[0005] Generating time of arrival correction information according to the leading edge information of the theoretical autocorrelation waveform of positioning signals with different fading values;

[0006] Calculating the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actually received signal;

[0007] Determining target correction information from the time of arrival correction information according to the leading edge slope, and determining the time of arrival of the actually received signal based on the target correction information.

[0008] The embodiment of the present application further provides a device for determining the arrival time, including:

[0009] A correction information generation module, configured to generate arrival time correction information according to the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values;

[0010] A leading edge slope calculation module, configured to calculate the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actually received signal;

[0011] An arrival time determination module, configured to determine target correction information from the arrival time correction information according to the leading edge slope, and determine the arrival time of the actually received signal based on the target correction information.

[0012] The embodiment of the present application further provides a signal receiving device, including:

[0013] One or more processors;

[0014] A storage device for storing one or more programs;

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for determining the arrival time.

[0016] The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned method for determining the arrival time is implemented. Description of the Drawings

[0017] Figure 1 It is a schematic diagram of the actually received signal in the case of multipath transmission;

[0018] Figure 2 It is a flowchart of a method for determining the arrival time provided by an embodiment;

[0019] Figure 3 It is a flowchart of a method for determining the arrival time provided by another embodiment;

[0020] Figure 4 It is a schematic diagram of the theoretical autocorrelation waveforms of m first equal division lines and n positioning signals provided by an embodiment;

[0021] Figure 5 It is a schematic diagram of the leading edge slope detection of a single-path signal provided by an embodiment;

[0022] Figure 6 It is a schematic diagram of the leading edge slope detection of a multipath signal provided by an embodiment;

[0023] Figure 7Schematic structural diagram of a device for determining time of arrival provided for an embodiment;

[0024] Figure 8 Schematic hardware structure diagram of a signal receiving device provided for an embodiment. Detailed implementation manners

[0025] The present application will be described below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than limiting the present application. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. Additionally, it should be noted that for the sake of description, only the parts related to the present application rather than all the structures are shown in the accompanying drawings.

[0026] When positioning devices in a wireless communication network, it is necessary to detect the time of arrival of signals. The detection of the time of arrival is usually achieved based on the detection of the slope of the theoretical autocorrelation triangular waveform of the signal. For example, the first maximum correlation peak is taken as the time of arrival of the signal. However, as the communication network environment becomes more and more complex and changeable, such as in indoor, dense urban areas and other environments with complex multipaths, due to the influence of noise and multipaths, the slope of the signal correlation waveform often becomes distorted.

[0027] Figure 1 Schematic diagram of the actual received signal in the case of multipath transmission. Figure 1 Taking the case of signal multipath transmission as an example, the dotted line represents the result of the signal after multipath transmission, and the solid line represents the waveform of the actual received signal at the receiving end. Obviously, the correlation waveform of the actual received signal is no longer an ideal triangular waveform. Therefore, the method based on slope detection to determine the time of arrival of the signal has a very large error. Even for a single-path signal, due to the instability of the channel quality, the influence of other noises or bandwidth limitations, the slope detection method has a large error, thus making it impossible to achieve high-precision measurement of the time of arrival in a complex wireless environment and bandwidth limitations.

[0028] In this embodiment, aiming at the low accuracy of measuring the time of arrival based on slope in a complex and changeable network environment, arrival time correction information is generated according to the theoretical autocorrelation waveform of the positioning signal, and the time amount of some leading edge positions of the actual received signal is corrected according to the theoretical arrival time correction information, which can pay attention to the detailed changes of the leading edge of the correlation waveform of the actual received signal in a multipath or noise environment, making the detection result of the leading edge slope of the actual received signal closer to the theoretical waveform, thereby improving the accuracy and reliability of the time of arrival detection.

[0029] Figure 2 Flowchart of a method for determining time of arrival provided for an embodiment, as shown in Figure 2As shown in the figure, the method provided in this embodiment includes steps 110-140.

[0030] In step 110, arrival time correction information is generated based on the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values.

[0031] In step 120, the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actually received signal is calculated.

[0032] In step 130, target correction information is determined from the arrival time correction information according to the leading edge slope.

[0033] In step 140, the arrival time of the actually received signal is determined based on the target correction information.

[0034] In this embodiment, the arrival time correction information is generated using the leading edge information of the theoretical autocorrelation waveform of the positioning signal. Among them, there can be multiple theoretical autocorrelation waveforms of the positioning signal, corresponding to different fading values respectively. For example, according to a certain rule, the theoretical autocorrelation waveforms of the positioning signal corresponding to different fading values are divided into several segments. According to the division result, several reference points on the leading edge of the theoretical autocorrelation wave can be determined. The arrival time correction information can be generated according to the time amounts corresponding to each reference point. The arrival time correction information can be stored in the form of a table. Each item in the arrival time correction information corresponds to a reference point and records the leading edge information of this reference point. The leading edge information can include slope, time amount, etc. The arrival time correction information generated according to the theoretical autocorrelation waveform conforms to the transmission result of the signal under ideal conditions.

