CN113156425A - Millimeter wave radar boundary intrusion data processing method based on big data - Google Patents
Millimeter wave radar boundary intrusion data processing method based on big data Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims description 7
- 230000001502 supplementing effect Effects 0.000 claims description 6
- 238000010835 comparative analysis Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 abstract description 11
- 230000007123 defense Effects 0.000 description 8
- 241000282326 Felis catus Species 0.000 description 6
- 230000009545 invasion Effects 0.000 description 4
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/886—Radar or analogous systems specially adapted for specific applications for alarm systems
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Abstract
The invention discloses a millimeter wave radar periphery intrusion data processing method based on big data, which is realized in a specific mode that an original database is established, collected data is compared and judged with the original data, preliminary data classification is carried out, data which is confirmed to be safe is supplemented into the original database, uncertain data is divided into suspicious data, unsafe data is divided into alarm data, repeated supplementary learning is carried out on data which is detected by a millimeter wave radar in real time, and the original database and an alarm database are perfected. The invention continuously expands and stores the original data, provides more and more comparison data for the subsequent data discrimination processing, and also provides more and more alarm data, so that the data acquisition and comparison of the intrusion system are more and more perfect, the probability of false data alarm is reduced, and the accuracy of the discrimination of the intrusion data system is improved.
Description
Technical Field
The invention relates to the technical field of radar scanning early warning of a surrounding defense area, in particular to a millimeter wave radar surrounding intrusion data processing method based on big data.
Background
For the enclosure defense area with the safety detection requirement, a corresponding detection monitoring system needs to be established. At present, a surrounding intrusion system based on a millimeter wave radar, a vibration optical cable, a vibration sensor or a capacitance disturbance type cable is applied to detection of a surrounding defense area, and in order to guarantee timeliness of intrusion alarm, data processing equipment of the system is completely placed on the site so as to realize real-time processing of surrounding intrusion sensing data, but the processing mode has the following problems: 1. the sensing data of the surrounding area is not deeply analyzed and judged, so that the misinformation and the reportation data are high; 2. the data processing equipment cannot be automatically configured according to the change of the environment and the service cycle, so that the service life of the system is not long.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the millimeter wave radar boundary intrusion data processing method based on the big data is provided, and the data acquisition and processing database is completed by continuously supplementing and checking the data of the surrounding boundary of the defense area, so that false alarms are reduced, and the accuracy of intrusion data discrimination and alarm is improved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a millimeter wave radar periphery intrusion data processing method based on big data comprises the following steps:
s1: acquiring original data of the boundary edge nodes through a millimeter wave radar, and uploading the original data to a data layer for storage;
s2: detecting and collecting real-time data of the boundary edge nodes, and uploading the real-time data to a data layer to perform comparative analysis with original stored data; if the data is the same as the original data, judging the data to be normal; if the difference exists between the data and the original data, the data is marked as data needing alarming, and alarming is carried out;
s3: manually checking the data needing to be alarmed in the step S2 to determine whether the data is normal, and if the data is normal, removing the alarm and storing and supplementing the data to form original data; if the data is abnormal, the detection data is marked as abnormal data, the characteristics of the abnormal data are stored, and the characteristic alarm of the abnormal data is set;
s4: and repeating the steps S2-S3, and continuously supplementing the original database and marking abnormal data.
Further, the abnormal data in step S3 is divided into suspicious data and alarm data, and different types of feature alarm settings are performed for different data types.
Further, checking and confirming the suspicious data, if the suspicious data is confirmed to be safe data, storing the suspicious data into original data, and removing characteristic alarm; if the data is confirmed to be unsafe data, the data is stored as alarm data and is set as a characteristic alarm of the alarm data.
Furthermore, a database is established for the service life of the millimeter radar wave equipment, the corresponding service life is set, and after the equipment reaches the service life, the data collected by the equipment is checked and judged regularly, so that the accuracy of data collection is ensured.
Further, data parameters of the data collected by the millimeter wave radar equipment under different weather conditions are subjected to characteristic marking and storage.
Compared with the prior art, the invention has the following beneficial effects:
(1) according to the invention, firstly, data acquired for the first time at the edge of a surrounding defense area is stored as original data through a millimeter wave radar, the data acquired later is discriminated and stored, the data is distinguished and classified, normal and safe data is supplemented into an original database, the original data is continuously expanded and stored, more and more comparison data are provided for subsequent data distinguishing processing, the data acquisition and comparison of an intrusion system are more and more perfect, the probability of false alarm of the data is reduced, and the accuracy of distinguishing the intrusion data system is improved.
(2) According to the invention, collected data are screened and reasonably classified, and corresponding characteristic alarm is set for the data of the same class, so that the accuracy and intelligence of intrusion system discrimination are further improved.
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Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The present invention will be further described with reference to the following description and examples, which include but are not limited to the following examples.
As shown in fig. 1:
when the data processing and analyzing method is realized, a distributed layout mode is adopted, a plurality of millimeter wave radar devices are arranged at edge nodes of a surrounding defense area, after detection devices are arranged, data acquired for the first time are used as original data for judging whether foreign objects invade, the original data comprise reflected wave band data and the like acquired by millimeter wave radar detection, and original storage data are obtained by storing data of the difference due to the fact that wave bands transmitted and received by the millimeter wave radars of different objects or living bodies are different.
After the collection and storage of the original data are completed, real-time detection and monitoring are carried out on the boundary edge through millimeter wave radar equipment, the detected data are matched and compared with the data of the original storage, when the monitored data are found to be not matched with the original data or have differences, alarm prompt is carried out, monitoring personnel carry out preliminary judgment on the invaded data according to the alarm prompt, if the data can distinguish that the data belong to safe invasion data through simple judgment, the data are confirmed to be safe invasion data, the data are supplemented and stored into the original database, the data serve as the original database at the present stage, the invasion data are continuously detected and supplemented in the same way, and the original database is continuously perfected.
