CN114363800A - Triangular positioning method based on CDR data - Google Patents
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- H04W4/02—Services making use of location information
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
Abstract
The invention discloses a triangulation location method based on CDR data, which comprises the following steps: acquiring third MR data with user information and a front-back switching chain relation by using the CDR data and the XDR data; constructing a user triangular distance positioning structure by using the third MR data; positioning the mobile user in real time by utilizing a triangular distance positioning structure; and the third MR data is acquired through multilevel user information backfill. The method comprises the steps of backfilling user information of first MR data to obtain second MR data, and then associating CDR data with the second MR data according to the same user and time sequence to obtain third MR data; by using the user information, the forward and backward switching chain relation and the RSRP information contained in the third MR data, the problem that the existing MR data cannot be triangulated under the condition that no 2 or more than 2 non-co-station adjacent regions exist is solved.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a triangulation positioning method based on CDR data.
Background
The signaling data and MR data combined correlation analysis based on operators, the product scheme for providing real-time and accurate positioning service for users is more and more mature in the market, and the positioning accuracy can reach 100M range from the original method of performing work parameter positioning with the accuracy of only 400M through single signaling data to the MR data-based high-accuracy fingerprint positioning.
However, fingerprint positioning has certain limitations, and is not suitable for situations such as a small base station density, an island station without a neighboring cell, less agps fingerprint data and the like in a remote area, and fingerprint positioning cannot be performed. The whole fingerprint location rate is only about 80%.
In order to more accurately locate the remaining 20% of data that cannot be located with fingerprints, triangulation is often used. In the actual calculation process, because the distance calculation error between the positioning point and the base station is large, the positioning point can not be calculated accurately, so that the overall accuracy of triangulation is low, and the triangulation can not be performed under the condition that the to-be-positioned point does not have an adjacent cell and belongs to the isolated station.
As shown in fig. 1, there are three non-collinear base stations a, B, C and an unknown terminal D on the plane, and the distances from the three base stations to the terminal D are measured as R1, R2 and R3, so that three intersecting circles can be drawn by taking the coordinates of the three base stations as the center of a circle and the distances from the three base stations to the unknown terminal as the radii, and as shown in fig. 1, the unknown node coordinates are the intersection points of the three circles. In actual measurement, due to measurement errors, three circles do not intersect at a point, but intersect at a region, as shown in fig. 2. In this case, the general solution is to solve using the least squares method.
Establishing an equation to obtain an equation set of the formula (1):
subtracting the nth equation from the first n-1 equations to obtain a matrix representation of equation (2):
AX＝b (2)
wherein:
solving it with least square
Solving the upper equation by a least square method to obtain an equation (3):
X＝(ATA)-1ATb (3)
however, the conventional triangulation method still has disadvantages, and has more limitations: the method comprises the following steps of (1) recording adjacent regions which need two or more different stations with positioning MR; the TA value of the main area is required to be known and is used for calculating the distance from the main area; providing an rsrp value of an adjacent cell for calculating the distance between a main area and the adjacent cell; the main area warp and weft values need to be provided; the warp and weft values of the adjacent regions need to be provided; the accuracy depends extremely on the distance calculation of the second and third stripes; the distance between the MR track point and the main area is calculated according to a TA value which is an integer, 1 TA is approximately equal to 78 meters, the distance precision obtained by converting the TA value fluctuates between 0 and 78 meters, the effective rate of the TA value in actual data is low, and 100% of each piece of MR data does not have the TA value. The distance between the MR track point and the adjacent region is estimated according to an ideal propagation attenuation model of the signal, and the estimation precision of the distance is greatly influenced by the influence factors such as waveguide effect, blocking of buildings, weather change and the like.
Therefore, the existing triangulation location method has too many limiting conditions, is difficult to realize, and cannot ensure the location precision.
