CN117880820A - Radio safety guarantee system and method for Internet of vehicles - Google Patents
Radio safety guarantee system and method for Internet of vehicles Download PDFInfo
- Publication number
- CN117880820A CN117880820A CN202410279639.1A CN202410279639A CN117880820A CN 117880820 A CN117880820 A CN 117880820A CN 202410279639 A CN202410279639 A CN 202410279639A CN 117880820 A CN117880820 A CN 117880820A
- Authority
- CN
- China
- Prior art keywords
- radio
- signal
- monitoring
- internet
- vehicles
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000012544 monitoring process Methods 0.000 claims abstract description 103
- 238000001228 spectrum Methods 0.000 claims abstract description 31
- 230000004927 fusion Effects 0.000 claims description 19
- 238000003745 diagnosis Methods 0.000 claims description 15
- 230000003595 spectral effect Effects 0.000 claims description 13
- 230000003044 adaptive effect Effects 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 8
- 238000005311 autocorrelation function Methods 0.000 claims description 7
- 239000011159 matrix material Substances 0.000 claims description 6
- 230000007613 environmental effect Effects 0.000 claims description 4
- 230000003993 interaction Effects 0.000 claims description 4
- 230000004807 localization Effects 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 230000006855 networking Effects 0.000 abstract description 23
- 238000004891 communication Methods 0.000 abstract description 11
- 238000005516 engineering process Methods 0.000 abstract description 2
- 238000007499 fusion processing Methods 0.000 abstract 1
- 238000013024 troubleshooting Methods 0.000 abstract 1
- 238000007726 management method Methods 0.000 description 10
- 230000000875 corresponding effect Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 5
- 238000012360 testing method Methods 0.000 description 5
- 230000002159 abnormal effect Effects 0.000 description 3
- 238000013136 deep learning model Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000013499 data model Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
- H04W16/10—Dynamic resource partitioning
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/90—Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Atmospheric Sciences (AREA)
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Emergency Management (AREA)
- Environmental & Geological Engineering (AREA)
- Public Health (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses the technical field of radio technology of the Internet of vehicles, and particularly discloses a radio safety guarantee system and a radio safety guarantee method of the Internet of vehicles, wherein the system comprises a plurality of sensor type radio monitoring receivers which are configured at two sides of an automatic driving road to form a radio monitoring seamless layout of the automatic driving road so as to monitor the radio spectrum data distribution on the automatic driving road and upload the monitored radio spectrum data to a cloud platform of the radio safety guarantee system of the Internet of vehicles; and fusing the received wireless spectrum data of the at least three sensor-type radio monitoring receivers nearby and providing intelligent car networking radio safety monitoring signal data and early warning signal data. The method carries out fusion processing on the detected data on the basis of the system, so that the automatic driving vehicle can fully cover and ensure radio communication, and the improvement of the safety of the internet of vehicles system of the automatic driving vehicle and the high-efficiency emergency rescue and troubleshooting are realized.
Description
Technical Field
The invention relates to the technical fields of internet of vehicles radio safety guarantee test, internet of vehicles communication data collection, internet of vehicles test data analysis and the like, in particular to an internet of vehicles radio safety guarantee system and an internet of vehicles radio safety guarantee method.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Along with the rapid development of the internet of vehicles technology, a vehicle communication network has become an important communication network form gradually, and has important application value in the aspects of realizing automatic driving of vehicles, intelligent transportation and the like. However, the presence of limited internet of vehicles radio spectrum resources and radio interference may affect the normal operation of the internet of vehicles. Therefore, how to realize the radio safety guarantee of the internet of vehicles becomes one of the hot spots of the current research, and is also an important and necessary guarantee for the internet of vehicles system and the automatic driving and intelligent transportation.
In the prior art, the Chinese patent publication No. CN103812577A, named abnormal radio signal automatic identification system and method thereof, discloses a frequency band scanning data obtained through a data interface, all signals and corresponding frequency points of the frequency band are monitored by adopting a segmentation dynamic self-adaptive threshold algorithm, the signal frequency points are subjected to intermediate frequency measurement or intermediate frequency direction finding to obtain detailed data of the signals, various characteristics of the signals are analyzed and processed, the extracted characteristics are input into an abnormal signal identification module, the category of the signals is identified, thus abnormal radio point information is obtained, but the system is based on GPS positioning, and is directly applied to the unmanned technical field and limited by network stability, and although the information processing capability of radio monitoring equipment is improved, normal traffic of an automatic driving vehicle is still not ensured when the network signals are not strong or stable.
