CN111505671A - Comprehensive judgment method for positioning reliability - Google Patents
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- CN111505671A CN111505671A CN202010286557.1A CN202010286557A CN111505671A CN 111505671 A CN111505671 A CN 111505671A CN 202010286557 A CN202010286557 A CN 202010286557A CN 111505671 A CN111505671 A CN 111505671A
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Abstract
The invention relates to the technical field of GNSS positioning navigation, in particular to a comprehensive judgment method and a comprehensive judgment system for positioning reliability, wherein correlation coefficients of various influencing factors are obtained according to the correlation between the plurality of influencing factors of the positioning reliability and a positioning result; dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result; calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; establishing a positioning reliability model according to the positioning accuracy of a plurality of levels; and obtaining the positioning precision of the user according to the positioning reliability model. All factors influencing positioning reliability are integrated, then a positioning reliability model is established, and positioning accuracy of the user is deduced according to all influence factor values of the user, so that the positioning accuracy of the user can be known more accurately and comprehensively, and the positioning accuracy of the user can be evaluated better.
Description
Technical Field
The invention relates to the technical field of GNSS positioning navigation, in particular to a comprehensive judgment method and a comprehensive judgment system for positioning reliability and a readable medium.
Background
Usually, after the end user obtains the positioning result, the positioning error index is used to measure the quality of the positioning result. The single positioning error index only measures the accuracy of the final result from the aspect of error and cannot reflect the reliability of the positioning result.
The document "reliability research of GPS positioning solution" gives a research on positioning reliability, but it mainly analyzes from the aspects of hardware and satellite configuration, which is far from enough to evaluate the positioning reliability.
Disclosure of Invention
In order to at least solve the technical problem and embody the comprehensive judgment method and the comprehensive judgment system of the positioning reliability more credibility in general, the invention provides the comprehensive judgment method and the comprehensive judgment system of the positioning reliability and a readable medium. The main technical scheme is as follows:
a comprehensive evaluation method for positioning credibility comprises the following steps: obtaining a correlation coefficient of each influence factor according to the correlation between the plurality of influence factors of the positioning reliability and the positioning result; dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result; calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; establishing a positioning reliability model according to the positioning accuracy of a plurality of levels; and obtaining the positioning precision of the user according to the positioning reliability model.
Preferably, the influencing factors comprise satellite numbers, Snr minimum values, Snr average values, continuous epochs, Ratio, constellation DOP values, errors in single-point pseudo range residuals, errors in rtk double-difference residuals, single-point variances and final solution variances.
Preferably, according to the influence of the influence factors on the positioning result, dividing the numerical value of each influence factor into intervals of different grades, wherein the grades are from a first grade, a second grade, a third grade to an nth grade, and the influence of the influence factors on the positioning precision is larger when the grades are larger; the interval values of the satellite number, the Snr minimum value, the Snr average value, the continuous epoch and the Ratio are increased along with the increase of the grade; the interval values of the constellation DOP value, the error in the single-point pseudo range residual, the error in the rtk double-difference residual, the single-point variance and the final solution variance are decreased gradually along with the increase of the grade.
Preferably, the positioning accuracy of multiple levels obtained by calculation by combining the correlation coefficient of each influence factor and the corresponding interval is specifically as follows: assigning different values corresponding to different intervals of the influence factors according to the influence of the influence factors on the positioning result; calculating the scores of a plurality of grades according to the correlation coefficient and the score corresponding to each interval; calculating a plurality of positioning accuracies in the interval where the score of each grade is located; with the confidence level of 95%, the positioning accuracy of each level is calculated.
Preferably, the obtaining of the positioning accuracy of the user according to the positioning reliability model specifically includes: calculating according to the numerical value of the user influence factors to obtain the grade of the user; and obtaining the positioning precision of the user by combining the grade of the user and the positioning credibility model.
Preferably, the calculation of the scores of the multiple grades from the correlation coefficients and the scores of the corresponding intervals specifically includes: accumulating the scores of each influence factor at different grades; the score is divided into a plurality of intervals of different grades.
Preferably, a plurality of positioning accuracies in the interval in which the score of each level is calculated, at this time, the positioning result to be measured is a known determination value, and the positioning accuracy is obtained by combining the positioning result obtained by the calculation with the known positioning result.
Preferably, the obtaining of the positioning accuracy of the user according to the positioning reliability model specifically includes: and resolving the value of the influence factor of the user to obtain a grade value of the user, and correspondingly obtaining the positioning precision of the user by using the credibility model.
