A method for solving topology sequence time difference considering communication delay

Abstract

The application relates to a topology sequence time difference solving method considering communication delay, comprising the following steps: acquiring a topology sequence of an aerial unmanned system and a topology sequence of a ground unmanned system; performing reverse processing on the topology sequence of the aerial unmanned system or the topology sequence of the ground unmanned system to acquire a similarity sequence of corresponding nodes; and calculating a topology sequence delay time based on the similarity sequence. The application aims at the problem that communication delay causes the signals collected by two systems to be out of synchronization, and proposes a method of matching two time sequences in reverse order under the condition that the time scales are the same, solving the time difference between the two out-of-synchronization time sequences, so that the time alignment of the out-of-synchronization time sequences is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal fusion processing considering communication delay, and particularly relates to a method for solving topological sequence time difference considering communication delay. BACKGROUND

[0002] Dynamic time warping (DTW) is a method for matching two time misaligned similarity sequences and calculating similarity, which can be used for time alignment of two time sequences. Dynamic time warping is often used in the field of speech recognition, and the main principle is as follows:

[0003] As shown in Figure 1 , dynamic time warping locally scales time sequences to achieve better matching effect. Two solid lines represent two time sequences, and the dashed line between the two time sequences represents the matching of the two sequences generated by the dynamic time warping algorithm. DTW defines the dashed line as the similarity of the matching of two data points, and the similarity of the two time sequences is obtained by calculating the sum of all dashed lines. When all data of the two time sequences have the same time delay, the horizontal coordinates of the two end points of the dashed line can be used to calculate the time delay of the data, and the mean value of the difference between the horizontal coordinates of the two end points of all dashed lines is usually taken as the time difference of the two time sequences. Let two time sequences to be calculated similarity be Q={q1,q2,...,q m} and C={q1,q2,...,q n}, the lengths of the two time sequences are m and n respectively. An m×n cost matrix D m×n is used to store the "distance" of each data point of the two time sequences, and a warping path is planned in the cost matrix D m×n . The path will pass through the entire matrix, and the kth element on the path is denoted as w k =(i,j) k , the horizontal and vertical coordinates of w k represent the index of the aligned data sequence. The warping path must start from w1=(1,1) and end at w k =(m,n) k , so that each coordinate in Q and C appears in the warping path. In addition, i and j in w(i,j) must be monotonically increasing, that is,

[0004] w k =(i,j),w k+1 =(i',j'),i≤i'≤i+1,j≤j'≤j+1

[0005] The method for obtaining the warping path according to the cost matrix D m×n is as follows:

[0006] D(i, j) = Dist(i, j) + min[D(i-1, j), D(i, j-1), D(i-1, j-1)]

[0007] Dynamic time warping can be used to solve the similarity and delay time difference of two time series, but this method also has a big defect, when the length of time series is long, the time complexity of cost matrix D m×n is Q(n 2 ), which needs to consume a lot of computing resources. SUMMARY

[0008] The purpose of the present application is to provide a topology sequence time difference solving method considering communication delay, aiming at the problem that the signals collected by two systems are not synchronized in time due to communication delay, the present application proposes a method of matching two time series in reverse order under the condition of the same time scale, to solve the time difference of two unsynchronized time series, so as to realize the time alignment of unsynchronized time series.

[0009] To achieve the above purpose, the present application provides the following scheme:

[0010] A topology sequence time difference solving method considering communication delay, comprising:

[0011] Obtaining a topology sequence of an aerial unmanned system and a topology sequence of a ground unmanned system;

[0012] Processing the topology sequence of the aerial unmanned system or the topology sequence of the ground unmanned system in reverse order to obtain a similarity sequence;

[0013] Based on the similarity sequence, calculating the topology sequence delay time.

[0014] Optionally, obtaining the similarity sequence comprises:

[0015] Judging the frequency of the topology sequence of the aerial unmanned system and the topology sequence of the ground unmanned system, judging whether the data update frequencies of the topology sequence of the aerial unmanned system and the topology sequence of the ground unmanned system are the same, if the same, extracting the topology sequence of the aerial unmanned system and the topology sequence of the ground unmanned system within a preset initial value based on a sliding time window, obtaining a first topology sub-sequence and a second topology sub-sequence, processing the first topology sub-sequence or the second topology sub-sequence in reverse, calculating the corresponding topology structure similarity, and obtaining the similarity sequence; if not the same, performing nearest matching on the topology sequence of the aerial unmanned system and the topology sequence of the ground unmanned system, calculating the correlation similarity, and obtaining the similarity sequence.

