Wifi multi-point accurate positioning method based on marketing, distribution and dispatching through technology

Abstract

The invention relates to a WIFI multi-point accurate positioning method based on a marketing, distribution and dispatching through technology, and the method comprises the following steps: 1, correcting personal errors through employing a WIFI multi-point accurate positioning algorithm and a topology auxiliary discrimination method; 2, a secondary positioning algorithm based on the received signal strength is adopted, and power grid GIS accurate positioning of the power grid equipment is achieved; step 3, adopting a power equipment accurate positioning algorithm based on two-point positioning to realize positioning measurement of coordinates of the power equipment; the method has the advantages of being more convenient, higher in acquisition precision and accurate in positioning information.

Description

Technical Field

[0001] The invention belongs to the technical field of electric power equipment positioning and measurement, and in particular relates to a WiFi multi-point precise positioning method based on operation, distribution and dispatching through technology. Background Art

[0002] The rapid economic development has led to an increasing demand for electricity in the entire society, which has led to a rapid improvement in my country's power system and automation level. The precise positioning of power equipment is a technical basis for both power system automation control and power repair and power industry capacity expansion. The complexity of power grid equipment continues to increase with economic development. The lean management of the power system requires the continuous improvement of the automation management level of power grid equipment. Combined with the data connection of the distribution and dispatching actively promoted by the State Grid Corporation in recent years, the precise positioning of power equipment is studied on the basis of completing the integration of various professional data. It can reversely verify the data quality of the distribution and dispatching data connection and further improve the lean management level of the power system. Among them, the accurate collection and location of power grid equipment information is a crucial content, which determines the actual effect of the final lean management. The current adoption The main positioning technologies used are: 1) outdoor positioning technology collection, which mainly relies on manual collection of GPS signals; 2) indoor equipment positioning technology, which relies on operators to carry background maps for on-site marking, and then perform GIS map modeling operations according to the marked graphics to realize this type of location information collection. It is relatively advantageous in outdoor equipment information collection, but the rapid development of urbanization in recent years has caused more complex power equipment to shift from outdoor to indoor. In the collection of indoor information, the GPS positioning module is completely relied upon to collect positioning information, which is limited to high-rise buildings and indoor environments, making it impossible to guarantee the accuracy of the location information and topological relationship of indoor power equipment. Therefore, it is very necessary to provide a more convenient, more accurate and accurate positioning information based on a wifi multi-point precise positioning method of the marketing, distribution and dispatching technology. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a more convenient, more accurate and precise wifi multi-point positioning method based on the deployment and coordination technology.

[0004] The object of the present invention is achieved by: a wifi multi-point precise positioning method based on the camping, deployment and coordination technology, the method comprising the following steps:

[0005] Step 1: Use WIFI multi-point precise positioning algorithm and topology-assisted identification method to correct human errors;

[0006] Step 2: Use a secondary positioning algorithm based on received signal strength to achieve accurate positioning of power grid GIS equipment;

[0007] Step 3: Use the power equipment precise positioning algorithm based on two-point positioning to realize the positioning measurement of the power equipment coordinates.

[0008] The WIFI multi-point precise positioning algorithm and topology-assisted discrimination method in step 1 specifically include the following steps:

[0009] Step 1.1: Trilateration algorithm;

[0010] Step 1.2: WIFI signal fingerprint positioning;

[0011] Step 1.3: Topology-assisted Wi-Fi positioning.

[0012] The trilateral measurement algorithm in step 1.1 is specifically as follows: when there are multiple WIFI signal sources indoors, the information of the intersection of multiple signal sources is calculated to obtain accurate positioning information. Assuming that the coordinates of the three signal acquisition sources BS1, BS2, and BS3 are (x1, y1), (x2, y2), and (x3, y3), the intersection of the three circles is the position of the mobile node MS, set to (x, y), and the distances from the mobile node to each base station are d1, d2, and d3, respectively. According to the geometric relationship, it can be seen that: Subtract the first two equations from the last equation of the system and use the simplified merging algorithm to get the position coordinates of the mobile node: From the above formula, we can get the position positioning information obtained by the three signal sources, thereby realizing the coordinate evaluation of multiple center points.