[0035] Since the slope of the actually received signal has been distorted, the slopes corresponding to the positions corresponding to the above reference points may be different, and the corresponding time amounts are also inaccurate. Therefore, it is inaccurate to determine the arrival time through slope detection. In this embodiment, according to the leading edge slope of the leading edge reference point of the actually received signal, the target correction information at the position corresponding to the leading edge reference point is searched in the arrival time correction information. Based on this, the time amount of the leading edge reference point of the actually received signal is corrected. On this basis, the earliest time among the corrected time amounts corresponding to each leading edge reference point (it can also be the average time amount obtained through mathematical statistical operations based on the earliest several times or the earliest type of time amount, etc.) can be used as the arrival time, thereby reducing the error of the arrival time of the actually received signal based on slope detection.

[0036] In one embodiment, the fading values of the positioning signals can be divided into several different values according to certain rules to obtain positioning signals corresponding to different fading values. For example, the positioning signals are normalized, and the maximum fading value is 1. The fading values are divided into three cases. Taking the fading values divided into three equal parts as an example, the fading values of the positioning signals are 1, 2 / 3, and 1 / 3 respectively, and the theoretical autocorrelation waveforms of the three positioning signals are obtained. For the theoretical autocorrelation waveform of each positioning signal, it can be divided into several segments according to certain rules, so as to determine several reference points on the leading edge. The time-of-arrival correction information is generated based on the slopes and time amounts corresponding to each reference point. For the correlation waveform of the actually received signal, it can be divided into several segments according to the same rules to obtain corresponding leading-edge reference points. According to the leading-edge slope of each leading-edge reference point, the item closest to it is determined from the time-of-arrival correction information respectively, which is the target correction information corresponding to the leading-edge reference point. In some embodiments, the theoretical autocorrelation waveform of the positioning signal is normalized according to the modulus value or the fading value, and the correlation waveform of the actually received signal is normalized according to the modulus value, so as to facilitate the selection of reference points and reduce the calculation amount.

[0037] The time-of-arrival determination method of this embodiment generates time-of-arrival correction information according to the theoretical autocorrelation waveform of the positioning signal, corrects the leading-edge reference points of the actually received signal according to the theoretical time-of-arrival correction information, and determines the time of arrival based on the data of the correlation waveform of the actually received signal after correction. It can pay attention to the details of the leading-edge change of the correlation waveform of the actually received signal in a multipath or noisy environment, make the detection result of the leading-edge slope of the actually received signal closer to the theoretical waveform, and thus improve the accuracy and reliability of the time-of-arrival detection.

[0038] Figure 3 The flowchart of a method for determining the time of arrival provided for another embodiment is as Figure 3 shown. The method provided in this embodiment includes steps 210-270.

[0039] In step 210, the autocorrelation waveform of the normalized positioning signal is equally divided into n parts according to the fading value, and the theoretical autocorrelation waveforms of n positioning signals corresponding to different fading values are obtained.

[0040] In step 220, the leading-edge height of the autocorrelation waveform of the normalized positioning signal is equally divided into m parts to obtain m first equal division lines.

[0041] In step 230, the time-of-arrival correction information is generated according to the m first equal division lines and the theoretical autocorrelation waveforms of the n positioning signals.

[0042] In this embodiment, the positioning signal is normalized according to the modulus value, that is, the maximum modulus value is 1. Dividing the autocorrelation waveform of the normalized positioning signal into n equal parts according to the fading value means: dividing the autocorrelation waveform of the normalized positioning signal into n cases, which are in turn: the case where the maximum modulus value of the autocorrelation function is 1, the case where the maximum modulus value of the autocorrelation function is (n - 1) / n, …, and the case where the maximum modulus value of the autocorrelation function is 1 / n. There are n positioning signals corresponding to different fading values. In addition, the autocorrelation waveform of the normalized positioning signal is equally divided into m parts from a leading edge height of 0 to 1, obtaining m first equal division lines, and the height of each part is 1 / m.

[0043] Figure 4 FIG. is a schematic diagram of the theoretical autocorrelation waveforms of m first equal division lines and n positioning signals provided for an embodiment. As Figure 4 shown, the leading edge heights corresponding to the m first equal division lines are successively 1 / m, 2 / m, …, m / m from bottom to top; the fading values corresponding to the theoretical autocorrelation waveforms of the n positioning signals are successively n / n, (n - 1) / n, …, 1 / n from top to bottom. Denote the time quantity corresponding to the intersection point of the i-th (i = 1, 2, ..., m) first equal division line and the autocorrelation waveform of the j-th (j = 1, 2, ..., n) fading value at the leading edge as T i,j , and denote the time quantity corresponding to the maximum fading value as T max . As Figure 4 shown, there are multiple intersection points at the leading edges of the m first equal division lines and the theoretical autocorrelation waveforms of the n positioning signals. Using these intersection points as reference points, the corresponding standard slopes and the corresponding arrival time correction values can be calculated to obtain arrival time correction information, which can be stored in tabular form.

[0044] In step 240, calculate the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actually received signal.

[0045] In this embodiment, for the actually received signal, some leading edge reference points are selected. For example, by equally dividing the correlation waveform of the actually received signal into m parts according to the modulus value to obtain the intersection points on the leading edge, and calculate the leading edge slopes of these intersection points. The rule for selecting leading edge reference points for the actually received signal is the same as the rule for selecting reference points for the theoretical autocorrelation waveform of the positioning signal, making the correction of the actually received signal closer to the theoretical autocorrelation waveform, with a higher matching degree between the correction information and the actually received signal, and improving the arrival time detection accuracy.

