CN105898696A - Interval confidence evaluation-based roadside node positioning method - Google Patents

Abstract

The present invention proposes a method for locating nodes along the road based on interval credibility evaluation, including steps: the nodes along the road initialize parameters and variables, and divide the adjacent roads into N intervals according to their own communication radius R and road conditions, and An energy attenuation list P is established for each interval; nodes along the road perform interval energy attenuation statistics according to the received vehicle information and signals; statistics are made on the energy attenuation list of each interval to obtain the credible value of the interval; select credible The interval is used for positioning; readjust according to the credible value of the interval. The invention divides the communication area, counts and analyzes a large number of vehicle position information and received signals, selects the vehicle coordinate interval with high reliability and the signal propagation attenuation in the interval for positioning calculation, and estimates the position coordinates of the nodes. The application development of vehicle ad hoc network positioning and security is of great significance.

Description

Node Location Method Along Road Based on Interval Credibility Evaluation

technical field

The invention belongs to the technical field of vehicle ad hoc networks, and in particular relates to a method for locating nodes along a road in a vehicle ad hoc network in a complex mobile environment.

Background technique

As a specific application of mobile ad hoc network in intelligent transportation system, vehicle ad hoc network is a special form of ad hoc network with the characteristics of open structure and flexibility. Its huge application potential has been valued by academia and industry. The location-based service is an important application basis in the vehicular ad hoc network.

Nodes along the road generally lack positioning devices due to cost issues. After this type of node is installed, it cannot obtain its own location information, and must analyze and calculate the current location based on the information released by other devices. The nodes of VANET are generally equipped with precise positioning systems, such as GPS, etc., which can support various location-based application services, such as assisted driving, traffic information release, inter-vehicle communication and access services, so vehicles can Broadcast its own location information to the nodes along the road, and cooperate with the positioning of nodes along the road.

When the nodes along the road have obtained enough position information released by the vehicle, the position estimation can be performed according to the vehicle coordinates and the received signal strength. However, there are many complicated factors in the VAN, which make the precise positioning of nodes along the road very difficult: first, the communication environment is very complex, there are various reflections, multipaths, fading and Doppler effects, these channels Factors will cause various changes in the signal reception strength, which affects the ranging accuracy in most positioning methods; secondly, obstacles along the road will affect the road nodes to receive information released by vehicles, making the received position information limited. It cannot meet the requirements of the positioning method for the number of beacons; finally, the self-organizing network of vehicles is similar to the existing network, and there are various attacks such as witches, wormholes, and replays. The existence of attacks will cause nodes along the road to receive wrong locations information, causing the position estimate to deviate significantly from the actual value.

The combination of various factors makes the location of nodes along the road very complicated. Although there are a lot of research on positioning methods in wireless sensor networks, due to the channel changes in the mobile environment, the existing ranging positioning methods become difficult to apply, and the non-ranging methods require complex routing and fixed beacon nodes, which are relatively difficult. The use of vehicle location information to complete positioning is less discussed. In addition, the current research pays less attention to the time-varying location information of a large number of different vehicles in the VAM, and these complex data can be better used for node positioning.

Contents of the invention

In order to solve the technical problem of inaccurate vehicle positioning in the mobile environment in the prior art, the present invention proposes a node positioning method along the road based on interval credibility evaluation, which is used in the self-organizing network of vehicles to assist nodes along the road in positioning. By dividing the communication area, Perform statistics and analysis on a large number of vehicle position information and received signals, select vehicle coordinate intervals with high reliability and interval signal propagation attenuation for positioning calculation, estimate the position coordinates of nodes, and position the vehicle self-organizing network in complex environments And security and other aspects of application development have great significance.

The present invention adopts the following technical solution to realize: the node location method along the road based on interval credibility evaluation, which is applied to the vehicle self-organizing network, including the following steps:

Step 1: The nodes along the road initialize the parameters and variables, divide the adjacent road into N intervals according to their own communication radius R and road conditions, and establish an energy attenuation list P for each interval. The energy attenuation list P includes Energy attenuation level and recording times;

Step 2: Nodes along the road perform interval energy attenuation statistics according to the received vehicle information and signals;

Step 3: Make statistics on the energy attenuation list of each interval to obtain the credible value of the interval;

Step 4: Select the credible interval for positioning;

Step 5: Readjust according to the credible value of the interval.

