Two-dimensional rapid radio wave propagation coverage interpolation method

Abstract

The invention discloses a two-dimensional rapid radio wave propagation coverage interpolation method, and relates to the field of radio, the two-dimensional rapid radio wave propagation coverage interpolation method comprises the following steps: 1, in an unknown calculation area, using a minimum rectangle to contain the calculation area, and segmenting the rectangular area at equal intervals to obtain a longitude and latitude array; step 2, obtaining grid data through a signal attenuation value of a node contained in software latitude and longitude data; step 3, calculating a first-order triangular interpolation function; the method has the beneficial effects that the data value of the unknown node can be obtained only by substituting the position information and data values of the unknown node and the surrounding known nodes into the interpolation algorithm; the number of nodes used for interpolation is equal to the number of terms of a polynomial, so that rapid interpolation is realized, high-precision interpolation is realized by selecting an area with a small interpolation error as an interpolation area, and an efficient and high-precision signal coverage result is provided for radio wave propagation coverage prediction.

Description

Technical Field

[0001] The invention relates to the field of radio, and in particular to a two-dimensional fast radio wave propagation coverage interpolation method. Background Art

[0002] The radio wave propagation coverage in the radio professional field is calculated by interpolation algorithm, which is a commonly used method in radio communication and radio wave propagation research. The interpolation algorithm can estimate the radio wave propagation characteristics of unknown points based on the known radio wave propagation data, thereby realizing the prediction and analysis of radio wave propagation coverage.

[0003] The electric field strength at unknown points can be estimated using interpolation algorithms through known electric field strength data points. This is crucial for evaluating the coverage and performance of radio systems. Interpolation algorithms can help analyze the propagation characteristics of radio waves in different environments, such as path loss, multipath effects, etc. This is of great significance for optimizing the design of radio systems and improving communication quality.

[0004] The existing interpolation algorithm has low accuracy and needs to be improved. Summary of the invention

[0005] The purpose of the present invention is to provide a two-dimensional fast radio wave propagation coverage interpolation method to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A two-dimensional fast radio wave propagation coverage interpolation method comprises the following steps:

[0008] Step 1: In the unknown calculation area, use a minimum rectangle to include the calculation area, divide the rectangular area into equal parts, and obtain the longitude and latitude array;

[0009] Step 2, obtaining grid data by using the signal attenuation value of the node including the latitude and longitude data of the software;

[0010] Step 3, calculate the first-order triangle interpolation function;

[0011] Step 4, calculate the P-order triangle interpolation function;

[0012] Step 5, select the interpolation area;

[0013] Step 6: Use the P-order triangular interpolation function to calculate the attenuation values ​​of the remaining unknown nodes through the known nodes to obtain the radio wave propagation coverage prediction result. In the difference function, (p+1)(p+2) / 2 data points are used for interpolation and form an interpolation polynomial, where p is the interpolation order.

[0014] As a further solution of the present invention: step 3 comprises:

[0015] Step 31, assuming an unknown function in a 1st order triangle;

[0016] Step 32, obtaining formulas of the unknown function at different directions;

[0017] Step 33, obtain the constant coefficient of the unknown function through the formula at different directions of the unknown function, obtain the first-order triangle interpolation function, and calculate the triangle area.

[0018] As a further solution of the present invention: In step 31, the first-order triangle interpolation is an interpolation polynomial formed by three data points. Assume that the unknown function in a first-order triangle is , the function can be expressed as

[0019] (1);

[0020] in, , and are the constant coefficients to be solved.

[0021] As a further solution of the present invention: in step 32, for a first-order linear triangle, the three vertices of the triangle are rotated in a counterclockwise direction with 1 , 2 and 3 Number and use , and Represent the corresponding function values, as shown below:

[0022] (2);

[0023] (3);

[0024] (4).

[0025] As a further solution of the present invention: In step 33, the constant coefficients are solved using formulas (2), (3) and (4) , and , and bring them back to formula (1), we get

[0026] (5);

[0027] in, is an interpolation function or an expansion function;

[0028] (6);

[0029] in,

[0030] (7);

[0031] = Area of ​​triangle (8).