[0046] In step 250, search for the target correction information in the arrival time correction information according to each leading edge slope. The target correction information includes the standard slope corresponding to each leading edge slope and the arrival time correction value corresponding to each standard slope.

[0047] The arrival time correction information stores multiple standard slopes and corresponding arrival time correction values. According to the leading edge slope of the actual received waveform, the closest standard slope can be found in the arrival time correction information, and the corresponding arrival time correction value can be read. Taking the example of equally dividing the relevant waveform of the actual received signal into m equal parts, the number of leading edge reference points is m, and the number of leading edge slopes is m, which are k r (r = 1, 2,..., m), then the number of target correction information found is also m, which are the standard slopes and arrival time correction values closest to k r The time amounts where the m leading edge reference points are located can be corrected respectively using the m arrival time correction values.

[0048] In step 260, the candidate arrival times corresponding to the respective leading edge slopes are calculated according to the respective arrival time correction values.

[0049] In step 270, the arrival time of the actual received signal is determined according to the respective candidate arrival times.

[0050] In this embodiment, for the m leading edge reference points and the m arrival time correction values found, m corrected arrival times, that is, candidate arrival times, are obtained in sequence. Clustering, averaging, etc. are performed on the candidate arrival times, so that the candidate arrival time corresponding to the cluster with the earliest time (the smallest time amount value) can be used as the arrival time of the actual received signal.

[0051] In one embodiment, the autocorrelation waveform of the normalized positioning signal is the autocorrelation waveform normalized according to the modulus value; the maximum value of the maximum modulus value of the theoretical autocorrelation waveforms of n positioning signals is 1, and the minimum value is 1 / n; m and n are negatively correlated with the arrival time correction accuracy respectively.

[0052] In this embodiment, according to the requirement of the accuracy of arrival time measurement (the minimum error of arrival time measurement), the theoretical autocorrelation waveform of the normalized positioning signal is equally divided into m equal parts according to the leading edge height and into n equal parts according to the fading value. The larger m is, the higher the accuracy, and the smaller the minimum error of arrival time measurement; the larger n is, the higher the accuracy, and the smaller the minimum error of arrival time measurement. Thus, the correction information at each position on the leading edge is comprehensively and carefully considered, and the accuracy of correcting the actual received waveform is improved. According to the accuracy requirement, the values of m and n can be determined through simulation.

[0053] In some embodiments, reference points on the theoretical autocorrelation waveforms of various fading values may also be divided and selected according to other rules, not necessarily in the form of equally dividing the leading edge height. For example, more segments may be divided in the steeper (large leading edge height change rate) or larger amplitude leading edge parts according to the statistical law of amplitude values to determine more reference points, so as to obtain a denser and more accurate standard slope and arrival time correction value; while for the gentler (small leading edge height change rate) or smaller amplitude leading edge parts, fewer reference points may be selected to simplify the calculation to a certain extent.

[0054] In one embodiment, the arrival time correction information includes a standard slope and an arrival time correction value.

[0055] Step 230 specifically includes:

[0056] Step 231: Calculate the standard slope corresponding to the intersection point of each of the first equally dividing lines and the leading edge of the theoretical autocorrelation waveform of each of the positioning signals.

[0057] Step 232: Determine the arrival time correction value corresponding to each standard slope according to the difference between the time amount corresponding to the maximum modulus value of the autocorrelation waveform of the normalized positioning signal and the time amount corresponding to each intersection point.

[0058] In this embodiment, the arrival time correction information includes a standard slope and an arrival time correction value. The standard slope corresponding to the intersection point of the i-th (i = 1, 2,..., m) first equally dividing line and the theoretical autocorrelation waveform of the positioning signal of the j-th (j = 1, 2,..., n) fading value is denoted as k i,j , and the corresponding arrival time correction value is denoted as α i,j . Then, the basis for generating the arrival time correction information is as follows: α i,j = T max - T i,j , i ∈ (1, m], j ∈ (1, n]. Wherein, k i,j is the standard slope in the table entry, α i,j is the arrival time correction value, T max is the time amount corresponding to the maximum modulus value of the theoretical autocorrelation waveform, T i,j is the time value corresponding to the data point where the maximum modulus value of the autocorrelation function is j / n and the leading edge height is i / m. is the data at the time of T i,j in the theoretical autocorrelation function, is the data at the time of T i,j+Δc in the theoretical autocorrelation function, and Δc is on the theoretical autocorrelation function waveform and T i,jThe time difference between adjacent data points at the intersection, L is the range of adjacent points used to calculate the slope, for example, L = 5. By determining the arrival time correction value based on the time quantity corresponding to the maximum modulus value, making the time quantity at each intersection closer to the maximum modulus value after adding a certain correction value, and applying this correction value to the actual received waveform, the accuracy of correcting the actual received waveform can be improved, and the detection accuracy can be enhanced.

