CN111505681A - Method and system for correcting rarefaction of positioning track - Google Patents
Method and system for correcting rarefaction of positioning track Download PDFInfo
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- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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- 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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- G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
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Abstract
The invention belongs to the field of path detection, and relates to a method and a system for correcting rarefaction of a positioning track. The method comprises a plurality of clients and a service end, and also comprises a first process: step A1, generating a position data set; step A2, a sliding window with a preset time length; step A3, determining the time between the time node of the last position data in the sliding window and the time node of the next position data outside the sliding window; step A4, judging position information; and step A5, returning to the step A1, outputting the current position data set as a first positioning track until the last data in the sliding window is the last data of the position data set, and then ending. The beneficial effects of the above technical scheme are: the accuracy of the position data is improved, the processing speed of the position data is improved, and the finally generated positioning track is smoother while the inflection point and the inflection point are kept.
Description
Technical Field
The invention belongs to the field of path detection, and relates to a method and a system for correcting rarefaction of a positioning track.
Background
In practical application, a user often carries a satellite positioning system such as a GPS and a beidou at a client for positioning, however, due to poor received signals at the client and interference of external factors, position data output from the client to a server is inaccurate, and a drift phenomenon occurs, thereby affecting accuracy of a user positioning track finally generated at the client.
In addition, when the server performs UI display rendering, the front-end processing speed is too slow and the network transmission time is too long due to too much position data to be processed.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention provides a method and system for correcting rarefaction of a positioning track.
A method for correcting and rarefying a positioning track is used for correcting and rarefying the positioning track and is characterized by comprising a plurality of clients and a server, wherein the clients are respectively and remotely connected with the server, each client is provided with an acquisition device, and the acquisition devices acquire position information of the corresponding client at a preset time interval, include the position information and a corresponding time node in position data and output the position data to the server;
the method further comprises a first process:
step A1, the server receives the position data, and generates a position data set by sequencing all the position data according to the sequence of the time nodes;
step A2, setting a sliding window with a preset time length in the server, wherein in an initial state, the initial end in the sliding window corresponds to the first position data in the position data set;
step a3, the server determines whether a time interval between a time node of the last position data in the sliding window and a time node of the next position data outside the sliding window is smaller than a preset time threshold:
if yes, go to step A4;
if not, the server controls the sliding window to slide forward by one time node, and then the step A5 is carried out;
step a4, the server determines whether the distance between the position information of the last position data in the current sliding window and the position information of the next position data outside the sliding window is less than a distance interval value:
if yes, correcting according to next position data outside the sliding window, and then turning to step A5;
if not, the server controls the sliding window to slide forwards for the preset time length, and then the step A5 is carried out;
and step A5, returning to the step A1, outputting the current position data set as a first positioning track until the last data in the sliding window is the last data of the position data set, and then ending.
Preferably, in step a4, the sliding window corrects the next position data outside the sliding window by using the following formula:
wherein the content of the first and second substances,
Preferably, the method further includes a second process, the second process is executed after the first process, and the second process includes:
step B1, the server side obtains a position data set corresponding to the first positioning track, and takes the first position data of the position data set as a clustering reference point;
step B2, the server side sequentially generates a first cluster set and a second cluster set according to the cluster reference point, the first cluster set at least comprises the cluster reference point and the position data of the i-th position of the cluster reference point, the second cluster set at least comprises the cluster reference point and the position data of the i + 1-th position of the cluster reference point, i is a natural number and is more than or equal to 1;
step B3, the server determines whether the distance difference between the farthest distance between the points in the first cluster set and the farthest distance between the points in the second cluster set is less than a preset distance threshold:
if not, making i +1 ═ i, so that the server reconstructs the first cluster set and the second cluster set, and then go to step B4;
if so, the server uses second location data after the current clustering reference point as the clustering reference point to reconstruct the first cluster set as a result cluster set, and then goes to step B4;
step B4, the server determines whether the last location data in the location data set is added to the first cluster set or serves as the clustering reference point:
if not, go to step B2;
if yes, go to step B5;
and step B5, the server side respectively processes the particle data corresponding to each result cluster set and replaces all the position data in the corresponding result cluster set, all the result cluster sets and all the cluster reference points after replacement are output as second positioning tracks, and then the process is finished.