[0013] The WIFI signal fingerprint positioning in step 1.2 is specifically as follows: the WIFI signal fingerprint positioning method is divided into two parts: historical positioning information and real-time positioning information. In the historical positioning stage, a number of sampling points are used at a fixed distance in the area to be positioned to form a historical record set L = {L1, L2, ..., Lm}, and each element Li, 1≤i≤m in L contains geographic coordinates and vector value information, geographic coordinates Pi = {Xi, Yi}, WIFI signal strength, RSSI vector Vi = [Vi.1, Vi.2, ..., Vi.j, ..., Vi.n], where Vi.j (1≤j≤n) represents the strength vector received from the jth WIFI signal source AP at the Li position; the k-means clustering algorithm is used to cluster all historical signal sources to generate the final WIFI signal historical record library; during real-time positioning, the real-time measured WIFI signal is compared with the information in the database using a matching algorithm to obtain the final positioning result.

[0014] The topology-assisted WIFI positioning in step 1.3 adopts a trilateral measurement algorithm combined with a topology-assisted discrimination method, including the following steps:

[0015] Step 1.31: GPS coordinates fix the scope of power equipment in an area and record the boundaries of such equipment;

[0016] Step 1.32: Use trilateration to obtain the WiFi location of each point. This location is described according to the principle of unprincipled hashing and has a large uncertainty.

[0017] Step 1.33: Determine the data records in the previous step, remove invalid determination positions outside the boundary limit range, and obtain a valid data set;

[0018] Step 1.34: Arrange the hashed WIIF positions according to the principle of topological connectivity to obtain N ordered data sets, and select the data of the N data sets according to the principle of one-to-many and one-to-one for power equipment, and eliminate the equipment with the arrangement order of many-to-one to obtain the data sequence of the topological principle, which is the accurate and effective power equipment location information;

[0019] Step 1.35: Repeat steps 1.31 to 1.34 for the eliminated location information, and finally all devices are located.

[0020] The data processing of the secondary positioning algorithm based on the received signal strength in step 2 is actually completed in the location server, specifically: the primary positioning of the secondary positioning method based on the received signal strength is to ensure the positioning speed, and to check whether the current network conditions are suitable for positioning based on the primary positioning; the secondary positioning is to reduce the positioning accuracy based on the data of the primary positioning so as to meet the positioning requirements of the system, that is, when a client is connected to the AP, the client will continue to scan the surrounding AP signals and send the strengths of all AP signals that can be detected to the location server. The location server calculates the location information according to the secondary positioning algorithm, and feeds back the client's true location to the client in combination with the AP's location data, so that it can obtain data information.

[0021] The electric power equipment precise positioning algorithm based on two-point positioning in step 3 includes the following steps:

[0022] Step 3.1: RSSI-based positioning technology;

[0023] Step 3.2: Accurate positioning algorithm based on two-point positioning.

[0024] The RSSI-based positioning technology in step 3.1 is specifically as follows: the positioning technology based on received signal strength RSSI ensures that at least three APs simultaneously receive the signal of the radio frequency identification card attached to the power equipment and obtain its RSSI value. The relative distance from the radio frequency identification card to each AP is obtained by the following formula, and then the location information of the power equipment can be determined by fusing it with the absolute coordinates of the AP using the trilateration method or the maximum likelihood estimation method. Where P(d) and P(d0) represent the signal strength at distances APd and d0, respectively; P(d) is the actual received power; P(d0) is the received power at the reference distance d0; η is the path loss coefficient; ξ δ is a zero-mean Gaussian random variable with standard deviation δ.