The technical problems to be solved by the invention are as follows: how to realize that the automatic driving vehicle can guarantee radio communication in a full coverage way, thereby realizing that the safety of a vehicle networking system of the automatic driving vehicle is guaranteed by improving the radio communication and realizing efficient emergency rescue.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a method for monitoring the radio spectrum distribution on the vehicle road by arranging sensor type radio monitoring receivers on two sides of an automatic driving roadbed, wherein the two sides of the automatic driving roadbed are intelligently monitored by using an energy-activated vehicle networking radio safety guarantee system such as a cloud-side cooperative operation system, an intelligent brain and the like, and a road radio interference signal is intelligently reported. Meanwhile, the system utilizes a big data model and intelligent management and analysis test data to provide an intelligent car networking radio safety monitoring and early warning system and method for on-line timely diagnosis of car networking signals.
The technical scheme adopted by the invention is as follows: a car networking radio security system, the security system comprising:
a sensor-type radio monitoring receiver, a plurality of which are configured near an automatic driving road, form an automatic driving road radio monitoring seamless layout, monitor radio spectrum data distribution on the automatic driving road, and upload the monitored radio spectrum data to a vehicle networking radio safety guarantee system cloud platform;
wherein: the cloud platform of the internet of vehicles radio safety guarantee system fuses the received wireless spectrum data of at least three nearby sensor type radio monitoring receivers, and provides intelligent internet of vehicles radio safety monitoring signal data and early warning signal data for intelligent management and analysis of data based on big data.
In this technical scheme, the safety guarantee system still includes the wisdom box, the wisdom box is configured to carry out collection, processing, storage and management on the wireless spectrum data that sensor type radio monitoring receiver received to and be used for realizing the construction of software and hardware decoupling.
In the technical scheme, the intelligent box processes and transmits acquired data through the side cloud cooperative operation system in the intelligent box, and meanwhile, wireless spectrum data is stored in the cloud platform of the internet of vehicles radio security assurance system.
In the technical scheme, the intelligent box is further configured on a vehicle-mounted on-line diagnosis mobile station, the vehicle-mounted on-line diagnosis mobile station is used for following the fault automatic driving intelligent automobile in a short distance, and performs wireless data interaction with the fault automatic driving intelligent automobile through a transmitting antenna and a receiving antenna, so that wireless fault diagnosis on the fault automatic driving intelligent automobile in a local area network is guaranteed.
In the technical scheme, a plurality of sensor type radio monitoring receivers are arranged near an automatic driving road in a staggered way, and the distance between any two adjacent sensor type radio monitoring receivers is 4-8 km.
In the technical scheme, the monitoring data of at least three sensor-type radio monitoring receivers are fused by adopting a nearby principle so as to update the intelligent management and analysis of the wireless spectrum data based on big data in real time, thereby providing real-time updated vehicle networking radio safety monitoring signal data and early warning signal data.
The radio safety guarantee method of the Internet of vehicles comprises the following steps:
acquiring wireless spectrum data from a plurality of sensor type radio monitoring receivers arranged beside an automatic driving road for fusion, and pre-establishing a database containing all radio situations on the automatic driving road on a cloud as a basic signal library; and
real-time monitoring road radio situation, obtaining real-time monitoring signalThe method comprises the steps of carrying out a first treatment on the surface of the And
real-time monitoring signal to be monitoredAnd the known signal in the base signal library +.>Performing autocorrelation operation through an autocorrelation function; and
judging the monitored signal according to the result of the autocorrelation operation and a preset threshold valueWhether the signal is matched with the legal signal threshold value in the base signal library or not, and updating the real-time signal matched with the legal signal threshold value in the base signal library into the base signal library.
In the technical scheme, if the result of the autocorrelation operation is within a preset threshold range, judging that the signal is legal, and updating the legal signal into a basic signal library; otherwise, judging other signals, triggering corresponding alarm mechanisms and recording related data.
In the technical scheme, the monitored real-time monitoring signalAnd the known signal in the base signal library +.>Performing autocorrelation operation by autocorrelation function to obtain monitored autocorrelation signal +.>The formula of (2) is:
（1）
wherein:is a monitored real-time monitoring signal, +.>Is a known signal in the base signal library, N is the time delay value, N is the length of the signal, < +.>Is by the known signal +.in the base signal library which is continuously modified by autocorrelation with time lag value n>May be a time-domain weighted signal;
the monitoring signals of the W sensor type radio monitoring receivers are fused by using a Kalman filter or an extended Kalman filter, and the fusion formula is as follows:
（2）
wherein:is the signal state estimate for the next instant after fusion, is->Is the signal state estimate at the current instant, +.>Is Kalman gain, < ->Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral amplitude of each frequency point at time k+1;
the position fusion formula for fusing the W sensor type radio monitoring receivers is as follows:
（3）
wherein: p (P) i Position estimation for a sensor type radio monitoring receiver, A i For the accuracy of a sensor-type radio monitoring receiver, P f Is melted intoThe position estimate of the receiver is monitored by the combined sensor radio.