[0059] Table 1 Arrival time correction information generated according to the theoretical autocorrelation waveforms of m first dividing lines and n positioning signals

[0060]

[0061] Table 1 shows the arrival time correction information generated according to the theoretical autocorrelation waveforms of m first dividing lines and n positioning signals. As shown in Table 1, the arrival time correction information is stored in the form of a table. The arrival time correction table can be a two-dimensional table, with the horizontal axis being n fading values and the vertical axis being m leading edge heights. The table entries include the standard slope and the arrival time correction value. The arrival time correction information corresponding to the theoretical autocorrelation waveform of the positioning signal of the i-th first dividing line and the j-th fading value includes the standard slope k i,j and the arrival time correction value α ij .

[0062] In one embodiment, step 240 specifically includes:

[0063] Step 241: Divide the leading edge height of the autocorrelation waveform of the actual received signal into m equal parts to obtain m second dividing lines;

[0064] Step 242: Determine m leading edge reference points according to the intersections of the m second dividing lines and the leading edge of the autocorrelation waveform of the actual received signal;

[0065] Step 243: Calculate the leading edge slopes corresponding to each of the leading edge reference points respectively.

[0066] In this embodiment, the leading edge height of the autocorrelation waveform of the actual received signal is divided into m equal parts to obtain m second dividing lines. In this embodiment, the rule for selecting the leading edge reference points for the actual received signal is the same as the rule for selecting the reference points for the theoretical autocorrelation waveform of the positioning signal, making the correction of the actual received signal closer to the theoretical autocorrelation waveform, with a higher matching degree between the correction information and the actual received signal, and improving the arrival time detection accuracy.

[0067] For the convenience of calculation, the correlation waveform of the actual received signal is normalized, and the height of each divided part is 1 / m. The amplitudes corresponding to each second equal line are 1 / m, 2 / m, …, m / m in sequence. The intersection point of each second equal line and the leading edge of the correlation waveform is a leading edge reference point. There are m reference points in total, corresponding to m leading edge slopes respectively. Denote the leading edge slope corresponding to each leading edge reference point as k r (r = 1, 2, ..., m). For each leading edge reference point (using adjacent points near it), calculate the leading edge slope k r The basis is as follows: Among them, is the data at the intersection point corresponding to the r-th second equal line, is the received correlation waveform data with a time interval of Δc from this intersection point, T r is the time quantity corresponding to this intersection point.

[0068] In one embodiment, the correlation waveform of the actual received signal is the correlation waveform normalized according to the modulus value. In this embodiment, by performing a mathematical correlation operation on the actual received signal and the transmission sequence locally stored in the signal receiving device, the correlation waveform of the actual received signal can be obtained. Dividing the whole correlation waveform by the maximum modulus value can obtain the normalized autocorrelation waveform.

[0069] In some embodiments, the leading edge reference points of the actual received waveform can also be selected according to other rules, not necessarily in the form of equally dividing the leading edge height. For example, according to the statistical law of the amplitude, more segments can be divided in the steeper (the leading edge height change rate is large) or larger amplitude leading edge part to determine more leading edge reference points for more precise correction; while for the flatter (the leading edge height change rate is small) or smaller amplitude leading edge part, fewer reference points can be selected to simplify the calculation to a certain extent.

[0070] In one embodiment, step 250 is specifically as follows:

[0071] For each of the leading edge slopes, use the standard slope closest to the leading edge slope in the arrival time correction information as the standard slope corresponding to the leading edge slope, and read the corresponding arrival time correction value.

[0072] For each leading edge slope denoted as k r , search the arrival time correction information (denoted as Ω), and obtain the standard slope closest to k r in the table entry: k r,i,j = min(|k i,j - k r |), k i,j ∈Ω, and the corresponding α i,j is the arrival time correction value corresponding to the table entry closest to k r .

[0073] In one embodiment, step 260 specifically includes:

[0074] Taking the sum of the actual time corresponding to each of the leading slopes and the corresponding arrival time correction value as the candidate arrival time corresponding to the leading slope.

[0075] In this embodiment, the actual time amount at the intersection of the r-th second bisector on the correlation waveform of the actually received signal is denoted as T r , then the corresponding corrected candidate arrival time can be denoted as TOA r = T r + α i,j .

[0076] In one embodiment, step 270 specifically includes:

[0077] Step 271: Establish clusters for each of the candidate arrival times according to the clustering discrimination threshold, and each cluster contains at least one candidate arrival time;

[0078] Step 272: Determine the arrival time of the actually received signal according to the cluster with the smallest value of the candidate arrival time.

[0079] In one embodiment, when the difference between any two candidate arrival times among the x candidate arrival times is less than or equal to the clustering discrimination threshold, the x candidate arrival times belong to one cluster, where x is an integer greater than or equal to 2.

[0080] In this embodiment, the basis for establishing the cluster is that for any TOA i and TOA j , i, j ∈ [1, m], if it satisfies: |TOA i -TOA j | ≤ Z, then TOA i and TOA j belong to one cluster, where Z is the clustering discrimination threshold and can be determined by simulation. The value of Z can be determined according to the arrival time measurement accuracy requirement.

[0081] In one embodiment, step 272 specifically includes:

[0082] Calculating the mean value of the candidate arrival times corresponding to each of the clusters, and taking the smallest mean value as the arrival time of the actually received signal.

[0083] In this embodiment, the average value of the candidate arrival times is calculated for each cluster as the candidate TOA of the cluster. The smallest cluster refers to the cluster where the smallest candidate TOA is located. For the candidate TOAs of all clusters, the smallest candidate TOA is taken as the earliest arrival time of the signal. In some embodiments, the cluster where the smallest candidate arrival time is located can also be taken as the smallest cluster, and the average value of the candidate arrival times corresponding to the smallest cluster is taken as the arrival time.

