CN112235807B - Networking method, device, equipment and medium of TDOA monitoring system - Google Patents
Networking method, device, equipment and medium of TDOA monitoring system Download PDFInfo
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- CN112235807B CN112235807B CN202011479438.4A CN202011479438A CN112235807B CN 112235807 B CN112235807 B CN 112235807B CN 202011479438 A CN202011479438 A CN 202011479438A CN 112235807 B CN112235807 B CN 112235807B
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Abstract
The invention provides a networking method, a networking device, networking equipment and networking media of a TDOA monitoring system, wherein the networking method comprises the following steps: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations; acquiring site position information of each of the plurality of detection sites; clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class; and networking at least part of the detection sites according to the clustering result.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle detection, in particular to a networking method, a networking device, networking equipment and networking media of a TDOA monitoring system.
Background
With the rapid development of the unmanned aerial vehicle industry, more and more unmanned aerial vehicles are applied to various fields, and black flight events also occur, so that people pay attention to the risk problems of unmanned aerial vehicle use safety, social security and the like, and the national supervisory control layer and social circles pay great attention, and therefore, the development trend of pursuing the accurate and efficient positioning of the unmanned aerial vehicle is in the industry.
TDOA location is a method of location using time differences, such as: by comparing the absolute time difference of the signal source of the unmanned aerial vehicle reaching each detection station, a hyperbola with the detection station as a focus and the distance difference as a long axis is made, and the intersection point of the hyperbolas is the position of the signal.
It can be seen that, TDOA positioning is to position an unmanned aerial vehicle by using the time difference of signals received by a plurality of detection stations, and in the prior art, because the positions of the detection stations are fixed, for different unmanned aerial vehicle signal sources, a single station distribution mode (which can also be understood as a networking mode) of the detection stations may have problems such as weak received signals, too large distance between the detection stations, and the like, which may cause inaccurate positioning of the unmanned aerial vehicle.
Disclosure of Invention
The invention provides a networking method, a networking device, networking equipment and networking media of a TDOA (time difference of arrival) monitoring system, which are used for solving the problem of inaccurate positioning of an unmanned aerial vehicle caused by weak received signals and overlarge detection station intervals.
According to a first aspect of the present invention, there is provided a networking method for a TDOA monitoring system, including: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
acquiring site position information of each of the plurality of detection sites;
clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class;
and networking at least part of the detection sites according to the clustering result.
Optionally, according to the clustering result, networking at least part of the detected sites, including:
if the number of probe stations included in any one of the first current classifications is equal to a predetermined number value N: determining that the probe sites included in the first current classification are in the same networking group; wherein N is an integer greater than 2.
Optionally, according to the clustering result, networking at least part of the detected sites, including:
if the number of the detection sites included in any one of the second current classifications is greater than the preset number value N:
determining at least one N-polygon according to the positions of the detection sites in the second current classification;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
Optionally, according to the clustering result, networking at least part of the detected sites, including:
if the number of the probing stations included in any one of the third current classifications is less than the predetermined number value N:
expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection stations,
determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
Optionally, determining that N probing stations are in the same networking group from among the L probing stations includes:
if L is equal to N, then: determining that the L probing sites are in the same networking group.
Optionally, determining that N probing stations are in the same networking group from among the L probing stations includes: if L is greater than N, then:
determining at least one N-polygon according to the positions of the L detection sites;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
Optionally, determining that N probing stations are in the same networking group from among the L probing stations includes: if L is less than N, then: and abandoning the detection stations contained in the third current classification to be networked.
Optionally, clustering the plurality of probe sites according to the site location information, the channel information, and the mode information to obtain a clustering result, including:
acquiring a distance threshold and a quantity threshold of clustering centers;
clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
According to a second aspect of the present invention, there is provided a networking device of a TDOA monitoring system, including:
an information determination module to: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
an information acquisition module to: acquiring site position information of each of the plurality of detection sites;
a clustering module to: clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class;
a networking module to: and networking at least part of the detection sites according to the clustering result.
Optionally, the networking module is specifically configured to: if the number of probe stations included in any one of the first current classifications is equal to a predetermined number value N: determining that the probe sites included in the first current classification are in the same networking group; wherein N is an integer greater than 2.
Optionally, the networking module is specifically configured to: if the number of the detection sites included in any one of the second current classifications is greater than the preset number value N:
determining at least one N-polygon according to the positions of the detection sites in the second current classification;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
Optionally, the networking module is specifically configured to: if the number of the probing stations included in any one of the third current classifications is less than the predetermined number value N:
expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection station positions;
determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
Optionally, the networking module is specifically configured to:
if L is equal to N, then: determining that the L probing sites are in the same networking group.