A comprehensive evaluation system for positioning credibility comprises: the correlation coefficient acquisition module is used for obtaining the correlation coefficient of each influence factor according to the correlation between the positioning reliability influence factors and the positioning result; the dividing module is used for dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result; the resolving module is used for resolving to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; the model establishing module is used for establishing a positioning reliability model according to the positioning accuracy of a plurality of levels; and the positioning precision obtaining module is used for obtaining the positioning precision of the user according to the positioning credibility model.
Readable medium having a program executable by a processor, the program, when executed, implementing the steps of the method.
Compared with the prior art, the invention discloses a comprehensive judgment method for positioning reliability, which comprises the following steps: obtaining a correlation coefficient of each influence factor according to the correlation between the plurality of influence factors of the positioning reliability and the positioning result; dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result; calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; establishing a positioning reliability model according to the positioning accuracy of a plurality of levels; and obtaining the positioning precision of the user according to the positioning reliability model. The method integrates all factors influencing positioning reliability, then establishes a positioning reliability model, deduces the positioning precision of the user according to all the influencing factor values of the user, more accurately and comprehensively learns the positioning precision of the user, and can better evaluate the positioning accuracy of the user.
Drawings
For a better understanding of the technical solution of the present invention, reference is made to the following drawings, which are included to assist in describing the prior art or embodiments. These drawings will selectively demonstrate articles of manufacture or methods related to either the prior art or some embodiments of the invention. The basic information for these figures is as follows:
FIG. 1 is a diagram illustrating a method for comprehensive evaluation of position confidence, according to an embodiment;
FIG. 2 is a block diagram of an integrated judgment system for location confidence in an embodiment;
Detailed Description
The technical means or technical effects related to the present invention will be further described below, and it is obvious that the examples provided are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step, will be within the scope of the present invention based on the embodiments of the present invention and the explicit or implicit representations or hints.
As shown in fig. 1, the invention discloses a comprehensive evaluation method for positioning reliability, which comprises the following steps: s1, obtaining the correlation coefficient of each influence factor according to the correlation between the plurality of influence factors of the positioning reliability and the positioning result; s2, dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result; s3, calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; s4, establishing a positioning reliability model according to the positioning accuracy of a plurality of levels; and S5, acquiring the positioning accuracy of the user according to the positioning reliability model. The method integrates all factors influencing positioning reliability, then establishes a positioning reliability model, deduces the positioning precision of the user according to all the influencing factor values of the user, more accurately and comprehensively learns the positioning precision of the user, and can better evaluate the positioning accuracy of the user.
The influencing factors comprise satellite numbers, Snr minimum values, Snr average values, continuous epochs, Ratio, constellation DOP values, errors in single-point pseudo range residuals, errors in rtk double-difference residuals, single-point variances and final solution variances.
S1, obtaining the correlation coefficient of each influence factor according to the correlation between the plurality of influence factors of the positioning reliability and the positioning result;
the correlation between the plurality of factors affecting the positioning reliability and the positioning result refers to the influence of each factor on the positioning result, for example, (1) the number of visible satellites in single-point positioning is at least 4 satellites that meet the requirement, and for differential positioning is at least 5 satellites. When the observation condition is fixed, the positioning can reach the best when the number of the visible satellites is in a certain range, that is to say, under a certain condition, the influence of the number of the visible satellites in a certain range on the positioning result is the most obvious. (2) The greater the DOP value of the constellation DOP value in a certain range, the more obvious the influence on the positioning precision is, and the worse the precision is. Generally in a position fix, a PDOP of less than 6 is satisfactory for a conventional position fix, and a PDOP of greater than 10 is not available. Under certain conditions, the smaller the DOP value, the more positive the influence on the reliability of positioning. (3) After the positions of the satellites are obtained, the position estimation of the observation station is carried out, namely, the single-point positioning process is carried out, each iteration is carried out, a group of pseudo-range residuals are obtained, each satellite has a residual value, and the value has the error characteristic and is possible to be positive and negative. The residual error of each satellite converges differently in the same iteration. As a result of the final iteration, this residual value is possible in both plus and minus tens, and even larger if the track is abnormal. But the residuals of the satellites