[0025] The precise positioning algorithm based on two-point positioning in step 3.2 comprises the following steps:

[0026] Step 3.21: First, a sampling point is marked between AP1 and AP2 in the GIS map. Then, the radio frequency identification card attached to the power equipment sends a radio frequency signal at the corresponding location point in the actual complex map. AP1 and AP2 receive the signal strength values ​​RSS1 and RSS2 of the identification card respectively. At the same time, the coordinate value information of the sampling point marked in the GIS map is sent to the database as a sample point. The next time AP1 and AP2 receive the signal strength value of the identification card and compare it with the signal strength value in the database, the best matching algorithm is used to calculate the mean square error of the signal strength to obtain the one with the smallest result. It is then determined that the coordinates of the location point of the power equipment are the coordinates of the location point of the sample point in the database (x a ,y a );

[0027] Step 3.22: Use the ratio of the signal strengths of the radio frequency identification cards attached to the power equipment received by the adjacent APs as the calculation standard, and calculate the ratio of the distances between the power equipment and the adjacent APs according to the ratio of the signal strengths. The distances between the APs are known, so the coordinates of the power equipment attached can be calculated by the distance ratio and the coordinates of the APs in the database; the coordinates of AP1 and AP2 are known to be (x1, y1), (x2, y2), the power equipment is (x, y), the distance between AP1 and AP2 is known to be d, d1 and d2 are the distances from the power equipment to AP1 and AP2 respectively, then: Let R be the ratio of d1 to d2, then: You can get: The above formula can be used to obtain the coordinates of the power equipment (x b ,y b );

[0028] Step 3.23: Finally, take the arithmetic mean of the coordinate values ​​obtained in step 3.21 and step 3.22. The final (x, y) is the coordinate value of the power equipment.

[0029] Beneficial effects of the present invention: The present invention is a wifi multi-point precise positioning method based on the operation, distribution and dispatching through-communication technology. During use, the present invention corrects the positioning error by the WIFI multi-point precise positioning algorithm and the topology auxiliary discrimination method with the multi-point center point approximation evaluation method, realizes the multi-point positioning and topology relationship auxiliary discrimination of WIFI positioning information, and realizes efficient and accurate GIS positioning information collection through the WIFI positioning information determined by the method; the present invention solves the problems of electromagnetic wave transmission and non-line-of-sight between AP and radio frequency identification card in the positioning technology based on received signal strength RSSI through a secondary positioning algorithm based on received signal strength and an electric power equipment precise positioning algorithm based on two-point positioning, and also solves the problems of large number of APs and networking difficulties, thereby realizing the precision of electric power equipment positioning information and the precision of equipment topology relationship, improving the credibility and accuracy of data, realizing the data interaction between positioning data and power grid GIS platform, and realizing high-precision positioning of electric power equipment in GIS in operation, distribution and dispatching work; the present invention has the advantages of being more convenient, having higher collection accuracy and accurate positioning information. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the trilateration method of the present invention.

[0031] Figure 2 This is a flow chart of the secondary positioning method of the present invention.

[0032] Figure 3 This is a schematic diagram of the RSSI positioning principle of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described below in conjunction with the accompanying drawings.

[0034] Example 1

[0035] like Figure 1-3 As shown, a WiFi multi-point precise positioning method based on the deployment and coordination technology, the method comprises the following steps:

[0036] Step 1: Use WIFI multi-point precise positioning algorithm and topology-assisted identification method to correct human errors;

[0037] Step 2: Use a secondary positioning algorithm based on received signal strength to achieve accurate positioning of power grid GIS equipment;

[0038] In this embodiment, data processing of the secondary positioning algorithm based on received signal strength is actually completed in the location server, specifically: the primary positioning of the secondary positioning method based on received signal strength is to ensure the positioning speed, and to check whether the current network conditions are suitable for positioning based on the primary positioning; the secondary positioning is performed on the basis of the data of the primary positioning to reduce the positioning accuracy so as to meet the positioning requirements of the system, that is, when a client is connected to an AP, the client will continue to scan the surrounding AP signals and send the strengths of all AP signals that can be detected to the location server. The location server calculates the location information based on the secondary positioning algorithm, and feeds back the client's true location to the client in combination with the AP's location data, so that it can obtain data information.