[0016] Optionally, the topological sequences of the aerial unmanned system and the ground unmanned system are locally matched, and the calculation of the correlation similarity comprises:

[0017] The topological sequences of the aerial unmanned system and the ground unmanned system are high-low frequency judged, the topological sequence with high update frequency is a high-frequency topological sequence, the topological sequence with low update frequency is a low-frequency topological sequence, the low-frequency topological sequence or the high-frequency topological sequence is processed in reverse order, the low-frequency topological sequence is divided, the midpoint between data points of every two low-frequency topological sequences is taken, when the data point of the high-frequency topological sequence falls on both sides of the data point of any low-frequency topological sequence, the topology structure of the data point of the low-frequency topological sequence is matched, and the correlation similarity of the data point of the low-frequency topological sequence and the data point of the high-frequency topological sequence is obtained.

[0018] Optionally, the method for obtaining the similarity sequence comprises:

[0019] L i (j)=f(A i (j),B i (t-j))

[0020] Wherein, L i (j) is a similarity calculation function, A i (j) is the jth topology structure of the topological sequence A i , B i (t-j) is the last jth topology structure of the topological sequence B i , i is the time of the extracted topological sequence, and j is the index of the node in the topological sequence.

[0021] Optionally, the calculation of the similarity sequence comprises:

[0022] The same time topology of the first topological subsequence and the second topological subsequence, i.e. the first topology and the second topology, is obtained, the similarity of the first topology and the second topology is calculated, when the end value of the preset initial value is reached, the calculation is stopped and the similarity of the first topological subsequence and the similarity of the second topological subsequence are obtained, and the topological sequence delay time is obtained based on the similarity of the first topological subsequence and the similarity of the second topological subsequence.

[0023] Optionally, the topological sequence delay time is obtained based on the similarity of the first topological subsequence and the similarity of the second topological subsequence, which comprises:

[0024] The similarity of the first topological subsequence and the similarity of the second topological subsequence are judged, the judged similarity of the first topological subsequence and the judged similarity of the second topological subsequence are calculated, a corresponding mean sequence is obtained, the position of the maximum similarity value is obtained based on the mean sequence, and the position of the maximum similarity value is calculated to obtain the topological sequence delay time.

[0025] Optionally, the method for calculating the judged similarity of the first topological subsequence and the judged similarity of the second topological subsequence is as follows:

[0026]

[0027] wherein L(j) is the mean value of the similarity of the jth node in all obtained topological similarities, k is the total number of the first topological sequence extracted, L i (j) is the jth value of the ith topological similarity sequence, i is the number of the topological similarity sequence, and j is the index of each similarity in the topological similarity sequence.

[0028] Optionally, the method for obtaining the topological sequence delay time is as follows:

[0029]

[0030] wherein Δt is the time difference between the first time sequence and the second sequence, t is the total length of the similarity sequence, and l idx is the position index of the maximum value of the similarity sequence.

[0031] The present application has the following beneficial effects:

[0032] The present application provides a topological sequence time difference solving method considering communication delay, wherein each node in the topological sequence only participates in calculation once through a reverse matching idea, and the calculation complexity of two time sequences with a length of n is Q(n) through the reverse matching idea, which has higher execution efficiency compared to the dynamic time planning time complexity Q(n 2 ). BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0034] Figure 1 The present application is a matching method for two time sequences in the background art;

[0035] Figure 2 Time alignment process flow of two topological sequences published at different times for embodiments of the present application;

[0036] Figure 3 UAV and UGV same frequency data sequence matching schematic diagram for embodiments of the present application;

[0037] Figure 4 Principle and premise that reverse sequence matching has a unique solution for embodiments of the present application;

[0038] Figure 5 Process flow of solving delay time in reverse sequence matching for embodiments of the present application;

[0039] Figure 6 UAV and UGV difference frequency data sequence matching schematic diagram for embodiments of the present application;

[0040] Figure 7 Relationship between number of similarity superimposed curves and superimposed effect of same frequency time sequence for embodiments of the present application; (a) is 10, 25, 50 times similarity superimposed effect of 12.5% interference target, (b) is 10, 25, 50 times similarity superimposed effect of 20% interference target, (c) is 10, 25, 50 times similarity superimposed effect of 25% interference target;

[0041] Figure 8 Topological sequence delay time solving error curve for embodiments of the present application;

[0042] Figure 9 Topological sequence under T UAV = 1s, T UGV = 5 / 3s, 7 / 3s for embodiments of the present application;

[0043] Figure 10 Difference frequency topological sequence delay time solving error curve for embodiments of the present application. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application.