Disclosure of Invention
In order to solve the problems, a triangulation method based on CDR data is provided, wherein user information backfill is carried out on first MR data to obtain second MR data, and then the CDR data are associated with the second MR data according to the same user and time sequence to obtain third MR data; by using the user information, the forward and backward switching chain relation and the RSRP information contained in the third MR data, the problem that the existing MR data cannot be triangulated under the condition that no 2 or more than 2 non-co-station adjacent regions exist is solved. By adopting the switching base station information and the RSRP information contained in the second CDR data to carry out mutual verification on the RSRP information of the adjacent region in the third MR data, the confidence coefficient of the RSRP value is improved, the gross error of the RSRP value is eliminated, the fluctuation of the RSRP value caused by external environmental factors is effectively identified, and the precision of triangulation is improved.
A triangulation method based on CDR data, comprising:
step 100, acquiring third MR data with user information and a front-back switching chain relation by using CDR data and XDR data;
200, constructing a user triangular distance positioning structure by using the third MR data;
300, positioning a mobile user in real time by using the triangular distance positioning structure;
and acquiring the third MR data through multilevel user information backfill.
With reference to the CDR data-based triangulation method of the present invention, in a first possible implementation, the step 100 includes:
With reference to the first possible implementation manner and the second possible implementation manner of the present invention, in a second possible implementation manner, the step 110 includes:
and step 112, converging and connecting the first MR data and the core network XDR signaling data in parallel.
With reference to the second possible implementation manner of the present invention, in a third possible implementation manner, the step 112 includes:
and step 1122, storing the user information fields imsi, mdn, imei in the second MR data in a manner of a HIVE table.
With reference to the first possible implementation manner of the present invention, in a fourth possible implementation manner, the step 120 includes:
and step 122, converging and connecting the first CDR data and the core network XDR signaling data in parallel to acquire second CDR data with user information.
With reference to the fourth possible implementation manner of the present invention, in a fifth possible implementation manner, the step 122 includes:
and 1222, storing the user information fields imsi, mdn, imei in the second CDR data in a HIVE table manner.
With reference to the first possible implementation manner of the present invention, in a sixth possible implementation manner, the step 130 includes:
In a seventh possible implementation manner, with reference to the CDR data-based triangulation method of the present invention, the step 200 includes:
and 250, constructing a user triangular distance positioning structure by using the non co-station distance.
With reference to the CDR data-based triangulation method of the present invention, in an eighth possible implementation manner, the step 200 further includes:
and 290, calculating the triangulation distance by using the average RSRP value.
With reference to the eighth possible implementation manner of the present invention, in a ninth possible implementation manner, the step 280 further includes:
The triangular positioning method based on the CDR data is implemented, the user information backfill is carried out on the first MR data to obtain the second MR data, and then the CDR data are associated with the second MR data according to the same user and time sequence to obtain the third MR data; by using the user information, the forward and backward switching chain relation and the RSRP information contained in the third MR data, the problem that the existing MR data cannot be triangulated under the condition that no 2 or more than 2 non-co-station adjacent regions exist is solved. By adopting the switching base station information and the RSRP information contained in the second CDR data to carry out mutual verification on the RSRP information of the adjacent region in the third MR data, the confidence coefficient of the RSRP value is improved, the gross error of the RSRP value is eliminated, the fluctuation of the RSRP value caused by external environmental factors is effectively identified, and the precision of triangulation is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of a prior art triangulation first embodiment;
FIG. 2 is a schematic diagram of a second embodiment of prior art triangulation;
FIG. 3 is a first schematic view of the triangulation of the present invention;
FIG. 4 is a second schematic view of the triangulation of the present invention;
FIG. 5 is a schematic diagram of a first embodiment of a CDR data based triangulation method of the present invention;
FIG. 6 is a schematic diagram of a second embodiment of a CDR data-based triangulation method according to the present invention;
FIG. 7 is a schematic diagram of a third embodiment of a CDR data-based triangulation method according to the present invention;
FIG. 8 is a schematic diagram of a fourth embodiment of a CDR data-based triangulation method of the present invention;
FIG. 9 is a diagram illustrating a fifth embodiment of CDR data based triangulation method according to the present invention;
FIG. 10 is a schematic diagram of a sixth embodiment of a CDR data based triangulation method of the present invention;
FIG. 11 is a schematic diagram of a seventh embodiment of a CDR data based triangulation method of the present invention;
FIG. 12 is a schematic diagram of an eighth embodiment of a CDR data-based triangulation method of the present invention;
FIG. 13 is a schematic diagram of a ninth embodiment of the CDR data based triangulation method of the present invention;
FIG. 14 is a schematic diagram of a tenth embodiment of the CDR data based triangulation method of the present invention;
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Other embodiments, which can be derived by one of ordinary skill in the art from the embodiments given herein without any creative effort, shall fall within the protection scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The existing triangulation location method has too many limiting conditions, is difficult to realize and cannot ensure the location precision.