[0032] As a further solution of the present invention: Step 4 includes: a p-order triangle unit has (p+1)(p+2) / 2 data points, one data point at each of the three vertices of the triangle, and the other data points are distributed in the triangle; within the triangle, the unknown function It can be expressed as:

[0033] (9);

[0034] The coefficients of the unknown function and the area of ​​the triangle are obtained through the coordinate values ​​of the three vertices; the coefficients and area of ​​the function are substituted into the following formula:

[0035] (10);

[0036] Establish a P-order triangle interpolation function, use three integers (I, J, K) to mark each node in the unit, so that the (n,0,0) node is node 1, the (0,n,0) node is node 2, and the (0,0,n) node is node 3. The interpolation function related to the node i [labeled (I,J,K)] can be written as:

[0037] (11);

[0038] In the formula is a polynomial defined as follows:

[0039] (12);

[0040] in , and The definition is similar to that of . Finally, the interpolation function can be obtained as follows:

[0041] (13).

[0042] Compared with the prior art, the beneficial effects of the present invention are: the interpolation algorithm of the present invention can obtain the data value of the unknown node by only bringing the position information and data values ​​of the unknown node and the surrounding known nodes into the interpolation algorithm; the number of nodes used for interpolation is equal to the number of terms of the polynomial to achieve fast interpolation, and high-precision interpolation is achieved by selecting an area with a smaller interpolation error as the interpolation area, thereby providing efficient and high-precision signal coverage results for radio wave propagation coverage prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Schematic diagram of a P-order triangle.

[0044] Figure 2 Flowchart for step 6.

[0045] Figure 3 Schematic diagram of the first-order interpolation area.

[0046] Figure 4 Schematic diagram of the second-order interpolation area.

[0047] Figure 5 Schematic diagram of the third-order interpolation area.

[0048] Figure 6 Schematic diagram of the 4th-order interpolation area. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0050] A two-dimensional fast radio wave propagation coverage interpolation method comprises the following steps:

[0051] Step 1: In the unknown calculation area, use a minimum rectangle to include the calculation area, divide the rectangular area into equal parts, and obtain the longitude and latitude array;

[0052] Step 2, obtaining grid data by using the signal attenuation value of the node including the latitude and longitude data of the software;

[0053] Step 3, calculate the first-order triangle interpolation function;

[0054] Step 4, calculate the P-order triangle interpolation function;

[0055] Step 5: Select the interpolation area. You should select the area with smaller interpolation error as the interpolation area to reduce the error. Figures 3 to 6 , which are the interpolation areas selected when they are 1st, 2nd, 3rd, and 4th order triangles respectively.

[0056] See also Figure 2 ,Step 6, use the P-order triangle interpolation function to calculate the attenuation values ​​of the remaining unknown nodes through the known nodes to obtain the radio wave propagation coverage prediction results. In the difference function, (p+1)(p+2) / 2 data points are used for interpolation and form an interpolation polynomial, and p is the interpolation order.

[0057] In this embodiment: Step 3 includes:

[0058] Step 31, assuming an unknown function in a 1st order triangle;

[0059] Step 32, obtaining formulas of the unknown function at different directions;

[0060] Step 33, obtain the constant coefficient of the unknown function through the formula at different directions of the unknown function, obtain the first-order triangle interpolation function, and calculate the triangle area.

[0061] In this embodiment: In step 31, the first-order triangle interpolation is an interpolation polynomial formed by three data points. Assume that the unknown function in a first-order triangle is , the function can be expressed as

[0062] (1);

[0063] in, , and are the constant coefficients to be solved.

[0064] In this embodiment: In step 32, for a first-order linear triangle, the three vertices of the triangle are rotated in a counterclockwise direction with 1 , 2 and 3 Number and use , and Represent the corresponding function values, as shown below:

[0065] (2);

[0066] (3);

[0067] (4).

[0068] In this embodiment: In step 33, the constant coefficients are solved using formulas (2), (3) and (4) , and , and bring them back to formula (1), we get

[0069] (5);

[0070] in, is an interpolation function or an expansion function;

[0071] (6);

[0072] in,

[0073] (7);

[0074] = Area of ​​triangle (8).