In the technical scheme, when other signals are interference signals, the interference signals need to be positioned, and the positioning method is an adaptive positioning algorithm:
according to the principle of nearby, the interference signals are fused with the nearby W sensor-type radio monitoring receiver signals to obtain the fused position estimation P f ，P f The fusion formula of (3);
or the positioning method is a multi-sensor fusion positioning algorithm: interference signal localization using adaptive filters, dynamically adjusting parameters based on real-time environmental conditions and signal data, estimating a next time adaptive monitored signal state estimate according to the following equation (4)：
（4）
Wherein:is the monitoring signal state estimation at the current moment, +.>Is an adaptive gain, < >>Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral magnitudes of the individual frequency bins at time k.
Compared with the prior art, the invention has the beneficial effects that:
1. the sensor type wireless monitoring receivers are innovated at two sides of the automatic driving road subgrade, so that a wireless monitoring seamless layout of the automatic driving road is formed, the wireless monitoring seamless layout is used for monitoring the wireless spectrum data distribution on the automatic driving road and uploading the monitored wireless spectrum data to the cloud platform of the wireless safety guarantee system of the internet of vehicles, and the wireless arrangement density is improved, so that the electromagnetic environment state on the automatic driving road can be monitored without blind spots.
2. And fusing the received wireless spectrum data of the at least three nearby sensor-type radio monitoring receivers, and providing intelligent vehicle networking radio safety monitoring signal data and early warning signal data for intelligent management and analysis of data based on big data.
3. The intelligent box is further configured on a vehicle-mounted online diagnosis mobile station, the vehicle-mounted online diagnosis mobile station is used for following the fault automatic driving intelligent automobile in a short distance, and performing wireless data interaction with the fault automatic driving intelligent automobile through a transmitting antenna and a receiving antenna, and is used for performing real-time online network access regulation test on the accident vehicle by using the vehicle networking online diagnosis system mobile station when an automatic driving accident occurs so as to monitor whether the vehicle communication equipment works normally or not and further judge the reason of the accident, so that intelligent traffic networking is realized.
4. The vehicle networking radio safety guarantee method is used for fusing wireless spectrum data acquired by a plurality of sensor type radio monitoring receivers arranged beside an automatic driving road, a basic signal library is built, signal matching and monitoring are carried out after the monitored real-time monitoring signals and known signals in the basic signal library are subjected to autocorrelation operation through autocorrelation functions, and further the automatic driving vehicle 600 can fully cover and guarantee radio communication, so that the safety of a vehicle networking system of the automatic driving vehicle is improved, and efficient emergency rescue is realized.
In summary, the system and the method for guaranteeing the radio safety of the internet of vehicles of the invention realize that the automatic driving vehicle can fully cover and guarantee the radio communication, and realize that the safety and the high-efficiency emergency rescue of the internet of vehicles of the automatic driving vehicle are guaranteed by improving the radio communication.
Drawings
FIG. 1 is a schematic diagram of a radio security system for Internet of vehicles;
FIG. 2 is a schematic structural diagram of a first embodiment of a car networking radio security system;
FIG. 3 is a schematic structural diagram of a second embodiment of a car networking radio security system;
FIG. 4 is a schematic structural diagram of a third embodiment of a car networking radio security system;
FIG. 5 is a flow chart of one embodiment of a method of car networking radio security;
FIG. 6 is an embodiment of one interference signal lookup for a car networking radio security method;
FIG. 7 is another embodiment of an interference signal lookup for a car networking radio security method;
wherein: 100-sensor type radio monitoring receiver, 200-internet of vehicles radio safety guarantee system cloud platform, 300-intelligent box, 400-on-vehicle on-line diagnosis mobile station, 500-automatic driving road, 600-automatic driving vehicle.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
As shown in the schematic structural diagrams of the car networking radio security system in the embodiments of fig. 1 and 2, the car networking radio security system includes a sensor type radio monitoring receiver and a cloud platform for uploading the monitored radio spectrum data to the car networking radio security system, wherein a plurality of the sensor type radio monitoring receivers are configured near the autopilot road 500 to form a seamless layout of the autopilot road radio monitoring for monitoring the radio spectrum data distribution on the autopilot road 500, and the sensor type radio security system is configured with the following components: the cloud platform of the internet of vehicles radio safety guarantee system fuses the received wireless spectrum data of at least three nearby sensor type radio monitoring receivers, and provides intelligent internet of vehicles radio safety monitoring signal data and early warning signal data for intelligent management and analysis of data based on big data. The cloud platform of the internet of vehicles radio security system can analyze the collected radio spectrum data and analyze the test data by utilizing a big data model. And the related radio interference warning and early warning information is sent to the user in a targeted manner by automatically generating a data analysis report so as to ensure the running safety of the vehicle.
In a specific implementation process, a database containing all radio situations on an automatic driving road is pre-established on the cloud platform 200 of the internet of vehicles radio security system and is used as a basic signal library; and the monitoring data of at least three roadbed sensor type radio monitoring receivers 100 are fused by adopting a nearby principle, so that the intelligent management and analysis of the wireless spectrum data based on big data are updated in real time, and the intelligent car networking radio safety monitoring data and the early warning signal data are provided, so that the arrangement density of radio signals is improved, the electromagnetic environment state on an automatic driving road can be monitored without blind spots, and the seamless layout of the automatic driving road radio monitoring is realized.
