CN113660607B - Data post-processing system and method based on WiFi-RTT ranging - Google Patents
Data post-processing system and method based on WiFi-RTT ranging Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
- G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/08—Systems for measuring distance only
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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- H—ELECTRICITY
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- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
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- H—ELECTRICITY
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- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The invention relates to a data post-processing system and a data post-processing method based on WiFi-RTT ranging, wherein the system comprises a central processing unit, a data acquisition system, a semi-system error calibration system and a positioning resolving system, and a mode discrimination system of the semi-system error calibration system performs mode discrimination through router information comparison and obtains a mode change time sequence; the half-system error resolving system resolves the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector; combining the half-system error vector and the mode change time sequence to obtain a half-system error time correction; the positioning calculation system obtains the final positioning calculation result with timing and no influence of system error through time interval limitation. According to the method, the return value state is screened, so that the semi-system error vectors in different time periods are effectively obtained, and the operation cost is greatly reduced; the error of the semi-system is predetermined through the calculation, so that the calculation cost of the positioning calculation is greatly reduced, and the positioning accuracy is improved.
Description
Technical Field
The invention relates to the technical field of indoor positioning, in particular to a data post-processing system and method based on WiFi-RTT ranging.
Background
The application of location based services has led to an increasing interest in positioning techniques, while at the same time placing higher demands on the accuracy of the positioning results. With the popularization and application of smart phones, providing a plurality of mobile phones based on location services will become a main carrier for high-precision positioning of the masses in the future. Since navigation signals based on Global Navigation Satellite Systems (GNSS) are difficult to be received indoors, they cannot be used for indoor positioning. In order to solve the indoor positioning problem, various technical solutions have been proposed, such as WiFi, ultra wideband, bluetooth, inertial sensors, etc., and compared with other technologies, wiFi has received more attention due to its huge audience and low price. The distance measurement modes such as ToA, TDoA and the like have serious deviation of distance measurement results due to clock error, so that the distance measurement modes are extremely unreasonable to be used for positioning. The RTT ranging method can provide a more accurate ranging result due to the influence of eliminating clock error, and cannot obtain a good positioning result due to the existence of a semi-system error. In the use process, the frequent change of the return value state of the router adds difficulty to indoor high-precision positioning, and no reasonable solution is proposed at present.
Disclosure of Invention
The invention aims to provide a data post-processing system and method based on WiFi-RTT ranging, so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: the data post-processing system based on WiFi-RTT distance measurement comprises a central processing unit, wherein the central processing unit is respectively connected with a data acquisition system, a semi-system error calibration system and a positioning resolving system,
the data acquisition system is used for acquiring and storing data into a data set; the data set is transmitted to the central processing unit for data preprocessing, and the central processing unit provides the information after data preprocessing for the semi-system error calibration system;
the half-system error calibration system comprises a mode screening system and a half-system error resolving system; the mode discrimination system performs mode discrimination through router information comparison, obtains a mode change time sequence, and transmits the mode change time sequence to the central processing unit and the half-system error resolving system; the half-system error resolving system utilizes a half-system error resolving algorithm to resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector; the half-system error calibration system transmits the half-system error vector to the central processing unit;
the central processing unit combines the half-system error vector and the mode change time sequence to obtain a half-system error time correction, and transmits the half-system error time correction to the positioning calculation system;
the positioning calculation system obtains a final positioning calculation result which is timed and has no influence of system errors through time interval limitation.
Furthermore, the data acquisition system performs active and passive data acquisition through the radio frequency signal or the inertial navigation system, the acquired data is stored in a data set according to the time stamp returned by the highest sampling frequency, in order to ensure the data integrity, each time stamp in the data set comprises data results provided by all signal sources, if the low-frequency sampling signal is not updated, the data results are kept unchanged, and the time stamp update is the same as the time stamp of the highest sampling frequency.
Further, in the data set, if the low-frequency sampling signal data timestamp is not matched with the highest sampling frequency timestamp, the highest sampling frequency timestamp closest to the low-frequency sampling signal data information is updated by the low-frequency sampling signal data information, and the highest sampling frequency timestamp is not forced to be rounded up.
Further, the data set comprises RTT ranging results, RSSI ranging results, RTT variance, time stamps and inertial navigation signals provided by the inertial navigation system and provided by the WiFi signal source.