involved in the solution do not deviate much, so the pseudorange residuals are used to roughly evaluate the gross error condition of a set of data. (4) The altitude, the altitude of the satellite, is generally not less than 10 degrees. The multipath can be effectively weakened by selecting a certain altitude angle, meanwhile, the altitude angle has a certain relation with the signal to noise ratio and the GDOP, certainly, the altitude angle is different in selection, the number of screened satellites is different, and under the condition that the number of visible satellites is large, the threshold value of the altitude angle can be increased, so that the influence of the multipath can be weakened. (5) When the signal-to-noise ratio is lower than a certain value, the observed data signal is weaker, and the quality of the observed data at the moment becomes lower. Signal-to-noise ratios within a certain range can make the data quality relatively good, worse outside the range, or even unusable. The signal-to-noise ratio is related to the elevation angle, and when the elevation angle is lower, the signal is lost more in the propagation path, and the signal-to-noise ratio is relatively smaller. Different receiving ends receive different signal-to-noise ratios in different environments, for example, the signal-to-noise ratio of a signal at the mobile phone end and a signal at the receiver end may be different. (6) And the square sum of the pseudo-range residuals is the rough difference further judged on the basis of the pseudo-range residuals, and if the square sum of the residuals is too large, the effectiveness of the positioning result in the single-point positioning is reduced. (7) The method is characterized in that the square sum of double-difference residuals is carried out, in the process of carrying out single inter-satellite difference, the clock difference of a receiver is eliminated, then the station difference is carried out, errors related to satellites are eliminated, error items such as ionospheric delay, tropospheric delay and multipath effect are only shown as the influence of each error item residual on observed quantity after model correction is carried out, the residual items are reduced in the process of double difference, particularly in the process of short base line measurement, because the distance between a reference station and a mobile station is not far, the correlation is large, and the error items related to propagation paths can be ignored. In addition, if the double-difference residual error is obviously skipped, the cycle slip of a non-reference satellite can exist. The double-difference residual after the test can be judged. When the post-test double-difference residual is large, there are two possibilities: firstly, the calculated position has deviation; secondly, the observed value has larger gross error, and in short, the positioning reliability is reduced. The continuity of the satellite observation has a certain influence on the positioning within a certain time, for example, when filtering is performed, a state vector of a previous epoch needs to be used, and if the satellite data continuity is poor, the reliability of the state vector will be reduced. When the continuity is poor, the satellite may lose lock, and the reliability of the carrier observation cannot be guaranteed, so that the continuity of the satellite needs to be tracked. (8) The ambiguity difference, for rtk positioned before and after the ambiguity search, the difference between the floating solution and the fixed solution fluctuates within a certain range. When the general ambiguity exceeds the limit, the fixing is not considered to be correct. If a fixed solution is obtained, the ratio exceeding the limit can be considered as one of the reliability evaluation indexes. The double-differenced ambiguity difference from the previous fixed epoch is invariant to cycle slip or reference star changes. Some ambiguity is found to change. And evaluating the reliability of the positioning result by comprehensively considering the number of the changes and the unchanged number, the size of the changes and the solved weight thereof. (9) The Ratio value, which is defined as the Ratio of the residual quadratic form of the suboptimal integer solution to the optimal integer solution, characterizes how close the floating solution is to the integer solution, and an empirical threshold c (e.g. 3) is typically set for the test, and when the Ratio value exceeds this threshold, the optimal ambiguity is considered to be the correctly fixed ambiguity, otherwise the fixation fails. Although the ratio-test based on the fixed threshold is most widely applied, the problem that the threshold is difficult to set still exists, especially under the dynamic observation condition, the observation environment is complex, the satellite geometric configuration is poor, the quality of the observation data is poor, the problems of 'abandon' or 'nano-fake' and the like usually occur when the threshold is set unreasonably, and the dynamic threshold is usually set for judgment. The dynamic threshold is mainly used for adjusting the threshold of the ratio and setting the threshold according to different ratio characteristics. If a fixed solution is obtained, the ratio value can be used as an index for evaluating the fixed solution. The index was evaluated in such a manner that the ratio value was highly reliable within a certain range, but was less reliable than a certain range, and was considered to be low in reliability even though a fixed solution was obtained. (10) The variance is located, and the variance of a parameter is an important precision index of the parameter. In RTD, RTK, a set of coefficient matrices and covariance matrices are required before filtering, where the diagonal elements of the covariance matrices are the variances corresponding to the double-difference parameters (double-difference observations), and the variances are related to factors such as the satellite system, the baseline length, the elevation angle, and the signal-to-noise ratio. And obtaining a covariance matrix before forming a double difference equation, wherein diagonal elements of the matrix are positioning result variances.