Preferably, the interval energy decay statistics described in step 2 are as follows:

The node obtains the coordinates of the information released by the vehicle according to the information released by the vehicle on the road, and determines the interval according to the coordinate information;

The node subtracts the transmission power in the vehicle's published information from the power actually received by the information, calculates the energy attenuation value, queries the energy attenuation list P according to the energy attenuation value to obtain the energy attenuation level, and uses the attenuation level in the energy attenuation list of the interval The number of records plus 1;

It is judged whether the accumulated value of the recording times of the attenuation level reaches the accumulated maximum value, if yes, then execute step 3, otherwise, continue to receive the information issued by the vehicle.

Preferably, the step 3 counts the energy attenuation list of each section as follows: according to the recording times of each level in the energy attenuation list, the total number of vehicle transmission information in each section is obtained, and the attenuation energy level with the largest number of records is obtained, Divide the maximum number of recorded times of attenuation energy level in each interval by the total number of recorded times, and the value is taken as the credible value of the interval.

Preferably, said step 4 selects a credible interval for positioning, including the following steps:

Step 41: Select the interval n _max with the largest credible value among all intervals;

Step 42: The positioning algorithm needs to use B position coordinates for positioning, divide N intervals into B areas, divide N by B, and obtain the quotient J and the remainder K, the first area b ₁ contains the maximum credible value interval, execute step 43, so that the first area contains a total of J+K intervals;

Step 43: Divide the first area: if the maximum credible value interval is L intervals away from the first or last interval, when L≤(J+K-1)/2, n _max is close to the first or last The L intervals of one interval and the J+K-1-L intervals on the other side are used as the first area b ₁ ; otherwise, when J+K-1 is an even number, the adjacent two sides of n _max are taken (J +K-1)/2 intervals, as the first area b ₁ ; when J+K-1 is an odd number, you can take (J+K)/2 intervals on either side, and take (J+K- 2)/2 intervals, as the first area b ₁ , execute step 44 after completion;

Step 44: Divide the remaining B-1 areas: divide the remaining N-(J+K) intervals into B-1 areas according to the method of equal division, and each area contains J intervals;

Step 45: Select the interval with the largest credible value from each area, select the median value of this interval as the credible coordinate, and select the attenuation level with the most records from the energy attenuation list of the largest interval in each interval, and query the energy Obtain the energy attenuation range from the attenuation list, take the median value as the energy attenuation value from the coordinate to the node, and calculate the credible distance from the coordinate to the node according to the wireless signal propagation model in space;

Step 46: According to the positioning method, use the credible coordinates and credible distances of multiple intervals to estimate the node position coordinates.

Preferably, said step 5 readjusts according to the credible value of the interval, and the steps are as follows:

Step 51: Determine whether the size of the interval with the largest credible value in the area is smaller than the precision requirement, if it is satisfied, then the interval where the area is located will not be adjusted, otherwise, go to step 52;

Step 52: Split the interval with the largest credible value in the region into two equal intervals;

Step 53: Merge the interval with the smallest credible value in the region with the interval with the smallest credible value in the adjacent same region;

Step 54: Renumber the intervals after splitting and merging in sequence;

Step 55: Clear the number of records in the energy attenuation list of the new section to zero. If all areas have been traversed, perform step 2; otherwise, perform step 51 to adjust the next area.

Compared with prior art, the present invention has following advantage:

1. The present invention uses the method of counting the information transmitted by multiple vehicles to carry out credible analysis on each section of the road, which overcomes the shortcomings of being easily disturbed by the environment and malicious damage by only using the information of one vehicle for positioning, and improves the positioning accuracy. robustness.

2. The method of the present invention also records the information sent by malicious vehicles in the vehicle ad hoc network, but when the number of malicious vehicles is less than that of normal vehicles, it has little influence on the credible value obtained by statistics; therefore, the method of the present invention can be compared Good defense against attacks by malicious vehicles.