[0084] The following takes a single-path signal and a multipath signal as examples respectively, and illustrates the arrival time detection process through examples.

[0085] Example 1: Determining the arrival time of a single-path signal based on leading edge slope detection

[0086] Parameter settings: The positioning signal transmitted by the base station is a positioning reference signal (PRS) of the 3rd Generation Partnership Project (3GPP) standard. The main parameters include a bandwidth of 100M, a physical cell identifier (PCI) of 1, a sampling period Ts = 8ns, and an oversampling factor of 30. For a single-path signal, the receiving end performs a correlation operation on the actual received signal and the local signal to obtain a correlation waveform.

[0087] 1) Normalize the positioning signal, divide the theoretical autocorrelation waveform of the normalized positioning signal into 10 equal parts according to the leading edge height, and divide it into 20 equal parts according to the fading value to generate arrival time correction information. Table 2 is the generated arrival time correction information table. As shown in Table 2, the correction table includes the standard slope and the corresponding arrival time correction value corresponding to different leading edge heights and fading values.

[0088] Table 2 Arrival time correction information table

[0089]

[0090] 2) Calculate the leading edge slope of the correlation waveform of the actual received signal. Figure 5 FIG. is a schematic diagram of the leading edge slope detection of a single-path signal provided by an embodiment. In the case where the actual received signal is a single-path signal and there is no multipath influence, its correlation waveform is as Figure 5 shown. Divide it into 10 equal parts according to the leading edge height, and calculate the leading edge slope at the intersection of each equal division line and the leading edge. There are 10 leading edge slopes, denoted as k r (r = 1, 2,..., 10).

[0091] 3) For each leading edge slope k rSearch the arrival time correction table respectively to determine the target correction information, specifically to find the standard slope k r closest to k r,i,j in Table 2, and read the corresponding arrival time correction value. For example, Figure 5 in, the leading edge slope of the leading edge reference point at the leading edge height of 1 / m (m = 10) is k1, and the standard slope closest to k1 in Table 2 is k 1,20 = 0.0071, then read the corresponding arrival time correction value as α 1,n = 109. Search each leading edge slope k r (r = 1, 2,..., 10) in this way, and a total of 10 arrival time correction values are obtained. α i,j (i = 1, 2,..., 10) are respectively: {109, 96, 84, 73, 62, 52, 42, 33, 22, 0}.

[0092] 4) Correct the time quantity corresponding to each leading edge reference point according to the target correction information. Figure 5 In the relevant waveforms shown, the original time quantities T r (i = 1, 2,..., 10) corresponding to each leading edge reference point are respectively: {245651, 245664, 245676, 245687, 245698, 245708, 245718, 245727, 245738, 245760}, then according to T r + τ i,j 10 corrected candidate arrival times are obtained respectively. The candidate arrival times are respectively: {245760, 245760, 245760, 245760, 245760, 245760, 245760, 245760, 245760, 245760}.

[0093] 5) Cluster the candidate arrival times. Let the clustering discrimination threshold Z = 5. The differences between the above candidate arrival times are all less than 5, so the above candidate arrival times all belong to the same cluster. This is because the single-path signal is not affected by multipath transmission, its relevant waveform is closer to the ideal state, and the error and fluctuation between the candidate arrival times are also small. The average value of the candidate arrival times in this cluster is 245760, that is, the finally measured TOA is 245760. The unit of the above time quantity is Ts / 30.

[0094] Example 2: Determine the arrival time based on the leading edge slope detection for multipath signals

[0095] Parameter settings: The positioning signal transmitted by the base station is a PRS signal compliant with the 3GPP standard. The main parameters include a bandwidth of 100M, a Physical Cell Identifier (PCI) of 1, a sampling period Ts = 8 ns, and an oversampling factor of 30. In this example, a multipath channel with two paths is constructed. The attenuation of the first path is 0.5, the second path has no attenuation, and the delay is 100(Ts / 30).

[0096] 1) Normalize the positioning signal, divide the theoretical autocorrelation waveform of the normalized positioning signal into 10 equal parts according to the leading edge height and 20 equal parts according to the fading value to generate arrival time correction information. Refer to Table 2.

[0097] 2) Calculate the leading edge slope of the correlation waveform of the actual received signal. Figure 6 FIG. is a schematic diagram of detecting the leading edge slope of a multipath signal provided for an embodiment. When the actual received signal is a multipath signal, the correlation waveform obtained after performing a correlation operation with the local signal is as shown in Figure 6 FIG., divide it into 10 equal parts according to the leading edge height, and calculate the leading edge slopes at the intersections of each equal division line and the leading edge. There are 10 leading edge slopes in total, denoted as k r (r = 1, 2,..., 10).

[0098] 3) For each leading edge slope k r search the arrival time correction table respectively to determine the target correction information. Specifically, find the standard slope k r in Table 2 that is closest to k i,j , and read the corresponding arrival time correction value. A total of 10 arrival time correction values are obtained, and α i,j (i = 1, 2,..., 10) are respectively: {94, 77, 66, 33, 41, 52, 42, 33, 22, 0}.