[0045] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0046] The present application takes the multi-target association of the air-ground unmanned system as an example, and takes the topological structure sequence constructed by the air-ground unmanned system as a time sequence signal to illustrate the technical solution of the present application. The multi-target association algorithm design process based on the topological sequence under the communication delay condition is as shown in Figure 2 . First, consider two time sequences with the same update frequency, reverse one of the two time sequences, and then perform reverse matching on the two processed sequences, and then calculate the topological structure similarity of each matching. Then consider two time sequences with different update frequencies.

[0047] Same frequency topological sequence time difference solving method

[0048] Suppose the data update frequency of the UAV and the UGV is consistent, and the same frequency time sequence is as shown in Figure 3 In a certain time period, there are two data sequences from the air-ground, and the delay time of the two data sequences is unknown. Invert one of the sequences, and sequentially solve the topological similarity with the other sequence in normal order. Then there is only one association in the data sequence that is associated at the same time (indicated by the red arrow). The similarity value at this place is theoretically the maximum among all similarity values.

[0049] (1) Reverse matching principle

[0050] Reverse matching is the core idea of solving the delay time difference under the condition of communication delay. Before describing this idea, it is first necessary to clarify that the air-ground unmanned system has the same time scale, that is, any time t Ref reflected on the UAV system has a time length t UAV and the time length t UGV of the UGV system satisfies t UAV =t UGV . Assuming that the time scales of the UAV and the UGV are the same, only the difference Δt between the initial value of the system time of the UAV and the initial value of the system time of the UGV needs to be solved to complete the time alignment of the two systems.

[0051] The multi-target azimuth topological sequence of the UAV at the kth time t1~t Ref calculated from a reference time t k can be expressed as The topological sequence from the perspective of the UGV can be expressed as Simplified as equation (4.1).

[0052]

[0053]

[0054] Let the a t1~t a of the UAV bek The sequence of k topologies at time t is a Z1, a Z2,…, a Z k-1 , a Z k} and the sequence of k topologies at time t is g t1, g t k . g Z1, g Z2,…, g Z k-1 , g Z k}. Since the time difference of communication delay Δt of the air-ground unmanned system cannot be infinite, and the length of the time period t k -t1 can be arbitrarily selected, only the case of Δt < t k -t1 is considered, which makes the reverse matching method have a solution of Δt in theory.

[0055] The following is the specific principle of reverse matching and the explanation of the solution of Δt under the assumption of Δt < t k -t1. First of all, it is clear that Δt = t g -t1. Assuming i t a - i t Then g t1、 g t k 、 a t1、 a t k satisfy equation (4.2) and equation (4.3).

[0056] g t1< a t k & a t1< g t k (4.2)

[0057] g t1< g t k & a t1< a t k (4.3)

[0058] Therefore, max( g t1, a t1) < min( a t k , g t kIf ) holds, then equation (4.4) holds, and Figure 4 The intersection of l1 and l2 shown is the solution that satisfies equation (4.4).

[0059]

[0060] st g t i = a t j (4.4)

[0061] like Figure 4 As shown, { a Z1, a Z2,…, a Z k-1 , a Z k}and{ g Z1, g Z2,…, g Z k-1 , g Z k Place it on two number axes, with the horizontal axis representing the time system of UAV and the vertical axis representing the time system of UGV. Then, respectively... g t1 and a t k , g t2 and a t k-1 , ..., g t k-1 and a t2, g t k and a time t1 ( g Z1, a Z k ), ( g Z2, a Z k-1 ), ……, ( g Z k-1 , a Z2), ( g Z k , a Matching is performed using Z1). According to equations (4.2) and (4.3), it can be seen that... a t1 < g t k We can obtain that k3 > 1 for l3, from g t1 < a t k We can deduce that k4 < 1 for l4. Therefore, there must be an intersection point between l1 and l2. a t j , g ti ), and this intersection point is located between the intersection points of l2 and l3, l4. a t j , g t i It satisfies equation (4.4), that is, at this time... a Z j and g Z i It is the only pair of ground multi-object topologies constructed at the same time, therefore a Z j and g Z i It has the highest similarity.