3. The size of the interval in the method of the present invention can be adjusted, so that the actual coordinates of the nodes can be better approached within a certain error tolerance range, and the accuracy requirements of the node position estimation can be satisfied.

4. The method of the present invention can combine intervals with less statistical times, so that the information of non-shielding intervals can be better used for positioning, and the influence of obstacles on positioning can be avoided.

Description of drawings

In order to illustrate the technical solution of the present invention more clearly, the accompanying drawings used in the description of the embodiments will be briefly introduced below; obviously, the accompanying drawings in the following description are some embodiments of the present invention, which are common to those skilled in the art As far as the skilled person is concerned, other drawings can also be obtained based on these drawings on the premise of not paying creative work.

Fig. 1 is the flow chart of the present invention based on the node location method along the road of interval credible assessment;

Fig. 2 is a schematic diagram and an energy attenuation list of nodes dividing roads within the communication range;

Fig. 3 is the flow chart of selecting a plurality of interval methods with maximum credible value;

Fig. 4 is a flow chart of the interval adjustment method.

detailed description

In order to describe the present invention more clearly, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific examples and accompanying drawings, but the embodiments of the present invention are not limited thereto. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

Example

Referring to Fig. 1, the present invention is based on the location method of nodes along the road based on interval credibility evaluation, which is applied to the location of nodes along the road in the vehicle ad hoc network in a complex mobile environment, and specifically includes the following steps:

Step 1: The nodes along the road initialize the parameters and variables, divide the adjacent road into N intervals according to their own communication radius R and road conditions, and establish an energy attenuation list P for each interval.

As shown in Figure 2, the node A divides the area of the road L within the communication radius R into N intervals, n ₁ , n ₂ ,..., n _N , and in this embodiment, the method of equally dividing the distance of the road L is used. interval.

The energy attenuation list P described in step 1 includes the following contents: energy attenuation level and recording times. In this embodiment, the received signal energy attenuation value p is divided as shown in Table 1:

Table 1 Classification of energy attenuation

Attenuation value (db) 0 0>p≥-5 -5>p≥-10 -10>p≥-15 Attenuation level 1 2 3 4 Attenuation value (db) -15＞p≥-20 -20＞p≥-25 -25＞p≥-30 -30>p Attenuation level 5 6 7 8 Attenuation value (db) -35>p≥-40 -40>p≥-45 -45＞p≥-50 -50>p≥-55 Attenuation level 9 10 11 12 Attenuation value (db) -55>p≥-60 -60＞p≥-65 -65>p≥-70 -70＞p Attenuation level 13 14 15 16

Each road section establishes its own energy attenuation list according to the above table. As shown in this embodiment, an energy attenuation list P ₁ , P ₂ , ..., P ₁₆ is established for n ₁ , n ₂ , ..., n ₁₆ intervals, All records are initialized to 0.

Step 2: Nodes along the road perform interval energy attenuation statistics according to the received vehicle release information and signals.

According to the information released by the vehicle on the road, the node can obtain the coordinates of the information released by the vehicle, and determine the interval according to the coordinate information, such as determining the _n6 interval of the road according to the coordinates of the vehicle.

The node then subtracts the transmission power P _Send in the information released by the vehicle from the power P _Rec that actually received the information, and calculates the energy attenuation value p=P _Send -P _Rec , and looks up Table 1 according to the value of p to obtain the attenuation level. Add 1 to the record count of the attenuation level in the energy attenuation list P _i of the interval.

It is judged whether the accumulated value of the recording times of the attenuation level reaches the accumulated maximum value, for example, 100, and if the accumulated value reaches the maximum value, then perform step 3, otherwise, continue to receive the location information.

Step 3: Make statistics on the energy attenuation list of each interval, obtain the total number of vehicle transmission information in each interval according to the recording times of each level in the energy attenuation list, and the attenuation energy level with the most recorded times, and calculate the Divide the maximum number of recorded times of attenuation energy level by the total number of recorded times, and the value is taken as the credible value of the interval. As shown in table 2:

Table 2 The power attenuation list of each interval and the interval credible value

In Table ₂ , when the number of recordings of the _12th energy attenuation level in interval _{n 2} reaches the maximum number of recordings, such as 100, then execute step 3 to count the largest The attenuation level of the number of records and the total number of records, and finally obtain the credible value.