According to another aspect of the present invention, a method for performing data post-processing based on WiFi-RTT ranging using the aforementioned system is provided, including the following steps:
the data acquisition system is used for acquiring and storing data into a data set; transmitting the data set to the central processing unit for data preprocessing;
step 2, the central processing unit provides the information after data preprocessing to the semi-system error calibration system;
step 3, the mode discrimination system in the half-system error calibration system performs mode discrimination through router information comparison, obtains a mode change time sequence, and transmits the mode change time sequence to the central processing unit and the half-system error calculation system;
step 4, the half-system error resolving system utilizes a half-system error resolving algorithm to resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector;
step 5, the half-system error calibration system transmits the half-system error vector to the central processing unit;
step 6, the central processing unit combines the half-system error vector and the mode change time sequence to obtain a half-system error time correction, and transmits the half-system error time correction to the positioning calculation system;
and 7, the positioning resolving system obtains a final positioning resolving result which is timed and has no influence of a system error through time interval limitation.
Further, the mode screening system obtains the information after data preprocessing, then performs data extraction, extracts relevant information of WiFi RTT to form a new data set, and the forming rule of the new data set is as follows:
(1) The state of the return value is changed, and the semi-system error sequence of the data result is changed;
(2) Compared with the data at the previous moment, if the number of routers is increased, the data state is changed, and the half-system error is reset;
(3) The return value state is unchanged, and the sequence of the return value numbers of the routers in the data set is unchanged;
(4) The abrupt change of the time difference between adjacent data is easier to cause the state change of the return value;
(5) The degree of correlation of the time difference mutation and the return value state change decreases as the sampling period increases;
(6) A floating point number greater than 0 and in the form of xx.xx is randomly generated for each router number to serve as the characteristic number of different routers.
Further, in the step 3, the mode discrimination system performs the information comparison strategy as follows:
(3.1) comparing the router numbers of the RTT ranging information at the moment and the router numbers of the previous 1 time, and if the router numbers at the moment are larger than the router numbers of the previous 1 time, considering the state change of the return value, and updating the mode change time sequence; if the numbers of the routers are the same for the two times, entering a step (3.2); if the number of the routers at the moment is smaller than that of the routers in the previous 1 time, entering a step (3.3);
(3.2) calculating a floating point number which randomly generates a form of xx.xx for each router number as the sum of feature numbers of different routers, and if the feature numbers are equal in two times, considering that the state of a return value is unchanged, and ending the operation; if the feature numbers are different in the front and back times, the state of the return value is considered to be changed, and the mode change time sequence is updated;
(3.3) calculating the sum of the feature numbers, if the difference between the sum of the feature numbers at the previous time and the sum of the feature numbers at the next time is equal to the sum of a certain feature number or a certain number of feature numbers at the previous time, considering that the router number set at the previous time completely comprises the router number set at the moment, namely no new router number appears, and taking the negative value of the time stamp as update data to update the mode change time sequence; otherwise, the return value state is considered to be changed, and the mode change time sequence is updated.
Further, in the step 4, the mode change time sequence and the preprocessed data are obtained through a half-system error resolving algorithm, and the half-system error vector is obtained through resolving according to the following steps:
step (4.1), obtaining the pattern change time series and the preprocessed data;
step (4.2), dividing the preprocessed data through the mode change time sequence to obtain a series of data spaces with stable semi-system errors;
step (4.3), setting half-system error parameters according to different routers for each data space; distinguishing different routers by utilizing the data format and how often the router appears in a data space;
step (4.4), establishing an observation equation: v=l 0 -l+XX i Wherein V represents the residual error, l 0 Representing the real distance between the mobile phone and the specific router, and l represents the observed result between the mobile phone and the specific router, XX i Representing the half-systematic error of a particular router XX in the current data space;
step (4.5), establishing a half-system error relation equation:
step (4.6), establishing a total relation equation of the semi-system errors:
step (4.7), establishing an indirect adjustment equation, wherein L=bx+delta, P, and carrying out equation solving according to a least square method to obtain a semi-system error vector; wherein B is a parameter matrix composed of reference positions and half-system errors, x comprises position vectors xyz and half-system errors the same as routers in number, delta is noise, mean value is 0, and variance is sigma 2 L is V, P in step S204, is a weight matrix, and is determined by the RTT variance.