In some embodiments, referring to the embodiment shown in fig. 3, the security system further comprises a smart box 300, wherein the smart box 300 is configured to up-collect, process, store and manage wireless spectrum data received by the sensor-type radio monitoring receiver, and to implement software and hardware decoupling. In a specific implementation process, the configuration of the intelligent box 300 and the sensor-type radio monitoring receiver 100 may be one-to-one configuration, or one-to-many configuration, that is, one intelligent box 300 corresponds to a plurality of sensor-type radio monitoring receivers 100, and the intelligent box 300 is adaptively debugged according to external conditions such as geographic environmental factors or climate when implementing.
In some embodiments, the smart box processes and transmits the acquired data through the edge cloud cooperative operation system in the smart box, and meanwhile, the wireless spectrum data is stored in the cloud platform of the internet of vehicles radio security assurance system, so that the signal transmission efficiency is higher, and the transmission quality is stronger.
Unlike the above embodiments, in other embodiments, referring to fig. 4, the smart box is further configured on a vehicle-mounted on-line diagnosis mobile station, where the vehicle-mounted on-line diagnosis mobile station is configured to closely follow the fault autopilot smart car, and perform wireless data interaction with the fault autopilot smart car through a transmitting antenna and a receiving antenna, so as to ensure wireless fault diagnosis on the fault autopilot smart car in a local area network, and in a specific implementation process, as long as the fault vehicle has the vehicle-mounted on-line diagnosis mobile station within a certain range, wireless fault diagnosis can be performed on the fault vehicle of autopilot, thereby solving the problem of unstable local wireless signal of the fault vehicle.
In some embodiments, as shown in fig. 1, a plurality of the sensor-type radio monitoring receivers are arranged around an automatic driving road in a staggered manner, and the distance between any two adjacent sensor-type radio monitoring receivers is 4-8 km, so that better overall coverage can be achieved.
In other embodiments, as shown in fig. 2-4, the monitoring data of at least three sensor-type radio monitoring receivers are fused using a proximity principle, so as to update the intelligent management and analysis of the wireless spectrum data based on big data in real time, to provide real-time updated internet-of-vehicles radio safety monitoring signal data and early warning signal data.
As shown in fig. 5, the radio security assurance method for the internet of vehicles includes:
s1, acquiring wireless spectrum data from a plurality of sensor type radio monitoring receivers arranged beside an automatic driving road for fusion, and pre-establishing a database containing all radio situations on the automatic driving road on a cloud as a basic signal library;
s2, real-time monitoring of road radio situation to obtain real-time monitoring signals；
S3, monitoring the real-timeMonitoring signalAnd the known signal in the base signal library +.>Performing autocorrelation operation through an autocorrelation function;
s4, judging a monitored monitoring signal according to the result of the autocorrelation operation and a preset threshold valueWhether the signal is matched with a legal signal threshold value in the basic signal library or not, and updating the signal which is matched with the legal signal threshold value in the basic signal library into the basic signal library in real time, so that timely calibration data are obtained, and the monitoring efficiency and accuracy are improved. Wherein: the database of radio situations includes internet of vehicles signals, cellular wireless communication signals, broadcast television signals, E-call signals, etc., and may be the spectral distribution, time domain waveforms, etc. of the monitoring signals. The feature data in the basic signal library can be used for training a deep learning model, such as a Convolutional Neural Network (CNN) or a cyclic neural network (RNN), so as to realize different data deep processing, and then the deep learning model is applied to the processing of the monitored signal features to obtain the specific signal feature representation to be monitored. Through the process, whether the monitored signal is a legal signal or an illegal signal or not can be comprehensively judged by utilizing the deep learning model and the autocorrelation algorithm, so that corresponding actions can be triggered to ensure the safety of the system.
In other embodiments, when the monitored signal is legal in step S4, if the result of the autocorrelation operation is within the preset threshold range, the signal is determined to be legal, and the legal signal is updated to the base signal library; otherwise, step S5 is entered, other signals are determined, and step S6 is entered to trigger a corresponding alarm mechanism and record relevant data. The other signals may be further classified according to signal classification, where in radio management work, radio signals are generally classified into legal signals, illegal signals, unknown signals, known signals, illegal signals, new signals, and the like, and when implemented, the threshold setting is adapted according to the situation that needs to be identified. The recorded related information includes data such as time, location, signal characteristics, etc.
Where legal signals refer to transmitting station signals that have been registered in the station database after approval, as registered in the radio management committee. An illegal signal refers to a signal that has been ascertained to be unauthorized and is transmitted by a person. An unknown signal refers to a signal that has been found to be unreported at the station database and whose properties have not been ascertained. Known signals refer to signals that have been found to be unreported at the station database, but whose properties have been ascertained, such as: intermodulation signals, system glitches, special signals of a special department, etc. The offending signal is recorded in the station database, but the amplitude of the signal received at the monitoring station is compared with the history, and the legal signal exceeds a certain range. A new signal refers to a signal that has not been present in the previous monitoring process and has not been registered in the station database.