Step 4: According to the number of beacons required by different positioning methods, select multiple credible intervals that meet the quantity requirements, take the median value of the interval coordinates, convert the energy attenuation value with the largest number of records into the propagation distance, and nodes along the road according to the coordinates and distance to calculate its own position coordinates.

Refer to Figure 3 for the method of selecting multiple intervals with the largest credible values, including the following steps:

Step 41: Select the interval n _max with the largest credible value among all intervals. As shown in the above table, the credible value of n ₂ reaches 0.59, which is the interval with the highest credible degree among all intervals.

Step 42: The positioning algorithm needs to use B position coordinates for positioning. The node divides the road into N intervals. Divide N by B to obtain a quotient of J and a remainder of K. Divide the N intervals into B areas, the first area b1 contains the maximum credible value interval, and perform step 43, so that the first area contains a total of J+K intervals.

The specific examples are shown in Table 2. For example, if the method of three-point positioning is adopted, then B=3 position coordinates are required, and these position coordinates will be selected from 3 areas. Divide the number of node-to-road intervals N=16 by the number of beacons required by the algorithm B=3, and the quotient J is 5, and the remainder K is 1, that is, the first area b ₁ of the interval n ₂ that contains the maximum credible value A total of ₆ intervals need to be included, and the other areas b2 and b3 contain ₅ intervals.

Step 43: Divide the first interval b ₁ , if the maximum credible value interval n _max is L intervals away from the first n _first or the last interval n _last , that is, L=max-first, or L=last-max, When L≤(J+K-1)/2, the L intervals near the first or last interval of n _max , and the J+K-1-L intervals on the other side are taken as the first area b ₁ ; Otherwise, when J+K-1 is an even number, take (J+K-1)/2 intervals on both sides of n _max as the first interval b ₁ ; when J+K-1 is an odd number, You can take (J+K)/2 intervals on one side and (J+K-2)/2 intervals on the other side as the first area b ₁ , and execute step 44 after completion.

Concrete example is as shown in table 2, and the interval of maximum credible value n ₂ is 1 interval away from the first interval n ₁ , and (J+K-1)/2=(5+1-1)/2=2.5, is greater than 1, so the first area contains only n ₁ intervals on one side of n ₂ , and the other side contains J+K-1-L=5+1-1-1=4 intervals, that is, the first area b ₁ includes 6 intervals n ₁ , n ₂ , n ₃ , n ₄ , n ₅ , and n ₆ .

Step 44: Divide the remaining areas, and divide the remaining N-(J+K) intervals into B-1 areas according to the method of equal division, and each interval includes J intervals.

The specific example is shown in Table 2. In addition to the interval contained in the first area, there are 10 intervals left. After equal division, the second area b ₂ contains n ₇ , n ₈ , n ₉ , n ₁₀ , n ₁₁ intervals, the third area b ₃ includes n ₁₂ , n ₁₃ , n ₁₄ , n ₁₅ , n ₁₆ intervals.

Step 45: Select the interval with the largest credible value from each area, select the median value of this interval as the credible coordinate, and select the attenuation level with the largest number of records from the energy attenuation list of the largest interval in each interval, and look up the table 1 Obtain the energy attenuation range, take the median value as the energy attenuation value from the coordinate to the node, and calculate the credible distance from the coordinate to the node according to the wireless signal propagation model in space.

The specific example is shown in Table 2 above. The maximum interval of the first area is n ₂ is 0.56, and the energy attenuation level with the largest number of records in this interval is 12. The maximum credible interval of the second area is n ₉ is 0.22. The most recorded energy attenuation level is 8, the maximum credible interval of the third area is n ₁₄ is 0.22, and the most recorded energy attenuation level in this interval is 10. According to Table 1, the energy attenuation range corresponding to each interval can be obtained. For example, the energy attenuation level with the most recorded number of n ₂ is 12, and the energy attenuation range is -50>p≥-55, and -52.5 can be taken as the midpoint of attenuation interval 2 Coordinates to the node's signal attenuation energy. Then, the distance d is calculated according to the wireless signal space model expressed by the following formula:

$\mathrm{<span\; class="notranslate">\; d</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; 10</span>}}^{\frac{\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; 0</span>}}}{\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; \&eta;</span>}}}$

Among them, P _d0 is the path loss power of the reference distance d ₀ , d ₀ is taken as 1 meter, η is the loss index of the wireless signal propagation path, η and P(d ₀ ) can be set through testing when installing the sensing node.