The beneficial effects are that:
compared with the prior art, the invention has the following advantages: the data processing process of the invention carries out element vectorization, and the semi-system error vector of different time periods can be effectively obtained by screening the state of the return value, thus greatly reducing the operation cost; the semi-system error is predetermined through the calculation, so that the calculation cost of the positioning calculation is greatly reduced, and the positioning accuracy is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a data post-processing system based on WiFi-RTT ranging according to an embodiment of the invention;
FIG. 2 is a flowchart of a discrimination algorithm for a suitable mode discrimination system according to an embodiment of the invention;
fig. 3 is a flow chart of a resolving algorithm suitable for a half-system error resolving system according to an embodiment of the present invention.
Reference numerals:
1. a central processing unit; 2. a data acquisition system; 3. a semi-system error calibration system; 4. a positioning calculation system; 5. a data set; 6. RTT ranging information; 7. RSSI ranging results; 8. RTT variance; 9. a time stamp; 10. inertial navigation signals provided by the inertial navigation system; 11. information after data preprocessing; 12. a mode discrimination system; 13. a pattern change time sequence; 14. a half-system error resolving system; 15. a half-system error calculation algorithm; 16. a semi-systematic error vector; 17. semi-systematic error time correction.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without the inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
Referring to fig. 1, according to an embodiment of the present invention, a data post-processing system based on WiFi-RTT ranging is provided, which includes a central processing unit 1, and a data acquisition system 2, a half-system error calibration system 3 and a positioning resolving system 4 are respectively connected to the central processing unit 1; the data acquisition system 2 acquires and stores data into a data set 5; the data set 5 includes, but is not limited to, RTT ranging information 6 provided by a WiFi signal source, RSSI ranging result 7, RTT variance 8, timestamp 9, inertial navigation signal 10 provided by an inertial navigation system, etc.; the data acquisition system 2 then transmits the data set 5 to the central processing unit 1 for data preprocessing, and the central processing unit 1 provides the data preprocessed information 11 to the semi-system error calibration system 3; the half-system error calibration system 3 includes a pattern discrimination system 12 and a half-system error calculation system 14; the mode discrimination system 12 performs mode discrimination through router information comparison and obtains a mode change time sequence 13, and then transmits the mode change time sequence to the central processing unit 1 and the half-system error resolving system 14; the half-system error resolving system 14 is provided with a half-system error resolving algorithm 15, and the half-system error resolving algorithm 15 can resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector 16; subsequently, the half-system error calibration system 3 transmits the half-system error vector 16 to the central processing unit 1, and the central processing unit 1 combines the half-system error vector 16 and the pattern change time sequence 13 to obtain a half-system error time correction 17, and then transmits the half-system error time correction 17 to the positioning calculation system 4; for the positioning solution system 4, the positioning solution system 4 may obtain the final timing, positioning solution result without systematic error effect through time interval limitation.
According to the embodiment of the invention, the data acquisition system 2 can perform active and passive data acquisition through a radio frequency signal or an inertial navigation system and the like, the acquired data is returned to the data set 5 according to the highest sampling frequency and is stored in the data set 5, in order to ensure the data integrity, for the data set 5, each time stamp in the data set 5 comprises data results provided by all signal sources, if the low-frequency sampling signal does not have data update, the data results are kept unchanged, and the time stamp update is the same as the highest sampling frequency time stamp;
according to the embodiment of the invention, in the data set 5, if the low-frequency sampling signal data timestamp is not matched with the highest sampling frequency timestamp, the highest sampling frequency timestamp closest to the low-frequency sampling signal data information is updated, and the upper rounding is not forced;
according to the embodiment of the invention, the mode screening system 12 extracts the data after obtaining the data preprocessing information 11, extracts the WiFi RTT related information to form a new data set, the mode change time sequence is extracted from the new data set, the new data set provides convenience for the extraction of the mode change time sequence, and the data set replaces all calculation after the original data set participates; the new dataset is formed as follows:
1. the state of the return value changes, and the semi-system error sequence of the data result changes; the return value state may be equivalent to the data set state in a certain sense, where, according to the embodiment of the present invention, the return value state refers to the return value state of WIFI-RTT, specifically includes the number of routers, RTT ranging information (6) between handsets and routers obtained by handsets, RSSI ranging result (7), RTT variance (8), timestamp (9), and the like, and preferably, the return value state must include the number of routers, the number and the time difference mutation, because the change of the three marks the change of the state of the whole data space, that is, the semi-system error contained in the data space has a change.
