Network verification method and device, electronic equipment and storage medium

Abstract

The invention provides a network verification method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a node type for verifying a target network and a plurality of verification units corresponding to the target network according to the access layer bandwidth of the target network and / or the credibility requirement of a current verification task, and then carrying out the verification of the target network in the plurality of verification units, selecting one verification unit with the verification duration smaller than a duration threshold value as a target verification unit, obtaining node information and track information corresponding to the target verification unit, and then determining a verification result of a track point at the previous moment based on tracks between every two different moments in the node information and the track information, and under the condition that the verification duration of the track information reaches the duration threshold, determining the verification result obtained in the verification duration as the verification result of the target verification unit, and re-determining the target verification unit until the verification durations of all the verification units reach the duration threshold, thereby obtaining the verification result of the target network. Therefore, verification of the sensing result of the base station is realized.

Description

Technical Field

[0001] This application relates to the field of wireless technology, and in particular to a network verification method, apparatus, electronic device, and storage medium. Background Technology

[0002] Base stations are the core carriers for realizing integrated communication and sensing functions. By reusing hardware, spectrum, and other resources, base stations can perform traditional data communication while additionally possessing the ability to detect, locate, and track surrounding targets. Verification of the communication network and sensing network is crucial for ensuring the reliability of results and improving performance and security. Summary of the Invention

[0003] This application aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the first objective of this application is to propose a network verification method that dynamically selects the node type for verification based on bandwidth and reliability requirements, corrects the trajectory of the previously output sensing results of the base station based on the posterior information transmitted by the base station, and verifies different units covered by the network using a polling method. This enables the verification of the base station sensing results to be completed by a third party, improving the flexibility of network verification, making the verification results more accurate, and thus improving the reliability of the sensing network.

[0005] The second objective of this application is to provide a network verification device.

[0006] The third objective of this application is to propose an electronic device.

[0007] The fourth objective of this application is to provide a computer-readable storage medium.

[0008] The fifth objective of this application is to provide a computer program product.

[0009] To achieve the above objectives, a network verification method is proposed in the first aspect of this application, comprising: Based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task, determine the node type of the target network to be verified and the multiple verification units corresponding to the target network, wherein the node type is an in-phase orthogonal IQ node or a point cloud node. Among the plurality of verification units, a verification unit whose verification duration is less than the duration threshold is randomly selected as the target verification unit; The base station acquires node information corresponding to the node type collected within the target verification unit, as well as trajectory information obtained by the base station from processing the node information. Based on the node information and the trajectory between every two different times in the trajectory information, the trajectory point of the previous time in the two different times is verified to determine the verification result of the trajectory point of the previous time. If the verification time for the trajectory information reaches the time threshold, the verification result determined within the verification time is determined as the verification result of the target verification unit, and the operation of determining the target verification unit is returned until the verification time of all verification units reaches the time threshold, and the verification result of the target network is obtained.

[0010] To achieve the above objectives, a second aspect of this application provides a network verification device, comprising: The first determining module is used to determine the node type for verifying the target network and multiple verification units corresponding to the target network based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task, wherein the node type is an in-phase orthogonal IQ node or a point cloud node. The second determining module is used to randomly select a verification unit whose verification time is less than a time threshold from the plurality of verification units as the target verification unit; The acquisition module is used to acquire node information corresponding to the node type collected by the base station in the target verification unit, and trajectory information obtained by the base station from processing the node information; The third determining module is used to verify the trajectory point of the previous time in the two different times based on the node information and the trajectory between every two different times in the trajectory information, and to determine the verification result of the trajectory point of the previous time. The fourth determining module is used to determine the verification result determined within the verification time as the verification result of the target verification unit when the verification time of the trajectory information reaches the time threshold, and return to execute the operation of determining the target verification unit until the verification time of all verification units reaches the time threshold, so as to obtain the verification result of the target network.

[0011] To achieve the above objectives, a third aspect of this application provides an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the network verification method as described in the first aspect embodiment.

[0012] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the network verification method as described in the first aspect embodiment.

[0013] To achieve the above objectives, a fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the network verification method as described in the first aspect embodiment.

[0014] The network verification method, apparatus, electronic device, and storage medium provided in this application determine the node type to be verified and multiple verification units corresponding to the network to be verified based on the access layer bandwidth of the network to be verified and the reliability requirements of the verification task. Multiple verification units are then sequentially verified using a polling method, ensuring that the verification time of each verification unit meets the time threshold. Furthermore, during the verification of each verification unit, node information corresponding to the node type in the base station and trajectory information output by the base station are obtained. The trajectory points corresponding to each moment in the trajectory information are verified. This allows for the verification of base station sensing results in a third-party system, improving the flexibility of sensing network verification, increasing the accuracy of the verification results, and ultimately enhancing the reliability of the sensing network.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a network verification method provided in an embodiment of this application. Figure 2 A schematic diagram illustrating a post-hoc correction provided in an embodiment of this application; Figure 3 This is a flowchart illustrating another network verification method provided in an embodiment of this application; Figure 4 A schematic diagram illustrating another a posteriori correction provided in an embodiment of this application; Figure 5 A schematic diagram of a network architecture compatible with multiple trust enhancement schemes is provided for an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a network verification device provided in an embodiment of this application. Detailed Implementation

[0017] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0018] The network verification method and apparatus of this application are described below with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart illustrating a network verification method provided in an embodiment of this application.