Preferably, the particle data is obtained in step B5 by processing according to the following formula:
wherein the content of the first and second substances,
p′xa longitude to represent the particle data;
p′ya latitude for representing the particle data;
preferably, the method further includes a third process, the third process is executed after the second process, and the third process includes:
step C1, the server acquires the position data set corresponding to the second positioning track, and uses the first position data of the position data set as an inflection point reference point;
step C2, the server sequentially arranges the inflection point reference point and the position data of the last three bits of the inflection point reference point in an inflection point reference set, and obtains a vector cross product result corresponding to the inflection point reference set;
step C3, the server determines whether the vector cross product result is less than zero:
if so, recording the third position data in the inflection point reference set as the important point, and then turning to the step C4;
if not, recording a third location data in the inflection point reference set as an insignificant point, and then proceeding to step C4;
step C4, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step C5;
if not, taking the position data of the next bit of the inflection point reference point as the inflection point reference point, and then returning to the step C2;
and step C5, the server deletes the position data corresponding to all the non-significant points in the inflection point reference set from the position data set, outputs the position data set at this time as a third positioning trajectory, and then ends.
Preferably, the method further includes a fourth process, the fourth process is executed after the third process, and the fourth process includes:
step D1, the server acquires the position data set corresponding to the third positioning track, and uses the first position data of the position data set as a break point reference point, a first angle threshold and a second angle threshold are preset in the server, the first angle threshold is smaller than the second angle threshold, and the server selects the first angle threshold and the second angle threshold as angle thresholds at intervals;
in an initial state, the server takes the first angle threshold as the angle threshold;
d2, the server side sequentially selects three position data according to the break point reference point to generate a break point reference set, and obtains a break point angle corresponding to the second position data in the break point reference set;
step D3, the server determines whether the importance of the second location data is greater than the importance of the third location data:
if yes, the server uses the second angle threshold as an angle threshold, and then goes to step D4;
if not, the server takes the first angle threshold as an angle threshold, and then goes to step D4;
step D4, the server side judges whether the break point angle is smaller than an angle threshold:
if so, the server records the second position data in the break point reference set as the important point, and then goes to step D5;
if not, the server records the second position data in the break point reference set as the unimportant point, and then goes to step D5;
step D5, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step D6;
if not, taking the next position data of the current inflection point reference point as the inflection point reference point, and then turning to step D2;
and D6, the server deletes all unimportant points in the position data set, outputs the position data set at the moment as a fourth positioning track, and then ends.
A system for correcting rarefaction of a positioning track is applied to the method for correcting rarefaction of the positioning track, and is characterized by comprising a plurality of clients and a service end;
each of the clients includes:
the acquisition unit is arranged on the client and used for acquiring the position information of the client at a preset time interval and outputting the position information and the corresponding time node included in position data;
the first acquisition unit is used for outputting a first instruction, and the first instruction is used for acquiring a first positioning track of the client;
the server is remotely connected with all the clients, and comprises:
the receiving unit is used for receiving the position data and sequencing all the position data according to the sequence of the time nodes to generate a position data set;
and the first processing unit is respectively connected with the first acquiring unit and the receiving unit and is used for receiving the first instruction and the position data set, judging whether the time interval between the time node of the last position data in the current sliding window and the time node of the next position data outside the sliding window is smaller than a preset time threshold value or not, correcting the position data according to the judgment result until the last data in the sliding window is the last data of the position data set, and outputting the position data set at the moment as a first positioning track.
Preferably, the client further includes:
the second acquisition unit is used for outputting a second instruction, and the second instruction is used for acquiring a second positioning track of the client;
the server side further comprises:
and the second processing unit is respectively connected with the second acquisition unit and the first processing unit and is used for acquiring the first positioning track processed by the first processing unit, clustering the first positioning track, and outputting all the result clustering sets and the clustering reference points after clustering as second positioning tracks.
Preferably, the client further includes:
a third obtaining unit, configured to output a third instruction, where the third instruction is used to obtain a third positioning track of the client;
the server side further comprises:
and the third processing unit is respectively connected with the third acquiring unit and the second processing unit, and is used for acquiring the second positioning track processed by the second processing unit, performing inflection point processing on the second positioning track, acquiring the position data set after the inflection point processing, and outputting the position data set as a third positioning track.
Preferably, the client further includes:
a fourth obtaining unit, configured to output a fourth instruction, where the fourth instruction is used to obtain a fourth positioning track of the client;
the server side further comprises:
and the fourth processing unit is respectively connected with the fourth acquiring unit and the third processing unit, and is used for acquiring the third positioning track processed by the third processing unit, performing inflection point processing on the third positioning track, acquiring the position data set after the inflection point processing, and outputting the position data set as a fourth positioning track.