2. If the number of routers increases, the data state must change and the half-system error must be reset, compared with the data at the previous time;
3. the return value state is unchanged, and the sequence of the return value numbers of the routers in the data set is unchanged;
4. the abrupt change of the time difference between adjacent data is easier to cause the state change of the return value;
5. the degree of correlation of the time difference mutation and the return value state change decreases as the sampling period increases;
6. randomly generating a floating point number which is larger than 0 and is in the shape of xx.xx (such as 26.12, 78.63 and the like) as the characteristic number of different routers for each router number;
according to an embodiment of the present invention, there is further provided a discrimination algorithm for the mode discrimination system 12, as shown in fig. 2, and in a specific application, the mode discrimination system 12 performs the following information comparison strategy:
s101, comparing the router numbers of the RTT ranging information at the moment and the router numbers of the previous 1 time, and if the router numbers at the moment are larger than the router numbers of the previous 1 time, considering the state change of the return value, and updating the mode change time sequence 13; the format of the mode change time sequence 13 may be [ t1 t2 t3 t4 … ti … tn ], where ti represents that the time stamp is the state change time of the return value, and n represents the total number of points of the sequence; the mode change time sequence records the moment when the router return value in one data set changes, namely the router return value states in time areas formed by two adjacent time stamps in the mode change time sequence are consistent, and the router return value states in different time areas are different. The initial value of the time change sequence is the moment when the state of the router changes for the first time; if the numbers of the routers are the same, step S102 is entered; if the number of routers at this time is smaller than the number of routers in the previous 1 time, step S103 is entered;
s102, calculating a floating point number which randomly generates a form of xx.xx for each router number as the sum of feature numbers of different routers, and if the feature numbers are equal in two times (such as 26.12, 78.63 and the like), considering that the state of a return value is unchanged, and ending the operation; if the feature numbers are different in the front and back two times, the state of the return value is considered to be changed, and the mode change time sequence 13 is updated;
s103, calculating the sum of feature numbers, if the difference between the sum of feature numbers at the previous time and the sum of feature numbers at the next time is equal to the sum of feature numbers at the previous time or the sum of feature numbers at the previous time, considering that the router number set at the previous time 1 completely comprises the router number set at the moment, namely no new router number appears, and taking a negative value of a time stamp as update data to update the mode change time sequence 13; otherwise, consider a return value state change, updating the pattern change time series 13;
according to an embodiment of the present invention, there is further provided a solution algorithm suitable for the half-system error resolving system 14, as shown in fig. 3, in which, in a specific application, the half-system error resolving algorithm 15 obtains the pattern change time sequence and the preprocessed data, and the half-system error vector 16 is obtained by resolving as follows:
s201, obtaining the mode change time sequence and the preprocessed data;
s202, dividing the preprocessed data through the mode change time sequence to obtain a series of data spaces with stable semi-system errors;
s203, setting half-system error parameters according to different routers for each data space; e.g., AAi, ABi, BCi, etc., where the first two capital letters are used to distinguish between different routers and the following capital letters are used to distinguish how many times the router appears in the data space;
s204, establishing an observation equation: v=l 0 -l+XX i Wherein V represents the residual error, l 0 Representing the real distance between the mobile phone and the specific router, and l represents the observed result between the mobile phone and the specific router, XX i Representing the half-systematic error of a particular router XX in the current data space;
s205, establishing a half-system error relation equation:where n is the number of routers, i.e. the number of routers that can communicate successfully with the handset at the moment. I.e. the number of routers in the position solution equation, which determines the number of half-system errors, since the number of routers each corresponds to one half-system error. On the premise that the multiplexer participates in position settlement, the method Cheng Hanyi considers that the error of the semi-system obeys normal distribution with the mean value of 0 and the variance of sigma, namely the mean value of zero.