Optionally, the networking module is further configured to: if L is greater than N, then:
determining at least one N-polygon according to the positions of the L detection sites;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
Optionally, the networking module is further configured to: if L is less than N, then: and abandoning the detection stations contained in the third current classification to be networked.
Optionally, the clustering module is specifically configured to:
acquiring a distance threshold and a quantity threshold of clustering centers;
clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
According to a third aspect of the present invention, there is provided an electronic device comprising a processor and a memory, the memory for storing code and associated data;
the processor is adapted to execute code in the memory for implementing the method according to the first aspect of the invention and its alternatives.
According to a fourth aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, carries out the method according to the first aspect of the present invention and its alternatives.
The networking method, the networking device, the networking equipment and the networking medium of the TDOA monitoring system provided by the invention can flexibly network a plurality of detection sites according to the channel information and the mode information of the unmanned aerial vehicle and the position information of each detection site aiming at different unmanned aerial vehicle signal sources, automatically select a better networking mode from large-scale detection sites to carry out TDOA positioning on the unmanned aerial vehicle, avoid the problem of inaccurate positioning of the unmanned aerial vehicle caused by weak received signals and overlarge space between the detection sites, and further optimize the positioning accuracy and efficiency of the unmanned aerial vehicle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic networking diagram of a TDOA monitoring system in an application scenario of the present invention;
FIG. 2 is a first flowchart illustrating a networking method of a TDOA monitoring system according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a networking method of a TDOA monitoring system according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of a networking method of the TDOA monitoring system according to an embodiment of the present invention;
FIG. 5 is a fourth flowchart illustrating a networking method of a TDOA monitoring system according to an embodiment of the present invention;
FIG. 6 is a fifth flowchart illustrating a networking method of a TDOA monitoring system according to an embodiment of the present invention;
FIG. 7 is a sixth flowchart illustrating a networking method of a TDOA monitoring system according to an embodiment of the present invention;
FIG. 8 is a schematic structural diagram of a networking device of a TDOA monitoring system according to an embodiment of the present invention;
fig. 9 is a schematic diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
In an exemplary application scenario, please refer to fig. 1, a plurality of probing stations are used to perform real-time location tracking on an unmanned aerial vehicle signal by using a TDOA location technology, because the positions of the probing stations are fixed, and each probing station has a limited probing range for the unmanned aerial vehicle signal, if randomly selecting the probing stations for networking, a location deviation may be caused due to an excessively large distance between the probing stations, and if networking of the probing stations is completed in advance, identification of the probing stations in the same networking group for the remote unmanned aerial vehicle may cause a location deviation due to signal strength.
Therefore, the TDOA monitoring system provided by the invention can perform real-time networking on each detection station according to the detected unmanned aerial vehicle signal, so that the networked multiple detection stations can avoid the problems of the unmanned aerial vehicle signal difference and the overlarge detection station distance.
Referring to fig. 2, a networking method of a TDOA monitoring system includes:
s1: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
s2: acquiring site position information of each of the plurality of detection sites;
s3: clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class;
s4: and networking at least part of the detection sites according to the clustering result.
Wherein, step S1 may be, for example: collecting and counting channel information and mode information of unmanned aerial vehicle signals received by each detection station;
step S2 may be, for example: the method comprises the steps of counting all detection stations receiving unmanned aerial vehicle signals, wherein the counting of the detection stations can specifically be the counting of position information of the detection stations, and other information of the detection stations can be counted besides the position information.
In one example, the statistical results are shown in table 1 below:
table 1 statistical examples of probing results
Each row in table 1, represents an object that needs networking for localization; the step S3 can be understood as clustering the plurality of probing sites according to the statistical results of the steps S1 and S2;
in one example, the clustering results are shown in table 2 below:
table 2 example of probing site clustering results
As can be understood by combining table 2 with fig. 1, it can be easily seen that, according to the clustering result obtained after the station position information, the channel information and the pattern information are clustered, the detection station with the distance between the detection stations and the signal strength (the closer the detection station is to the unmanned aerial vehicle, the stronger the unmanned aerial vehicle signal can be received) which are matched with each other can be preliminarily screened.
Step S4 may be understood as further screening the better matched probing stations preliminarily screened after clustering to obtain networking results of multiple probing stations.
Therefore, the networking method, the networking device, the networking equipment and the networking medium of the TDOA monitoring system provided by the invention can flexibly network a plurality of detection sites according to the channel information and the mode information of the unmanned aerial vehicle and the position information of each detection site aiming at different unmanned aerial vehicle signal sources, automatically select a better networking mode from large-scale detection sites to carry out TDOA positioning on the unmanned aerial vehicle, avoid the problem of inaccurate positioning of the unmanned aerial vehicle caused by weak received signals and overlarge detection site intervals, and further optimize the positioning accuracy and efficiency of the unmanned aerial vehicle.