The beneficial effects of the above technical scheme are: the accuracy of the position data is improved, the processing speed of the position data is improved, and the finally generated positioning track is smoother while the inflection point and the inflection point are kept.
Drawings
FIG. 1 is a schematic flow chart of a first process in a preferred embodiment of the present invention;
FIG. 2 is a schematic flow chart of a second process in a preferred embodiment of the present invention;
FIG. 3 is a flow chart of a third process in a preferred embodiment of the present invention;
FIG. 4 is a schematic diagram of cross multiplication in a third process in a preferred embodiment of the present invention;
FIG. 5 is a schematic flow chart of a fourth process in a preferred embodiment of the present invention;
FIG. 6 is a schematic structural view of a preferred embodiment of the present invention;
FIG. 7 is a schematic illustration of the bleaching in a preferred embodiment of the present invention;
FIG. 8 is a schematic illustration of a preferred embodiment of the present invention after a drift correction;
FIG. 9 is a diagram of the original trajectory in a preferred embodiment of the present invention;
FIG. 10 is a diagram of a modified trajectory in a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
A method for correcting rarefaction of a positioning track is used for correcting rarefaction of the positioning track and comprises a plurality of clients and a service end, wherein the clients are respectively and remotely connected with the service end, each client is provided with an acquisition device, the acquisition devices acquire position information of the corresponding clients at a preset time interval, and the position information and corresponding time nodes are included in position data and output to a server;
the method also comprises a first process:
step A1, the server receives the position data and sorts all the position data in the sequence of time nodes to generate a position data set;
step A2, setting a sliding window with a preset time length in the server, wherein in the initial state, the initial end in the sliding window corresponds to the first position data in the position data set;
step a3, the server determines whether the time interval between the time node of the last position data in the current sliding window and the time node of the next position data outside the sliding window is less than a preset time threshold:
if yes, go to step A4;
if not, the server side controls the sliding window to slide forward by a time node, and then the step A5 is carried out;
step a4, the server determines whether the distance between the position information of the last position data in the current sliding window and the position information of the next position data outside the sliding window is less than a distance interval value:
if yes, correcting according to next position data outside the sliding window, and then turning to step A5;
if not, the server side controls the sliding window to slide forwards for a preset time length, and then the step A5 is carried out;
and step A5, returning to the step A1, outputting the current position data set as a first positioning track until the last data in the sliding window is the last data of the position data set, and then ending.
Specifically, a user often carries a satellite positioning system such as a GPS and a beidou at a client for positioning, however, due to poor received signals at the client and interference of external factors, position data output from the client to a server is inaccurate, and a drift phenomenon occurs, so that accuracy of a user positioning track finally generated at the client is affected.
Therefore, a method for correcting and rarefying the positioning track is set, a client acquires position information at a preset time interval, the position information can be regarded as a position point with latitude and longitude, the position information and a corresponding time node are included in position data and sent to a server, and the server sorts the position information to generate a position data set P { P ═ P { (P) }1,p2,…pnIn which p is1For presenting clientsThe location data, corresponding to p, sent to the server for the first time2For expressing the position data sent by the client to the server for the first time, the position data set can represent the change process of the position information of the client.
Correspondingly, the server side is provided with a sliding window, the initial end in the sliding window corresponds to the first position data in the position data set, the tail end corresponds to the other position data in the position data set, traversal in the position data set is realized by controlling the sliding of the sliding window, and the correction of the position data is completed. Where the sliding window fixedly includes five position data and the position data within the sliding window is accurate by default.
In order to make the position data more accurate, considering that the server collects the position information at a preset time interval, then the time interval between the time node of the position data corresponding to the tail end in the sliding window and the time node of the next position data outside the sliding window is judged, if the time interval is smaller than a preset time threshold, it is indicated that the position data at this time is timely sent by the client and timely received by the server, the position data at this time is accurate and has a reference value, then step a4 is performed, and the server judges whether the distance between the position information of the position data corresponding to the tail end in the current sliding window and the position information of the next position data outside the sliding window is smaller than a distance interval value: if so, the current position information is accurate, and if not, the current position information is inaccurate, and the position information of the next position data outside the sliding window can be corrected.