In order to solve the above problems, a triangulation method based on CDR data is proposed.
By adopting the switching base station information and the RSRP information contained in the CDR data to carry out mutual verification on the RSRP information of the adjacent regions in the MR data, the confidence coefficient of the RSRP value is improved, the gross error of the RSRP value is eliminated, the fluctuation of the RSRP value caused by external environment factors is effectively identified, and the precision of triangulation is improved.
Fig. 5 shows a schematic diagram of a CDR data-based triangulation method according to a first embodiment of the present invention, including:
step 100, acquiring third MR data with user information and a front-back switching chain relation by using CDR data and XDR data; 200, constructing a user triangular distance positioning structure by using the third MR data; 300, positioning the mobile user in real time by utilizing a triangular distance positioning structure; and the third MR data is acquired through multilevel user information backfill.
The method comprises the steps of backfilling user information of first MR data to obtain second MR data, and then associating CDR data with the second MR data according to the same user and time sequence to obtain third MR data; by using the user information, the forward and backward switching chain relation and the RSRP information contained in the third MR data, the problem that the existing MR data cannot be triangulated under the condition that no 2 or more than 2 non-co-station adjacent regions exist is solved.
In a preferred embodiment, as shown in fig. 6, fig. 6 is a schematic diagram of a second embodiment of CDR data-based triangulation method according to the present invention, and step 100 includes:
In general:
the wireless MR data is measurement data reported periodically by a cell, and the period is generally set to 10 s. The measured data includes:
base station information: enodbid, cellid;
user equipment information: enb 1apid, mmegoroupid, mmeco, mmes1 apid.
The wireless CDR data, i.e., call detail records, describes the overall process of call connection. The parameters recorded in the CDR data are from the original signaling message data. In LTE, an end user counts as a call every time a service occurs. Therefore, the inside includes:
the accurate time of each service occurrence of the user;
information of base station where service occurs: the group consisting of enodbid, cellid,
user equipment information: enb 1apid, mmegoroupid, mmeco, mmes1 apid;
switching chain information: cdr _ start time, ho _ first _ src _ bid, ho _ first _ src _ lid, ho _ last _ src _ lid, ho _ first _ rsrp, ho _ last _ rsrp.
The core network XDR data is also called signaling data, which includes:
base station information: enodbid, cellid;
user equipment information: enb 1apid, mmegoroupid, mmeco, mmes1 apid;
user information: imsi, mdn, imei.
Preferably, as shown in fig. 7, fig. 7 is a schematic diagram of a third embodiment of the CDR data-based triangulation method according to the present invention, and step 110 includes:
In a preferred embodiment, as shown in fig. 8, fig. 8 is a schematic diagram of a fourth embodiment of CDR data-based triangulation method according to the present invention, and step 112 includes:
Preferably, step 120 comprises: referring to fig. 9, fig. 9 is a schematic diagram of a fifth embodiment of the CDR data-based triangulation method of the present invention, step 121, accessing wireless first CDR data and core network XDR signaling data by using kafka or flink; and step 122, converging and connecting the first CDR data and the core network XDR signaling data in parallel to acquire second CDR data with user information.
In a preferred embodiment, as shown in fig. 10, fig. 10 is a schematic diagram of a sixth embodiment of CDR data-based triangulation method in the present invention, and step 122 includes: step 1221, backfilling user information fields imsi, mdn, imei in the core network XDR signaling data into the first CDR data, and acquiring second CDR data with user information; and 1222, storing the user information fields imsi, mdn, imei in the second CDR data in a HIVE table manner.