[0062] (2) Topological similarity calculation

[0063] Reverse matching requires Figure 4 shown g t1 and a t k , g t2 and a t k-1 , ..., g t k-1 and a t2, g t k and a time t1 ( g Z1, a Z k ), ( g Z2, a Z k-1 ), ……, ( g Z k-1 , a Z2), ( g Z k , a Match Z1). Calculate ( a t j , g t i ) corresponding a Z j and g Z i The method for similarity is determined based on the actual topological structure, and the specific calculation formula is not the subject of this invention.

[0064] (3) Obtain the delay time

[0065] Algorithm 1 is a delay time calculation algorithm based on reverse matching topological sequence. The algorithm uses the reverse matching idea to calculate the delay time of the air-to-ground unmanned system as follows: Figure 5As shown, the whole process is divided into 6 steps. Topological sequence delay time solving algorithm based on reverse matching

[0066] Input: UAV topological sequence A and UAV topological sequence B;

[0067] Output: Delay time Δt of topological sequence A relative to topological sequence B;

[0068] Extract topological subsequences {A1, A2, …, A k} and {B1, B2, …, B k} of length t using sliding time window;

[0069] Calculate similarity sequence L i of all subsequences A i and B i :

[0070] Calculate L i according to reverse matching idea;

[0071] L i (j) = f(A i (j), B i (t-j));

[0072] Wherein, L i (j) is similarity calculation function, A i (j) is the jth topological structure of topological sequence A i , B i (t-j) is the jth topological structure from the end of topological sequence B i , i is the time of extracted topological sequence, and j is the index of node in topological sequence.

[0073] Obtain similarity sequence L i of A i and B i ;

[0074] Obtain similarity sequence {L1, L2, …, L k} of all subsequences {A1, A2, …, A k} and {B1, B2, …, B k};

[0075]

[0076] Wherein, L(j) is the average similarity of the jth node in all obtained topological similarities, k is the total number of extracted first topological sequences, L i (j) is the jth value of the ith topological similarity sequence, i is the number of topological similarity sequence, and j is the index of each similarity in topological similarity sequence.

[0077] l max = max(L)

[0078] Obtain l max Index position l in L idx ;

[0079]

[0080] Where, Δt is the time difference between the first time sequence and the second sequence, t is the total length of the similarity sequence, l idx is the position index of the maximum value of the similarity in the similarity sequence;

[0081] First step: Obtain the sequence of the topology structure. At the kth moment, construct the topology sequence according to the topology structure method According to formula (4.1), the sequence composed of k topological structures at k moments within the time range of t1~t k Can be expressed as{ s Z1, s Z2,..., s Z k-1 , s Z k}.

[0082] Second step: Reverse matching. For the sequence of k topological structures at k moments within the time range of t1~t k { a Z1, a Z2,…, a Z k-1 , a Z k} and{ g Z1, g Z2,..., g Z k-1 , g Z k}, Select one of the sequences and reverse it to{ g Z k , g Z k-1 ,..., g Z2, g Z1}.

[0083] Third step: Calculate the topology similarity.{ a Z1, a Z2,..., a Z k-1 , a Z k} and{ g Z k ,g Z k-1 ,…, g Z2, g Z1} is a topological structure sequence, taking the topological structure at the second moment as an example, that is, the topological structure of the UAV perspective a Z2and the topological structure of the UGV perspective g Z k-1 . Record a Z2and g Z k-1 The similarity of L ＜2,k-1＞ .