Further, in order to make the value of the distance interval value more reasonable, the server obtains the position average value of all position data in the current sliding window, and performs linear operation to generate a distance interval value s, which can be represented by the following formula:
based on data analysis of multiple servers, common occurrence modes of users, and rules of change of location information, m here is the number of data contained in the sliding window, which is usually 5, and k is usually 2.
In a preferred embodiment of the present invention, in step a4, the sliding window corrects the next position data outside the sliding window by using the following formula:
wherein the content of the first and second substances,
Specifically, the server side usually corrects the position data by using the formula (2), and the influence of the accumulation effect on the positioning track of the user can be reduced by a difference correction mode, so that the accuracy of the position data is improved.
In a preferred embodiment of the present invention, the method further includes a second process, and the second process is executed after the first process, as shown in fig. 2, the second process includes:
step B1, the server side obtains a position data set corresponding to the first positioning track, and takes the first position data of the position data set as a clustering reference point;
step B2, the server side sequentially generates a first cluster set and a second cluster set according to the cluster reference point, the first cluster set at least comprises the cluster reference point and the position data of the i-th position of the cluster reference point, the second cluster set at least comprises the cluster reference point and the position data of the i + 1-th position of the cluster reference point, i is a natural number, and i is more than or equal to 1;
step B3, the server determines whether the distance difference between the farthest distance between the points in the first cluster set and the farthest distance between the points in the second cluster set is less than a preset distance threshold:
if not, making i +1 ═ i, so that the server reconstructs the first cluster set and the second cluster set, and then going to step B4;
if so, the server uses the second position data after the current clustering reference point as a clustering reference point to reconstruct the first cluster set as a result cluster set, and then goes to step B4;
step B4, the server determines whether the last location data in the location data set is added to the first cluster set or used as a cluster reference point:
if not, go to step B2;
if yes, go to step B5;
and step B5, the server side respectively processes the particle data corresponding to each result cluster set and replaces all position data in the corresponding result cluster set, all result cluster sets and all cluster reference points after replacement are output as second positioning tracks, and then the process is finished.
Specifically, in consideration of the fact that the client acquires and transmits the position information at the preset time interval, in order to make the position information more accurate, the set time interval is smaller, the acquired position information is too much, and the speed is reduced during subsequent processing due to too much information.
Setting a second process, regarding the situation that the position information in a period of time is not changed or is changed little, the position information collected by the server can be regarded as the current position point, including the longitude and latitude of the client at the moment, the second process processes the position data in sequence, and the first cluster set P' ═ { P ═ is used for processing the position data1,p2,…piAnd a second set of clusters P ═ P1,p2,…pi+1Comparing the distances between the two clusters, judging whether the second position data behind the cluster point can be clustered, if the second position data can not be clustered, taking the second position data as a new cluster point, repeating the steps, and finally generating a plurality of result cluster sets and a plurality of cluster reference points, wherein the distance between each cluster reference point and the adjacent position data is too large, and the distance between the position data in each result cluster set is too small.
For example, when a user drives a bus at a bus station and the like, although the position information may slightly change, the position information does not exceed the range of the bus station, and the changed position information in the bus station is clustered into a result cluster set through clustering in the second process, so that convenience is brought to data processing, and finally generated positioning tracks are more visual.
In a preferred embodiment of the present invention, step B5 uses the following formula to obtain particle data:
wherein the content of the first and second substances,
p′xlongitude for representing the particle data;
p′ylatitude used for representing particle data;
in a preferred embodiment of the present invention, the method further includes a third process, and the third process is executed after the second process, as shown in fig. 3, where the third process includes:
step C1, the server side obtains a position data set corresponding to the second positioning track, and takes the first position data of the position data set as an inflection point reference point;
step C2, the server side arranges the inflection point reference point and the position data of the last three bits of the inflection point reference point in a inflection point reference set in sequence, and obtains the vector cross product result corresponding to the inflection point reference set;
step C3, the server side judges whether the vector cross product result is less than zero:
if so, recording the third position data in the inflection point reference set as the important point, and then turning to the step C4;
if not, recording the third position data in the inflection point reference set as the unimportant point, and then going to step C4;
in step C4, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step C5;
if not, taking the position data of the next position of the current inflection point reference point as the inflection point reference point, and then returning to the step C2;
and step C5, the server deletes the position data corresponding to all the non-important points in the inflection point reference set from the position data set, outputs the position data set at the moment as a third positioning track, and then ends.