Preferably, as shown in fig. 11, fig. 11 is a schematic diagram of a seventh embodiment of the CDR data-based triangulation method in the present invention, and step 130 includes: step 131, backfilling the switching chain information CDR _ start time, ho _ first _ src _ bid, ho _ last _ src _ bid, ho _ first _ rsrp, and ho _ last _ rsrp in the second CDR data into the second MR data to obtain third MR data; step 132, storing the switching chain information cdr _ start time, ho _ first _ src _ bid, ho _ first _ src _ rd, ho _ last _ src _ bid, ho _ first _ rsrp, and ho _ last _ rsrp in the third MR data in a HIVE table manner.
In a preferred embodiment, as shown in fig. 12, fig. 12 is a schematic diagram of an eighth embodiment of a CDR data-based triangulation method according to the present invention, and step 200 includes: step 210, acquiring the number of the non-co-station adjacent cells in the third MR data, and if the number of the non-co-station adjacent cells is less than two, performing the next step; step 220, obtaining the CDR associated information of the second CDR data corresponding to the user information through the user information in the third MR data; step 230, obtaining second CDR data which are not co-sited with the main service cell in the latest time sequence through the CDR association information; step 240, extracting longitude and latitude information and RSRP information of at least two pieces of second CDR data to calculate a non-co-station distance; and 250, constructing a user triangular distance positioning structure by using the non co-station distance.
Referring to fig. 3, fig. 3 is a first schematic diagram of triangulation according to the present invention, which utilizes multiple pieces of second CDR data in the same third user MR data neighbor time sequence, wherein the base station and RSRP information contained in the second CDR data can be used to construct the conditions of two or more than two different co-station neighbor cells of triangulation, so as to implement triangulation.
Preferably, as shown in fig. 13, fig. 13 is a schematic diagram of a ninth embodiment of the CDR data-based triangulation method in the present invention, and step 200 further includes: step 260, acquiring the number of the non-co-station adjacent cells in the third MR data, and if the number of the non-co-station adjacent cells is more than or equal to two, performing the next step; step 270, acquiring multiple pieces of base station information overlapped in the second CDR data and the third MR data; step 280, obtaining average RSRP values of a plurality of base stations; and 290, calculating the triangulation distance by using the average RSRP value.
In a preferred embodiment, as shown in fig. 14, fig. 14 is a schematic diagram of a tenth embodiment of the CDR data-based triangulation method in the present invention, and step 280 further includes: step 281, performing mutual verification on the RSRP value of the second CDR data and the RSRP value in the third MR data; step 282, if the difference between the RSRP value of the second CDR data and the RSRP value of the third MR data is smaller than the threshold range, obtaining an average RSRP value by averaging.
If the third MR data includes a plurality of non-co-sited neighbors, as shown in fig. 4, fig. 4 is a second schematic diagram of the triangulation positioning of the present invention, and the base stations included in the plurality of second CDR data of the user coincide with the plurality of base stations in the neighbor of the third MR data in a shorter time.
Then, the RSRP information of the base station in the part can be extracted from the second CDR data, the RSRP information and the RSRP value of the neighboring cell in the third MR data are mutually verified, if the difference range is within the threshold range, the verification is considered to be qualified, a new RSRP value of the neighboring cell is obtained by averaging, the distance between the new RSRP value and the neighboring cell is calculated according to the new RSRP value and the propagation model, otherwise, the information of the neighboring cell is discarded, and the triangular positioning is not involved.
The advantage of doing so can effectually reduce the influence of external environment factor to the RSRP value, rejects the gross error of RSRP value, improves the precision of distance calculation.
The triangular positioning method based on the CDR data is implemented, the user information backfill is carried out on the first MR data to obtain the second MR data, and then the CDR data are associated with the second MR data according to the same user and time sequence to obtain the third MR data; by using the user information, the forward and backward switching chain relation and the RSRP information contained in the third MR data, the problem that the existing MR data cannot be triangulated under the condition that no 2 or more than 2 non-co-station adjacent regions exist is solved. By adopting the switching base station information and the RSRP information contained in the second CDR data to carry out mutual verification on the RSRP information of the adjacent region in the third MR data, the confidence coefficient of the RSRP value is improved, the gross error of the RSRP value is eliminated, the fluctuation of the RSRP value caused by external environmental factors is effectively identified, and the precision of triangulation is improved.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent replacements, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A triangulation method based on CDR data, comprising:
step 100, acquiring third MR data with user information and a front-back switching chain relation by using CDR data and XDR data;
200, constructing a user triangular distance positioning structure by using the third MR data;
300, positioning a mobile user in real time by using the triangular distance positioning structure;
and acquiring the third MR data through multilevel user information backfill.