[0075] In this example: See Figure 1 , step 4 includes: a p-order triangle unit has (p+1)(p+2) / 2 data points, one data point at each of the three vertices of the triangle, and the other data points are calculated according to Figure 1 The distribution shown is in a triangle; within the triangle, the unknown function It can be expressed as:

[0076] (9);

[0077] Substituting the coordinate values ​​of the three vertices into formulas (6) and (8) will yield the coefficients of the unknown function and the area of ​​the triangle. Substituting the coefficients and area of ​​the function into the following formula:

[0078] (10);

[0079] Establish a P-order triangle interpolation function and mark each node in the unit with three integers (I, J, K), such as Figure 1 As shown, let the (n, 0, 0) node be node 1, the (0, n, 0) node be node 2, and the (0, 0, n) node be node 3. The interpolation function related to node i [labeled (I, J, K)] can be written as:

[0080] (11);

[0081] In the formula is a polynomial defined as follows:

[0082] (12);

[0083] in , and The definition is similar to that of . Finally, the interpolation function can be obtained as follows:

[0084] (13).

[0085] The interpolation algorithm of the present invention can obtain the data value of the unknown node by simply bringing the position information and data values ​​of the unknown node and the surrounding known nodes into the interpolation algorithm; the number of nodes used for interpolation is equal to the number of terms of the polynomial to achieve fast interpolation, and high-precision interpolation is achieved by selecting an area with a smaller interpolation error as the interpolation area, providing efficient and high-precision signal coverage results for radio wave propagation coverage prediction.

[0086] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered as exemplary and non-restrictive in all respects.

[0087] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A two-dimensional fast radio wave propagation coverage interpolation method, characterized in that: The two-dimensional fast radio wave propagation coverage interpolation method comprises the following steps: Step 1: In the unknown calculation area, use a minimum rectangle to include the calculation area, divide the rectangular area into equal parts, and obtain the longitude and latitude array; Step 2, obtaining grid data by using the signal attenuation value of the node including the latitude and longitude data of the software; Step 3, calculate the first-order triangle interpolation function; Step 4, calculate the P-order triangle interpolation function; Step 5, select the interpolation area; Step 6: Use the P-order triangular interpolation function to calculate the attenuation values ​​of the remaining unknown nodes through the known nodes to obtain the radio wave propagation coverage prediction result. In the difference function, (p+1)(p+2) / 2 data points are used for interpolation and form an interpolation polynomial, where p is the interpolation order.

2. The two-dimensional fast radio wave propagation coverage interpolation method according to claim 1, characterized in that: Step 3 includes: Step 31, assuming an unknown function in a 1st order triangle; Step 32, obtaining formulas of the unknown function at different directions; Step 33, obtain the constant coefficient of the unknown function through the formula at different directions of the unknown function, obtain the first-order triangle interpolation function, and calculate the triangle area.

3. The two-dimensional fast radio wave propagation coverage interpolation method according to claim 2, characterized in that: In step 31, the first-order triangle interpolation is an interpolation polynomial formed by three data points. Assume that the unknown function in a first-order triangle is , the function can be expressed as （1）； in, , and are the constant coefficients to be solved.

4. The two-dimensional fast radio wave propagation coverage interpolation method according to claim 3, characterized in that: In step 32, for a 1st order linear triangle, the three vertices of the triangle are rotated in a counterclockwise direction with 1 , 2 and 3 Number and use , and Represent the corresponding function values, as shown below: （2）； （3）； （4）。 5. The two-dimensional fast radio wave propagation coverage interpolation method according to claim 4, characterized in that: In step 33, use formulas (2), (3) and (4) to solve for the constant coefficients , and , and bring them back to formula (1), we get （5）； in, is an interpolation function or an expansion function; （6）； in, （7）； = Area of ​​triangle (8).

6. The two-dimensional fast radio wave propagation coverage interpolation method according to any one of claims 1 to 5, characterized in that: Step 4 includes: a p-order triangle unit has (p+1)(p+2) / 2 data points, one data point at each of the three vertices of the triangle, and the other data points are distributed in the triangle; within the triangle, the unknown function It can be expressed as: （9）； The coefficients of the unknown function and the area of ​​the triangle are obtained through the coordinate values ​​of the three vertices; the coefficients and area of ​​the function are substituted into the following formula: （10）； Establish a P-order triangle interpolation function, use three integers (I, J, K) to mark each node in the unit, so that the (n, 0, 0) node is node 1, the (0, n, 0) node is node 2, and the (0, 0, n) node is node 3. The interpolation function related to node i [labeled (I, J, K)] can be written as: （11）； In the formula is a polynomial defined as follows: （12）； in , and The definition is similar to that of . Finally, the interpolation function can be obtained as follows: （13）。

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