Specifically, considering that the inflection point in the positioning track of the client is important, a third process is set, and in order to solve the problem that the position information in a period of time is uniformly changed at an angle, the server acquires a position data set corresponding to the second positioning track, uses the first position data of the position data set as an inflection point reference point, sequentially selects four position data according to the inflection point reference point to generate an inflection point reference set, and judges whether a vector cross product result q corresponding to the inflection point reference set is smaller than zero, as shown in fig. 4, a point B is set as an inflection point reference point, and a cross product result q is obtained by calculating according to the following formula:
if the cross multiplication result q is smaller than zero, the inflection point reference point is indicated to have a certain change angle, and the point has reference significance for angle change in the inflection point reference set, so that the point needs to be reserved, otherwise, the point can be deleted, and through a third processing process, the angle profile of the positioning track can be reserved to the maximum extent while the data calculation amount is further reduced.
For example, if a user drives a straight road and a winding road in a driving path, a positioning track is generated in which only the head end and the tail end of the straight road need to be determined in a straight road portion, and each bent break point in the road needs to be clearly positioned in a winding road portion. And through the breakpoint processing in the third process, each breakpoint with the change of the motion angle in the driving process is reserved, so that the finally generated positioning track is more visual.
In a preferred embodiment of the present invention, the method further includes a fourth process, and the fourth process is executed after the third process, as shown in fig. 5, the fourth process includes:
step D1, the server acquires a position data set corresponding to the third positioning track, and presets a first angle threshold and a second angle threshold in the server by taking the first position data of the position data set as a break point reference point, wherein the first angle threshold is smaller than the second angle threshold, and the server selects the first angle threshold and the second angle threshold at intervals as angle thresholds;
in an initial state, the server takes a first angle threshold value as an angle threshold value;
d2, the server side sequentially selects three position data according to the break point reference point to generate a break point reference set, and obtains a break point angle corresponding to the second position data in the break point reference set;
step D3, the server determines whether the importance of the second location data is greater than the importance of the third location data:
if so, the server uses the second angle threshold as an angle threshold, and then goes to step D4;
if not, the server takes the first angle threshold as an angle threshold, and then goes to step D4;
step D4, the server side judges whether the break point angle is smaller than the angle threshold:
if so, the server records the second position data in the breakpoint reference set as the important point, and then goes to step D5;
if not, the server records the second position data in the breakpoint reference set as the unimportant point, and then goes to step D5;
step D5, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step D6;
if not, taking the next position data of the current inflection point reference point as the inflection point reference point, and then turning to the step D2;
and D6, the server deletes all the unimportant points in the position data set, outputs the position data set at the moment as a fourth positioning track, and then ends.
Specifically, in order to improve the accuracy of data processing and make the positioning track smoother, a fourth process is set, the server comprehensively judges the importance of the second position data and the third position data in each break point reference set according to the third positioning track, if the second position data is more important than the third position data in the whole positioning track, a larger second angle threshold is selected as an angle threshold, and then the server judges that the probability that the break point angle corresponding to the second position data is smaller than the angle threshold is larger, the second position data can be recorded as the important point to be reserved, and otherwise, the second position data is deleted.
Here, by judging the importance to select the value of the angle threshold, the possibility that the position data is reserved or deleted can be controlled, the flexibility of data processing is improved, and adaptive data reservation is realized.
In addition, the importance here can be defined manually by the operator when performing data processing according to the actual path situation.
A system for correcting rarefaction of positioning track, which is applied to the above method for correcting rarefaction of positioning track, as shown in fig. 6, includes a plurality of clients 1 and a server 2;
each client 1 includes:
the acquisition unit 11 is arranged on the client 1 and used for acquiring the position information of the client 1 at a preset time interval and outputting the position information and the corresponding time node included in position data;
the first acquiring unit 12, the first acquiring unit 12 is configured to output a first instruction, and the first instruction is used to acquire a first positioning track of the client 1;
the server 2 is remotely connected with all the clients 1, and the server 2 comprises:
the receiving unit 21 is configured to receive the position data, and sort all the position data in the order of the time nodes to generate a position data set;
and the first processing unit 22 is connected to the first obtaining unit 12 and the receiving unit 21, and is configured to receive the first instruction and the position data set, determine whether a time interval between a time node of last position data in the current sliding window and a time node of next position data outside the sliding window is smaller than a preset time threshold, modify the position data according to a determination result, and output the position data set at the time as the first positioning track when the last data in the sliding window is the last data of the position data set.