2. The method of claim 1, wherein the step 100 comprises:
step 110, performing correlation between the first MR data and core network XDR signaling data to backfill user information, and acquiring second MR data with user information;
step 120, performing correlation between the first CDR data and core network XDR signaling data to backfill user information, and acquiring second CDR data with user information;
step 130, correlating the second CDR data and the second MR data of the same user according to a time sequence, and backfilling the handover chain information of the second CDR data to the second MR data to obtain third MR data having user information and a front-back handover chain relationship.
3. The method of claim 2, wherein the step 110 comprises:
step 111, accessing wireless first MR data and core network XDR signaling data by adopting kafka or flink;
and step 112, converging and connecting the first MR data and the core network XDR signaling data in parallel.
4. The method of claim 3, wherein the step 112 comprises:
step 1121, backfilling user information fields imsi, mdn, imei in the core network XDR signaling data into the first MR data, and acquiring second MR data with user information;
and step 1122, storing the user information fields imsi, mdn, imei in the second MR data in a manner of a HIVE table.
5. The method of claim 2, wherein the step 120 comprises:
step 121, accessing wireless first CDR data and core network XDR signaling data by adopting kafka or flink;
and step 122, converging and connecting the first CDR data and the core network XDR signaling data in parallel to acquire second CDR data with user information.
6. The method of claim 5, wherein the step 122 comprises:
step 1221, backfilling user information fields imsi, mdn, imei in the core network XDR signaling data into the first CDR data, and acquiring second CDR data with user information;
and 1222, storing the user information fields imsi, mdn, imei in the second CDR data in a HIVE table manner.
7. The method of claim 2, wherein the step 130 comprises:
step 131, backfilling the switching chain information CDR _ start time, ho _ first _ src _ bid, ho _ last _ src _ bid, ho _ first _ rsrp, and ho _ last _ rsrp in the second CDR data into the second MR data to obtain third MR data;
step 132, storing the switching chain information cdr _ start time, ho _ first _ src _ bid, ho _ first _ src _ rd, ho _ last _ src _ bid, ho _ first _ rsrp, and ho _ last _ rsrp in the third MR data in a HIVE table manner.
8. The method of claim 1, wherein the step 200 comprises:
step 210, acquiring the number of non-co-located neighbor cells in the third MR data, wherein if the number of non-co-located neighbor cells is less than two, performing the next step;
step 220, obtaining CDR associated information of the second CDR data corresponding to the user information through the user information in the third MR data;
step 230, obtaining second CDR data which is not co-sited with the primary serving cell in the latest time sequence according to the CDR association information;
step 240, extracting longitude and latitude information and RSRP information of at least two pieces of second CDR data to calculate a non-co-station distance;
and 250, constructing a user triangular distance positioning structure by using the non co-station distance.
9. The method of claim 8, wherein the step 200 further comprises:
step 260, acquiring the number of the non-co-sited neighbor cells in the third MR data, wherein if the number of the non-co-sited neighbor cells is greater than or equal to two, the next step is performed;
step 270, acquiring multiple pieces of base station information overlapped in the second CDR data and the third MR data;
step 280, obtaining average RSRP values of the plurality of base stations;
and 290, calculating the triangulation distance by using the average RSRP value.
10. The CDR data-based triangulation method according to claim 9, wherein said step 280 further comprises:
step 281, performing mutual verification on the RSRP value of the second CDR data and the RSRP value in the third MR data;
step 282, if the difference between the RSRP value of the second CDR data and the RSRP value of the third MR data is smaller than the threshold range, obtaining the average RSRP value by averaging.
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| 徐珊珊;余健;王计斌: ""基于OTT与MR数据的自适应WKNN室外定位方法"", 《江苏通信》 * |
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