S206, establishing a half-system error overall relation equation:
s207, establishing an indirect adjustment equation, wherein L=Bx+delta, and P, and carrying out equation solving according to a least square method to obtain a semi-system error vector 16;
wherein B is a parameter matrix composed of reference positions and half-system errors, and x comprisesThe position vector xyz and the same half-systematic error as the number of routers, delta is noise, mean is 0, variance is sigma 2 L is V, P in step S204, is a weight matrix, and is determined by the RTT variance.
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 (7)
1. The data post-processing system based on WiFi-RTT distance measurement is characterized by comprising a central processing unit, wherein the central processing unit is respectively connected with a data acquisition system, a semi-system error calibration system and a positioning resolving system,
the data acquisition system is used for acquiring and storing data into a data set; the data set is transmitted to the central processing unit for data preprocessing, and the central processing unit provides the information after data preprocessing for the semi-system error calibration system;
the half-system error calibration system comprises a mode screening system and a half-system error resolving system; the mode discrimination system performs mode discrimination through router information comparison, obtains a mode change time sequence, and transmits the mode change time sequence to the central processing unit and the half-system error resolving system; the half-system error resolving system utilizes a half-system error resolving algorithm to resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector; the half-system error calibration system transmits the half-system error vector to the central processing unit;
the central processing unit combines the half-system error vector and the mode change time sequence to obtain a half-system error time correction, and transmits the half-system error time correction to the positioning calculation system;
the positioning resolving system obtains a final positioning resolving result without influence of a system error through time interval limitation;
the half-system error resolving system utilizes a half-system error resolving algorithm to resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector, and the method comprises the following specific steps:
step (4.1), obtaining the pattern change time series and the preprocessed data;
step (4.2), dividing the preprocessed data through the mode change time sequence to obtain a series of data spaces with stable semi-system errors;
step (4.3), setting half-system error parameters according to different routers for each data space; distinguishing different routers by utilizing the data format and how often the router appears in a data space;
step (4.4), establishing an observation equation: v=l 0 -l+XX i Wherein V represents the residual error, l 0 Representing the real distance between the mobile phone and the specific router, and l represents the observed result between the mobile phone and the specific router, XX i Representing the half-systematic error of a particular router XX in the current data space;
step (4.5), establishing a half-system error relation equation:
step (4.6), establishing a total relation equation of the semi-system errors:
step (4.7), establishing an indirect adjustment equation, wherein L=bx+delta, P, and carrying out equation solving according to a least square method to obtain a semi-system error vector; wherein B is a parameter matrix composed of reference positions and half-system errors, x comprises position vectors xyz and half-system errors the same as routers in number, delta is noise, mean value is 0, and variance is sigma 2 L is V, P in step S204, is a weight matrix, and is determined by the RTT variance.
2. The data post-processing system based on WiFi-RTT ranging according to claim 1, wherein the data acquisition system performs active and passive data acquisition through a radio frequency signal or an inertial navigation system, and returns the acquired data to a data set according to a time stamp with a highest sampling frequency, and in order to ensure data integrity, each time stamp in the data set includes data results provided by all signal sources, and if a low frequency sampling signal does not have data update, the data results remain unchanged, and the time stamp update is the same as the time stamp with the highest sampling frequency.
3. The WiFi-RTT ranging based data post-processing system according to claim 2, wherein in the data set, if the low frequency sampling signal data time stamp does not match the highest sampling frequency time stamp, the low frequency sampling signal data information updates the highest sampling frequency time stamp closest to the time stamp, and no further rounding is forced.
4. The WiFi-RTT ranging based data post processing system according to claim 1, wherein the data set includes RTT ranging information provided by a WiFi signal source, RSSI ranging results, RTT variance, time stamp, inertial navigation signal provided by an inertial navigation system.