[0039] Step 3: Use the power equipment precise positioning algorithm based on two-point positioning to realize the positioning measurement of the power equipment coordinates.

[0040] The present invention is a wifi multi-point precise positioning method based on the operation, distribution and dispatching through-communication technology. In use, the present invention corrects the positioning error by using the WIFI multi-point precise positioning algorithm and the topology auxiliary discrimination method with the multi-point center point approximation evaluation method, realizes the multi-point positioning and topology relationship auxiliary discrimination of WIFI positioning information, and realizes efficient and accurate GIS positioning information collection through the WIFI positioning information determined by the method; the present invention solves the problems of electromagnetic wave transmission and non-line-of-sight between AP and radio frequency identification card in the positioning technology based on received signal strength RSSI through the secondary positioning algorithm based on received signal strength and the power equipment precise positioning algorithm based on two-point positioning, and also solves the problems of large number of APs and networking difficulties, thereby realizing the precision of power equipment positioning information and the precision of equipment topology relationship, improving the credibility and accuracy of data, realizing the data interaction between positioning data and power grid GIS platform, and realizing high-precision positioning of power equipment in GIS in operation, distribution and dispatching work; the present invention has the advantages of being more convenient, having higher collection accuracy and accurate positioning information.

[0041] Example 2

[0042] like Figure 1-3 As shown, a WiFi multi-point precise positioning method based on the deployment and coordination technology, the method comprises the following steps:

[0043] Step 1: Use WIFI multi-point precise positioning algorithm and topology-assisted identification method to correct human errors;

[0044] In this embodiment, a WIFI multi-point precise positioning algorithm and a topology-assisted identification method are used, which specifically includes the following steps:

[0045] Step 1.1: Trilateration algorithm;

[0046] Specifically, when there are multiple WIFI signal sources indoors, the information of the intersection of multiple signal sources is calculated to obtain accurate positioning information. Assuming that the coordinates of the three signal sources BS1, BS2, and BS3 are (x1, y1), (x2, y2), and (x3, y3), the intersection of the three circles is the position of the mobile node MS, set to (x, y), and the distances from the mobile node to each base station are d1, d2, and d3, respectively. According to the geometric relationship, it can be seen that: Subtract the first two equations from the last equation of the system and perform a simplified merging algorithm to obtain the position coordinates of the mobile node: From the above formula, we can get the position information obtained by the three signal sources, thereby realizing the coordinate evaluation of multiple center points.

[0047] Step 1.2: WIFI signal fingerprint positioning;

[0048] Specifically, the WIFI signal fingerprint positioning method is divided into two parts: historical positioning information and real-time positioning information. In the historical positioning stage, a number of sampling points are used at a fixed distance in the area to be positioned to form a historical record set L = {L1, L2, ..., Lm}. Each element Li, 1≤i≤m in L contains geographic coordinates and vector value information, geographic coordinates Pi = {Xi, Yi}, WIFI signal strength, RSSI vector Vi = [Vi.1, Vi.2, ..., Vi.j, ..., Vi.n], where Vi.j (1≤j≤n) represents the strength vector received from the jth WIFI signal source AP at the Li position; the k-means clustering algorithm is used to cluster all historical signal sources to generate the final WIFI signal historical record library (fingerprint information); during real-time positioning, the real-time measured WIFI signal is compared with the information in the database using a matching algorithm to obtain the final positioning result.

[0049] Step 1.3: Topology-assisted Wi-Fi positioning.