In some of these embodiments, as shown in FIG. 5, in step S3, the monitored real-time monitoring signal is monitoredAnd the known signal in the base signal library +.>Performing autocorrelation operation by using autocorrelation function to obtain monitored autocorrelation signalThe formula of (2) is:
（1）
wherein:is a monitored real-time monitoring signal, +.>Is a known signal in the base signal library, N is the time delay value, N is the length of the signal, < +.>Is by the known signal +.in the base signal library which is continuously modified by autocorrelation with time lag value n>May be a time-domain weighted signal;
the monitoring signals of the W sensor type radio monitoring receivers are fused by using a Kalman filter or an extended Kalman filter, and the fusion formula is as follows:
（2）
wherein:is the signal state estimate for the next instant after fusion, is->Is the signal state estimate at the current instant, +.>Is Kalman gain, < ->Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral amplitude of each frequency point at time k+1;
the position fusion formula for fusing the W sensor type radio monitoring receivers is as follows:
（3）
wherein: p (P) i Position estimation for a sensor type radio monitoring receiver, A i For the accuracy of a sensor-type radio monitoring receiver, P f The position estimate of the receiver is monitored for the sensor-after-fusion radio. The fusion in the system can flexibly call at least 3 sensor type radio monitoring receivers according to the nearby principle (aiming at the interference source) to carry out interference source positioning measurement, and the more the sensor type radio monitoring receivers are fused (weighted according to weights), the more accurate the positioning is, and the more accurate the radio signal monitoring is.
In other embodiments, when the other signal is an interference signal, it needs to be located, as shown in S7 and S8 in fig. 6, the method of locating is an adaptive locating algorithm:
according to the principle of nearby, the interference signals are fused with the nearby W sensor-type radio monitoring receiver signals to obtain the fused position estimation P f ，P f The fusion formula of (3);
in addition, when the other signals are interference signals, the signals need to be positioned, and the positioning can also be performed by using a multi-sensor fusion positioning algorithm shown in the embodiment of fig. 7: interference signal localization using adaptive filters, dynamically adjusting parameters based on real-time environmental conditions and signal data, estimating a next time adaptive monitored signal state estimate according to the following equation (4)：
（4）
Wherein:is the monitoring signal state estimation at the current moment, +.>Is an adaptive gain, < >>Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral magnitudes of the individual frequency bins at time k.
Then, it is judged by step S10If the signal is an interference signal, the positioning is performed, and if not, the operation is repeated by returning to step S9. The positioning algorithm improves the positioning accuracy and efficiency of the interference source in the radio safety guarantee system of the Internet of vehicles.
The embodiments of the present invention are disclosed as preferred embodiments, but not limited thereto, and those skilled in the art will readily appreciate from the foregoing description that various extensions and modifications can be made without departing from the spirit of the present invention.
Claims (10)
1. The radio safety guarantee system of the internet of vehicles is characterized in that the safety guarantee system comprises:
the sensor type radio monitoring receivers are configured on two sides of an automatic driving road, form an automatic driving road radio monitoring seamless layout, are used for monitoring radio spectrum data distribution on the automatic driving road, and are used for uploading the monitored radio spectrum data to a cloud platform of the internet of vehicles radio safety guarantee system;
wherein: the cloud platform of the internet of vehicles radio safety guarantee system fuses the received wireless spectrum data of at least three nearby sensor type radio monitoring receivers, and provides intelligent internet of vehicles radio safety monitoring signal data and early warning signal data for intelligent management and analysis of data based on big data.
2. The internet of vehicles radio security system of claim 1, wherein: the security system further comprises a smart box configured to up-collect, process, store and manage wireless spectrum data received by the sensor-type radio monitoring receiver, and to enable software and hardware decoupling to be built.
3. The internet of vehicles radio security system of claim 2, wherein: the intelligent box processes and transmits the acquired data through an edge cloud cooperative operation system in the intelligent box, and meanwhile, wireless spectrum data are stored in a cloud platform of the internet of vehicles radio security system.
4. The internet of vehicles radio security system of claim 3, wherein: the intelligent box is further configured on a vehicle-mounted on-line diagnosis mobile station, and the vehicle-mounted on-line diagnosis mobile station is used for following the fault autopilot intelligent automobile in a short distance and performing wireless data interaction with the fault autopilot intelligent automobile through a transmitting antenna and a receiving antenna.
5. The internet of vehicles radio security system of any of claims 1-4, wherein: the plurality of sensor-type radio monitoring receivers are arranged in the vicinity of an automatic driving road in a staggered manner, and the distance between any two adjacent sensor-type radio monitoring receivers is 4-8 km.