In a preferred embodiment of the present invention, the client 1 further includes:
the second obtaining unit 13 is configured to output a second instruction, where the second instruction is used to obtain a second positioning track of the client 1;
the server 2 further comprises:
and the second processing unit 23 is connected with the second obtaining unit 13 and the first processing unit 22 respectively, and is configured to obtain the first positioning track processed by the first processing unit 22, perform clustering processing on the first positioning track, and obtain all result clustering sets and clustering reference points after the clustering processing to output as second positioning tracks.
In a preferred embodiment of the present invention, the client 1 further includes:
a third obtaining unit 14, where the third obtaining unit 14 is configured to output a third instruction, and the third instruction is used to obtain a third positioning track of the client 1;
the server 2 further comprises:
and the third processing unit 24 is connected to the third acquiring unit 14 and the second processing unit 23, respectively, and is configured to acquire the second positioning trajectory processed by the second processing unit 23, perform inflection point processing on the second positioning trajectory, acquire a position data set after the inflection point processing, and output the position data set as a third positioning trajectory.
In a preferred embodiment of the present invention, the client 1 further includes:
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to output a fourth instruction, and the fourth instruction is used to obtain a fourth positioning track of the client 1;
the server 2 further comprises:
and the fourth processing unit 25 is connected to the fourth acquiring unit 15 and the third processing unit 24, respectively, and is configured to acquire the third positioning track processed by the third processing unit 24, perform inflection point processing on the third positioning track, acquire a position data set after the inflection point processing, and output the position data set as the fourth positioning track.
Specifically, in actual use, the plurality of servers 2 all send the acquired position data to the servers 2 through the acquisition unit 11, and can send the first instruction, the second instruction, the third instruction or the fourth instruction according to actual requirements, and correspondingly, the servers 2 can also perform position data according to the corresponding instructions and output corresponding positioning tracks.
In conclusion, the method has high-efficiency correction capability, the first process and the sliding window are set to correct the position data, and the second process, the third process and the fourth process are set, so that the data volume is reduced to about 50% of the original data volume, very similar contours and important inflection points can be reserved, the processing efficiency is improved, and the accuracy of a processing result is improved.
In a preferred embodiment of the invention, the drift is seen to be more severe in the raw, untreated drift point, as can be seen from figures 7 and 8. After the correction of the algorithm, the drift point is corrected.
In a preferred embodiment of the present invention, the original trajectory diagram of fig. 9 has 2257 points, and fig. 10 shows 1029 points after calculation by the algorithm, so that the data amount is greatly reduced compared to the original data, and the features and contours of the trajectory are retained.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. A method for correcting and rarefying a positioning track is used for correcting and rarefying the positioning track and is characterized by comprising a plurality of clients and a server, wherein the clients are respectively and remotely connected with the server, each client is provided with an acquisition device, and the acquisition devices acquire position information of the corresponding client at a preset time interval, include the position information and a corresponding time node in position data and output the position data to the server;
the method further comprises a first process:
step A1, the server receives the position data, and generates a position data set by sequencing all the position data according to the sequence of the time nodes;
step A2, setting a sliding window with a preset time length in the server, wherein in an initial state, the initial end in the sliding window corresponds to the first position data in the position data set;
step a3, the server determines whether a time interval between a time node of the last position data in the sliding window and a time node of the next position data outside the sliding window is smaller than a preset time threshold:
if yes, go to step A4;
if not, the server controls the sliding window to slide forward by one time node, and then the step A5 is carried out;
step a4, the server determines whether the distance between the position information of the last position data in the current sliding window and the position information of the next position data outside the sliding window is less than a distance interval value:
if yes, correcting according to next position data outside the sliding window, and then turning to step A5;
if not, the server controls the sliding window to slide forwards for the preset time length, and then the step A5 is carried out;
and step A5, returning to the step A1, outputting the current position data set as a first positioning track until the last data in the sliding window is the last data of the position data set, and then ending.