[0050] Specifically, the trilateral measurement algorithm is combined with the topology-assisted discrimination method, including the following steps:

[0051] Step 1.31: GPS coordinates fix the scope of power equipment in an area and record the boundaries of such equipment;

[0052] Step 1.32: Use trilateration to obtain the WiFi location of each point. This location is described according to the principle of unprincipled hashing and has a large uncertainty.

[0053] Step 1.33: Determine the data records in the previous step, remove invalid determination positions outside the boundary limit range, and obtain a valid data set;

[0054] Step 1.34: Arrange the hashed WIIF positions according to the principle of topological connectivity to obtain N ordered data sets, and select the data of the N data sets according to the principle of one-to-many and one-to-one for power equipment, and eliminate the equipment with the arrangement order of many-to-one to obtain the data sequence of the topological principle, which is the accurate and effective power equipment location information;

[0055] Step 1.35: Repeat steps 1.31 to 1.34 for the eliminated location information, and finally all devices are located.

[0056] Step 2: Use a secondary positioning algorithm based on received signal strength to achieve accurate positioning of power grid GIS equipment;

[0057] Step 3: Use the power equipment precise positioning algorithm based on two-point positioning to realize the positioning measurement of the power equipment coordinates.

[0058] In this embodiment, a precise positioning algorithm for electric power equipment based on two-point positioning is adopted, which includes the following steps:

[0059] Step 3.1: RSSI-based positioning technology;

[0060] Specifically, the positioning technology based on received signal strength RSSI ensures that at least three APs receive the signal of the RFID card attached to the power equipment at the same time and obtain its RSSI value. The relative distance from the RFID card to each AP is obtained by the following formula, and then the location information of the power equipment can be determined by fusing it with the absolute coordinates of the AP using trilateration or maximum likelihood estimation. Where P(d) and P(d0) represent the signal strength at distances APd and d0, respectively; P(d) is the actual received power; P(d0) is the received power at the reference distance d0; η is the path loss coefficient; ξ δ is a zero-mean Gaussian random variable with standard deviation δ.

[0061] Step 3.2: Accurate positioning algorithm based on two-point positioning.

[0062] In this embodiment, since the RSSI-based positioning technology makes the transmission of electromagnetic waves in a complex environment very different from that on the ground, the positioning error of the positioning technology based on the received signal strength RSSI increases; in addition, some large equipment in a complex environment makes the AP and the radio frequency identification card non-line-of-sight, which will greatly affect the positioning error of the positioning technology; at the same time, the algorithm must ensure that at least three APs simultaneously receive the signal of the radio frequency identification card attached to the same power equipment, which greatly increases the number of APs in a complex environment. Therefore, the present invention proposes an improved precise positioning algorithm based on two-point positioning for the above method, including the following steps:

[0063] Step 3.21: First, a sampling point is marked between AP1 and AP2 in the GIS map. Then, the radio frequency identification card attached to the power equipment sends a radio frequency signal at the corresponding location point in the actual complex map. AP1 and AP2 receive the signal strength values ​​RSS1 and RSS2 of the identification card respectively. At the same time, the coordinate value information of the sampling point marked in the GIS map is sent to the database as a sample point. The next time AP1 and AP2 receive the signal strength value of the identification card and compare it with the signal strength value in the database, the best matching algorithm is used to calculate the mean square error of the signal strength to obtain the one with the smallest result. It is then determined that the coordinates of the location point of the power equipment are the coordinates of the location point of the sample point in the database (x a ,y a );

[0064] Step 3.22: Use the ratio of the signal strengths of the radio frequency identification cards attached to the power equipment received by the adjacent APs as the calculation standard, and calculate the ratio of the distances between the power equipment and the adjacent APs according to the ratio of the signal strengths. The distances between the APs are known, so the coordinates of the power equipment attached can be calculated by the distance ratio and the coordinates of the APs in the database; the coordinates of AP1 and AP2 are known to be (x1, y1), (x2, y2), the power equipment is (x, y), the distance between AP1 and AP2 is known to be d, d1 and d2 are the distances from the power equipment to AP1 and AP2 respectively, then: Let R be the ratio of d1 to d2, then: You can get: The above formula can be used to obtain the coordinates of the power equipment (x b ,y b );

[0065] Step 3.23: Finally, take the arithmetic mean of the coordinate values ​​obtained in step 3.21 and step 3.22. The final (x, y) is the coordinate value of the power equipment.