[0099] 4) Correct the time quantities corresponding to each leading edge reference point according to the target correction information. Figure 6 In the correlation waveform shown in FIG., the original time quantities T r (r = 1, 2,..., 10) corresponding to each leading edge reference point are respectively: {245664, 245686, 245705, 245723, 245803, 245814, 245824, 245833, 245843, 245864}. Then, according to T r + τ i,j , 10 corrected candidate arrival times are obtained respectively. The candidate arrival times are respectively: {245758, 245763, 245771, 245756, 245844, 245866, 45866, 245866, 245865, 245864}.

[0100] 5) Cluster the candidate arrival times. Let the clustering discrimination threshold Z = 5. The smallest cluster obtained is {245756, 245758}. The average value of the candidate arrival times in this cluster is 245757, that is, the finally measured TOA is 245757. The above time unit is Ts / 30.

[0101] For the arrival time determination method of the above embodiment, by normalizing and equally dividing the theoretical autocorrelation waveform of the positioning signal and the correlation waveform of the actual received signal, the reference point is determined to make the corresponding positions of the theoretical autocorrelation waveform and the correlation waveform of the actual received signal correspond. Using the theoretical standard slope and the arrival time correction value to correct the time quantity of the leading edge reference point of the actual received signal. On this basis, the arrival time is determined according to the minimum cluster, which can significantly reduce the influence of the bandwidth signal on the slope detection, refine the change details of the leading edge of the autocorrelation signal in the multipath environment, and improve the detection accuracy.

[0102] The embodiment of the present application also provides a device for determining the arrival time. Figure 7 It is a schematic structural diagram of a device for determining the arrival time provided by an embodiment. As Figure 7 shown, the device for determining the arrival time includes: a correction information generation module 310, a leading edge slope calculation module 320, and an arrival time determination module 330.

[0103] The correction information generation module 310 is configured to generate arrival time correction information according to the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values;

[0104] The leading edge slope calculation module 320 is configured to calculate the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal;

[0105] The arrival time determination module 330 is configured to determine the target correction information from the arrival time correction information according to the leading edge slope, and determine the arrival time of the actual received signal based on the target correction information.

[0106] For the device for determining the arrival time of this embodiment, the arrival time correction information is generated according to the theoretical autocorrelation waveform of the positioning signal, and the time quantity of some leading edge positions of the actual received signal is corrected according to the theoretical arrival time correction information, which can pay attention to the change details of the leading edge of the correlation waveform of the actual received signal in the multipath or noise environment, make the detection result of the leading edge slope of the actual received signal closer to the theoretical waveform, thereby improving the accuracy and reliability of the arrival time detection.

[0107] In an embodiment, the correction information generation module 310 includes:

[0108] The first equal division unit is configured to equally divide the autocorrelation waveform of the normalized positioning signal according to the fading value into n, obtaining the theoretical autocorrelation waveforms of n positioning signals corresponding to different fading values;

[0109] The second equal division unit is configured to equally divide the front edge height of the autocorrelation waveform of the normalized positioning signal into m, obtaining m first equal division lines;

[0110] The correction unit is configured to generate the arrival time correction information according to the m first equal division lines and the theoretical autocorrelation waveforms of the n positioning signals;

[0111] Wherein, both m and n are integers greater than 2.

[0112] In an embodiment, the arrival time correction information includes a standard slope and an arrival time correction value;

[0113] The correction unit includes:

[0114] The first calculation subunit is configured to calculate the standard slope corresponding to the intersection point of each of the first equal division lines and the front edge of the theoretical autocorrelation waveform of each positioning signal;

[0115] The second calculation subunit is configured to determine the arrival time correction value corresponding to each standard slope according to the difference between the time amount corresponding to the maximum modulus value of the autocorrelation waveform of the normalized positioning signal and the time amount corresponding to each intersection point.

[0116] In an embodiment, the front edge slope calculation module 320 includes:

[0117] The third equal division unit is configured to equally divide the front edge height of the correlation waveform of the actually received signal into m, obtaining m second equal division lines;

[0118] The reference point determination unit is configured to determine m front edge reference points according to the intersection points of the m second equal division lines and the front edge of the correlation waveform of the actually received signal;

[0119] The slope calculation module is configured to calculate the front edge slope corresponding to each of the front edge reference points respectively.

[0120] In an embodiment, the arrival time determination module 330 includes:

[0121] The search unit is configured to search for target correction information in the arrival time correction information according to each front edge slope, and the target correction information includes the standard slope corresponding to each front edge slope and the arrival time correction value corresponding to each standard slope;

[0122] The candidate time calculation unit is configured to calculate the candidate arrival time corresponding to each front edge slope according to each arrival time correction value;

[0123] An arrival time determination unit, configured to determine the arrival time of the actual received signal according to each of the candidate arrival times.

[0124] In one embodiment, the search unit is specifically configured to:

[0125] For each of the leading edge slopes, use the standard slope in the arrival time correction information that is closest to the leading edge slope as the standard slope corresponding to the leading edge slope, and read the corresponding arrival time correction value.

[0126] In one embodiment, the candidate time calculation unit is specifically configured to:

[0127] Use the sum of the actual time corresponding to each of the leading edge slopes and the corresponding arrival time correction value as the candidate arrival time corresponding to the leading edge slope.