6. The internet of vehicles radio security system of claim 5, wherein: the monitoring data of at least three sensor-type radio monitoring receivers are fused by adopting a nearby principle.
7. The radio safety guarantee method for the Internet of vehicles is characterized by comprising the following steps of:
acquiring wireless spectrum data from a plurality of sensor type radio monitoring receivers arranged beside an automatic driving road for fusion, and pre-establishing a database containing all radio situations on the automatic driving road on a cloud as a basic signal library; and
real-time monitoring road radio situation, obtaining real-time monitoring signalThe method comprises the steps of carrying out a first treatment on the surface of the And
real-time monitoring signal to be monitoredAnd the known signal in the base signal library +.>Performing autocorrelation operation through an autocorrelation function; and
judging the monitored signal according to the result of the autocorrelation operation and a preset threshold valueWhether it matches a legal signal threshold in the base signal library.
8. The internet of vehicles radio security method of claim 7, wherein: if the result of the autocorrelation operation is within a preset threshold range, judging that the signal is legal, and updating the legal signal into a basic signal library; otherwise, judging other signals, triggering corresponding alarm mechanisms and recording related data.
9. The internet of vehicles radio security method of claim 8, wherein: real-time monitoring signal to be monitoredAnd the known signal in the base signal library +.>The autocorrelation operation is performed by an autocorrelation function,the monitored autocorrelation signal +.>The formula of (2) is:
（1）
wherein:is a monitored real-time monitoring signal, +.>Is a known signal in the base signal library, N is the length of the signal,is by the known signal +.in the base signal library which is continuously modified by autocorrelation with time lag value n>Is used for correcting signals;
the monitoring signals of the W sensor type radio monitoring receivers are fused by using a Kalman filter or an extended Kalman filter, and the fusion formula is as follows:
（2）
wherein:is the signal state estimate for the next instant after fusion, is->Is an estimate of the signal state at the current instant k, +.>Is Kalman gain, < ->Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral amplitude of each frequency point at time k+1;
the position fusion formula for fusing the W sensor type radio monitoring receivers is as follows:
（3）
wherein: p (P) i Position estimation for a sensor type radio monitoring receiver, A i For the accuracy of a sensor-type radio monitoring receiver, P f The position estimate of the receiver is monitored for the sensor-after-fusion radio.
10. The method for guaranteeing radio safety of internet of vehicles according to claim 9, wherein when the other signals are interference signals, the positioning is needed, and the positioning method is an adaptive positioning algorithm:
according to the principle of nearby, the interference signals are fused with the nearby W sensor-type radio monitoring receiver signals to obtain the fused position estimation P f ，P f The fusion formula of (3);
or the positioning method is a multi-sensor fusion positioning algorithm: interference signal localization using adaptive filters, dynamically adjusting parameters based on real-time environmental conditions and signal data, estimating a next time adaptive monitored signal state estimate according to the following equation (4)：
（4）
Wherein:is the monitoring signal state estimation at the current moment, +.>Is an adaptive gain, < >>Is a measure of the magnitude of the spectral data at the corresponding frequency point, +.>Is a measurement matrix of the spectral magnitudes of the individual frequency bins at time k.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410279639.1A CN117880820B (en) | 2024-03-12 | 2024-03-12 | Radio safety guarantee system and method for Internet of vehicles |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410279639.1A CN117880820B (en) | 2024-03-12 | 2024-03-12 | Radio safety guarantee system and method for Internet of vehicles |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117880820A true CN117880820A (en) | 2024-04-12 |
| CN117880820B CN117880820B (en) | 2024-05-17 |
Family
ID=90595371
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410279639.1A Active CN117880820B (en) | 2024-03-12 | 2024-03-12 | Radio safety guarantee system and method for Internet of vehicles |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117880820B (en) |
Citations (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103108003A (en) * | 2011-11-11 | 2013-05-15 | 北京开元智信通软件有限公司 | Mobile car networking cloud service platform system |