[0084] Step 4: Calculate the similarity of the topological structure. For the a Z2and g Z k-1 Type, use a specific formula to obtain the similarity of the two topological structures

[0085] Step 5: Obtain the sequence of topological structure similarity. For the sequence of topological structures { a Z1, a Z2,..., a Z k-1 , a Z k} and { g Z1, g Z2,..., g Z k-1 , g Z k}, perform steps 3 and 4 on each pair of elements to obtain the corresponding L ＜1,k＞ , L ＜2,k-1＞ , …, L ＜k-1,2＞ , L ＜k,1＞ , which constitutes the topological sequence similarity sequence {L ＜1,k＞ , L ＜2,k-1＞ , …, L ＜k-1,2＞ , L ＜k,1＞}.

[0086] Step 6: Curve superposition solution. {L ＜1,k＞ , L ＜2,k-1＞ , …, L ＜k-1,2＞ , L ＜k,1＞} is the similarity sequence obtained within the t1~t k time range. By obtaining multiple t1~t k time sequence samples, multiple similarity sequence curves are obtained, and the mean value of these curves at the same position is calculated. Assuming that the highest point of the mean curve is L ＜i,j＞ , the position of L ＜i,j＞ on the mean curve corresponds to a t i andg t j solutions for obtaining delay time.

[0087] 2, difference frequency topology sequence association algorithm

[0088] Due to the different configurations of sensors and computers of air-ground unmanned systems, the data processing and update frequency may also differ, according to the reverse order matching principle, the reverse order matching can guarantee that the method has a unique solution when the number of two sequences is the same, in the case of different data update frequencies of air-ground unmanned systems, it is impossible to guarantee one-to-one matching of two sequences. Figure 6 As shown in the figure, the UAV updates 5 data sequences in the time, and the UGV updates 8 time sequences. This part mainly designs a solution for the communication delay of different frequencies.

[0089] The nearest matching method is used for the problem of different data update frequencies, as shown in the figure, low frequency and high frequency are the results of comparison of two topology sequences, among the two topology sequences, the one with high update frequency is called high frequency topology sequence, and the one with low update frequency is called low frequency topology sequence, and the time sequence with high data frequency is taken as the reference, and the time sequence with low data frequency is matched. The low frequency time sequence is divided, and the midpoint between every two data points is taken, when the high frequency data falls on both sides of a low frequency data point, the topology structure of the data point is matched. As shown in the figure, after the UAV sequence is processed in reverse order, the 2nd data and the 3rd data of the UGV time sequence correspond to the 4th data of the UAV time sequence, so the 2nd data and the 3rd data of the UGV time sequence are matched with the 4th data of the UAV time sequence, and the association similarity thereof is calculated (the similarity calculated here is the similarity of the 2nd data and the 4th data, which is the similarity of two nodes). Figure 7 Figure 6 After the above processing, the same frequency time sequence reverse order matching algorithm is used to solve the time difference of the different frequency time sequences (two topology sequences with the same frequency have the same data quantity in the same time, so there is a one-to-one correspondence between the data; two time sequences with different frequencies have different data quantities in the same time, and the data cannot be one-to-one corresponding; the nearest principle is actually to find the one-to-one correspondence of the latter, and then it can be solved like the same frequency time sequence).

[0090] The present application proposes a reverse order matching idea, which makes the calculation complexity of two time sequences with a length of n to be Q(n) through the reverse order matching mode, and has high execution efficiency.

[0091] The present application proposes a reverse order matching idea, which makes the calculation complexity of two time sequences with a length of n to be Q(n) through the reverse order matching mode, and has high execution efficiency. Figure 7 The similarity mean curve of the reverse order matching results of different frequency time sequences is shown in the figure, the peak value in the curve is unique and distinct, and can be used to solve the time difference of two time sequences with delay, wherein,​Figure 7 (a) 10, 25, 50 times similarity curve superposition effect when 12.5% interference target, Figure 7 (b) 10, 25, 50 times similarity curve superposition effect when 20% interference target, Figure 7 (c) 10, 25, 50 times similarity curve superposition effect when 25% interference target. Figure 8 The solving error of the delay time difference of two same-frequency time series within the range of ±50s is shown, wherein 1s is the minimum time unit for solving, and the curve result shows that the solving error is basically maintained within ±3s and is not affected by the true value of the delay time. Figure 9 The similarity mean curve of the superposition of the reverse matching results of different times of difference-frequency time series in the presence of different proportion interference targets is shown, the peak in the curve is unique and distinct, and can be used to solve the time difference of two time series with delay. Figure 10 The solving error of the delay time difference of two difference-frequency time series within the range of ±50s is shown, wherein 1s is the minimum time unit for solving, and the curve result shows that the solving error is basically maintained within ±2s and is not affected by the true value of the delay time.