From this step, the midpoint position coordinates M ₂ (x ₂ , y ₂ ), M ₉ (x ₉ , y ₉ ) and M ₁₄ (x ₁₄ , y ₁₄ ) of n ₂ , n ₉ and n ₁₄ can be obtained, as The credible coordinates, and the distances d ₂ , d ₉ and d ₁₂ from these coordinates to node A are taken as credible distances.

Step 46: According to the positioning method, use the midpoint coordinates of the credible interval and the distance to the node to estimate the node position coordinates.

As in the example in Table 2, M ₂ , M ₉ and M ₁₄ , and d ₂ , d ₉ and d ₁₂ are obtained, that is, the position coordinates of node A can be estimated by the method of three-point positioning.

Step 5: Readjust the road interval according to the credible value of the interval.

The method of interval adjustment is shown in Figure 4, which includes the following steps:

Step 51: Determine whether the size of the interval with the largest credible value in each area is less than the precision requirement, if it is satisfied, then the interval where this area is located will not be adjusted, and continue to execute step 51 to adjust the next area, otherwise, execute step 52.

For example, in the example in Table 2, the interval size of interval n ₂ is 5 meters, and the accuracy requirement set by the node is 8 meters, then there is no need to adjust all the intervals of the first area b ₁ where n ₂ is located; if If the interval size of interval n ₂ is 10 meters, it is necessary to adjust the interval for area b ₁ .

Step 52: Split the interval with the largest credible value in each area into two equal intervals.

For example, in the example in Table 2, it is assumed that the interval sizes of n ₂ , n ₉ and n ₁₄ are all larger than the accuracy requirements, and interval adjustment is required. n ₂ is the interval with the largest credible value in area b ₁ , so n ₂ can be Split into two intervals n _{2_1} and n _{2_2} , n ₉ is the interval with the largest credible value in area b ₂ , so it can be split into two intervals n _{9_1} and n _{9_2} , n ₁₄ is the interval with the largest credible value in area b ₃ The interval, so it can be split into two intervals of n _{14_1} and n _{14_2} , and the above split can be split by equidistant.

Step 53: Merge the interval with the smallest credible value in each area with the interval with the smallest credible value in the adjacent same area.

As in the example in Table ₂ , _n6 is the interval with the smallest credible value in area b1, and its adjacent interval belonging to area b1 is only _n5 , so these two intervals are _merged into interval _{n6_5} ; _n8 is the area In the interval with the smallest credible value in b ₂ , there are n ₇ and n ₉ in the adjacent intervals belonging to area b ₂ , the credible value of n ₇ is 0.17, and the credible value of n ₉ is 0.22, because the credible value of n ₇ The value is small, so the n ₇ and n ₈ intervals are merged into the interval n _{8_7} ; n ₁₂ is the interval with the smallest credible value in the area b ₃ , and the adjacent interval belonging to the area b ₃ is only n ₁₃ , so these two intervals are merged into interval n _{12_13} .

Step 54: Renumber the intervals after splitting and merging in sequence.

As in the example in Table 2, after the splitting and merging in steps 52 and 53, new interval divisions are obtained as shown in Table 3, and these intervals are renumbered. The serial number of the original n ₃ interval in the new interval division has changed to For example, the serial numbers of the split intervals n _{2_1} and n _{2_2} in the new interval division have changed to and For example, the serial number of the merged interval n _{8_7} in the new interval division has changed to

Step 55: Clear the number of records in the energy attenuation list of the new section to zero. If all areas have been traversed, perform step 2; otherwise, perform step 51 to adjust the next area.

The above is only a preferred embodiment of the present invention, it should be pointed out that, for those of ordinary skill in the art, without departing from the principle of the present invention, some improvements and modifications can also be made, and these improvements and modifications can also be made. It should be regarded as the protection scope of the present invention.