[0066] The present invention is a wifi multi-point precise positioning method based on the operation, distribution and dispatching through-communication technology. In use, the present invention corrects the positioning error by using the WIFI multi-point precise positioning algorithm and the topology auxiliary discrimination method with the multi-point center point approximation evaluation method, realizes the multi-point positioning and topology relationship auxiliary discrimination of WIFI positioning information, and realizes efficient and accurate GIS positioning information collection through the WIFI positioning information determined by the method; the present invention solves the problems of electromagnetic wave transmission and non-line-of-sight between AP and radio frequency identification card in the positioning technology based on received signal strength RSSI through the secondary positioning algorithm based on received signal strength and the power equipment precise positioning algorithm based on two-point positioning, and also solves the problems of large number of APs and networking difficulties, thereby realizing the precision of power equipment positioning information and the precision of equipment topology relationship, improving the credibility and accuracy of data, realizing the data interaction between positioning data and power grid GIS platform, and realizing high-precision positioning of power equipment in GIS in operation, distribution and dispatching work; the present invention has the advantages of being more convenient, having higher collection accuracy and accurate positioning information.

Claims

1. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology, characterized by: The method comprises the following steps: Step 1: Use WIFI multi-point precise positioning algorithm and topology-assisted identification method to correct human errors; Step 2: Use a secondary positioning algorithm based on received signal strength to achieve accurate positioning of power grid GIS equipment; Step 3: Use the power equipment precise positioning algorithm based on two-point positioning to realize the positioning measurement of the power equipment coordinates.

2. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 1, characterized in that: The WIFI multi-point precise positioning algorithm and topology-assisted discrimination method in step 1 specifically include the following steps: Step 1.1: Trilateration algorithm; Step 1.2: WIFI signal fingerprint positioning; Step 1.3: Topology-assisted Wi-Fi positioning.

3. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 2, characterized in that: The trilateral measurement algorithm in step 1.1 is specifically as follows: when there are multiple WIFI signal sources indoors, the information of the intersection of multiple signal sources is calculated to obtain accurate positioning information. Assuming that the coordinates of the three signal acquisition sources BS1, BS2, and BS3 are (x1, y1), (x2, y2), and (x3, y3), the intersection of the three circles is the position of the mobile node MS, set to (x, y), and the distances from the mobile node to each base station are d1, d2, and d3, respectively. According to the geometric relationship, it can be seen that: Subtract the first two equations from the last equation of the system and perform a simplified merging algorithm to obtain the position coordinates of the mobile node: From the above formula, we can get the position information obtained by the three signal sources, thereby realizing the coordinate evaluation of multiple center points.

4. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 2, characterized in that: The WIFI signal fingerprint positioning in step 1.2 is specifically as follows: the WIFI signal fingerprint positioning method is divided into two parts: historical positioning information and real-time positioning information. In the historical positioning stage, a number of sampling points are used at a fixed distance in the area to be positioned to form a historical record set L = {L1, L2, ..., Lm}, and each element Li, 1≤i≤m in L contains geographic coordinates and vector value information, geographic coordinates Pi = {Xi, Yi}, WIFI signal strength, RSSI vector Vi = [Vi.1, Vi.2, ..., Vi.j, ..., Vi.n], where Vi.j (1≤j≤n) represents the strength vector received from the jth WIFI signal source AP at the Li position; the k-means clustering algorithm is used to cluster all historical signal sources to generate the final WIFI signal historical record library; during real-time positioning, the real-time measured WIFI signal is compared with the information in the database using a matching algorithm to obtain the final positioning result.

5. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 2, characterized in that: The topology-assisted WIFI positioning in step 1.3 adopts a trilateral measurement algorithm combined with a topology-assisted discrimination method, including the following steps: Step 1.31: GPS coordinates fix the scope of power equipment in an area and record the boundaries of such equipment; Step 1.32: Use trilateration to obtain the WiFi location of each point. This location is described according to the principle of unprincipled hashing and has a large uncertainty. Step 1.33: Determine the data records in the previous step, remove invalid determination positions outside the boundary limit range, and obtain a valid data set; Step 1.34: Arrange the hashed WIIF positions according to the principle of topological connectivity to obtain N ordered data sets, and select the data of the N data sets according to the principle of one-to-many and one-to-one for power equipment, and eliminate the equipment with the arrangement order of many-to-one to obtain the data sequence of the topological principle, which is the accurate and effective power equipment location information; Step 1.35: Repeat steps 1.31 to 1.34 for the eliminated location information, and finally all devices are located.

6. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 1, characterized in that: The electric power equipment precise positioning algorithm based on two-point positioning in step 3 includes the following steps: Step 3.1: RSSI-based positioning technology; Step 3.2: Accurate positioning algorithm based on two-point positioning.

7. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 6, characterized in that: The RSSI-based positioning technology in step 3.1 is specifically as follows: the positioning technology based on received signal strength RSSI ensures that at least three APs simultaneously receive the signal of the radio frequency identification card attached to the power equipment and obtain its RSSI value. The relative distance from the radio frequency identification card to each AP is obtained by the following formula, and then the location information of the power equipment can be determined by fusing it with the absolute coordinates of the AP using the trilateration method or the maximum likelihood estimation method. Where P(d) and P(d0) represent the signal strength at distances APd and d0, respectively; P(d) is the actual received power; P(d0) is the received power at the reference distance d0; η is the path loss coefficient; ξ δ is a zero-mean Gaussian random variable with standard deviation δ.

8. A WiFi multi-point precise positioning method based on the camping, deployment and coordination technology as claimed in claim 6, characterized in that: The precise positioning algorithm based on two-point positioning in step 3.2 comprises the following steps: Step 3.21: First, a sampling point is marked between AP1 and AP2 in the GIS map. Then, the radio frequency identification card attached to the power equipment sends a radio frequency signal at the corresponding location point in the actual complex map. AP1 and AP2 receive the signal strength values ​​RSS1 and RSS2 of the identification card respectively. At the same time, the coordinate value information of the sampling point marked in the GIS map is sent to the database as a sample point. The next time AP1 and AP2 receive the signal strength value of the identification card and compare it with the signal strength value in the database, the best matching algorithm is used to calculate the mean square error of the signal strength to obtain the one with the smallest result. It is then determined that the coordinates of the location point of the power equipment are the coordinates of the location point of the sample point in the database (x a ,y a ); Step 3.22: Use the ratio of the signal strengths of the radio frequency identification cards attached to the power equipment received by the adjacent APs as the calculation standard, and calculate the ratio of the distances between the power equipment and the adjacent APs according to the ratio of the signal strengths. The distances between the APs are known, so the coordinates of the power equipment attached can be calculated by the distance ratio and the coordinates of the APs in the database; the coordinates of AP1 and AP2 are known to be (x1, y1), (x2, y2), the power equipment is (x, y), the distance between AP1 and AP2 is known to be d, d1 and d2 are the distances from the power equipment to AP1 and AP2 respectively, then: Let R be the ratio of d1 to d2, then: You can get: The above formula can be used to obtain the power equipment coordinates (x b ,y b ); Step 3.23: Finally, take the arithmetic mean of the coordinate values ​​obtained in step 3.21 and step 3.

22. The final (x, y) is the coordinate value of the power equipment.

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