CN114885298B - Rainfall intensity monitoring method based on mobile signaling data - Google Patents
Rainfall intensity monitoring method based on mobile signaling data Download PDFInfo
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- CN114885298B CN114885298B CN202210534266.9A CN202210534266A CN114885298B CN 114885298 B CN114885298 B CN 114885298B CN 202210534266 A CN202210534266 A CN 202210534266A CN 114885298 B CN114885298 B CN 114885298B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
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- G01W1/14—Rainfall or precipitation gauges
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
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Abstract
The invention provides a rainfall intensity monitoring method based on mobile signaling data, which establishes a rainfall intensity level identification model by combining a rainfall intensity level label and a machine learning multi-classification algorithm on the basis of acquiring a user terminal feedback signaling parameter statistic, and realizes effective rainfall intensity monitoring in the range of each communication base station cell; the invention has the advantages of extremely low cost and strong feasibility, can be widely applied to real-time monitoring of rainfall information near the ground with large-area coverage and high space-time resolution, and has wide practical application prospect.
Description
Technical Field
The invention belongs to the technical field of near-ground weather hydrologic information detection based on ubiquitous electromagnetic signals, and particularly relates to a rainfall intensity monitoring method based on mobile signaling data.
Background
The mobile signaling data is a type of data which is acquired and recorded by a communication base station in the communication process of the mobile terminal, comprises the space-time information of the mobile terminal, and is mainly used for monitoring whether the mobile terminal can normally communicate in a network in service. After the treatments of decryption, desensitization and the like, massive mobile signaling data are successfully applied to the fields of intelligent traffic perception, population flow monitoring and the like. However, the above application focuses mainly on the space-time attribute of mobile signaling data, and does not fully utilize the interaction of mobile communication with space elements during non-line-of-sight propagation and the space element information implicitly carried thereby.
The occurrence of heavy rainfall not only can produce strong erosion effect on soil, but also is a direct cause of natural disasters such as flood, debris flow and the like. In addition, rainfall is one of important factors influencing the near-ground mobile communication process, and the rainfall intensity directly determines the electromagnetic propagation signal quality of mobile communication. The rainfall intensity information monitoring by taking the communication base station as a basic unit is realized by extracting the rainfall related parameters of the electromagnetic propagation path in the mobile signaling data, so that the method has the advantages of low cost, wide space coverage, near ground of a measured object and the like, and has great potential in theory for being applied to rainfall intensity monitoring services in the fields of weather, hydrology, communication and the like.
Disclosure of Invention
In order to solve the technical problems, the invention provides a rainfall intensity monitoring method based on mobile signaling data, which acquires a rainfall intensity sensitive feature matrix by extracting communication quality related statistics of the mobile signaling data in a certain area; determining a rainfall intensity level label matrix based on a rainfall cylinder synchronous observation result of a certain matching principle, and establishing a data set; and constructing a rainfall intensity level identification model by combining a multi-classification algorithm, and realizing rainfall intensity monitoring in the cell range of each communication base station. The method is based on mobile signaling data captured by the communication base station, can effectively identify the rainfall intensity level information represented by the area, and can be widely applied to real-time monitoring of meteorological hydrologic information in multiple scenes.
In order to achieve the above object, the present invention provides a rainfall intensity monitoring method based on mobile signaling data, comprising the following steps:
acquiring a rainfall intensity sensitive characteristic matrix and a rainfall intensity level label matrix, and establishing a data set based on the rainfall intensity sensitive characteristic matrix and the rainfall intensity level label matrix;
based on a multi-classification algorithm, establishing a rainfall intensity level identification model;
testing the rainfall intensity level identification model based on the data set;
and based on the rainfall intensity level identification model after the test, completing rainfall intensity monitoring in the cell range of each communication base station.
Optionally, the method for acquiring the rainfall intensity sensitive feature matrix comprises the following steps:
and acquiring feedback signaling parameter statistics of the user terminal, and acquiring a rainfall intensity sensitive characteristic matrix based on the feedback signaling parameter statistics of the user terminal.