[0128] In one embodiment, the arrival time determination unit includes:

[0129] A clustering subunit, configured to establish a clustering of each of the candidate arrival times according to a clustering discrimination threshold, and each clustering contains at least one candidate arrival time;

[0130] A time determination subunit, configured to determine the arrival time of the actual received signal according to the clustering with the smallest value of the candidate arrival time.

[0131] In one embodiment, the time determination subunit is specifically configured to:

[0132] Use the mean value of the candidate arrival times in the clustering with the smallest value of the candidate arrival time as the arrival time of the actual received signal.

[0133] In one embodiment, when the difference between any two candidate arrival times among x candidate arrival times is less than or equal to the clustering discrimination threshold, the x candidate arrival times belong to one clustering, where x is an integer greater than or equal to 2.

[0134] In one embodiment, the autocorrelation waveform of the normalized positioning signal is an autocorrelation waveform normalized according to the modulus value;

[0135] The maximum value of the maximum modulus value of the theoretical autocorrelation waveforms of the n positioning signals is 1, and the minimum value is 1 / n;

[0136] m and n are respectively negatively correlated with the arrival time correction accuracy.

[0137] In one embodiment, the correlation waveform of the actual received signal is a correlation waveform normalized according to the modulus value.

[0138] The arrival time determination device proposed in this embodiment and the arrival time determination method proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to in any of the above embodiments, and this embodiment has the same beneficial effects as those of the execution of the arrival time determination method.

[0139] An embodiment of the present application further provides a signal receiving device. The arrival time determination method can be executed by the arrival time determination device, and the arrival time determination device can be implemented in a software and / or hardware manner and integrated in the signal receiving device.

[0140] Figure 8 FIG. is a schematic hardware structure diagram of a signal receiving device provided in an embodiment. As Figure 8 shown, a signal receiving device provided in this embodiment includes: a processor 410 and a storage device 420. The processor in this signal receiving device can be one or more. Figure 8 Taking one processor 410 as an example, the processor 410 and the storage device 420 in the device can be connected through a bus or other means. Figure 8 Taking the connection through the bus as an example.

[0141] The one or more programs are executed by the one or more processors 410, so that the one or more processors implement the arrival time determination method described in any of the above embodiments.

[0142] The storage device 420 in this signal receiving device, as a computer-readable storage medium, can be used to store one or more programs. The programs can be software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the arrival time determination method in the embodiments of the present invention (for example, the modules in the arrival time determination device shown in Figure 7 include: a correction information generation module 310, a leading edge slope calculation module 320, and an arrival time determination module 330). The processor 410 executes various functional applications and data processing of the signal receiving device by running the software programs, instructions, and modules stored in the storage device 420, that is, implements the arrival time determination method in the above method embodiments.

[0143] The storage device 420 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the device (such as the arrival time correction information, leading edge slope, etc. in the above embodiments). In addition, the storage device 420 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some instances, the storage device 420 may further include a memory remotely set relative to the processor 410, and these remote memories can be connected to the signal receiving device through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] Moreover, when one or more programs included in the above signal receiving device are executed by the one or more processors 410, the following operations are implemented: generating arrival time correction information according to the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values; calculating the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal; determining target correction information from the arrival time correction information according to the leading edge slope, and determining the arrival time of the actual received signal based on the target correction information.

[0145] The signal receiving device proposed in this embodiment and the method for determining the arrival time proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to any of the above embodiments, and this embodiment has the same beneficial effects as the method for determining the arrival time.

[0146] The embodiment of the present application also provides a storage medium containing computer-executable instructions. The computer-executable instructions are used to execute a method for determining the arrival time when executed by a computer processor. The method includes: generating arrival time correction information according to the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values; calculating the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal; determining target correction information from the arrival time correction information according to the leading edge slope, and determining the arrival time of the actual received signal based on the target correction information.

[0147] From the above description of the embodiments, those skilled in the art can understand that this application can be implemented by means of software and general-purpose hardware, or by hardware. Based on such an understanding, the technical solution of this application can be embodied in the form of a software product, and this computer software product can be stored in a computer-readable storage medium, such as a floppy disk of a computer, a read-only memory (ROM), a random access memory (RAM), a flash memory (FLASH), a hard disk, or an optical disc, etc., including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method described in any embodiment of this application.

[0148] As described above, the above are only exemplary embodiments of this application and are not used to limit the protection scope of this application.

[0149] Any block diagram of a logical process in the drawings of this application can represent program steps, or can represent interconnected logical circuits, modules, and functions, or can represent a combination of program steps and logical circuits, modules, and functions. The computer program can be stored on a memory. The memory can be of any type suitable for the local technical environment and can be implemented using any suitable data storage technology, such as, but not limited to, read-only memory (ROM), random access memory (RAM), optical memory devices and systems (digital versatile disc DVD or CD disc), etc. The computer-readable medium can include a non-transitory storage medium. The data processor can be of any type suitable for the local technical environment, such as, but not limited to, a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (FGPA), and a processor based on a multi-core processor architecture.

[0150] Through exemplary and non-limiting examples, a detailed description of the exemplary embodiments of this application has been provided above. However, considering the accompanying drawings and the claims, various modifications and adjustments to the above embodiments will be obvious to those skilled in the art without departing from the scope of the invention. Therefore, the proper scope of the invention will be determined according to the claims.

