Rapid generation method of radio monitoring coverage model based on Aovullage-Hartt

Abstract

The invention discloses a method for rapidly generating a radio monitoring coverage model based on Aovullage-Hartt, and belongs to the field of radio. The method specifically comprises the following steps: for a certain urban area monitored by radio, introducing a correction factor s (alpha) of the building density in the urban area on the basis of radio wave propagation path loss of an Aovullan model, and obtaining a corrected propagation path loss calculation formula to carry out secondary loss attenuation; then, equivalently segmenting a geographic layer according to a three-dimensional space by using a fast algorithm, extracting point-surface data in the space, and substituting the point-surface data into propagation path loss calculation to obtain field intensity information of space points; and meanwhile, performing field intensity information calculation on the building in the three-dimensional space by adopting geographic space layer collision analysis. And finally, by taking monitoring range edge feature data of road test as a standard data set, comparing the field intensity information of the space points and the field intensity information of the building, and realizing multi-dimensional visualization of the radio monitoring coverage in the three-dimensional geographic space. According to the method, the calculation time is shortened, and the efficiency is improved.

Description

Technical Field

[0001] The invention belongs to the field of radio, and relates to a method for quickly generating a radio monitoring coverage model based on Okumura-Hart. Background Art

[0002] At present, there are two conventional methods for calculating the coverage of radio monitoring facilities:

[0003] Method 1: Calculate the coverage range by selecting a suitable radio wave propagation model, such as the Okumura-Hata model ITU-R P.1546 Recommendation model; the Okumura-Hata model (hereinafter referred to as the Okumura model) theoretically uses the median path loss of the field strength in large urban areas with quasi-flat terrain as a benchmark, and uses correction factors to correct factors such as different propagation environments and terrain conditions. It is applicable to VHF and UHF frequency bands. However, for the prediction of field strength in densely populated large urban areas, the model has large errors and inaccurate coverage edge features due to factors such as dense buildings, complex road conditions, and terrain. Therefore, it is not used in most actual field strength measurement processes.

[0004] Method 2: Refer to the building environment around the monitoring facility, estimate the approximate range boundary, and then plan the test path in combination with the actual road environment, and finally conduct manual field testing, which greatly improves the accuracy of the edge features of the coverage range. However, this method often requires a lot of manpower, material resources and time, and is greatly affected by the actual road traffic environment during the field road test.

[0005] Therefore, improving the calculation formula of the radio wave propagation model, quickly calculating the propagation loss, and accurately determining the edge characteristics of the radio monitoring coverage range are technical problems that urgently need to be solved. Summary of the invention

[0006] In view of the above problems, the present invention proposes a method for quickly generating a radio monitoring coverage model based on Okumura-Hart. Through loss improvement, collision analysis or machine learning, the calculation time of the model is controlled to within 30 minutes. At the same time, the accuracy of the calculation result is close to 65% of the road test, and the efficiency is improved by more than 800 times. It solves the problems of time-consuming, labor-intensive, difficult calculation and large errors in the current radio monitoring coverage modeling to the greatest extent.

[0007] The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart has the following specific steps:

[0008] Step 1: For a certain urban area under radio monitoring, obtain multiple groups of Okumura model wave propagation path loss L values ​​by changing the distance parameter d, and use the maximum loss value in each group as the judgment basis to obtain multiple groups of latitude and longitude data of the coverage area, and substitute them into the geographic information platform to obtain the two-dimensional display effect S0 of the coverage area.

[0009] The calculation formula of propagation path loss L is:

[0010] L=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r

[0011] f represents the operating frequency; h b represents the effective height of the base station antenna; a(h m ) represents the mobile station antenna correction factor; h m represents the effective height of the mobile station antenna; d represents the distance between the base station and the terminal; r represents the long-distance transmission correction factor.

[0012] Step 2: introduce the correction factor s(α) of the building density in the urban area into the calculation formula of the radio wave propagation path loss L of the Okumura model to perform secondary loss attenuation to obtain the corrected propagation path loss L';

[0013] The calculation formula is as follows:

[0014]

[0015] Among them, s(α) represents the correction factor of urban building density; α represents the building density.

[0016] The corrected propagation path loss L' is calculated as:

[0017] L'=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r -s(α)

[0018] Step 3: After extracting the building density α, change the parameter d again to obtain multiple sets of corrected propagation path loss L' values, substitute them into the geographic information platform, and obtain a two-dimensional display effect S1 of the urban coverage area.