5. A method of data post-processing based on WiFi-RTT ranging using the system according to any of claims 1-4, comprising the steps of:
the data acquisition system is used for acquiring and storing data into a data set; transmitting the data set to the central processing unit for data preprocessing;
step 2, the central processing unit provides the information after data preprocessing to the semi-system error calibration system;
step 3, the mode discrimination system in the half-system error calibration system performs mode discrimination through router information comparison, obtains a mode change time sequence, and transmits the mode change time sequence to the central processing unit and the half-system error calculation system;
step 4, the half-system error resolving system utilizes a half-system error resolving algorithm to resolve the information after the data preprocessing through the mode change time sequence to obtain a half-system error vector;
step 5, the half-system error calibration system transmits the half-system error vector to the central processing unit;
step 6, the central processing unit combines the half-system error vector and the mode change time sequence to obtain a half-system error time correction, and transmits the half-system error time correction to the positioning calculation system;
and 7, the positioning resolving system obtains a final positioning resolving result which is timed and has no influence of a system error through time interval limitation.
6. The method for performing WiFi-RTT ranging based data post processing according to claim 5, wherein the mode screening system obtains the data pre-processed information and then performs data extraction, extracts WiFi RTT related information to form a new data set, and the formation rule of the new data set is as follows:
(1) The state of the return value is changed, and the semi-system error sequence of the data result is changed;
(2) Compared with the data at the previous moment, if the number of routers is increased, the data state is changed, and the half-system error is reset;
(3) The return value state is unchanged, and the sequence of the return value numbers of the routers in the data set is unchanged;
(4) The abrupt change of the time difference between adjacent data is easier to cause the state change of the return value;
(5) The degree of correlation of the time difference mutation and the return value state change decreases as the sampling period increases;
(6) A floating point number greater than 0 and in the form of xx.xx is randomly generated for each router number to serve as the characteristic number of different routers.
7. The method for performing WiFi-RTT ranging based data post-processing according to claim 5, wherein in the step 3, the mode discrimination system performs the following information comparison scheme:
(3.1) comparing the router numbers of the RTT ranging information at the moment and the router numbers of the previous 1 time, and if the router numbers at the moment are larger than the router numbers of the previous 1 time, considering the state change of the return value, and updating the mode change time sequence; if the numbers of the routers are the same for the two times, entering a step (3.2); if the number of the routers at the moment is smaller than that of the routers in the previous 1 time, entering a step (3.3);
(3.2) calculating a floating point number which randomly generates a form of xx.xx for each router number as the sum of feature numbers of different routers, and if the feature numbers are equal in two times, considering that the state of a return value is unchanged, and ending the operation; if the feature numbers are different in the front and back times, the state of the return value is considered to be changed, and the mode change time sequence is updated;
(3.3) calculating the sum of the feature numbers, if the difference between the sum of the feature numbers at the previous time and the sum of the feature numbers at the next time is equal to the sum of a certain feature number or a certain number of feature numbers at the previous time, considering that the router number set at the previous time completely comprises the router number set at the moment, namely no new router number appears, and taking the negative value of the time stamp as update data to update the mode change time sequence; otherwise, the return value state is considered to be changed, and the mode change time sequence is updated.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013188113A1 (en) * | 2012-06-14 | 2013-12-19 | Qualcomm Incorporated | Round trip time (rtt) based ranging system and method |
| CN112929822A (en) * | 2021-02-08 | 2021-06-08 | 中国科学院空天信息创新研究院 | Return value state monitoring system based on WiFi-RTT ranging |
| CN112954589A (en) * | 2021-02-08 | 2021-06-11 | 中国科学院空天信息创新研究院 | Monitoring and positioning system based on WIFI-RTT (wireless fidelity-round-trip time) ranging |
-
2021
- 2021-08-16 CN CN202110939433.3A patent/CN113660607B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013188113A1 (en) * | 2012-06-14 | 2013-12-19 | Qualcomm Incorporated | Round trip time (rtt) based ranging system and method |
| CN112929822A (en) * | 2021-02-08 | 2021-06-08 | 中国科学院空天信息创新研究院 | Return value state monitoring system based on WiFi-RTT ranging |
| CN112954589A (en) * | 2021-02-08 | 2021-06-11 | 中国科学院空天信息创新研究院 | Monitoring and positioning system based on WIFI-RTT (wireless fidelity-round-trip time) ranging |
Non-Patent Citations (2)
| Title |
|---|
| 基于Wi-Fi信道状态信息的室内定位技术现状综述;陈锐志;叶锋;;武汉大学学报(信息科学版)(12);全文 * |
| 基于惯导/数据链的动态相对定位方法;郝菁;蔚保国;何成龙;;计算机测量与控制(10);全文 * |
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