The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined in this invention may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed in the present invention.

Claims (5)

1. The node location method along the road based on interval credibility evaluation, which is applied to the vehicle self-organizing network, is characterized in that, comprising the following steps: Step 1: The nodes along the road initialize parameters and variables, divide the adjacent road into N intervals according to their own communication radius R and road conditions, and establish an energy attenuation list P for each interval. The energy attenuation list P includes Energy attenuation level and recording times; Step 2: Nodes along the road perform interval energy attenuation statistics according to the received vehicle information and signals; Step 3: Make statistics on the energy attenuation list of each interval to obtain the credible value of the interval; Step 4: Select the credible interval for positioning; Step 5: Readjust according to the credible value of the interval. 2. The positioning method according to claim 1, wherein the interval energy attenuation statistics in step 2 are as follows: The node obtains the coordinates of the information released by the vehicle according to the information released by the vehicle on the road, and determines the interval according to the coordinate information; The node subtracts the transmission power in the vehicle's published information from the power actually received by the information, calculates the energy attenuation value, queries the energy attenuation list P according to the energy attenuation value to obtain the energy attenuation level, and uses the attenuation level in the energy attenuation list of the interval Add 1 to the number of records; It is judged whether the accumulated value of the recording times of the attenuation level reaches the accumulated maximum value, if yes, then execute step 3, otherwise, continue to receive the information issued by the vehicle. 3. The positioning method according to claim 1, wherein the step 3 performs statistics on the energy attenuation list of each interval as follows: obtain vehicle emission information in each interval according to the record times of each level in the energy attenuation list The total number of times, and the attenuation energy level with the most recorded times, divide the maximum number of attenuation energy level records in each interval by the total number of records, and the value is taken as the credible value of the interval. 4. The positioning method according to claim 1, wherein said step 4 selects a credible interval for positioning, comprising the following steps: Step 41: Select the interval n _max with the largest credible value among all intervals; Step 42: The positioning algorithm needs to use B position coordinates for positioning, divide N intervals into B areas, divide N by B, and obtain the quotient J and the remainder K, the first area b ₁ contains the maximum credible value interval, execute step 43, so that the first area contains a total of J+K intervals; Step 43: Divide the first area: if the maximum credible value interval is L intervals away from the first or last interval, when L≤(J+K-1)/2, n _max is close to the first or last The L intervals of one interval and the J+K-1-L intervals on the other side are used as the first area b ₁ ; otherwise, when J+K-1 is an even number, the adjacent two sides of n _max are taken (J +K-1)/2 intervals, as the first area b ₁ ; when J+K-1 is an odd number, you can take (J+K)/2 intervals on either side, and take (J+K- 2)/2 intervals, as the first area b ₁ , execute step 44 after completion; Step 44: Divide the remaining B-1 areas: divide the remaining N-(J+K) intervals into B-1 areas according to the method of equal division, and each area contains J intervals; Step 45: Select the interval with the largest credible value from each area, select the median value of this interval as the credible coordinate, and select the attenuation level with the most records from the energy attenuation list of the largest interval in each interval, and query the energy Obtain the energy attenuation range from the attenuation list, take the median value as the energy attenuation value from the coordinate to the node, and calculate the credible distance from the coordinate to the node according to the wireless signal propagation model in space; Step 46: According to the positioning method, use the credible coordinates and credible distances of multiple intervals to estimate the node position coordinates. 5. The positioning method according to claim 4, wherein said step 5 is readjusted according to the credible value of the interval, and the steps are as follows: Step 51: Determine whether the size of the interval with the largest credible value in the area is smaller than the precision requirement, if it is satisfied, then the interval where the area is located will not be adjusted, otherwise, go to step 52; Step 52: Split the interval with the largest credible value in the region into two equal intervals; Step 53: Merge the interval with the smallest credible value in the region with the interval with the smallest credible value in the adjacent same region; Step 54: Renumber the intervals after splitting and merging in sequence; Step 55: Clear the number of records in the energy attenuation list of the new section to zero. If all areas have been traversed, perform step 2; otherwise, perform step 51 to adjust the next area.