In one embodiment, referring to fig. 3 and fig. 6, step S4 includes:
s41: whether the number of the detection sites included in any one of the first current classifications is equal to a preset number value N or not; wherein N is an integer of 2 or more.
If the number of probe stations included in any of the first current classifications is equal to the preset number N, it can be understood that the determination result in step S41 is yes, step S42 can be implemented: determining that the probe sites included in the first current classification are in the same networking group;
if the number of probe sites included in any one of the current classifications is not equal to the preset number N, it can be understood that the determination result in step S41 is no, then step S43 may be implemented: whether the number of the detection stations contained in any one second current classification is larger than a preset number value N or not;
if the number of probe stations included in any of the second current classifications is greater than the predetermined number N, it is determined that the determination result in step S43 is yes, and step S44 may be implemented: determining at least one N-polygon according to the positions of the detection sites in the second current classification; then step S45 is performed: and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
If the number of probe stations included in any one of the second current classifications is smaller than the predetermined number value N, it can be understood that the determination result in step S43 is no, and step S46 may be implemented: expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection station positions; then step S47 is performed: determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
In one embodiment, referring to fig. 4 and fig. 6, step S47 includes:
s471: whether L is equal to N;
if L is equal to N, it is understood that the determination result in step S471 is yes, step S472 may be implemented: determining that the L probing sites are in the same networking group;
if L is not equal to N, it can be understood that the determination result in step S471 is no, and step S473 can be implemented: whether L is greater than N;
if L is greater than N, it is determined that the determination result in step S473 is yes, step S474 may be performed: determining at least one N-polygon according to the positions of the L detection sites; then, step S475 is performed: and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
If L is smaller than N, it can be understood that the determination result in step S473 is no, and step S476 may be implemented: and abandoning the detection stations contained in the third current classification to be networked.
In one embodiment, referring to fig. 5 and fig. 6, step S3 includes:
s31: acquiring a distance threshold and a quantity threshold of clustering centers;
s32: clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
The detection stations in the same category may detect the same unmanned aerial vehicle signal source by using the same channel information and mode information.
In one example, the clustering method may adopt kmeans clustering, and the specific clustering process is as follows: selecting the number of clustering centers (namely the quantity threshold of the clustering centers) from 1, carrying out kmeans clustering on the detection stations based on the distance between the detection stations, calculating the distances between all the detection stations and the clustering centers after the clustering is finished, determining the maximum distance D between the detection stations and the clustering centers, if D is smaller than the distance threshold, selecting the current number of the clustering centers and the clustering result, and terminating the clustering process. In other examples, other clustering methods may be used. In the actual working process, please refer to fig. 6 and 7, the signal detection is performed on the drone signal, then the detection result is counted (i.e., steps S1 and S2 are performed), after completion, the station clustering can be performed (i.e., step S3 is performed), after completion of step S3, step S4 is performed, wherein step S4 includes step S46 (i.e., station expansion), steps S44 to S45, and steps S474 to S475 (i.e., station screening).
Referring to fig. 8, a networking device 5 of a TDOA monitoring system is provided, which includes:
an information determination module 51 for: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
an information acquisition module 52 configured to: acquiring site position information of each of a plurality of detection sites;
a clustering module 53 configured to: clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class; wherein channel information and mode information of the probing stations in the same class are the same;
a networking module 54 configured to: and networking at least part of the detection sites according to the clustering result.
In an embodiment, the networking module 54 is specifically configured to: if the number of probe stations included in any one of the first current classifications is equal to a predetermined number value N: determining that the probe sites included in the first current classification are in the same networking group; wherein N is an integer greater than 2.
In an embodiment, the networking module 54 is specifically configured to: if the number of the detection sites included in any one of the second current classifications is greater than the preset number value N:
determining at least one N-polygon according to the positions of the detection sites in the second current classification;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
In an embodiment, the networking module 54 is specifically configured to: if the number of the probing stations included in any one of the third current classifications is less than the predetermined number value N:
expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection stations,
determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
In an embodiment, the networking module 54 is specifically configured to:
if L is equal to N, then: determining that the L probing sites are in the same networking group.
In an embodiment, the networking module 54 is specifically configured to: if L is greater than N, then:
determining at least one N-polygon according to the positions of the L detection sites;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
In one embodiment, the networking module 54 is further configured to: if L is less than N, then: and abandoning the detection stations contained in the third current classification to be networked.
In an embodiment, the clustering module 53 is specifically configured to:
acquiring a distance threshold and a quantity threshold of clustering centers;
clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
Referring to fig. 9, an electronic device 6 is provided, which includes:
a processor 61; and the number of the first and second groups,
a memory 63 for storing executable instructions of the processor;
wherein the processor 61 is configured to perform the above-mentioned method via execution of the executable instructions.
The processor 61 is capable of communicating with the memory 63 via the bus 62.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the above-mentioned method.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (12)
1. A networking method of a TDOA monitoring system is characterized by comprising the following steps:
determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
acquiring site position information of each of the plurality of detection sites;
clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class; wherein channel information and mode information of the probing stations in the same class are the same;
according to the clustering result, networking at least part of the detection sites, wherein the networking specifically comprises at least one of the following steps:
if the number of probe stations included in any one of the first current classifications is equal to a predetermined number value N: determining that the probe sites included in the first current classification are in the same networking group; wherein N is an integer greater than 2;
if the number of the detection sites included in any one of the second current classifications is greater than the preset number value N: determining at least one N-polygon according to the positions of the detection sites in the second current classification;
determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group;
if the number of the probing stations included in any one of the third current classifications is less than the predetermined number value N: expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection station positions;
determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
2. The networking method of a TDOA monitoring system, as set forth in claim 1, wherein determining from said L probing sites that N probing sites are in the same networking group comprises:
if L is equal to N, then: determining that the L probing sites are in the same networking group.
3. The networking method of a TDOA monitoring system, as set forth in claim 1, wherein determining from said L probing sites that N probing sites are in the same networking group comprises: if L is greater than N, then:
determining at least one N-polygon according to the positions of the L detection sites;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
4. The networking method of a TDOA monitoring system, as set forth in claim 1, wherein determining from said L probing sites that N probing sites are in the same networking group, further comprises: if L is less than N, then: and abandoning the detection stations contained in the third current classification to be networked.
5. The networking method for a TDOA monitoring system according to any one of claims 1 to 4, wherein clustering said plurality of probing sites according to said site location information, said channel information and said pattern information to obtain a clustering result comprises:
acquiring a distance threshold and a quantity threshold of clustering centers;
clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
6. A networking device of a TDOA monitoring system, comprising:
an information determination module to: determining channel information and mode information of unmanned aerial vehicle signals detected by each detection station in a plurality of detection stations;
an information acquisition module to: acquiring site position information of each of the plurality of detection sites;
a clustering module to: clustering the plurality of detection sites according to the site position information, the channel information and the mode information to obtain a clustering result, wherein the clustering result comprises at least one class and detection sites contained in each class; wherein channel information and mode information of the probing stations in the same class are the same;
a networking module to: according to the clustering result, networking at least part of the detection sites, wherein the networking specifically comprises at least one of the following steps:
if the number of probe stations included in any one of the first current classifications is equal to a predetermined number value N: determining that the probe sites included in the first current classification are in the same networking group; wherein N is an integer greater than 2;
if the number of the detection sites included in any one of the second current classifications is greater than the preset number value N: determining at least one N-polygon according to the positions of the detection sites in the second current classification;
determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group;
if the number of the probing stations included in any one of the third current classifications is less than the predetermined number value N: expanding the detection stations according to the geometric position centers of all the detection station positions in the third current classification and a preset expansion radius to obtain L detection station positions;
determining that N detection sites are in the same networking group from the L detection sites; wherein L is an integer of 1 or more.
7. The networking device of the TDOA monitoring system according to claim 6, wherein the networking module is specifically configured to:
if L is equal to N, then: determining that the L probing sites are in the same networking group.
8. The networking device of the TDOA monitoring system according to claim 6, wherein said networking module is further configured to: if L is greater than N, then:
determining at least one N-polygon according to the positions of the L detection sites;
and determining N detection sites corresponding to the N-polygon with the largest area in the at least one N-polygon, and determining that the N detection sites are in the same networking group.
9. The networking device of the TDOA monitoring system according to claim 6, wherein said networking module is further configured to: if L is less than N, then: and abandoning the detection stations contained in the third current classification to be networked.
10. The networking device of a TDOA monitoring system according to any one of claims 6 to 9, wherein said clustering module is specifically configured to:
acquiring a distance threshold and a quantity threshold of clustering centers;
clustering the detection sites according to the distance threshold, the quantity threshold and site position information of the detection sites, and enabling: the channel information and mode information of the probing stations in the same class are the same.
11. An electronic device, comprising a processor and a memory,
the memory is used for storing codes and related data;
the processor to execute code in the memory to implement the method of any one of claims 1 to 5.
12. A storage medium having stored thereon a computer program which, when executed by a processor, carries out the method of any one of claims 1 to 5.
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| CN202011479438.4A CN112235807B (en) | 2020-12-16 | 2020-12-16 | Networking method, device, equipment and medium of TDOA monitoring system |
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| CN202011479438.4A CN112235807B (en) | 2020-12-16 | 2020-12-16 | Networking method, device, equipment and medium of TDOA monitoring system |
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| CN112235807B true CN112235807B (en) | 2021-04-20 |
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