When the data cannot be determined to be safe through preliminary judgment, the data is divided into suspicious data to wait for further confirmation; if the data intrusion is determined to be unsafe through preliminary judgment, the data is divided into alarm data, the characteristic value of the intrusion data is recorded, characteristic alarm is set for the characteristic value, if the data is detected again next time, alarm prompt is directly carried out to remind personnel of the intrusion of dangerous data information, and the personnel prepare for emergency protection.
And finally confirming the specific condition of the data in a background or field real-time confirmation mode for the data classified as suspicious through preliminary judgment, supplementing the data into the original database if the data is finally confirmed to be the safety data, removing the alarm, automatically defaulting the data to be the safety data if the data is detected again next time, and not prompting the alarm. If the data are finally determined to be unsafe data, the data are directly divided into the data needing to be alarmed, corresponding characteristic alarming is set similarly, if the data are detected again next time, alarming prompt is directly carried out, personnel are reminded of dangerous data information intrusion, and the personnel are ready for emergency protection. By continuously judging the intrusion data, the intrusion data are increased, and the original data are supplemented and perfected, so that the alarm accuracy of the intrusion system is gradually improved.
Because the millimeter radar wave reflection characteristics are different under different weather conditions, a database under corresponding weather conditions can be established according to different weather conditions, and the consistency of radar data under different weather conditions is found out through continuous data accumulation to form a weather theme; and judging the intruding data according to different weather themes, thereby improving the accuracy of interpretation. Meanwhile, data loss and functional equipment decline can occur to the equipment according to the service life, and data analysis and judgment need to be made to the whole period of the equipment and uploaded to the cloud. Due to different investment time of the radars and the terminals in each defense area, early warning marks are made for the equipment and the terminals which reach the service life.
The invention is illustrated below by way of example of an early warning enclosure for an airport:
the airport early warning enclosure system is 100M of one monitoring point, 1 point of four scanning devices and one matched early warning processing device. Assuming that the diameter of an airport is 10 kilometers and the airport is divided into four areas AB, C and D, under the existing early warning system, a section of unknown biological wave band appears in the area A and breaks into the range of the boundary, and early warning appears; the early warning is cancelled after the cat is checked to be a cat; after 10 minutes, the cat enters zone B from another entrance, the zone B alarm will simultaneously sound again and the personnel will need to recheck for the intruder. Repeated alarms, false data reports, missed reports, and the like often occur.
The specific technical scheme of the technology is as follows: through data distributed processing, initial data acquired by various regions are stored to the cloud, and the data are divided into three data layers, namely original data, suspicious data and alarm data. If the band of a cat entering the area a is S1, the original data S1 is a cat, and the data is simultaneously transferred to the processing terminal devices of the areas, and then when all areas of the area AB C D enter a cat again, the early warning system refers to the original data for reference and comparison, and then determines as safety data, so that no false alarm or false report occurs. The first level is mutual defense area learning, and an original database is established. Then, after screening, the special, unreferenced and unreterminable data are listed in a suspicious database; the wave bands which can be directly judged as the invasion can be uploaded and learned, an alarm database is established, and the alarm accuracy of the early warning system is improved.
The above-mentioned embodiment is only one of the preferred embodiments of the present invention, and should not be used to limit the scope of the present invention, but all the insubstantial modifications or changes made within the spirit and scope of the main design of the present invention, which still solve the technical problems consistent with the present invention, should be included in the scope of the present invention.
Claims (5)
1. A millimeter wave radar periphery intrusion data processing method based on big data is characterized in that: the method comprises the following steps:
s1: acquiring original data of the boundary edge nodes through a millimeter wave radar, and uploading the original data to a data layer for storage;
s2: detecting and collecting real-time data of the boundary edge nodes, and uploading the real-time data to a data layer to perform comparative analysis with original stored data; if the data is the same as the original data, judging the data to be normal; if the difference exists between the data and the original data, the data is marked as the data needing alarming, and alarming is carried out;
s3: manually checking the data needing to be alarmed in the step S2 to determine whether the data is normal, and if the data is normal, removing the alarm and storing and supplementing the data to form original data; if the data is abnormal, the detection data is marked as abnormal data, the characteristics of the abnormal data are stored, and the characteristic alarm of the abnormal data is set;
s4: and repeating the steps S2-S3, and continuously supplementing the original database and marking abnormal data.
2. The millimeter wave radar periphery intrusion data processing method based on the big data as claimed in claim 1, wherein: the abnormal data in step S3 is divided into suspicious data and alarm data, and different types of feature alarm settings are performed for different data types.
3. The millimeter wave radar periphery intrusion data processing method based on the big data as claimed in claim 2, wherein: checking and confirming the suspicious data, if the suspicious data is confirmed to be safe data, storing the suspicious data into original data, and removing characteristic alarm; if the data is confirmed to be unsafe data, the data is stored as alarm data and is set as a characteristic alarm of the alarm data.
4. The millimeter wave radar periphery intrusion data processing method based on the big data as claimed in claim 3, wherein: and establishing a database for the service life of the millimeter radar wave equipment, setting corresponding service life, and periodically checking and judging the data acquired by the equipment after the equipment reaches the service life, so as to ensure the accuracy of data acquisition.
5. The millimeter wave radar periphery intrusion data processing method based on the big data as claimed in claim 4, wherein: and carrying out characteristic marking and storage on data parameters of the data acquired by the millimeter wave radar equipment under different weather conditions.
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