| CN103152114A (en) * | 2013-02-22 | 2013-06-12 | 云南大学 | Mobile coordinated radio monitoring method |
| CN103200525A (en) * | 2013-03-15 | 2013-07-10 | 安徽皖通科技股份有限公司 | System for collection and service of car networking roadside information |
| CN104994601A (en) * | 2015-06-01 | 2015-10-21 | 南京邮电大学 | 4G vehicle smart terminal system |
| CN105306910A (en) * | 2015-12-01 | 2016-02-03 | 苏州统购信息科技有限公司 | Internet of vehicles monitoring system |
| CN107332927A (en) * | 2017-07-30 | 2017-11-07 | 成都优瑞商务服务有限公司 | A kind of network-building method of new-energy automobile car networking system |
| CN108415057A (en) * | 2018-01-25 | 2018-08-17 | 南京理工大学 | A kind of relative positioning method that unmanned fleet cooperates with roadside unit |
| CN108710898A (en) * | 2018-04-24 | 2018-10-26 | 武汉理工大学 | Travel safety ensuring system based on Multi-sensor Fusion and method |
| CN108886767A (en) * | 2016-03-25 | 2018-11-23 | 松下电器（美国）知识产权公司 | The improved assignment of radio resource for vehicle communication |
| CN110491153A (en) * | 2019-07-23 | 2019-11-22 | 深圳市新桓信息技术研究院有限公司 | A kind of intelligent management system of car networking |
| CN112564797A (en) * | 2020-11-25 | 2021-03-26 | 重庆邮电大学 | Vehicle-mounted communication system based on LED communication |
| CN112770349A (en) * | 2020-12-24 | 2021-05-07 | 天津光电通信技术有限公司 | Intelligent monitoring analysis platform based on 5G wireless spectrum |
| CN112770325A (en) * | 2020-12-09 | 2021-05-07 | 华南理工大学 | Cognitive Internet of vehicles spectrum sensing method based on deep learning |
| US20210204302A1 (en) * | 2019-12-26 | 2021-07-01 | Intel Corporation | Network component, system and method |
| CN113347254A (en) * | 2021-06-02 | 2021-09-03 | 安徽工程大学 | Intelligent traffic control car networking system based on V2X and control method thereof |
| CN113362606A (en) * | 2021-07-23 | 2021-09-07 | 重庆智和慧创科技有限公司 | Car road is anticollision integrated control system in coordination based on car networking |
| CN113655275A (en) * | 2021-08-27 | 2021-11-16 | 中国科学院云南天文台 | Space radio environment measurement and control device and system |
| CN115639818A (en) * | 2022-10-11 | 2023-01-24 | 重庆车联网科技有限公司 | Vehicle-road cooperative big data intelligent system |
| CN116158117A (en) * | 2020-06-25 | 2023-05-23 | 交互数字专利控股公司 | Method, apparatus and system for multiplexing sensing and measurement data between control plane and user plane |
| CN116170347A (en) * | 2022-12-29 | 2023-05-26 | 信通院车联网创新中心(成都)有限公司 | Time-frequency performance test method for road side perception system of Internet of vehicles |
| KR20230100477A (en) * | 2021-12-28 | 2023-07-05 | 주식회사 디에이치오토웨어 | Method and apparatus for data security for autonomous vehicle |
| CN116412854A (en) * | 2022-01-05 | 2023-07-11 | 深圳市威宇智通科技有限公司 | Road surface information data acquisition system based on 5G car networking |
| CN117558129A (en) * | 2023-11-14 | 2024-02-13 | 长沙云软信息技术有限公司 | Intelligent positioning system and method for expressway construction |
-
2024
- 2024-03-12 CN CN202410279639.1A patent/CN117880820B/en active Active
Patent Citations (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103108003A (en) * | 2011-11-11 | 2013-05-15 | 北京开元智信通软件有限公司 | Mobile car networking cloud service platform system |
| CN103152114A (en) * | 2013-02-22 | 2013-06-12 | 云南大学 | Mobile coordinated radio monitoring method |
| CN103200525A (en) * | 2013-03-15 | 2013-07-10 | 安徽皖通科技股份有限公司 | System for collection and service of car networking roadside information |
| CN105516294A (en) * | 2013-03-15 | 2016-04-20 | 安徽皖通科技股份有限公司 | Internet of Vehicles road side information acquisition and issuing road network structure |
| CN104994601A (en) * | 2015-06-01 | 2015-10-21 | 南京邮电大学 | 4G vehicle smart terminal system |
| CN105306910A (en) * | 2015-12-01 | 2016-02-03 | 苏州统购信息科技有限公司 | Internet of vehicles monitoring system |
| CN108886767A (en) * | 2016-03-25 | 2018-11-23 | 松下电器（美国）知识产权公司 | The improved assignment of radio resource for vehicle communication |
| CN107332927A (en) * | 2017-07-30 | 2017-11-07 | 成都优瑞商务服务有限公司 | A kind of network-building method of new-energy automobile car networking system |
| CN108415057A (en) * | 2018-01-25 | 2018-08-17 | 南京理工大学 | A kind of relative positioning method that unmanned fleet cooperates with roadside unit |
| CN108710898A (en) * | 2018-04-24 | 2018-10-26 | 武汉理工大学 | Travel safety ensuring system based on Multi-sensor Fusion and method |
| CN110491153A (en) * | 2019-07-23 | 2019-11-22 | 深圳市新桓信息技术研究院有限公司 | A kind of intelligent management system of car networking |
| US20210204302A1 (en) * | 2019-12-26 | 2021-07-01 | Intel Corporation | Network component, system and method |