2. The method of claim 1, wherein in step a4, the sliding window corrects the next position data outside the sliding window by using the following formula:
wherein the content of the first and second substances,
3. The method of claim 1, further comprising a second process, the second process being performed after the first process, the second process comprising:
step B1, the server side obtains a position data set corresponding to the first positioning track, and takes the first position data of the position data set as a clustering reference point;
step B2, the server side sequentially generates a first cluster set and a second cluster set according to the cluster reference point, the first cluster set at least comprises the cluster reference point and the position data of the i-th position of the cluster reference point, the second cluster set at least comprises the cluster reference point and the position data of the i + 1-th position of the cluster reference point, i is a natural number and is more than or equal to 1;
step B3, the server determines whether the distance difference between the farthest distance between the points in the first cluster set and the farthest distance between the points in the second cluster set is less than a preset distance threshold:
if not, making i +1 ═ i, so that the server reconstructs the first cluster set and the second cluster set, and then go to step B4;
if so, the server uses second location data after the current clustering reference point as the clustering reference point to reconstruct the first cluster set as a result cluster set, and then goes to step B4;
step B4, the server determines whether the last location data in the location data set is added to the first cluster set or serves as the clustering reference point:
if not, go to step B2;
if yes, go to step B5;
and step B5, the server side respectively processes the particle data corresponding to each result cluster set and replaces all the position data in the corresponding result cluster set, all the result cluster sets and all the cluster reference points after replacement are output as second positioning tracks, and then the process is finished.
4. The method of claim 3, wherein the particle data obtained in step B5 is obtained by the following formula:
wherein the content of the first and second substances,
p′xa longitude to represent the particle data;
p′ya latitude for representing the particle data;
5. A method for correcting rarefaction of a localized track as claimed in claim 3, further comprising a third process, said third process being performed after said second process, said third process comprising:
step C1, the server acquires the position data set corresponding to the second positioning track, and uses the first position data of the position data set as an inflection point reference point;
step C2, the server sequentially arranges the inflection point reference point and the position data of the last three bits of the inflection point reference point in an inflection point reference set, and obtains a vector cross product result corresponding to the inflection point reference set;
step C3, the server determines whether the vector cross product result is less than zero:
if so, recording the third position data in the inflection point reference set as the important point, and then turning to the step C4;
if not, recording a third location data in the inflection point reference set as an insignificant point, and then proceeding to step C4;
step C4, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step C5;
if not, taking the position data of the next bit of the inflection point reference point as the inflection point reference point, and then returning to the step C2;
and step C5, the server deletes the position data corresponding to all the non-significant points in the inflection point reference set from the position data set, outputs the position data set at this time as a third positioning trajectory, and then ends.
6. The method of claim 5, further comprising a fourth process, the fourth process being performed after the third process, the fourth process comprising:
step D1, the server obtains the location data set corresponding to the third positioning track, and uses the first location data of the location data set as a break point reference point, a first angle threshold and a second angle threshold are preset in the server, the first angle threshold is smaller than the second angle threshold, the server selects the first angle threshold and the second angle threshold at intervals as angle thresholds, and the server uses the first angle threshold as the angle threshold in an initial state;
d2, the server side sequentially selects three position data according to the break point reference point to generate a break point reference set, and obtains a break point angle corresponding to the second position data in the break point reference set;
step D3, the server determines whether the importance of the second location data is greater than the importance of the third location data:
if yes, the server uses the second angle threshold as an angle threshold, and then goes to step D4;
if not, the server takes the first angle threshold as an angle threshold, and then goes to step D4;
step D4, the server side judges whether the break point angle is smaller than an angle threshold:
if so, the server records the second position data in the break point reference set as the important point, and then goes to step D5;
if not, the server records the second position data in the break point reference set as the unimportant point, and then goes to step D5;
step D5, the server determines whether the inflection point reference set includes the last location data of the location data set:
if yes, go to step D6;
if not, taking the next position data of the current inflection point reference point as the inflection point reference point, and then turning to step D2;
and D6, the server deletes all unimportant points in the position data set, outputs the position data set at the moment as a fourth positioning track, and then ends.
7. A system for location track correction rarefaction, applied to the method for location track correction rarefaction of claims 1-6, comprising a plurality of clients and a server;
each of the clients includes:
the acquisition unit is arranged on the client and used for acquiring the position information of the client at a preset time interval and outputting the position information and the corresponding time node included in position data;
the first acquisition unit is used for outputting a first instruction, and the first instruction is used for acquiring a first positioning track of the client;
the server is remotely connected with all the clients, and comprises:
the receiving unit is used for receiving the position data and sequencing all the position data according to the sequence of the time nodes to generate a position data set;
and the first processing unit is respectively connected with the first acquiring unit and the receiving unit and is used for receiving the first instruction and the position data set, judging whether the time interval between the time node of the last position data in the current sliding window and the time node of the next position data outside the sliding window is smaller than a preset time threshold value or not, correcting the position data according to the judgment result until the last data in the sliding window is the last data of the position data set, and outputting the position data set at the moment as a first positioning track.