[0020] Currently, for communication networks, operators can obtain network status data through feedback from third-party terminals. However, for sensing networks, the entire process of target feature calculation is completed within the base station. Operators have no other channels to obtain network status data and lack an effective network monitoring mechanism. Furthermore, the sensing performance of sensing base stations is greatly affected by network parameters, and the sensing results are probabilistic. After the sensing function is activated, there is often no true value for the target, and the system cannot confirm the authenticity and validity of the sensing results, leading to doubts about the reliability of the base station's sensing results.

[0021] To address this issue, this application provides a network verification method that achieves superior sensing performance compared to base stations by using third-party data processing based on in-phase and quadrature (IQ) nodes or point cloud nodes, thereby enabling verification and status monitoring of base station sensing results.

[0022] like Figure 1 As shown, the network verification method may include the following steps: Step 101: Determine the node type of the target network and the multiple verification units corresponding to the target network based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task.

[0023] The target network refers to the sensing network of the sensing base station.

[0024] The node types are either in-phase orthogonal IQ nodes or point cloud nodes.

[0025] The verification unit can be selected at different levels according to the data volume corresponding to the node type. It can be at the cell level, cluster level (such as the Master Building Baseband Unit (MasterBBU) level) or higher cluster level (such as the Operations and Maintenance Center (OMC) level).

[0026] In this embodiment, the sensing base station utilizes two time slots in the communication frame structure to complete low-altitude target sensing, outputting the distance, angle, and velocity information of the sensed target, thus extending the base station's communication capabilities to sensing capabilities. When the sensing function is enabled, the base station's active antenna unit (AAU) transmits electromagnetic signals and receives the target's reflected echo. The echo is mixed, filtered, and sampled using analog-to-digital (AD) conversion to become a digital IQ signal. Then, the IQ data is processed by the slave building baseband unit (slaveBBU), undergoing range velocity (RV) spectrum estimation, target detection, trajectory tracking, and target classification to obtain the target trajectory and attribute information for a single station. Subsequently, the master baseband unit (MasterBBU) is responsible for fusing and deduplicating the trajectories of multiple stations, reporting the deduplication result to the sensing function (SF) network element. The SF forwards the relevant information to the application platform. In addition, the MasterBBU can also connect to the network management system to periodically send cell quality information.

[0027] Because the signal processing between IQ nodes and point cloud nodes in a base station involves the entire signal processing process, including RV spectrum estimation, CFAR detection, and distance and angle measurement, these processing modules are coupled, making it difficult to extract intermediate data suitable for the verification platform. Furthermore, the process between point cloud nodes and single-station trajectory generation also involves the extraction and processing of features from discrete detection points to the single-station sensed object. Therefore, when verifying the sensing results of a base station, the verification node can have two options: IQ data nodes or point cloud data. The closer the data is to the underlying layer, the less information loss; the larger the data volume, the greater its gain when used for verification.

[0028] In this embodiment, IQ data is the raw digital signal, which contains all channel information in the electromagnetic reflection path. Therefore, when using IQ nodes for network verification, the gain is high, but the data transmission pressure is large. Point cloud nodes can only verify the status and performance of the base station data processing part, resulting in a lower verification gain, but the data volume is small and the transmission pressure is small. Therefore, the node type used for network verification can be dynamically and flexibly selected according to the access layer bandwidth of the target network and / or the reliability requirements of the current verification task. For example, in key protection areas, the reliability requirements of the verification task are high. If the access layer bandwidth can meet the IQ data transmission requirements, IQ node verification is preferred. In other scenarios, point cloud node verification can be selected.

[0029] Optionally, if the access layer bandwidth is greater than or equal to the first threshold, the node type can be determined to be an IQ node.

[0030] The first threshold is a value greater than the minimum bandwidth required for IQ data transmission.

[0031] In this embodiment of the application, when the access layer bandwidth is greater than or equal to the first threshold, the transmission of IQ data will not cause service failure due to insufficient service and can reserve redundant bandwidth to cope with bandwidth fluctuations and other issues, and has high stability. Therefore, at this time, the node type of network verification can be determined to be an IQ node.

[0032] Alternatively, if the access layer bandwidth is less than the first threshold, the node type can be determined as a point cloud node.

[0033] Alternatively, if the credibility requirement is greater than the second threshold and the access layer bandwidth is greater than the third threshold, the node type is determined to be an IQ node.

[0034] The second threshold can be a value that can be dynamically set according to actual needs. For example, in specific implementation, the credibility requirements of different verification tasks can be classified. When the credibility requirement level of a certain verification task is greater than a certain level, it is determined that the credibility requirement is greater than the second threshold. Alternatively, it can be determined by other means. This application does not limit this.

[0035] The third threshold is less than the first threshold. The third threshold is the minimum bandwidth required to meet IQ data transmission requirements, such as 20 gigabits per second (Gbps).

[0036] In this embodiment of the application, when the credibility requirement is greater than the second threshold and the access layer bandwidth is greater than the third threshold, in order to ensure the credibility of the verification, the node type of the network verification can be determined to be an IQ node.

[0037] In this embodiment, the IQ node data exhibits almost no information loss, but the data volume is large, requiring high transmission bandwidth. For example, based on a sampling rate of 32.72 MHz and a 20% time-domain resource utilization rate, the IQ data volume of a single cell is approximately 20 Gbps. Therefore, due to bandwidth limitations, the verification platform can only verify a single cell at any given time. When the base station sensing network covers multiple cells, each cell can be designated as a verification unit, and a round-robin verification mode can be adopted for multiple cells.

[0038] Because the amount of point cloud data is relatively small, the verification platform can verify multiple cells simultaneously. Therefore, when the node type is determined to be a point cloud node, the verification unit corresponding to the target network can be at the cluster level. For example, if the deployment location is at the MasterBBU level, the verification platform can be responsible for the status and performance verification of all base stations within its cluster. If it is at the OMC level, a cluster polling mechanism is required to complete the verification of all clusters within its jurisdiction.

[0039] In this embodiment, by dynamically selecting IQ or point cloud verification nodes based on network bandwidth and verification reliability requirements, different scenario requirements can be met, and the flexibility of network verification can be improved.

[0040] Step 102: Among multiple verification units, randomly select a verification unit whose verification duration is less than the duration threshold as the target verification unit.

[0041] The duration threshold is the minimum time required to determine whether each verification unit has been fully verified, and it can be dynamically set according to actual needs.

[0042] In this embodiment of the application, in order to ensure the accuracy and reliability of the verification results and to fully reflect the network performance, a sufficient verification time is required when verifying each verification unit to avoid the randomness of the verification results. Therefore, verification units with a verification time of less than the time threshold can be selected sequentially from multiple verification units as target verification units for verification.

[0043] It should be noted that, in this embodiment of the application, after the verification is started, the network management system or operation and maintenance center can be used to monitor the verification time of each verification unit. If the time threshold is not reached, the monitoring continues. If the time threshold is reached and there are unverified verification units, the gateway can select an unverified verification unit and generate a verification start command for that verification unit. Then, after receiving the verification start command sent by the network management system, the verification platform can determine the verification unit contained in the command as the target verification unit.

[0044] In this embodiment, a multi-station polling verification mechanism is established. Through polling-based single-station or cluster-level verification, low-cost full network verification coverage can be achieved, thereby improving the quality of network verification.

[0045] Step 103: Obtain the node information corresponding to the node type collected by the base station in the target verification unit, and the trajectory information obtained by the base station from processing the node information.

[0046] Among them, node information refers to the information obtained by the base station at this type of node.

[0047] In this embodiment, the node information corresponding to the IQ node is the original digital signal, which contains all channel information in the electromagnetic reflection path. Based on this digital signal, information such as the position, velocity, and attributes of the target object can be obtained through signal processing and data processing. The node information corresponding to the IQ node transmitted by the base station to the verification platform in real time may include at least one of the following fields: timestamp, IQ digital signal (I-channel and Q-channel), array longitude, array latitude, array azimuth, array tilt, array flip angle, transmit beam pointing (horizontal or vertical), transmit beam identifier, number of BF beams, and BF beam pointing (horizontal or vertical).

[0048] It should be noted that, in addition to the data transmitted in real time as mentioned above, the base station can also provide waveform configuration parameters and beam pattern information to the verification platform as supporting basic information.

[0049] In this embodiment, the node information corresponding to the point cloud node can include the characteristic (distance, angle, velocity) information of each scattering point in the reflection path. Third-party verification based on the point cloud node data can realize the result verification of the base station data processing part. The node information corresponding to the point cloud node transmitted by the base station to the verification platform in real time can include at least one of the following fields: timestamp, detection point distance, detection point velocity, detection point azimuth, detection point vertical angle, detection point signal-to-noise ratio, array longitude, array latitude, array azimuth, array tilt angle, array flip angle, transmitted beam pointing (horizontal or vertical), and transmitted beam identifier. The amount of data of the point cloud node is related to the number of detection points that pass the detection threshold.

[0050] Trajectory information refers to the single-station trajectory data obtained by the base station after processing IQ data or point cloud data through the slave BBU. The trajectory information may include the trajectory results perceived by the base station on the target at each time moment, such as target position information and target speed information.

[0051] In this embodiment of the application, the base station can continuously transmit electromagnetic signals to the target verification unit, receive the reflected echo of the sensing target in the target verification unit, and obtain the node information corresponding to different node types and the trajectory information of the generated sensing target through data processing, and can transmit this information to the verification platform in real time.

[0052] Step 104: Based on the node information and the trajectory between every two different times in the trajectory information, verify the trajectory point of the previous time in the two different times and determine the verification result of the trajectory point of the previous time.

[0053] In this embodiment, although the base station needs to output information such as the distance, angle, and speed of the sensed target in real time, the verification platform, as a state and performance verification device, does not need to provide real-time processing results. It can leverage its time-based processing advantage to gain more performance. Therefore, posterior information can be obtained through the delayed output of the base station, and the base station's decision in the previous moment can be corrected, improving the accuracy of the base station's sensing output results and thus enabling the verification of the base station's sensing network.

[0054] In this embodiment, the trajectory result corresponding to the data received by the base station at a certain moment can be output after a certain time unit delay. Therefore, the trajectory information output after a certain time unit interval at that moment can be used as the posterior information at that moment to correct the base station's perception decision at that moment. At that moment (i.e., the previous moment), the base station can determine at least one point associated with the perceived target by processing node information. These points may contain noise. Subsequently, the base station's perception network can choose to associate one of these points to determine the trajectory of the perceived target. When verifying the trajectory point at the previous moment, the verification result of the trajectory point at the previous moment can be obtained by comparing the trajectory features within the time period of the two moments before and after, and by updating the trajectory point associated with the previous moment. The verification result may include information such as whether the base station's trajectory perception decision is correct and the correct trajectory position.

[0055] The following is based on Figure 2 Let's take an example to illustrate the process of verifying the trajectory points of the earlier time point between two different time points. Figure 2 This is a schematic diagram of a post-hoc correction provided in an embodiment of this application.

[0056] exist Figure 2 In this context, time t0 is the time preceding the target verification. If the trajectory result at time t0 (i.e., the true trajectory of the target perceived at time t0) is output after a delay of T time units, the trajectory between time t0 and time tT can be used as posterior information to correct the decision at time t0.

[0057] In this embodiment of the application, by processing the node information, it can be determined that at time t0, there are two target locations that the trajectory can be associated with. Figure 2 The points are labeled as associated target 1 and associated target 2. When verifying the trajectory points at time t0, the trajectory from t0-T (i.e., the time T time units before time t0) to tT can be divided into three segments, such as... Figure 2 The tracks are labeled as trajectory 1, trajectory 2, and trajectory 3. Then, the features of each trajectory segment are calculated, denoted as feature vector 1, feature vector 2, and feature vector 3. Components in the feature vectors can include target velocity, target radar cross section (RCS), target heading, etc. Next, the similarity between each pair of feature vectors can be calculated. Based on the similarity, it is determined whether there is an association error between the associated trajectory points on the trajectory at time t0. If an error is found, other associated targets are replaced, and the trajectory features are recalculated, thus obtaining the verification result for the trajectory points at time t0.

[0058] It should be noted that time t0 is not a fixed time, but a time that changes over time. For example, a sliding time window can be used to achieve dynamic monitoring and verification of continuous time intervals, so that the trajectory information output by the base station at multiple times can be corrected within the verification period, and the verification of the corresponding verification unit can be completed.

[0059] In this embodiment, by delaying the output to obtain posterior information and correcting previous decisions, the impact of clutter on detection performance can be reduced and the accuracy of the verification results can be improved.

[0060] Step 105: If the verification time for trajectory information reaches the time threshold, the verification result determined within the verification time is determined as the verification result of the target verification unit. Then, return to execute the operation of determining the target verification unit until the verification time of all verification units reaches the time threshold, and obtain the verification result of the target network.

[0061] In this embodiment, by determining the node type to be verified and multiple verification units corresponding to the network to be verified based on the access layer bandwidth of the network to be verified and the reliability requirements of the verification task, multiple verification units are sequentially verified in a round-robin manner, so that the verification time of each verification unit meets the time threshold. When verifying each verification unit, the node information corresponding to the node type in the base station and the trajectory information output by the base station are obtained, and the trajectory points corresponding to each moment in the trajectory information are verified. Thus, the verification of the base station perception results can be realized in a third-party system, which improves the flexibility of the perception network verification, makes the verification results more accurate, and helps to improve the reliability of the perception network.

[0062] This embodiment provides another network verification method. Figure 3 This is a flowchart illustrating another network verification method provided in an embodiment of this application.

[0063] like Figure 3 As shown, the network verification method may include the following steps: Step 301: Determine the node type of the target network and the multiple verification units corresponding to the target network based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task.

[0064] Step 302: Among multiple verification units, randomly select a verification unit whose verification duration is less than the duration threshold as the target verification unit.

[0065] Step 303: Obtain the node information corresponding to the node type collected by the base station in the target verification unit, and the trajectory information obtained by the base station from processing the node information.

[0066] For a detailed description of steps 301 to 303 above, please refer to other embodiments of this application, which will not be repeated here.

[0067] Step 304: Verify the trajectory points at each moment in the trajectory information based on a sliding window of a preset time length, and determine the end time of each sliding window as the first moment to be verified.

[0068] In this embodiment, the time length corresponding to the sliding window can be dynamically set as needed, for example, it can be one-quarter of the time period of the base station delay output. The sliding step size of the sliding window can also be dynamically set as needed, and this application does not limit it.

[0069] Step 305: Based on the first time point and the time period length of the base station delay output, determine the second time point for the first time point verification reference.

[0070] In this embodiment, the time period length of the base station delay output can be determined based on the base station's attributes or by statistical analysis of the base station's historical operating data. The time interval of one time period after the first time moment is determined as the second time moment for verification reference.

[0071] Step 306: Based on the information corresponding to the first moment in the node information and the trajectory between the first and second moments in the trajectory information, verify the trajectory points at the first moment in the trajectory information to obtain the verification result.

[0072] Optionally, the starting time of the sliding window corresponding to the first moment can be determined as the third moment, and the fourth moment can be determined based on the first moment and the time period length.

[0073] The fourth moment occurs before the third moment.

[0074] In this embodiment of the application, the moment that is one time period before the first moment can be determined as the fourth moment. For example, if the first moment is t0 and the time period is 4, the fourth moment is t0-4.

[0075] Then, determine the first feature vector of the trajectory between the first and second time points, the second feature vector of the trajectory between the third and first time points, and the third feature vector of the trajectory between the fourth and third time points. Based on each pair of feature vectors in the first, second, and third feature vectors, calculate the distance between the feature vectors.

[0076] In this embodiment, the trajectory between the first and second moments, the trajectory between the third and first moments, and the trajectory between the fourth and third moments can be determined from the trajectory information. Then, feature extraction is performed on each trajectory to extract the distance, velocity, and RCS of the trajectory, etc., to obtain the feature vector corresponding to the trajectory. Afterwards, the distance between every two feature vectors can be calculated using the following formula (1).

[0077] (1) Where X and Y represent two different feature vectors, such as the first feature vector and the second feature vector, and D is the distance between these two feature vectors. D represents the covariance of features X and Y. The smaller D is, the higher the similarity between X and Y.

[0078] Subsequently, if the distance does not meet the preset conditions, based on the information corresponding to the first moment in the node information, at least one candidate trajectory point associated with the trajectory point at the first moment can be determined, and a candidate trajectory point can be randomly selected to update the trajectory information.

[0079] Optionally, in the embodiments of this application, the preset condition can be that the distance between the first feature vector and the third feature vector is less than a distance threshold, and the distance between the first feature vector and the second feature vector, and the distance between the second feature vector and the third feature vector are both greater than or equal to the distance threshold.

[0080] The distance threshold, denoted as H, can be a custom value set as needed. If the value is less than H, it can be determined that X and Y have the same characteristics; otherwise, in If the value is greater than or equal to H, it can be determined that the characteristics of X and Y are inconsistent.

[0081] In this embodiment, if the distance between the first feature vector and the third feature vector is less than a distance threshold, it indicates that the trajectory between the first and second moments is consistent with the trajectory between the fourth and third moments. However, if the distance between the first and second feature vectors, and the distance between the second and third feature vectors, are both greater than or equal to the distance threshold, it indicates that there may be an error in the trajectory point association at the first moment. Therefore, it is necessary to select new trajectory points, perform secondary trajectory association on the first moment, and update the trajectory information.

[0082] It should be noted that if the distance meets the preset conditions, there is no need to perform secondary track association. The result of primary track association is output, that is, the verification result is that the base station's perception of the target in the verification unit is correct at the first moment.

[0083] Finally, based on the updated trajectory information, the operation of determining the feature vector can be returned until the distance corresponding to any candidate trajectory point meets the preset conditions or there are no candidate trajectory points that have not been updated, and the verification result is obtained.

[0084] In this embodiment of the application, when all candidate trajectory points are used to update trajectory information and the distance calculated each time does not meet the preset conditions, the trajectory at the first moment can be predicted, such as using the trajectory between the first and second moments, and the trajectory between the fourth and third moments, to predict the trajectory from the third moment to the first moment.

[0085] The following is based on Figure 4 Taking the example of the process of verifying the trajectory points at the first moment, Figure 4 This is a schematic diagram illustrating another a posteriori correction provided in an embodiment of this application.

[0086] exist Figure 4 In the diagram, each point represents a target detection point sensed by the base station at a certain distance and time. t1 is the first time point, the sliding window duration is 1, and the feature vector of the trajectory between t0 and t1 is P1=[R1,V1,...]. The trajectory direction is deflected north by 45°. At time t1, two trajectory points appear around the trajectory, located at... Figure 4 The targets are labeled A1 and B1. In the first round of track association, the base station selects clutter point B1 as the associated target, and the target trajectory is briefly deflected by the clutter. At this time, with a delay output period of 4, the decision result at time t0 can be corrected using time t4.

[0087] First, at time t4, we can statistically analyze the trajectory features of three time periods: t0-4 to t0-2, t0-1 to t0, and t1 to t4 (denoted as trajectory 1, trajectory 2, and trajectory 3, respectively). Then, according to the formula (1) above, we can calculate the distance between the feature vectors of each pair of trajectories. We can determine that trajectory 3 and trajectory 1 have similar features, and their trajectories are both 45°, while the heading of trajectory 2 has a large deviation. Therefore, we can return to the trajectory association process at time t0, select point A1 as the association target, and perform trajectory tracking until time t4, then recalculate the trajectory features of trajectory 1, trajectory 2, and trajectory 3. With point A1 as the association target, we can determine that the features of trajectory 1, trajectory 2, and trajectory 3 are all similar, and output the trajectory verification result at time t0.

[0088] Step 307: If the verification time for trajectory information reaches the time threshold, the verification result determined within the verification time is determined as the verification result of the target verification unit. Then, return to execute the operation of determining the target verification unit until the verification time of all verification units reaches the time threshold, and obtain the verification result of the target network.

[0089] For a detailed description of step 307 above, please refer to other embodiments of this application, which will not be repeated here.

[0090] In this embodiment, by obtaining posterior information through delayed output and correcting previous decisions, the impact of clutter on detection performance can be reduced and the accuracy of verification results can be improved.

[0091] It should be noted that, in this embodiment of the application, after the verification platform starts verification, the verification duration of each verification unit can also be monitored using a network management system or operation and maintenance center. The network management system is responsible for configuring the start and stop of verification, and the verification platform executes verification-related operations according to the instructions of the network management system.

[0092] Optionally, instructions can be queried periodically based on preset time intervals.

[0093] The preset time interval can be a value that can be dynamically set according to the actual verification needs, and this application does not impose any restrictions on it.

[0094] Then, upon receiving the verification start command sent by the network management system, the first identification information in the verification start command is determined. If the first identification information does not match the second identification information of the target verification unit currently being verified, the verification unit corresponding to the first identification information is determined as the new target verification unit.

[0095] Afterwards, feedback information associated with the verification start command can be sent to the network administrator.

[0096] In this embodiment, the verification platform can periodically query the network management command. If there is no new verification command, it maintains the current verification status of the verification unit. If a new verification command is received, it initializes, starts the verification work of the new verification unit, and sends the verification result to the network management after the verification is completed.

[0097] In this embodiment, after the verification process is initiated, the network management system can periodically monitor whether the verification units currently in the verification state have reached the specified verification duration, i.e., the duration threshold. If the verification duration has not been reached, monitoring continues. If the specified duration has been reached and there are still unverified verification units, verification instructions and identifiers of the verification units to be verified are issued. Alternatively, if the specified duration has been reached and all verification units have completed verification, a verification end instruction is issued to the verification platform.

[0098] Optionally, after the timed query instruction is executed based on a preset time interval, the verification result of the target network can be obtained based on the verification results of multiple verification units corresponding to the target network upon receiving the verification end instruction sent by the network management system. The verification end instruction is given when the verification duration of all verification units reaches the duration threshold.

[0099] It should be noted that the verification result of the target network obtained using the network verification method provided in this application can improve the credibility of the base station sensing network in various ways, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of a network architecture that is compatible with multiple trust enhancement schemes, provided as an embodiment of this application.

[0100] like Figure 5 In method 1 shown, when the verification platform acts as a pure verification device, it can output the verification results of the target network to the network management system. Alternatively, as... Figure 5 In method 2 shown, when the verification platform acts as a replacement for base station post-processing, the verification result can be directly transmitted to the SF, replacing some functional modules of the base station, or, as shown... Figure 5 As shown in Method 3, when the verification platform is used as an external support for base station performance, the verification results can also be returned to the base station side (SlaveBBU or MasterBBU) to assist in improving some of the base station's algorithm capabilities.

[0101] In this embodiment of the application, through this network architecture, the base station can flexibly select different trust enhancement schemes according to scenario requirements, providing more options for base station trust enhancement.

[0102] To implement the above embodiments, this application also proposes a network verification device.

[0103] Figure 6 This is a schematic diagram of the structure of a network verification device provided in an embodiment of this application.

[0104] like Figure 6 As shown, the network verification device includes: The first determining module 601 is used to determine the node type of the target network and the multiple verification units corresponding to the target network based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task, wherein the node type is an in-phase orthogonal IQ node or a point cloud node. The second determining module 602 is used to randomly select a verification unit whose verification time is less than the time threshold from multiple verification units as the target verification unit; The acquisition module 603 is used to acquire node information corresponding to the node type collected by the base station in the target verification unit, as well as trajectory information obtained by the base station from processing the node information. The third determining module 604 is used to verify the trajectory points of the previous time between two different time points based on node information and trajectory information between every two different time points, and to determine the verification result of the trajectory points of the previous time point. The fourth determination module 605 is used to determine the verification result determined within the verification time as the verification result of the target verification unit when the verification time of the trajectory information reaches the time threshold, and return to execute the operation of determining the target verification unit until the verification time of all verification units reaches the time threshold, and obtain the verification result of the target network.

[0105] Optionally, the first determining module 601 can be specifically used for: If the access layer bandwidth is greater than or equal to the first threshold, the node type is determined to be an IQ node; or, If the access layer bandwidth is less than the first threshold, the node type is determined to be a point cloud node; or... If the credibility requirement is greater than the second threshold and the access layer bandwidth is greater than the third threshold, the node type is determined to be an IQ node, where the third threshold is less than the first threshold.

[0106] Optionally, the third determining module 604 can be specifically used for: The trajectory points at each moment in the trajectory information are verified based on a sliding window of a preset time length, and the end time of each sliding window is determined as the first moment to be verified. Based on the first moment and the time period length of the base station delay output, determine the second moment for the first moment verification reference; Based on the information corresponding to the first moment in the node information and the trajectory between the first and second moments in the trajectory information, the trajectory points at the first moment in the trajectory information are verified to obtain the verification result.

[0107] Optionally, the third determining module 604 can be specifically used for: The starting time of the sliding window corresponding to the first time point is determined as the third time point; Based on the first moment and the length of the time period, the fourth moment is determined, wherein the fourth moment is before the third moment; Determine the first feature vector of the trajectory between the first and second time points, the second feature vector of the trajectory between the third and first time points, and the third feature vector of the trajectory between the fourth and third time points; Calculate the distance between the feature vectors based on each pair of feature vectors in the first, second, and third feature vectors; If the distance does not meet the preset conditions, at least one candidate trajectory point associated with the trajectory point at the first moment is determined based on the information corresponding to the first moment in the node information. Randomly select a candidate trajectory point and update the trajectory information; Based on the updated trajectory information, the operation of determining the feature vector is performed until the distance corresponding to any candidate trajectory point meets the preset condition or there are no candidate trajectory points that have not been updated, and then the verification result is obtained.

[0108] Optionally, the preset conditions are that the distance between the first feature vector and the third feature vector is less than a distance threshold, and the distance between the first feature vector and the second feature vector, and the distance between the second feature vector and the third feature vector are both greater than or equal to the distance threshold.

[0109] Optionally, the second determining module 602 can be specifically used for: The command is queried periodically based on a preset time interval; Upon receiving the verification start command sent by the network management system, determine the first identification information in the verification start command; If the first identification information does not match the second identification information of the target verification unit currently being verified, the verification unit corresponding to the first identification information is determined as the new target verification unit. Send feedback information associated with the verification start command to the network administrator.

[0110] Optionally, the second determining module 602 can be specifically used for: Upon receiving the verification end command sent by the network management system, the verification result of the target network is obtained based on the verification results of multiple verification units corresponding to the target network. The verification end command is given when the verification time of all verification units reaches the time threshold.

[0111] It should be noted that the foregoing explanation of the network verification method embodiment also applies to the network verification device of this embodiment, and will not be repeated here.

[0112] In this embodiment, the node type to be verified and multiple verification units corresponding to the network to be verified are determined according to the access layer bandwidth of the network to be verified and the reliability requirements of the verification task. Multiple verification units are verified sequentially in a round-robin manner, so that the verification time of each verification unit meets the time threshold. When verifying each verification unit, the node information corresponding to the node type in the base station and the trajectory information output by the base station are obtained. The trajectory points corresponding to each moment in the trajectory information are verified. Thus, the verification of the base station perception results can be realized in a third-party system, which improves the flexibility of the perception network verification, makes the verification results more accurate, and helps to improve the reliability of the perception network.

[0113] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0114] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0115] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application comply with relevant laws and regulations and do not violate public order and good morals.