Optionally, the method for obtaining the feedback signaling parameter statistic of the user terminal comprises the following steps:
acquiring a user terminal return signaling parameter in real time, and performing decryption and desensitization on the user terminal return signaling parameter;
dividing the de-ciphered and de-sensitized user terminal feedback signaling parameters into a plurality of value intervals, and counting the count value of the user terminal feedback signaling parameters in each value interval in a preset period to obtain the statistics of the user terminal feedback signaling parameters.
Optionally, the features of the rainfall intensity sensitive Feature matrix i The expression of (2) is:
wherein Count j,k Refers to a certain base station in the jth period Range k And the count value of the value interval, P is the total cycle number.
Optionally, the method for acquiring the rainfall intensity level label matrix comprises the following steps:
and acquiring a raindrop cylinder synchronous observation result, and acquiring a rainfall intensity grade label matrix based on the raindrop cylinder synchronous observation result.
Optionally, the method for acquiring the synchronous observation result of the rain gauge is as follows:
and synchronously measuring the accumulated rainfall of each rainfall cylinder in the period, and dividing the accumulated rainfall into a plurality of rainfall intensity levels to be used as a rainfall cylinder synchronous observation result.
Alternatively, the expression of the rainfall intensity level is:
wherein [ a ] s-1 ,a s ) (s=1, 2, …, S) is the intensity range corresponding to the S-th rainfall intensity level.
Optionally, based on the synchronous observation result of the rainfall cylinder, the method for obtaining the rainfall intensity level label matrix comprises the following steps:
and matching the rainfall intensity level with a communication base station in a corresponding period based on a matching principle, and establishing a rainfall intensity level label matrix.
Optionally, the rainfall intensity level label matrix expression is:
wherein, the liquid crystal display device comprises a liquid crystal display device,is the spatial position of the i-th base station, is ∈>Is the spatial position of the o-th rain gauge.
Compared with the prior art, the invention has the following advantages and technical effects:
the invention provides a rainfall intensity monitoring method based on mobile signaling data, which establishes a rainfall intensity level identification model by combining a rainfall intensity level label and a machine learning multi-classification algorithm on the basis of acquiring a user terminal feedback signaling parameter statistic, and realizes effective rainfall intensity monitoring in the range of each communication base station cell; meanwhile, the method only needs to export the background data of the mobile communication network service operation as input, so the cost is extremely low, the practicability is high, and the method can be widely applied to real-time monitoring of the rainfall information near the ground with large-area coverage and high space-time resolution. The method can be applied to actual business as a new rainfall intensity level identification method.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:
fig. 1 is a schematic diagram of a communication base station, a user terminal, and a rainfall intensity monitoring method based on mobile signaling data according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for monitoring rainfall intensity based on mobile signaling data in an embodiment of the present invention;
fig. 3 is a schematic diagram of an RSRQ signaling parameter value interval in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a test confusion matrix for a rainfall intensity level recognition model in an example of the invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
As shown in fig. 1-2, the present embodiment provides a rainfall intensity monitoring method based on mobile signaling data, which mainly includes the following steps of obtaining a rainfall intensity sensitive feature matrix by extracting relevant statistics of communication quality of mobile signaling data in a certain area; determining a rainfall intensity level label matrix based on a rainfall cylinder synchronous observation result of a certain matching principle, and establishing a data set; and constructing a rainfall intensity level identification model by combining a multi-classification algorithm, and realizing rainfall intensity monitoring in the cell range of each communication base station.
Further, the method for acquiring the communication quality related statistics of the user terminal based on the mobile signaling data captured by the communication base station in a certain area comprises the following steps:
there are N normally operating communication base stations eNB in the area 1 ,eNB 2 ,…,eNB N Each communication base station captures signaling parameters returned by the user terminal in real time, wherein the signaling parameters include, but are not limited to, RSRQ (Reference Signal Receiving Quality), and only records the communication quality after decryption and desensitizationSignaling parameters of the gateway;
dividing the signaling parameter into M value intervals Range 1 ,Range 2 ,…,Range M In a certain period p (min) Counting the Count value Count of the user terminal feedback signaling parameters in each value interval 1 ,Count 2 ,…,Count M 。
Specifically, 28459 communication base stations eNB which normally operate exist in the area 1 ,eNB 2 ,…,eNB 20459 Each communication base station captures signaling data returned by the user terminal in real time, and only records signaling parameters RSRQ (Reference Signal Receiving Quality) after decryption and desensitization;
as shown in fig. 3, RSRQ signaling parameters are divided into 18 value intervals Range 1 ,Range 2 ,…,Range 18 Counting Count of the user terminal returning RSRQ signaling parameter in each value interval by taking 60min as a period 1 ,Count 2 ,…,Count 18 ；
Further, according to the obtained count value of each value interval, a rainfall intensity sensitive characteristic matrix of the communication base station is established:
wherein Count j,k Refers to a certain base station in the jth period Range k And the count value of the value interval, P is the total cycle number.
Specifically, according to the obtained value interval counts, a rainfall intensity sensitive characteristic matrix of the communication base station is established:
wherein Count j,k Refers to a certain base station in the jth period Range k The count value of the value interval is 144.
Further, there are D rain Gauge cartridges in the area 1 ,Gauge 2 ,…,Gauge D Same step by stepRow observation, S rainfall intensity levels were divided according to the cumulative rainfall Acc (mm) measured in period p by each rain gauge:
wherein [ a ] s-1 ,a s ) (s=1, 2, …, S) is the intensity range corresponding to the S-th rainfall intensity level. The rainfall intensity ranking criteria include, but are not limited to, a classification of 5 (0 mmh-1,5 mmh-1), [5mmh-1,10 mmh-1), [10mmh-1,20 mmh-1), [20mmh-1,40 mmh-1), [40mmh-1, +).
Specifically, 307 rain Gauge cartridges are present in the area 1 ,Gauge 2 ,…,Gauge 317 The observation was performed synchronously, and 5 rainfall intensity levels were divided according to the cumulative rainfall Acc (mm) measured in 60min by each rainfall cylinder:
wherein [ a ] s-1 ,a s ) (s=1, 2, …, 5) is the intensity range corresponding to the s-th rainfall intensity level.
Further, according to a certain matching principle, the rainfall intensity levels divided by the D rainfall cylinders are used as labels to be matched with N communication base stations in a corresponding period, and a label matrix is established:
wherein, the liquid crystal display device comprises a liquid crystal display device,is the spatial position of the i-th base station, is ∈>Is the spatial position of the o-th rain gauge. Wherein the communication base station and the rain gauge matching principle include, but are not limited to, a distance minimization principle.
Specifically, according to the minimum distance matching principle, rainfall intensity levels divided by 307 rainfall cylinders are used as labels to be matched with 28459 communication base stations in a corresponding period, and a label matrix is established:
wherein, the liquid crystal display device comprises a liquid crystal display device,is the spatial position of the i-th base station, is ∈>Is the spatial position of the o-th rain gauge.
Further, a data set [ Feature, target ] is established according to the Feature matrix and the tag matrix, and a rainfall intensity level identification model is established and tested by combining a multi-classification algorithm, so that rainfall intensity monitoring in the cell range of each communication base station is realized. Among them, multi-classification algorithms include, but are not limited to, integration methods.
Specifically, a data set (Feature, target) is established according to the Feature matrix and the tag matrix, a training set and a testing set are divided according to a ratio of 4:1, and a rainfall intensity level identification model is established and tested by combining an integration algorithm (consisting of 30 nearest neighbor learners), so that rainfall intensity monitoring in the cell range of each communication base station is realized. Fig. 4 is a test confusion matrix for a rainfall intensity level recognition model.
Further, in the actual application process, according to the mobile signaling parameter statistics captured by the communication base station, the rainfall intensity level in the cell range of each communication base station can be directly obtained.