| CN116158117A (en) * | 2020-06-25 | 2023-05-23 | 交互数字专利控股公司 | Method, apparatus and system for multiplexing sensing and measurement data between control plane and user plane |
| CN112564797A (en) * | 2020-11-25 | 2021-03-26 | 重庆邮电大学 | Vehicle-mounted communication system based on LED communication |
| CN112770325A (en) * | 2020-12-09 | 2021-05-07 | 华南理工大学 | Cognitive Internet of vehicles spectrum sensing method based on deep learning |
| CN112770349A (en) * | 2020-12-24 | 2021-05-07 | 天津光电通信技术有限公司 | Intelligent monitoring analysis platform based on 5G wireless spectrum |
| CN113347254A (en) * | 2021-06-02 | 2021-09-03 | 安徽工程大学 | Intelligent traffic control car networking system based on V2X and control method thereof |
| CN113362606A (en) * | 2021-07-23 | 2021-09-07 | 重庆智和慧创科技有限公司 | Car road is anticollision integrated control system in coordination based on car networking |
| CN113655275A (en) * | 2021-08-27 | 2021-11-16 | 中国科学院云南天文台 | Space radio environment measurement and control device and system |
| KR20230100477A (en) * | 2021-12-28 | 2023-07-05 | 주식회사 디에이치오토웨어 | Method and apparatus for data security for autonomous vehicle |
| CN116412854A (en) * | 2022-01-05 | 2023-07-11 | 深圳市威宇智通科技有限公司 | Road surface information data acquisition system based on 5G car networking |
| CN115639818A (en) * | 2022-10-11 | 2023-01-24 | 重庆车联网科技有限公司 | Vehicle-road cooperative big data intelligent system |
| CN116170347A (en) * | 2022-12-29 | 2023-05-26 | 信通院车联网创新中心(成都)有限公司 | Time-frequency performance test method for road side perception system of Internet of vehicles |
| CN117558129A (en) * | 2023-11-14 | 2024-02-13 | 长沙云软信息技术有限公司 | Intelligent positioning system and method for expressway construction |
Non-Patent Citations (5)
| Title |
|---|
| BO DENG等: ""A Survey on Integration of Network Communication into Vehicle Real-Time Motion Control"", 《 IEEE COMMUNICATIONS SURVEYS & TUTORIALS ( VOLUME: 25, ISSUE: 4, FOURTHQUARTER 2023)》, 14 July 2023 (2023-07-14) * |
| 俞毅等: ""车联网路侧信息采集与服务平台解决方案"", 《中国交通信息化》, 10 August 2011 (2011-08-10) * |
| 刘琪等: ""基于5G的车联网体系架构及其应用研究"", 《移动通信》, 15 November 2019 (2019-11-15) * |
| 张永宏: ""基于5G车联网的智慧交通平台搭建"", 《通信与信息技术》, 10 December 2022 (2022-12-10) * |
| 韩将星: ""5G时代无线电监测站智能互联网平台技术研究"", 《通信技术》, 31 May 2020 (2020-05-31), pages 1 - 4 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117880820B (en) | 2024-05-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112216097A (en) | Method and device for detecting blind area of vehicle | |
| US7986247B2 (en) | Advisory system for previewing local conditions on a highway | |
| KR101493360B1 (en) | Method of vehicle driving managing through detection state change of around cars and system for it | |
| US9344856B2 (en) | Detection of false vehicle-to-vehicle emergency brake light messages | |
| US10049568B2 (en) | Method for identifying a vehicle-borne transmitter | |
| Haferkamp et al. | Radio-based traffic flow detection and vehicle classification for future smart cities | |
| CN105303886A (en) | Traffic information early warning processing method and apparatus, terminal and early warning server | |
| CN114175126A (en) | Object classification based on wireless communication | |
| US20230097606A1 (en) | System, device, method and program that predict communication quality | |
| CN110599791A (en) | Information monitoring method, device and equipment | |
| Sharma et al. | Pearson correlation analysis to detect misbehavior in vanet | |
| al Janaby et al. | Tracking high-speed users using SNR-CQI mapping in LTE-A networks | |
| CN116299389A (en) | Connection vehicle-based road surface quality determination | |
| Aljeri et al. | A probabilistic neural network-based road side unit prediction scheme for autonomous driving | |
| CN117880820B (en) | Radio safety guarantee system and method for Internet of vehicles | |
| Kim et al. | VANET Jamming and Adversarial Attack Defense for Autonomous Vehicle Safety. | |
| Ma et al. | Performance analysis of joint radar and communication enabled vehicular ad hoc network | |
| US20030030571A1 (en) | Collaborative speed detection warning device | |
| CN116880472B (en) | Intelligent detection system for travel obstacle of open-air unmanned mine car | |
| Sonny et al. | Deep learning-based smart parking solution using channel state information in LTE-based cellular networks | |
| US11307578B2 (en) | Manual drive changing notification apparatus and method of vehicle and vehicle including the same | |
| Kihei et al. | Predicting car collisions using rssi | |
| CN115063980B (en) | Self-adaptive vehicle abnormal running detection method and device and terminal equipment | |
| CN108631892B (en) | Method for detecting satellite radio broadcast interference at a vehicle | |
| CN114640947A (en) | Real-time data transmission system in Internet of vehicles |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |