CN116482713A - Navigation data verification method for Beidou navigation receiver - Google Patents
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- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The invention discloses a navigation data verification method for a Beidou navigation receiver, relates to the technical field of Beidou navigation, and aims to solve the problems of unstable navigation data transmission and single data verification. The navigation data verification method for the Beidou navigation receiver can effectively improve the matching degree between the data set transmission number and the actual conditions of the channels according to the data transmission module, so that the stability of monitoring data in transmission can be improved, the comprehensiveness of receiving and storing the monitoring data is ensured according to the classified data decision module, the data can be called according to classification in use, the interference of different classified data is prevented, the data is called more accurately, the operation is simpler and more convenient, meanwhile, the safety of the classified data is ensured according to the data storage module, and the same monitoring data is respectively subjected to data verification by adopting a comparison verification method, a parity check method and a neural network method.
Description
Technical Field
The invention relates to the technical field of Beidou navigation, in particular to a navigation data verification method for a Beidou navigation receiver.
Background
The Beidou satellite navigation system is self-developed in China and is also a second and subsequent third mature satellite navigation system.
The Chinese patent with publication number CN105629264B discloses a navigation data verification method for a GPS/Beidou navigation receiver, by carrying out cyclic shift operation of one-time exclusive OR operation on original data, comparing an operation result with received verification data, judging the accuracy of the received original data according to the comparison result, greatly reducing the operation amount, being applicable to a GPS and a Beidou navigation system at the same time, and not needing de-interleaving operation for a non-first word in the Beidou navigation system, improving the verification efficiency, and the patent solves the problem of single operation of data, but has the following problems in actual operation:
1. when the navigation data of the receiver are collected, the accuracy of the collected data is poor, and data matching errors are caused by the fact that data are not unified during data collection.
2. The navigation monitoring data in the receiver is not effectively classified, so that the data cannot be effectively classified for storage and management, and the safety of the data is reduced.
3. The data verification mode is too single, so that the verification result is inaccurate, and data clustering analysis is not performed on the verified data, so that the safety coefficient of the verified data is reduced.
Disclosure of Invention
The invention aims to provide a navigation data verification method for a Beidou navigation receiver, which can effectively improve the matching degree between the data set transmission number and the actual conditions of channels according to the data set transmission number setting of a data transmission module, so that the stability of monitoring data in transmission can be improved, the comprehensiveness of receiving and storing the monitoring data is ensured according to a classification data decision module, the data can be called according to classification in use, the interference of different classification data is prevented, the data call is more accurate, the operation is simpler and more convenient, meanwhile, the safety of the classification data is ensured according to a data storage module, the same monitoring data is respectively subjected to data verification by adopting a comparison verification method, a parity check method and a neural network method, the data of different types is cached in corresponding sub-target cache spaces, the caching effect of monitoring data information is ensured, the safety coefficient of the monitoring data information is also improved, and the problems in the prior art can be solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a navigation data verification method for a beidou navigation receiver, comprising the following steps:
s1, acquiring navigation data, namely acquiring interface data according to a Beidou navigation terminal, analyzing the acquired data into original data, generating a corresponding positioning tag according to an analysis result, and storing tag data;
s2: data classification and data verification: classifying the data according to the collected monitoring data, and then checking the classified data for a plurality of times, wherein the checking method adopts a plurality of modes for checking, and the checking quantity of each mode is a plurality of times;
s3: checking data caching: and classifying the data verified in different modes according to the navigation monitoring data after verification, and storing the different data according to the space capacity after classification, wherein key data information in the different data is extracted, and the information type of the verification data is determined according to the key data information.
Preferably, for the acquisition of navigation data in S1, the method includes:
the navigation data monitoring module is used for:
according to the wireless data received by the receiver, uniformly acquiring the data of the wireless data, and uniformly monitoring the acquired data;
the monitoring data detection module is used for:
generating monitoring data for the uniformly received data, and carrying out delay detection on the monitoring data, wherein the generated monitoring data is modulated into monitoring data uniform with the pre-detection data according to the pre-detection data of the data and the generated monitoring data; wherein the pre-detection data value can be automatically debugged on the receiver
A data synchronization module for:
and carrying out data synchronization on the detected monitoring data, wherein the monitoring data in the same time period are generated into the same serial number data, the same serial number data are packed, and a monitoring data packet is generated after the packing is completed.
Preferably, for the acquisition of navigation data in S1, further comprising:
the data transmission module is used for:
transmitting the generated monitoring data packet to a next server through a communication channel for data processing, wherein the data transmission speed of the communication channel in the monitoring data transmission process for the monitoring data packet is obtained, the communication channel with the highest data transmission speed is obtained, and the channel with the largest capacity is extracted from the rest communication capacity in the fastest channel to be used as a target channel;
a data binding module for:
and storing the monitoring data packets in the target channel, and binding the stored data in different time periods with the data packets. .
Preferably, for classification of data types in S2, the method includes:
the data classification module is used for:
the method comprises the steps of performing data type screening on received monitoring data and taking the data type screening as classified data to be stored;
the classified data processing module is used for:
acquiring capacity coefficients of storage areas of the classified data, wherein the capacity coefficients of the storage areas represent used space of the storage areas, and searching for available target storage areas;
the classified data decision module is used for:
setting the number of the copies and a storage perception strategy when the classified data are stored;
wherein storing the awareness policy includes determining data nodes of the categorized data storage area for storing categorized data
A data storage module for:
and storing the classified data to be stored and the copy number into a target storage area, and recording the storage information of the operation behavior data to be stored and the copy number.
Preferably, the method for data verification in S2 includes:
a contrast verification method for:
directly carrying out numerical comparison on the classified monitoring data and the data to be compared, wherein the comparison times of the same monitoring data and the data to be compared are not less than one time
Parity check method for:
in the stored monitoring data and transmission, one bit is additionally added in the byte for checking errors, the check bit can be calculated through exclusive OR of the data bits, and the check is carried out according to the fact that the number of '1' in the digital bits of the transmitted group of binary codes is odd or even. Odd parity is used, otherwise even parity.
Preferably, the data verification method further comprises:
neural network method for:
firstly, forward transmission is carried out on monitoring data, wherein the monitoring data is transmitted from a low level to a high level;
counter-propagating when the data result obtained by propagation does not coincide with the expected data result, wherein the counter-propagating is to conduct propagation training from a high level to a bottom layer;
the propagation training process comprises the following steps:
firstly, initializing and setting the weight of data, and after the setting is completed, forward transmitting parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value;
when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence;
wherein the errors of each layer are the total errors of the network; when the error is equal to or less than the desired value, then training is complete.
Preferably, the data verification method further comprises:
acquiring base station positioning data of at least three fixed base stations in different directions around the Beidou navigation terminal;
constructing a plane coordinate system according to the base station positioning data;
importing the stored navigation data of the Beidou navigation terminal with the positioning tag into a plane coordinate system to form plane point cloud data with time sequence change;
abnormal point data is removed through cluster analysis of the plane point cloud data;
performing time sequence vector change analysis on the plane point cloud data from which the abnormal point data are removed to obtain a vector change rate average value of the Beidou navigation terminal navigation data;
the newly acquired Beidou navigation terminal navigation data are imported into a plane coordinate system to perform time sequence vector change analysis, so that the current vector change rate is obtained;
and taking the deviation of the current vector change rate and the vector change rate mean value as a standard for checking whether the latest acquired Beidou navigation terminal navigation data passes or not, wherein the deviation is not larger than a preset change threshold value.
Preferably, for the buffering of the verification data in S3, the method includes:
a data capacity determining module for:
determining a target cache space corresponding to the monitoring data information according to the checked information type, extracting capacity information of the target cache space, and determining a first residual available space capacity of the target cache space according to the capacity information;
a space division module for:
dividing a target cache space into a first block according to a type identifier, adding a block identifier to the divided sub-target cache space, and dividing each sub-target cache space into a second block to obtain a first storage item and a second storage item corresponding to each sub-target cache space, wherein the block identifier corresponds to the type identifier;
the data caching module is used for:
and respectively extracting target contents of the monitoring data information corresponding to each data type according to the type identifier, and respectively caching the type identifier and the target contents into a first storage item and a second storage item.
Preferably, the data capacity determining module is further configured to:
the method comprises the steps of firstly obtaining the data length of monitoring data information, clustering the monitoring data information when the first residual available space capacity is larger than the data length to obtain a sub-data type set corresponding to the short message data information, and setting a type identifier for each sub-data type.
Preferably, for the key data information extracted in S3, further including:
respectively generating a binary tree representation to be inspected according to key data information of different data, and carrying out normalization processing on the binary tree representation to be inspected;
respectively adopting type binary tree representation to the information types, and carrying out normalization processing on the type binary tree representation;
the matching degree of the binary tree representation to be inspected and the type binary tree representation is calculated by adopting the following formula:
in the above, D i,j Representing the matching degree of the ith binary tree representation to be examined and the jth type binary tree representation; s is S i Representing a node information sequence represented by an ith binary tree to be examined; l (L) j A node information sequence representing a j-th type binary tree representation; n (N) mat (S i ,L j ) The node information sequence represented by the ith binary tree to be examined and the node information sequence represented by the jth binary tree type are represented by the same node information number of the corresponding nodes from the root node; n (N) Si Representing the total number of node information of the node information sequence represented by the ith binary tree to be examined; n (N) Lj A node information total number representing a node information sequence represented by the j-th type binary tree;
for each homonym matching degree of the same binary tree representation to be examined and various binary tree representations, if the homonym matching degree is not less than a preset threshold value, classifying the data corresponding to the binary tree representation to be examined as the information type with the highest matching degree; if a plurality of homonymy matching degrees are not smaller than a preset threshold value, the following processing is carried out:
extracting secondary data information except key data information from the data corresponding to the binary tree representation to be inspected, generating a second binary tree representation to be inspected, calculating a second matching degree of the second binary tree representation to be inspected and the type binary tree representation, and determining the information type with the highest second matching degree as the information type of the data corresponding to the binary tree representation to be inspected.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the navigation data verification method for the Beidou navigation receiver, the monitoring data detection module is used for pre-detection, adjustment and modification can be carried out according to the needs, synchronization accuracy of positive film acquisition is guaranteed, detection and modification can be carried out on delay of the positive film acquisition, use convenience is improved, data synchronization acquisition is achieved according to the data synchronization module, serial numbers are added in synchronization messages, the problem of data packet matching errors between transmission possibly caused by uncertainty of transmission delay is avoided, the matching degree between the data set transmission number and the actual channel condition can be effectively improved according to the data transmission module, stability of monitoring data in transmission can be improved, and influence on data transmission efficiency due to channel blocking caused by overlarge data transmission quantity due to incapability of targeted adjustment according to parameters such as the actual channel saturation is effectively prevented.
2. According to the navigation data checking method for the Beidou navigation receiver, the data type of the monitoring data can be screened according to the data classification module, the comprehensiveness of the reception and storage of the classified data is ensured according to the classified data decision module, the data can be called according to the classification during use, interference of different classified data is prevented, the data is called more accurately, the operation is simpler and more convenient, meanwhile, the safety of the classified data is ensured according to the data storage module, the data incompleteness caused by the classified data loss is prevented, the reliability and the practicability of a system are enhanced, the same monitoring data are respectively checked by adopting a comparison check method, a parity check method and a neural network method, the comparison check method, the parity check method and the neural network method are respectively checked for a plurality of times, and then the check result is analyzed, and the three check methods can enable the check result to be more accurate.
3. According to the navigation data verification method for the Beidou navigation receiver, the data capacity determining module is used for analyzing the monitoring data information, so that the information type of the short message data information is accurately and effectively confirmed, the determination of the target cache space for caching the short message data information is facilitated, each sub-target storage space is divided again, the caching effect and the caching accuracy of each type of data content and type identification are guaranteed, different types of data are cached in the corresponding sub-target cache space, the caching effect of the monitoring data information is guaranteed, and the safety coefficient of the monitoring data information is also improved.
Drawings
FIG. 1 is a schematic overall flow chart of the present invention;
FIG. 2 is a schematic diagram of a navigation data acquisition module according to the present invention;
FIG. 3 is a schematic diagram of a data type classification module according to the present invention;
FIG. 4 is a schematic diagram of a buffer module for checking data according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that in the prior art, when navigation data of a receiver are collected, the accuracy of the collected data is poor, and when data are collected, data matching errors are caused by data unification is not performed, please refer to fig. 1 and 2, the present embodiment provides the following technical scheme:
a navigation data verification method for a beidou navigation receiver, comprising the following steps:
s1, acquiring navigation data, namely acquiring interface data according to a Beidou navigation terminal, analyzing the acquired data into original data, generating a corresponding positioning tag according to an analysis result, and storing tag data;
s2: data classification and data verification: classifying the data according to the collected monitoring data, and then checking the classified data for a plurality of times, wherein the checking method adopts a plurality of modes for checking, and the checking quantity of each mode is a plurality of times;
s3: checking data caching: and classifying the data verified in different modes according to the navigation monitoring data after verification, and storing the different data according to the space capacity after classification, wherein key data information in the different data is extracted, and the information type of the verification data is determined according to the key data information.
For the acquisition of navigation data in S1, comprising: the navigation data monitoring module is used for: according to the wireless data received by the receiver, uniformly acquiring the data of the wireless data, and uniformly monitoring the acquired data; the monitoring data detection module is used for: generating monitoring data for the uniformly received data, and carrying out delay detection on the monitoring data, wherein the generated monitoring data is modulated into monitoring data uniform with the pre-detection data according to the pre-detection data of the data and the generated monitoring data; the pre-detection data value can be automatically debugged on the receiver; a data synchronization module for: and carrying out data synchronization on the detected monitoring data, wherein the monitoring data in the same time period are generated into the same serial number data, the same serial number data are packed, and a monitoring data packet is generated after the packing is completed.
For the acquisition of navigation data in S1, further comprising: the data transmission module is used for: transmitting the generated monitoring data packet to a next server through a communication channel for data processing, wherein the data transmission speed of the communication channel in the monitoring data transmission process for the monitoring data packet is obtained, the communication channel with the highest data transmission speed is obtained, and the channel with the largest capacity is extracted from the rest communication capacity in the fastest channel to be used as a target channel; a data binding module for: and storing the monitoring data packets in the target channel, and binding the stored data in different time periods with the data packets.
Specifically, the pre-detection is performed through the monitoring data detection module, adjustment and modification can be performed according to the requirement, the synchronous accuracy of positive film acquisition is guaranteed, detection and modification can be performed on delay of the positive film acquisition, the use convenience is improved, the data synchronous acquisition is realized according to the data synchronous module, the serial number is added in the synchronous message, the problem of data packet matching errors between transmission possibly caused by uncertainty of transmission delay is avoided, the matching degree between the data set transmission number and the actual channel condition can be effectively improved according to the setting of the data set transmission number of the data transmission module, the stability of monitoring data in transmission can be improved, the situation that the data cannot be subjected to targeted adjustment according to parameters such as the actual channel saturation is effectively prevented, and the data transmission efficiency is affected by channel blocking caused by overlarge data transmission quantity.
In order to solve the problem that in the prior art, navigation monitoring data in a receiver is not effectively classified, so that the data cannot be effectively classified, stored and managed, and the security of the data is reduced, referring to fig. 3, the present embodiment provides the following technical scheme:
the classification for the data type in S2 includes: the data classification module is used for: the method comprises the steps of performing data type screening on received monitoring data and taking the data type screening as classified data to be stored; the classified data processing module is used for: acquiring capacity coefficients of storage areas of the classified data, wherein the capacity coefficients of the storage areas represent used space of the storage areas, and searching for available target storage areas; the classified data decision module is used for: setting the number of the copies and a storage perception strategy when the classified data are stored; wherein storing the awareness policy includes determining data nodes of the categorized data storage area for storing categorized data; a data storage module for: and storing the classified data to be stored and the copy number into a target storage area, and recording the storage information of the operation behavior data to be stored and the copy number.
Specifically, the data type of the monitoring data can be screened according to the data classification module, the comprehensiveness of the classified data receiving and storing is ensured according to the classified data decision module, the data can be called according to the classification during use, the interference of different classified data is prevented, the data calling is more accurate, the operation is simpler and more convenient, meanwhile, the safety of the classified data is ensured according to the data storage module, the incomplete data caused by the classified data loss is prevented, and the reliability and the practicability of the system are enhanced.
In order to solve the problems of single checking method and poor accuracy of checking data when checking navigation data in the prior art, the embodiment provides the following technical scheme:
a method for data verification in S2, comprising: a contrast verification method for: directly carrying out numerical comparison on the classified monitoring data and the data to be compared, wherein the comparison times of the same monitoring data and the data to be compared are not less than once; parity check method for: in the stored monitoring data and transmission, one bit is additionally added in the byte for checking errors, the check bit can be calculated through exclusive OR of the data bits, and the check is carried out according to the fact that the number of '1' in the digital bits of the transmitted group of binary codes is odd or even. Odd parity is adopted, otherwise even parity is adopted; neural network method for: firstly, forward transmission is carried out on monitoring data, wherein the monitoring data is transmitted from a low level to a high level; counter-propagating when the data result obtained by propagation does not coincide with the expected data result, wherein the counter-propagating is to conduct propagation training from a high level to a bottom layer; the propagation training process comprises the following steps: firstly, initializing and setting the weight of data, and after the setting is completed, forward transmitting parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value; when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence; wherein the errors of each layer are the total errors of the network; when the error is equal to or less than the desired value, then training is complete.
Specifically, the same monitoring data are respectively subjected to data verification by adopting a contrast verification method, a parity verification method and a neural network method, the contrast verification method, the parity verification method and the neural network method are respectively tested for a plurality of times, then the verification result is analyzed, meanwhile, the accuracy of the contrast verification method is optimal, but the verification efficiency is lower, wherein the parity verification method is usually specially provided with a parity check bit, and the number of 1's in the group of codes is made to be odd or even by using the parity check bit. If odd check is used, when the receiving end receives the group of codes, checking whether the number of '1' is odd, thereby determining the correctness of the transmitted codes, the neural network method obtains an output value through forward propagation of parameter data through a convolution layer, a lower layer and a full connection layer, the forward propagation is to forward propagate the parameter data from a low level to a high level, when a data result obtained by propagation is inconsistent with an expected value, the backward propagation is to propagate an error from the high level to the bottom layer, when the error is larger than an expected value after the training is finished, the error of a downsampling layer and the convolution layer is sequentially obtained, when the error is equal to or smaller than the expected value, the training is finished, the parameter data can pass through each hidden layer when the parameter data passes through the forward propagation training, finally lost data is obtained when the parameter data passes through the hidden layer, a backward propagation mechanism is formed by forward feedback of a layer according to a gradient decreasing formula, the quality of the verification can be optimized.
The method for data verification in S2 further comprises the following steps:
acquiring base station positioning data of at least three fixed base stations in different directions around the Beidou navigation terminal;
constructing a plane coordinate system according to the base station positioning data;
importing the stored navigation data of the Beidou navigation terminal with the positioning tag into a plane coordinate system to form plane point cloud data with time sequence change;
abnormal point data is removed through cluster analysis of the plane point cloud data;
performing time sequence vector change analysis on the plane point cloud data from which the abnormal point data are removed to obtain a vector change rate average value of the Beidou navigation terminal navigation data;
the newly acquired Beidou navigation terminal navigation data are imported into a plane coordinate system to perform time sequence vector change analysis, so that the current vector change rate is obtained;
and taking the deviation of the current vector change rate and the vector change rate mean value as a standard for checking whether the latest acquired Beidou navigation terminal navigation data passes or not, wherein the deviation is not larger than a preset change threshold value.
The base station positioning data of the fixed base station is introduced to construct a plane coordinate system, navigation data are brought into the plane coordinate system to form an intuitive coordinate graph, and on the basis, change analysis is carried out, so that the correctness of the data can be effectively checked, and the checking accuracy and reliability are improved; time information of data acquisition is still associated through data entering a plane coordinate system, so that time sequence vector change analysis can be realized.
In order to solve the problem that in the prior art, data cluster analysis is not performed on the data after verification, resulting in reduction of the security coefficient of the data after verification, referring to fig. 4, the present embodiment provides the following technical scheme:
for the caching of the verification data in S3, including: a data capacity determining module for: determining a target cache space corresponding to the monitoring data information according to the checked information type, extracting capacity information of the target cache space, and determining a first residual available space capacity of the target cache space according to the capacity information; a space division module for: dividing a target cache space into a first block according to a type identifier, adding a block identifier to the divided sub-target cache space, and dividing each sub-target cache space into a second block to obtain a first storage item and a second storage item corresponding to each sub-target cache space, wherein the block identifier corresponds to the type identifier; the data caching module is used for: and respectively extracting target contents of the monitoring data information corresponding to each data type according to the type identifier, and respectively caching the type identifier and the target contents into a first storage item and a second storage item. The data capacity determining module is further configured to: the method comprises the steps of firstly obtaining the data length of monitoring data information, clustering the monitoring data information when the first residual available space capacity is larger than the data length to obtain a sub-data type set corresponding to the short message data information, and setting a type identifier for each sub-data type.
Specifically, the monitoring data information is analyzed through the data capacity determining module, so that the information type of the short message data information is accurately and effectively confirmed, the target cache space for caching the short message data information is conveniently determined, each sub-target storage space is divided again, the cache effect and the cache accuracy of each type of data content and type identification are guaranteed, different types of data are cached in the corresponding sub-target cache space, the cache effect of the monitoring data information is guaranteed, and the safety coefficient of the monitoring data information is also improved.
For the key data information extracted in S3, further including:
respectively generating a binary tree representation to be inspected according to key data information of different data, and carrying out normalization processing on the binary tree representation to be inspected;
respectively adopting type binary tree representation to the information types, and carrying out normalization processing on the type binary tree representation;
the matching degree of the binary tree representation to be inspected and the type binary tree representation is calculated by adopting the following formula:
in the above, D i,j Representing the matching degree of the ith binary tree representation to be examined and the jth type binary tree representation; s is S i Representing a node information sequence represented by an ith binary tree to be examined; l (L) j A node information sequence representing a j-th type binary tree representation; n (N) mat (S i ,L j ) The node information sequence represented by the ith binary tree to be examined and the node information sequence represented by the jth binary tree type are represented by the same node information number of the corresponding nodes from the root node; n (N) Si Representing the total number of node information of the node information sequence represented by the ith binary tree to be examined; n (N) Lj A node information total number representing a node information sequence represented by the j-th type binary tree;
for each homonym matching degree of the same binary tree representation to be examined and various binary tree representations, if the homonym matching degree is not less than a preset threshold value, classifying the data corresponding to the binary tree representation to be examined as the information type with the highest matching degree; if a plurality of homonymy matching degrees are not smaller than a preset threshold value, the following processing is carried out:
extracting secondary data information except key data information from the data corresponding to the binary tree representation to be inspected, generating a second binary tree representation to be inspected, calculating a second matching degree of the second binary tree representation to be inspected and the type binary tree representation, and determining the information type with the highest second matching degree as the information type of the data corresponding to the binary tree representation to be inspected.
By adopting the scheme, the information types of different data can be classified rapidly and accurately, so that the data can be stored and used conveniently; the key data information is used as a main investigation item, so that the operation amount can be reduced, and the operation resource can be saved; if necessary, secondary data information is used as an investigation item, so that the rationality and accuracy of matching judgment and classification can be improved; the method has the advantages that through conversion into a tree structure and combination of matching degree calculation, investigation contents can be refined, accuracy is further improved, and objectivity and reliability of results can be improved; through normalization processing, the structure of the binary tree representation to be examined and the structure of the type binary tree representation are more standard, and matching degree comparison calculation is convenient.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A navigation data verification method for a Beidou navigation receiver is characterized by comprising the following steps of: the method comprises the following steps:
s1, acquiring navigation data, namely acquiring interface data according to a Beidou navigation terminal, analyzing the acquired data into original data, generating a corresponding positioning tag according to an analysis result, and storing tag data;
s2: data classification and data verification: classifying the data according to the collected monitoring data, and then checking the classified data for a plurality of times, wherein the checking method adopts a plurality of modes for checking, and the checking quantity of each mode is a plurality of times;
s3: checking data caching: and classifying the data verified in different modes according to the navigation monitoring data after verification, and storing the different data according to the space capacity after classification, wherein key data information in the different data is extracted, and the information type of the verification data is determined according to the key data information.
2. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: for the acquisition of navigation data in S1, comprising:
the navigation data monitoring module is used for:
according to the wireless data received by the receiver, uniformly acquiring the data of the wireless data, and uniformly monitoring the acquired data;
the monitoring data detection module is used for:
generating monitoring data for the uniformly received data, and carrying out delay detection on the monitoring data, wherein the generated monitoring data is modulated into monitoring data uniform with the pre-detection data according to the pre-detection data of the data and the generated monitoring data; wherein the pre-detection data value can be automatically debugged on the receiver
A data synchronization module for:
and carrying out data synchronization on the detected monitoring data, wherein the monitoring data in the same time period are generated into the same serial number data, the same serial number data are packed, and a monitoring data packet is generated after the packing is completed.
3. The method for checking navigation data of a beidou navigation receiver according to claim 2, wherein: for the acquisition of navigation data in S1, further comprising:
the data transmission module is used for:
transmitting the generated monitoring data packet to a next server through a communication channel for data processing, wherein the data transmission speed of the communication channel in the monitoring data transmission process for the monitoring data packet is obtained, the communication channel with the highest data transmission speed is obtained, and the channel with the largest capacity is extracted from the rest communication capacity in the fastest channel to be used as a target channel;
a data binding module for:
and storing the monitoring data packets in the target channel, and binding the stored data in different time periods with the data packets.
4. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: the classification for the data type in S2 includes:
the data classification module is used for:
the method comprises the steps of performing data type screening on received monitoring data and taking the data type screening as classified data to be stored;
the classified data processing module is used for:
acquiring capacity coefficients of storage areas of the classified data, wherein the capacity coefficients of the storage areas represent used space of the storage areas, and searching for available target storage areas;
the classified data decision module is used for:
setting the number of the copies and a storage perception strategy when the classified data are stored;
wherein storing the awareness policy includes determining data nodes of the categorized data storage area for storing categorized data;
a data storage module for:
and storing the classified data to be stored and the copy number into a target storage area, and recording the storage information of the operation behavior data to be stored and the copy number.
5. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: a method for data verification in S2, comprising:
a contrast verification method for:
directly carrying out numerical comparison on the classified monitoring data and the data to be compared, wherein the comparison times of the same monitoring data and the data to be compared are not less than once;
parity check method for:
in the stored monitoring data and transmission, one bit is additionally added in the byte for checking errors, the check bit can be calculated through exclusive or of the data bit, and checking is carried out according to the fact that the number of 1's in the transmitted set of binary codes is odd or even, and odd is called odd check, and otherwise even check is called even check.
6. The method for checking navigation data of a Beidou navigation receiver of claim 5, wherein: the data verification method further comprises the following steps:
neural network method for:
firstly, forward transmission is carried out on monitoring data, wherein the monitoring data is transmitted from a low level to a high level;
counter-propagating when the data result obtained by propagation does not coincide with the expected data result, wherein the counter-propagating is to conduct propagation training from a high level to a bottom layer;
the propagation training process comprises the following steps:
firstly, initializing and setting the weight of data, and after the setting is completed, forward transmitting parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value;
when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence;
wherein the errors of each layer are the total errors of the network; when the error is equal to or less than the desired value, then training is complete.
7. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: the data verification method further comprises the following steps:
acquiring base station positioning data of at least three fixed base stations in different directions around the Beidou navigation terminal;
constructing a plane coordinate system according to the base station positioning data;
importing the stored navigation data of the Beidou navigation terminal with the positioning tag into a plane coordinate system to form plane point cloud data with time sequence change;
abnormal point data is removed through cluster analysis of the plane point cloud data;
performing time sequence vector change analysis on the plane point cloud data from which the abnormal point data are removed to obtain a vector change rate average value of the Beidou navigation terminal navigation data;
the newly acquired Beidou navigation terminal navigation data are imported into a plane coordinate system to perform time sequence vector change analysis, so that the current vector change rate is obtained;
and taking the deviation of the current vector change rate and the vector change rate mean value as a standard for checking whether the latest acquired Beidou navigation terminal navigation data passes or not, wherein the deviation is not larger than a preset change threshold value.
8. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: for the caching of the verification data in S3, including:
a data capacity determining module for:
determining a target cache space corresponding to the monitoring data information according to the checked information type, extracting capacity information of the target cache space, and determining a first residual available space capacity of the target cache space according to the capacity information;
a space division module for:
dividing a target cache space into a first block according to a type identifier, adding a block identifier to the divided sub-target cache space, and dividing each sub-target cache space into a second block to obtain a first storage item and a second storage item corresponding to each sub-target cache space, wherein the block identifier corresponds to the type identifier;
the data caching module is used for:
and respectively extracting target contents of the monitoring data information corresponding to each data type according to the type identifier, and respectively caching the type identifier and the target contents into a first storage item and a second storage item.
9. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: the data capacity determining module is further configured to:
the method comprises the steps of firstly obtaining the data length of monitoring data information, clustering the monitoring data information when the first residual available space capacity is larger than the data length to obtain a sub-data type set corresponding to the short message data information, and setting a type identifier for each sub-data type.
10. The method for checking navigation data of a beidou navigation receiver according to claim 1, wherein: for the key data information extracted in S3, further including:
respectively generating a binary tree representation to be inspected according to key data information of different data, and carrying out normalization processing on the binary tree representation to be inspected;
respectively adopting type binary tree representation to the information types, and carrying out normalization processing on the type binary tree representation;
the matching degree of the binary tree representation to be inspected and the type binary tree representation is calculated by adopting the following formula:
in the above, D i,j Representing the matching degree of the ith binary tree representation to be examined and the jth type binary tree representation; s is S i Node information sequence representing the ith binary tree to be examined；L j A node information sequence representing a j-th type binary tree representation; n (N) mat (S i ,L j ) The node information sequence represented by the ith binary tree to be examined and the node information sequence represented by the jth binary tree type are represented by the same node information number of the corresponding nodes from the root node; n (N) Si Representing the total number of node information of the node information sequence represented by the ith binary tree to be examined; n (N) Lj A node information total number representing a node information sequence represented by the j-th type binary tree;
for each homonym matching degree of the same binary tree representation to be examined and various binary tree representations, if the homonym matching degree is not less than a preset threshold value, classifying the data corresponding to the binary tree representation to be examined as the information type with the highest matching degree; if a plurality of homonymy matching degrees are not smaller than a preset threshold value, the following processing is carried out:
extracting secondary data information except key data information from the data corresponding to the binary tree representation to be inspected, generating a second binary tree representation to be inspected, calculating a second matching degree of the second binary tree representation to be inspected and the type binary tree representation, and determining the information type with the highest second matching degree as the information type of the data corresponding to the binary tree representation to be inspected.
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| CN118112624A (en) * | 2024-04-25 | 2024-05-31 | 江西省军民融合研究院 | Unmanned aerial vehicle position communication method and system based on Beidou positioning |
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| CN117792806A (en) * | 2023-12-26 | 2024-03-29 | 安徽思宇微电子技术有限责任公司 | Power consumption information acquisition terminal based on POE power supply |
| CN118112624A (en) * | 2024-04-25 | 2024-05-31 | 江西省军民融合研究院 | Unmanned aerial vehicle position communication method and system based on Beidou positioning |
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