Claims

1. A method for determining the arrival time, characterized in that Including: Generating arrival time correction information based on the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values; Calculating the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal; Determining target correction information from the arrival time correction information according to the leading edge slope, and determining the arrival time of the actual received signal based on the target correction information.

2. The method for determining the arrival time according to claim 1, characterized in that, The generating arrival time correction information based on the leading edge information of the theoretical autocorrelation waveform of the positioning signal with different fading values includes: Dividing the autocorrelation waveform of the normalized positioning signal into n equal parts according to the fading value to obtain n theoretical autocorrelation waveforms of the positioning signal corresponding to different fading values; Dividing the leading edge height of the autocorrelation waveform of the normalized positioning signal into m equal parts to obtain m first equal division lines; Generating the arrival time correction information according to the m first equal division lines and the n theoretical autocorrelation waveforms of the positioning signal; Wherein, both m and n are integers greater than 2.

3. The method for determining the arrival time according to claim 2, wherein The arrival time correction information includes a standard slope and an arrival time correction value; The generating the arrival time correction information according to the m first equal division lines and the n theoretical autocorrelation waveforms of the positioning signal includes: Calculating the standard slope corresponding to the intersection point of each of the first equal division lines and the leading edge of each of the theoretical autocorrelation waveforms of the positioning signal; Determining the arrival time correction value corresponding to each standard slope according to the difference between the time amount corresponding to the maximum modulus value of the autocorrelation waveform of the normalized positioning signal and the time amount corresponding to each intersection point.

4. The method for determining the arrival time according to claim 2, wherein The calculating the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal includes: Dividing the leading edge height of the correlation waveform of the actual received signal into m equal parts to obtain m second equal division lines; Determining m leading edge reference points according to the intersection points of the m second equal division lines and the leading edge of the correlation waveform of the actual received signal; Respectively calculating the leading edge slope corresponding to each of the leading edge reference points.

5. The method for determining the arrival time according to claim 4, wherein The determining target correction information from the arrival time correction information according to the leading edge slope, and determining the arrival time of the actual received signal based on the target correction information includes: Searching for target correction information in the arrival time correction information according to each leading edge slope, where the target correction information includes the standard slope corresponding to each leading edge slope and the arrival time correction value corresponding to each standard slope; Calculating the candidate arrival time corresponding to each leading edge slope according to each arrival time correction value; Determining the arrival time of the actual received signal according to each candidate arrival time.

6. The method for determining the arrival time according to claim 5, wherein The searching for target correction information in the arrival time correction information according to each leading edge slope includes: For each leading edge slope, taking the standard slope closest to the leading edge slope in the arrival time correction information as the standard slope corresponding to the leading edge slope, and reading the corresponding arrival time correction value.

7. The method according to claim 5, characterized in that, The calculating the candidate arrival time corresponding to each leading edge slope according to each arrival time correction value includes: Taking the sum of the actual time corresponding to each leading edge slope and the corresponding arrival time correction value as the candidate arrival time corresponding to the leading edge slope.

8. The method for determining the arrival time according to claim 5, characterized in that Determining the arrival time of the actual received signal according to each of the candidate arrival times includes: Establishing clusters of each of the candidate arrival times according to a clustering discrimination threshold, where each cluster contains at least one candidate arrival time; Determining the arrival time of the actual received signal according to the cluster with the smallest value of the candidate arrival time.

9. The method for determining the arrival time according to claim 5, wherein Determining the arrival time of the actual received signal according to each of the candidate arrival times includes: Establishing clusters of each of the candidate arrival times according to a clustering discrimination threshold, where each cluster contains at least one candidate arrival time; Calculating the mean value of the candidate arrival times corresponding to each of the clusters, and taking the smallest mean value as the arrival time of the actual received signal.

10. The method for determining the arrival time according to claim 8, wherein When the difference between any two candidate arrival times among x candidate arrival times is less than or equal to the clustering discrimination threshold, the x candidate arrival times belong to one cluster, where x is an integer greater than or equal to 2.

11. The method for determining the arrival time according to claim 2, wherein The autocorrelation waveform of the normalized positioning signal is the autocorrelation waveform normalized according to the modulus value; The maximum value of the maximum modulus value of the theoretical autocorrelation waveforms of the n positioning signals is 1, and the minimum value is 1 / n; m and n are respectively negatively correlated with the arrival time correction accuracy.

12. The method for determining the arrival time according to claim 1, characterized in that The correlation waveform of the actual received signal is the correlation waveform normalized according to the modulus value.

13. An arrival time determination device, characterized in that, Including: A correction information generation module, configured to generate arrival time correction information according to the leading edge information of the theoretical autocorrelation waveforms of the positioning signals with different fading values; A leading edge slope calculation module, configured to calculate the leading edge slope corresponding to the leading edge reference point of the correlation waveform of the actual received signal; An arrival time determination module, configured to determine target correction information from the arrival time correction information according to the leading edge slope, and determine the arrival time of the actual received signal based on the target correction information.

14. A signal receiving device, characterized in that, Including: One or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the arrival time as described in any one of claims 1-12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for determining the arrival time as described in any one of claims 1-12.

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