[0019] After the correction factor is introduced, the monitoring coverage model in the two-dimensional display effect S1 is transformed from an approximate circle to an irregular shape, and its edge features begin to appear.

[0020] Step 4: Use a fast algorithm to divide the geographic layer corresponding to the urban area into equal parts in three-dimensional space, extract the segmentation point surface data in the space, substitute it into the corrected propagation path loss L' calculation to obtain the field strength information of the spatial point;

[0021] The segmentation point and surface data include latitude and longitude, altitude, signal strength and density parameters of different buildings in space;

[0022] The purpose of acquiring field strength information is to convert the radio monitoring coverage from a two-dimensional plane to a three-dimensional space display with multiple perspectives.

[0023] Specifically, the space building is subjected to secondary attenuation according to the calculated corrected propagation path loss L', and finally the value of the field strength is obtained.

[0024] Step 5: Use geospatial layer collision analysis to calculate the field strength information of buildings in three-dimensional space.

[0025] When radio wave transmission encounters an obstruction, the signal loss is attenuated again using the corrected propagation path loss L' calculation formula according to the ratio of the contact area of ​​the obstruction occupied during the radio wave signal transmission process. The field strength information in the three-dimensional space behind the obstruction can be calculated, making the edge features of the monitoring coverage range clearer.

[0026] Step 6: Use the edge feature data of the monitoring range of the road test as the standard data set, compare the field strength information of the spatial points and buildings, analyze the differences and perform calibration corrections, and finally achieve multi-dimensional visualization of the radio monitoring coverage in three-dimensional geographic space.

[0027] After obtaining the field strength data in three-dimensional space through repeated verification through road test calibration and machine learning, it is converted into scattered heat map data through the geographic information platform. The size of the spatial field strength data is distinguished and modified with different colors, and combined with the edge feature data calculated by the fast algorithm, it finally realizes the multi-dimensional visualization of the radio monitoring coverage in the three-dimensional geographic space when looking up, looking down and looking horizontally.

[0028] The advantages of the present invention are:

[0029] 1) Based on the rapid generation method of radio monitoring coverage model of Okumura-Hart, it can quickly and accurately generate a heat map of radio monitoring coverage according to the actual urban environment and combined with the spatial field strength value, ensuring that various radio monitoring services can be carried out quickly and normally, and providing better auxiliary decision-making for the effective promotion of scientific monitoring of radio spectrum and electromagnetic environment supervision.

[0030] 2) Based on the Okumura-Hart radio monitoring coverage model rapid generation method, it can clearly show the edge characteristics of the monitoring coverage range, and can calculate the field strength within the coverage range according to the actual environment, and can increase the accuracy to 65%, achieving the actual display effect. Moreover, the time for implementing the calculation process is compressed to within 30 minutes, and the efficiency is increased by more than 800 times.

[0031] 3) Based on the Okumura-Hata model, a rapid generation method for radio monitoring coverage models is proposed. Through repeated loss correction, collision analysis, and machine learning steps, the total output time of the rapid algorithm modeling is less than 25 minutes, which is more than 860 times more efficient than the Okumura-Hata model. It can effectively solve many problems existing in the conventional modeling of radio monitoring coverage at this stage.

[0032] 4) Based on the rapid generation method of radio monitoring coverage model of Okumura-Hart, the edge characteristics of the radio monitoring coverage area are obvious, and its clarity, three-dimensional display and other effects are greatly improved, and the accuracy is close to 65% of method 2. It can be seen that the fast algorithm can quickly and accurately generate a heat map of the radio monitoring coverage area based on the actual urban environment and combined with the spatial field strength value. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flow chart of a method for rapidly generating a radio monitoring coverage model based on Okumura-Hart of the present invention;

[0034] Figure 2 It is a two-dimensional coverage display diagram obtained by using the Okumura-Hata model after introducing the correction factor in the present invention;

[0035] Figure 3 It is a three-dimensional space effect map obtained by dividing the geographical layer into equal parts in three-dimensional space. DETAILED DESCRIPTION

[0036] In order to facilitate those skilled in the art to understand and implement the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only partial embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present invention.

[0037] The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart has the following specific steps:

[0038] Step 1: For a certain urban area under radio monitoring, obtain multiple groups of Okumura model wave propagation path loss L values ​​by changing the distance parameter d, and use the maximum loss value in each group as the judgment basis to obtain multiple groups of latitude and longitude data of the coverage area, and substitute them into the geographic information platform to obtain the two-dimensional display effect S0 of the coverage area.