8. The system of claim 7, wherein the client further comprises:
the second acquisition unit is used for outputting a second instruction, and the second instruction is used for acquiring a second positioning track of the client;
the server side further comprises:
and the second processing unit is respectively connected with the second acquisition unit and the first processing unit and is used for acquiring the first positioning track processed by the first processing unit, clustering the first positioning track, and outputting all the result clustering sets and the clustering reference points after clustering as second positioning tracks.
9. The system of claim 8, wherein the client further comprises:
a third obtaining unit, configured to output a third instruction, where the third instruction is used to obtain a third positioning track of the client;
the server side further comprises:
and the third processing unit is respectively connected with the third acquiring unit and the second processing unit, and is used for acquiring the second positioning track processed by the second processing unit, performing inflection point processing on the second positioning track, acquiring the position data set after the inflection point processing, and outputting the position data set as a third positioning track.
10. The system of claim 9, wherein the client further comprises:
a fourth obtaining unit, configured to output a fourth instruction, where the fourth instruction is used to obtain a fourth positioning track of the client;
the server side further comprises:
and the fourth processing unit is respectively connected with the fourth acquiring unit and the third processing unit, and is used for acquiring the third positioning track processed by the third processing unit, performing inflection point processing on the third positioning track, acquiring the position data set after the inflection point processing, and outputting the position data set as a fourth positioning track.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113777643A (en) * | 2021-07-30 | 2021-12-10 | 国网浙江杭州市余杭区供电有限公司 | Fault early warning method and device for preventing transmission line from being broken outside |
| CN114911887A (en) * | 2022-04-22 | 2022-08-16 | 阿波罗智联(北京)科技有限公司 | Data processing method, device, equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103500516A (en) * | 2013-09-26 | 2014-01-08 | 深圳市宏电技术股份有限公司 | High-efficiency trace replay method and system based on electronic map |
| WO2016165606A1 (en) * | 2015-04-16 | 2016-10-20 | 腾讯科技（深圳）有限公司 | Data collection method, device, and system |
| US20170227364A1 (en) * | 2016-02-10 | 2017-08-10 | Fujitsu Limited | Information processing apparatus and trajectory information generating method |
| CN109766777A (en) * | 2018-12-18 | 2019-05-17 | 东软集团股份有限公司 | Detection method, device, storage medium and the electronic equipment of abnormal track |
| CN109870713A (en) * | 2019-01-08 | 2019-06-11 | 武汉众智鸿图科技有限公司 | A kind of GPS track curve generation method and device |
| CN109917430A (en) * | 2019-04-03 | 2019-06-21 | 安徽中科智能感知产业技术研究院有限责任公司 | A kind of satellite positioning track drift method for correcting error based on smooth trajectory algorithm |
-
2020
- 2020-04-23 CN CN202010328446.2A patent/CN111505681B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103500516A (en) * | 2013-09-26 | 2014-01-08 | 深圳市宏电技术股份有限公司 | High-efficiency trace replay method and system based on electronic map |
| WO2016165606A1 (en) * | 2015-04-16 | 2016-10-20 | 腾讯科技（深圳）有限公司 | Data collection method, device, and system |
| US20170227364A1 (en) * | 2016-02-10 | 2017-08-10 | Fujitsu Limited | Information processing apparatus and trajectory information generating method |
| CN109766777A (en) * | 2018-12-18 | 2019-05-17 | 东软集团股份有限公司 | Detection method, device, storage medium and the electronic equipment of abnormal track |
| CN109870713A (en) * | 2019-01-08 | 2019-06-11 | 武汉众智鸿图科技有限公司 | A kind of GPS track curve generation method and device |
| CN109917430A (en) * | 2019-04-03 | 2019-06-21 | 安徽中科智能感知产业技术研究院有限责任公司 | A kind of satellite positioning track drift method for correcting error based on smooth trajectory algorithm |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113777643A (en) * | 2021-07-30 | 2021-12-10 | 国网浙江杭州市余杭区供电有限公司 | Fault early warning method and device for preventing transmission line from being broken outside |
| CN114911887A (en) * | 2022-04-22 | 2022-08-16 | 阿波罗智联(北京)科技有限公司 | Data processing method, device, equipment and storage medium |
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