[0092] The above-described embodiments are only descriptions of the preferred modes of the present application and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those skilled in the art shall fall within the protection scope determined by the claims of the present application.

Claims

1. A method for solving topology sequential time difference considering communication delay, characterized in that, The method comprises the following steps: obtaining a topological sequence of an aerial unmanned system and a topological sequence of a ground unmanned system, the topological sequence of the aerial unmanned system being a multi-target azimuth topological sequence in the perspective of the aerial unmanned system, and the topological sequence of the ground unmanned system being a multi-target azimuth topological sequence in the perspective of the ground unmanned system; performing reverse processing on the topological sequence of the aerial unmanned system or the topological sequence of the ground unmanned system to obtain a similarity sequence; the step of obtaining the similarity sequence comprises: performing frequency judgment on the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system to determine whether the data update frequencies of the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system are the same, if the data update frequencies are the same, extracting the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system within a preset initial value based on a sliding time window to obtain a first topological sub-sequence and a second topological sub-sequence, performing inversion processing on the first topological sub-sequence or the second topological sub-sequence, calculating the corresponding topological structure similarity to obtain the similarity sequence, if the data update frequencies are not the same, performing nearest matching on the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system to calculate the correlation similarity and obtain the similarity sequence; calculating a topological sequence delay time based on the similarity sequence; wherein, is a time difference by which the first time series precedes the second series, is a total length of the similarity series, is a position index of the maximum value of the similarity in the similarity series.

2. The method of claim 1, wherein the method further comprises: the step of performing nearest matching on the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system to calculate the correlation similarity comprises: performing high-low frequency judgment on the topological sequence of the aerial unmanned system and the topological sequence of the ground unmanned system, the topological sequence with a high update frequency being a high-frequency topological sequence, and the topological sequence with a low update frequency being a low-frequency topological sequence, performing reverse processing on the low-frequency topological sequence or the high-frequency topological sequence, dividing the low-frequency topological sequence, taking the midpoint between data points of every two low-frequency topological sequences, when a data point of the high-frequency topological sequence falls on either side of a data point of the low-frequency topological sequence, matching the topological structure of the data point of the low-frequency topological sequence, and obtaining the correlation similarity of the data point of the low-frequency topological sequence and the data point of the high-frequency topological sequence respectively.

3. The method of claim 1, wherein the method further comprises: the method for obtaining the similarity sequence comprises: wherein, is a similarity calculation function, is a topology sequence is the jth topology structure of the topology sequence is a topology sequence is the jth topology structure of the topology sequence is the time of the extracted topology sequence, is the index of the node in the topology sequence.

4. The method of claim 1, wherein the method further comprises: the step of calculating the similarity sequence comprises: obtaining the same time topologies of the first topological sub-sequence and the second topological sub-sequence, i.e., a first topology and a second topology, calculating the similarity of the first topology and the second topology, stopping the calculation and obtaining the similarity of the first topological sub-sequence and the similarity of the second topological sub-sequence when the end value of the preset initial value is reached, and obtaining the topological sequence delay time based on the similarity of the first topological sub-sequence and the similarity of the second topological sub-sequence.

5. The method of claim 4, wherein the method further comprises: the step of obtaining the topological sequence delay time based on the similarity of the first topological sub-sequence and the similarity of the second topological sub-sequence comprises: The similarity of the first topological subsequence and the similarity of the second topological subsequence are judged, the judged similarity of the first topological subsequence and the judged similarity of the second topological subsequence are calculated, a mean sequence corresponding to the calculation is obtained, a position of a maximum value of the similarity based on the mean sequence is obtained, and the position of the maximum value of the similarity is calculated to obtain a topological sequence delay time.

6. The method of claim 5, wherein the method further comprises: The method for calculating the judged similarity of the first topological subsequence and the judged similarity of the second topological subsequence is: wherein, is the average of the similarity of the jth node among all the topology similarities obtained, is the total number of the first topology sequence extracted, is the jth value of the ith topology similarity sequence, is the number of the topology similarity sequence, is the index of each similarity in the topology similarity sequence.

Images