[0039] Based on the theoretical basis of the Okumura model radio wave propagation path loss calculation method, the calculation formula is:

[0040] L=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r

[0041] f represents the operating frequency, in megahertz (MHz); h b Represents the effective height of the base station antenna, in meters (m); a (h m ) represents the mobile station antenna correction factor, in decibels (dB); h m Represents the effective height of the mobile station antenna, in meters (m). m When it is 1.5m, ignore a(h m ) ; d represents the distance between the base station and the terminal, in meters (m); r represents the long-distance transmission correction factor, in decibels (dB). When d<20m, r=1.

[0042] Step 2: introduce the correction factor s(α) of the building density in the urban area into the calculation formula of the radio wave propagation path loss L of the Okumura model to perform secondary loss attenuation to obtain the corrected propagation path loss L';

[0043] By analyzing the calculation formula of the radio wave propagation path loss of the Okumura model, the factors affecting the basic transmission loss are found. The reason is that the radio propagation path loss will change continuously with the influence of external factors, forming a multipath change effect. For example, reflections from the earth and buildings will cause the phasor superposition of multipath effects, and signal changes will occur at the wavelength level. Considering that the calculation formula of the Okumura model ignores the effects of reflection and shielding from buildings, the range results are inaccurate. After studying the propagation characteristics of terrestrial fixed services, the calculation formula for the building density correction factor is obtained as follows:

[0044]

[0045] Among them, s(α) represents the urban building density correction factor, the unit is decibel (dB); α represents the building density.

[0046] After obtaining the correction factor, the parameter is incorporated into the calculation formula of the Okumura model to perform secondary loss attenuation. The calculation formula for the corrected propagation path loss L' is:

[0047] L'=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r -s(α)

[0048] Step 3: After extracting the building density α, change the parameter d again to obtain multiple sets of corrected propagation path loss L' values, substitute them into the geographic information platform, and obtain a two-dimensional display effect S1 of the urban coverage area.

[0049] like Figure 2 As shown, after the correction factor is introduced, the monitoring coverage model in the two-dimensional display effect S1 is transformed from an approximate circle to an irregular shape, and its edge features begin to appear, and the display effect is improved. However, since the field strength signal between complex buildings cannot be calculated, the edge features of the coverage area are right-angled, and there are still accuracy problems.

[0050] Step 4: Use a fast algorithm to divide the geographic layer corresponding to the urban area into equal parts in three-dimensional space, extract the segmentation point surface data in the space, substitute it into the corrected propagation path loss L' calculation to obtain the field strength information of the spatial point;

[0051] Relative to the coverage area of ​​the monitoring facilities, whether calculated through the radio wave propagation model or through manual field road test of the radio monitoring coverage, it is impossible to fully take into account the influencing factors brought by the objective environment, resulting in the presentation of the radio monitoring coverage as a plane structure. Therefore, it is necessary to change the traditional calculation and presentation methods, calculate the radio wave propagation path loss in three-dimensional space, obtain the field strength value data in three-dimensional space, and convert the radio monitoring coverage from a two-dimensional plane to a multi-perspective three-dimensional space display.

[0052] The segmentation point surface data include latitude and longitude, altitude, signal strength and density parameters of different buildings in space;

[0053] The purpose of acquiring field strength information is to convert the radio monitoring coverage from a two-dimensional plane to a three-dimensional space display with multiple perspectives.

[0054] Specifically, the space building is subjected to secondary attenuation according to the calculated corrected propagation path loss L', and finally the value of the field strength is obtained.

[0055] Step 5: Use geospatial layer collision analysis to calculate the field strength information of buildings in three-dimensional space.

[0056] When radio wave transmission encounters obstructions such as buildings, the signal loss is attenuated again using the corrected propagation path loss L' calculation formula according to the ratio of the contact area of ​​the obstructing object occupied during the transmission of the radio wave signal, and the field strength information in the three-dimensional space behind the obstructions such as buildings can be measured, making the edge features of the monitoring coverage clearer. This makes up for the defect that the field strength between complex buildings cannot be calculated after the correction factor is introduced.