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. A rainfall intensity monitoring method based on mobile signaling data is characterized by comprising the following steps,
acquiring a rainfall intensity sensitive characteristic matrix and a rainfall intensity level label matrix, and establishing a data set based on the rainfall intensity sensitive characteristic matrix and the rainfall intensity level label matrix;
based on a multi-classification algorithm, establishing a rainfall intensity level identification model;
testing the rainfall intensity level identification model based on the data set;
based on the rainfall intensity level identification model after the test, completing rainfall intensity monitoring in the cell range of each communication base station;
the method for acquiring the rainfall intensity sensitive characteristic matrix comprises the following steps:
acquiring feedback signaling parameter statistics of a user terminal, and acquiring a rainfall intensity sensitive feature matrix based on the feedback signaling parameter statistics of the user terminal;
the method for obtaining the feedback signaling parameter statistic of the user terminal comprises the following steps:
acquiring a user terminal return signaling parameter in real time, and performing decryption and desensitization on the user terminal return signaling parameter;
dividing the de-ciphered and de-sensitized user terminal return signaling parameters into a plurality of value intervals, and counting the count value of the user terminal return signaling parameters in each value interval in a preset period to obtain user terminal return signaling parameter statistics;
acquiring relevant statistics of communication quality of a user terminal based on mobile signaling data captured by a communication base station in a certain area, comprising the following steps:
there are N normally operating communication base stations eNB in the area 1 , eNB 2 , …, eNB N Each communication base station captures signaling parameters returned by the user terminal in real time, wherein the signaling parameters comprise, but are not limited to, RSRQ, and recording signaling parameters related to communication quality after decryption and desensitization;
dividing the signaling parameter into M value intervals Range 1 , Range 2 , …, Range M Counting the Count value Count of the user terminal feedback signaling parameter in each value interval in a certain period p (min) 1 , Count 2 , …, Count M ；
Rainfall intensity sensitive characteristic matrixThe expression of (2) is:
wherein Count j,k Refers to a certain base station in the jth period Range k And the count value of the value interval, P is the total cycle number.
2. The method for monitoring rainfall intensity based on mobile signaling data according to claim 1, wherein the method for obtaining the rainfall intensity level label matrix is as follows:
and acquiring a raindrop cylinder synchronous observation result, and acquiring a rainfall intensity grade label matrix based on the raindrop cylinder synchronous observation result.
3. The rainfall intensity monitoring method based on mobile signaling data according to claim 2, wherein the method for acquiring the synchronous observation result of the rainfall cylinder is as follows:
and synchronously measuring the accumulated rainfall of each rainfall cylinder in a preset period, and dividing the accumulated rainfall into a plurality of rainfall intensity levels to be used as a rainfall cylinder synchronous observation result.
4. A rainfall intensity monitoring method based on mobile signaling data according to claim 3 wherein the expression of the rainfall intensity level is:
wherein [ a ] s-1 , a s ) (s=1, 2, …, s) is the intensity range corresponding to the s-th rainfall intensity level,A CC is the cumulative rainfall over period p.
5. The method for monitoring rainfall intensity based on mobile signaling data according to claim 4, wherein the method for obtaining the rainfall intensity level label matrix based on the synchronous observation result of the rainfall cylinder is as follows:
and matching the rainfall intensity level with a communication base station in a corresponding period based on a matching principle, and establishing a rainfall intensity level label matrix.
6. The mobile signaling data based rainfall intensity monitoring method of claim 5 wherein the rainfall intensity level label matrix expression is:
wherein (1)>Is the spatial position of the i-th base station, is ∈>Is the spatial position of the o-th rain gauge.
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| CN113466969A (en) * | 2021-05-11 | 2021-10-01 | 深圳捷豹电波科技有限公司 | Rainfall monitoring method, receiving device, rainfall monitoring system and storage medium |
| WO2021197167A1 (en) * | 2020-03-30 | 2021-10-07 | 国防科技大学 | Rainfall and water vapor comprehensive measurement device and method based on dual-frequency dual-polarization microwave link |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103616736A (en) * | 2013-09-06 | 2014-03-05 | 中国人民解放军理工大学 | Rainfall foundation monitoring method based on GNSS signal depolarization effect |
| WO2021197167A1 (en) * | 2020-03-30 | 2021-10-07 | 国防科技大学 | Rainfall and water vapor comprehensive measurement device and method based on dual-frequency dual-polarization microwave link |
| CN112051576A (en) * | 2020-08-31 | 2020-12-08 | 江苏微之润智能技术有限公司 | Intelligent multi-frequency microwave rainfall monitoring method |
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