[0116] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0117] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0118] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0119] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0120] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0121] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0122] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0123] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0124] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0125] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A network verification method, wherein, include: Based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task, determine the node type of the target network to be verified and the multiple verification units corresponding to the target network, wherein the node type is an in-phase orthogonal IQ node or a point cloud node. Among the plurality of verification units, a verification unit whose verification duration is less than the duration threshold is randomly selected as the target verification unit; The base station acquires node information corresponding to the node type collected within the target verification unit, as well as trajectory information obtained by the base station from processing the node information. Based on the node information and the trajectory between every two different times in the trajectory information, the trajectory point of the previous time in the two different times is verified to determine the verification result of the trajectory point of the previous time. If the verification time for the trajectory information reaches the time threshold, the verification result determined within the verification time is determined as the verification result of the target verification unit, and the operation of determining the target verification unit is returned until the verification time of all verification units reaches the time threshold, and the verification result of the target network is obtained.

2. The method as described in claim 1, wherein, The step of determining the node type for verifying the target network based on the access layer bandwidth of the target network and / or the reliability requirements of the current verification task includes: If the access layer bandwidth is greater than or equal to a first threshold, the node type is determined to be an IQ node; or, If the access layer bandwidth is less than the first threshold, the node type is determined to be a point cloud node; or, If the credibility requirement is greater than the second threshold and the access layer bandwidth is greater than the third threshold, the node type is determined to be an IQ node, wherein the third threshold is less than the first threshold.

3. The method as described in claim 1, wherein, The step of verifying the trajectory points at the previous time point between the two different time points based on the node information and the trajectory information includes: The trajectory points at each moment in the trajectory information are verified based on a sliding window of a preset time length, and the end time of each sliding window is determined as the first moment to be verified. Based on the first moment and the time period length of the base station delay output, a second moment for verification reference of the first moment is determined; Based on the information corresponding to the first time in the node information and the trajectory between the first time and the second time in the trajectory information, the trajectory points at the first time in the trajectory information are verified to obtain the verification result.

4. The method of claim 3, wherein, The method of verifying the trajectory points at the first moment in the trajectory information based on the information corresponding to the first moment in the node information and the trajectory between the first moment and the second moment in the trajectory information to obtain the verification result includes: The starting time of the sliding window corresponding to the first time point is determined as the third time point; Based on the first moment and the time period length, a fourth moment is determined, wherein the fourth moment is prior to the third moment; Determine a first feature vector of the trajectory between the first time point and the second time point, a second feature vector of the trajectory between the third time point and the first time point, and a third feature vector of the trajectory between the fourth time point and the third time point; Calculate the distance between the feature vectors based on every two feature vectors in the first feature vector, the second feature vector, and the third feature vector; If the distance does not meet the preset conditions, at least one candidate trajectory point associated with the trajectory point at the first time is determined based on the information corresponding to the first time in the node information. Randomly select one of the candidate trajectory points and update the trajectory information; Based on the updated trajectory information, the operation of determining the feature vector is returned until the distance corresponding to any candidate trajectory point meets the preset condition or there are no unupdated candidate trajectory points, and the verification result is obtained.

5. The method of claim 4, wherein, The preset condition is that the distance between the first feature vector and the third feature vector is less than a distance threshold, and the distance between the first feature vector and the second feature vector, and the distance between the second feature vector and the third feature vector are both greater than or equal to the distance threshold.

6. The method according to any one of claims 1-5, wherein, Also includes: The command is queried periodically based on a preset time interval; Upon receiving a verification start command sent by the network management system, determine the first identification information in the verification start command; If the first identification information does not match the second identification information of the target verification unit currently being verified, the verification unit corresponding to the first identification information is determined as the new target verification unit. Send feedback information associated with the verification start command to the network management system.

7. The method of claim 6, wherein, Following the timed query instruction based on a preset time interval, the following is also included: Upon receiving the verification end instruction sent by the network management system, the verification result of the target network is obtained based on the verification results of multiple verification units corresponding to the target network, wherein the verification end instruction means that the verification time of all verification units has reached the time threshold.

8. A network verification device, wherein, include: The first determining module is used to determine the node type for verifying the target network and multiple verification units corresponding to the target network based on the access layer bandwidth of the target network and / or the credibility requirements of the current verification task, wherein the node type is an in-phase orthogonal IQ node or a point cloud node. The second determining module is used to randomly select a verification unit whose verification time is less than a time threshold from the plurality of verification units as the target verification unit; The acquisition module is used to acquire node information corresponding to the node type collected by the base station in the target verification unit, and trajectory information obtained by the base station from processing the node information; The third determining module is used to verify the trajectory point of the previous time in the two different times based on the node information and the trajectory between every two different times in the trajectory information, and to determine the verification result of the trajectory point of the previous time. The fourth determining module is used to determine the verification result determined within the verification time as the verification result of the target verification unit when the verification time of the trajectory information reaches the time threshold, and return to execute the operation of determining the target verification unit until the verification time of all verification units reaches the time threshold, so as to obtain the verification result of the target network.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the network verification method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the network verification method as described in any one of claims 1-7.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the network verification method according to any one of claims 1-7.

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