[0057] Step 6: Use the edge feature data of the monitoring range of the road test as the standard data set, compare the field strength information of the spatial points and buildings with the standard data set, analyze the differences and perform calibration corrections, and finally achieve multi-dimensional visualization of the radio monitoring coverage in three-dimensional geographic space.

[0058] After obtaining the field strength data in three-dimensional space through repeated verification by road test calibration and machine learning, it is converted into scattered point heat map data through the geographic information platform, and the size of the spatial field strength data is distinguished and modified with different colors, and combined with the edge feature data calculated by the fast algorithm, it finally realizes the multi-dimensional visualization of the radio monitoring coverage in the three-dimensional geographic space, such as looking up, looking down and looking horizontally. Figure 3 shown.

Claims

1. A method for rapidly generating a radio monitoring coverage model based on Okumura-Hart, characterized in that: The specific steps are as follows: Step 1: Calculate the radio wave propagation path loss L of the Okumura model as a basis for a certain urban area under radio monitoring; The calculation formula of propagation path loss L is: L=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r f represents the operating frequency; h b represents the effective height of the base station antenna; a(h m ) represents the mobile station antenna correction factor; h m represents the effective height of the mobile station antenna; d represents the distance between the base station and the terminal; r represents the long-distance transmission correction factor; Step 2: introduce the correction factor s(α) of the building density in the urban area into the calculation formula of the radio wave propagation path loss L to perform secondary loss attenuation to obtain the corrected propagation path loss L'; The correction factor formula is as follows: Among them, s(α) represents the correction factor of urban building density; α represents the building density; The corrected propagation path loss L' is calculated as: L'=69.55+26.16lgf-13.82lgh b -a(h m )+(44.9-6.55lgh b )(lgd) r -s(α) Step 3: After extracting the building density α, obtain multiple sets of corrected propagation path loss L' values ​​by changing the distance parameter d, substitute them into the geographic information platform, and obtain the two-dimensional display effect S1 of the urban coverage area, which initially shows the edge characteristics; Step 4: Use a fast algorithm to divide the geographic layer corresponding to the urban area into equal parts in three-dimensional space, extract the segmentation point surface data in the space, substitute it into the corrected propagation path loss L' calculation to obtain the field strength information of the spatial point; Step 5: Use geospatial layer collision analysis to calculate the field strength information of buildings in three-dimensional space; Step 6: Use the edge feature data of the monitoring range of the road test as the standard data set, compare the field strength information of the spatial points and buildings, analyze the differences and perform calibration corrections, and finally achieve multi-dimensional visualization of the radio monitoring coverage in three-dimensional geographic space.

2. The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart as claimed in claim 1, characterized in that: In the step one, the radio wave propagation path loss L values ​​of multiple groups of Okumura models are obtained by changing the distance parameter d, and the maximum loss value in each group is used as the judgment basis to obtain multiple groups of latitude and longitude data of the coverage range, and substitute them into the geographic information platform to obtain a two-dimensional display effect S0 of the coverage range.

3. The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart as claimed in claim 1, characterized in that: In the step 3, the initial appearance of edge features means that after the correction factor is introduced, the monitoring coverage model in the two-dimensional display effect S1 is transformed from an approximate circle to an irregular shape compared with the two-dimensional display effect S0.

4. The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart as claimed in claim 1, characterized in that: In the step 4, the segmentation point surface data includes the latitude and longitude, altitude, signal strength and density parameters of different buildings in the space; The purpose of acquiring field strength information is to convert the radio monitoring coverage from a two-dimensional plane to a three-dimensional space display with multiple perspectives.

5. The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart as claimed in claim 1, characterized in that: In the step five, when the radio wave transmission encounters an obstruction, the signal loss is attenuated again using the corrected propagation path loss L' calculation formula according to the ratio of the contact area of ​​the obstruction occupied during the radio wave signal transmission process, and the field strength information in the three-dimensional space behind the obstruction can be calculated, making the edge features of the monitoring coverage range clearer.

6. The method for rapidly generating a radio monitoring coverage model based on Okumura-Hart as claimed in claim 1, characterized in that: In the step six, after the field strength data in the three-dimensional space is obtained through repeated verification by road test calibration and machine learning, it is converted into scattered point heat map data through the geographic information platform, and the size of the spatial field strength data is distinguished and modified with different colors, and combined with the edge feature data calculated by the fast algorithm, finally realizing the multi-dimensional visualization of the radio monitoring coverage in the three-dimensional geographic space, looking up, looking down and looking horizontally.

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