S2, dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result;
based on the influence of each influence factor on the positioning result, dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factor on the positioning result, wherein the grades are from a first grade, a second grade, a third grade to an nth grade, and the influence of the influence factor on the positioning precision is larger when the grade is larger; the interval values of the satellite number, the Snr minimum value, the Snr average value, the continuous epoch and the Ratio are increased along with the increase of the grade; the interval values of the constellation DOP value, the error in the single-point pseudo range residual, the error in the rtk double-difference residual, the single-point variance and the final solution variance are decreased gradually along with the increase of the grade. In this embodiment, the numerical value of each influence factor is divided into 5-level intervals. In other embodiments, the division into other levels is also possible, and is not limited herein.
S3, calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor;
the positioning accuracy of multiple levels obtained by resolving by combining the correlation coefficient and the corresponding interval of each influence factor is specifically as follows: assigning different values corresponding to different intervals of the influence factors according to the influence of the influence factors on the positioning result; calculating the scores of a plurality of grades according to the correlation coefficient and the score corresponding to each interval; calculating a plurality of positioning accuracies in the interval where the score of each grade is located; with the confidence level of 95%, the positioning accuracy of each level is calculated. The calculation of the correlation coefficient and the score of each corresponding interval to obtain the scores of multiple grades specifically comprises the following steps: accumulating the scores of each influence factor at different grades; the score is divided into a plurality of intervals of different grades. And calculating a plurality of positioning accuracies in the interval where the score of each grade is located, wherein the positioning result to be measured is a known determined value at the moment, and the positioning accuracy is obtained by combining the positioning result obtained by calculation with the known positioning result.
In one embodiment, the influence of the above influencing factors is divided into five levels. As follows. In table 1, each influence factor is divided into 5 levels, and each level gives a corresponding index.
TABLE 1 factor rankings
TABLE 2 correlation coefficient of each factor with localization result and rating of each grade
The score weight of a certain factor in the positioning reliability can be analyzed by combining the data in the table 1, for example, if the satellite number is in the range of [4,12], the score belongs to L eve.1, namely 2 × 0.55 × 1.1, the score of other factors is also calculated, and the final score sum is the reliability score of the positioning result.
The scoring condition of the credibility can be divided into five grades according to the sequence from low grade to high grade;
TABLE 3 confidence score cases
If there are a plurality of sample sets of positioning results of epochs, subsamples between each credibility scoring area can be obtained, then 95% of statistical solution is carried out on the samples, and the obtained precision value between each scoring area is obtained, after a large number of samples are tested, the precision of the corresponding credibility between each scoring area can be obtained, for example, L eve.5 scoring is 13 scoring, the precision value is 0.1m under the condition that the credibility is 95%, therefore, a connection is established among the three, namely, the total scoring is known, the precision can be known by knowing the credibility, and finally, the precision is m from the perspective of a user, namely, under the condition that the credibility is 95% under the condition that the total scoring is n scoring.
S4, establishing a positioning reliability model according to the positioning accuracy of a plurality of levels;
the credibility score is divided into 5 grades, the interval of each grade corresponds to a positioning accuracy, the score in each interval corresponds to each influence factor value such as the corresponding satellite number, and therefore a positioning credibility model can be established by using the scores of the intervals and the corresponding positioning accuracy.
And S5, acquiring the positioning accuracy of the user according to the positioning reliability model.
Obtaining the positioning accuracy of the user according to the positioning reliability model, specifically: calculating according to the numerical value of the user influence factors to obtain the grade of the user; and obtaining the positioning precision of the user by combining the grade of the user and the positioning credibility model.
The specific method for obtaining the positioning accuracy of the user according to the positioning reliability model is as follows: and resolving the value of the influence factor of the user to obtain a grade value of the user, and correspondingly obtaining the positioning precision of the user by using the credibility model.
When the positioning accuracy of the user needs to be obtained, the credibility score of the user at the position is obtained by utilizing the number of satellites of the user and other influence factors, and the positioning accuracy of the user is obtained by utilizing the credibility model.
As shown in fig. 2, the present invention discloses a comprehensive evaluation system for positioning reliability, which comprises: s10, a correlation coefficient obtaining module for obtaining the correlation coefficient of each influence factor according to the correlation between the positioning reliability influence factors and the positioning result; s20, a dividing module, which is used for dividing the value of each influence factor into intervals of different grades according to the influence of the influence factor on the positioning result; s30, a resolving module is used for resolving to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor; s40, a model establishing module is used for establishing a positioning reliability model according to the positioning accuracy of a plurality of grades; and S50, a positioning precision obtaining module for obtaining the positioning precision of the user according to the positioning credibility model.
Readable medium having a program executable by a processor, the program, when executed, implementing the steps of the method.
It will be appreciated by those skilled in the art that, in the case of common sense, descriptions of some of the steps described above may be stored in a readable medium in the form of a computer program.
The various embodiments or features mentioned herein may be combined with each other as additional alternative embodiments without conflict, within the knowledge and ability level of those skilled in the art, and a limited number of alternative embodiments formed by a limited number of combinations of features not listed above are still within the scope of the present disclosure, as understood or inferred by those skilled in the art from the figures and above.
Finally, it is emphasized that the above-mentioned embodiments, which are typical and preferred embodiments of the present invention, are only used for explaining and explaining the technical solutions of the present invention in detail for the convenience of the reader, and are not used to limit the protection scope or application of the present invention.
Therefore, any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be covered within the protection scope of the present invention.
Claims (10)
1. A comprehensive evaluation method for positioning reliability is characterized by comprising the following steps:
obtaining a correlation coefficient of each influence factor according to the correlation between the plurality of influence factors of the positioning reliability and the positioning result;
dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result;
calculating to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor;
establishing a positioning reliability model according to the positioning accuracy of a plurality of levels;
and obtaining the positioning precision of the user according to the positioning reliability model.
2. The method of claim 1, wherein:
the influencing factors comprise satellite numbers, Snr minimum values, Snr average values, continuous epochs, Ratio, constellation DOP values, errors in single-point pseudo range residuals, errors in rtk double-difference residuals, single-point variances and final solution variances.
3. The method of claim 2, wherein:
dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result, wherein the grades are from a first grade, a second grade, a third grade to an nth grade, and the influence of the influence factors on the positioning precision is larger when the grades are larger;
the interval values of the satellite number, the Snr minimum value, the Snr average value, the continuous epoch and the Ratio are increased along with the increase of the grade;
the interval values of the constellation DOP value, the error in the single-point pseudo range residual, the error in the rtk double-difference residual, the single-point variance and the final solution variance are decreased gradually along with the increase of the grade.
4. The method of claim 3, wherein: the positioning accuracy of multiple levels obtained by resolving by combining the correlation coefficient and the corresponding interval of each influence factor is specifically as follows:
assigning different values corresponding to different intervals of the influence factors according to the influence of the influence factors on the positioning result;
calculating the scores of a plurality of grades according to the correlation coefficient and the score corresponding to each interval;
calculating a plurality of positioning accuracies in the interval where the score of each grade is located;
with the confidence level of 95%, the positioning accuracy of each level is calculated.
5. The method of claim 4, wherein:
obtaining the positioning accuracy of the user according to the positioning reliability model, specifically:
calculating according to the numerical value of the user influence factors to obtain the grade of the user;
and obtaining the positioning precision of the user by combining the grade of the user and the positioning credibility model.
6. The method of claim 4, wherein:
the calculation of the correlation coefficient and the score of each corresponding interval to obtain the scores of multiple grades specifically comprises the following steps:
accumulating the scores of each influence factor at different grades;
the score is divided into a plurality of intervals of different grades.
7. The method of claim 6, wherein:
and calculating a plurality of positioning accuracies in the interval where the score of each grade is located, wherein the positioning result to be measured is a known determined value at the moment, and the positioning accuracy is obtained by combining the positioning result obtained by calculation with the known positioning result.
8. The method of claim 4, wherein:
the specific method for obtaining the positioning accuracy of the user according to the positioning reliability model is as follows: and resolving the value of the influence factor of the user to obtain a grade value of the user, and correspondingly obtaining the positioning precision of the user by using the credibility model.
9. A comprehensive evaluation system for positioning reliability, comprising:
the correlation coefficient acquisition module is used for obtaining the correlation coefficient of each influence factor according to the correlation between the positioning reliability influence factors and the positioning result;
the dividing module is used for dividing the numerical value of each influence factor into intervals of different grades according to the influence of the influence factors on the positioning result;
the resolving module is used for resolving to obtain positioning accuracy of multiple levels by combining the correlation coefficient and the corresponding interval of each influence factor;
the model establishing module is used for establishing a positioning reliability model according to the positioning accuracy of a plurality of levels;
and the positioning precision obtaining module is used for obtaining the positioning precision of the user according to the positioning credibility model.
10. A readable medium having a program executable by a processor, characterized in that:
the program when executed implements the steps of the method of any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113050135A (en) * | 2021-03-26 | 2021-06-29 | 同济大学 | Low-cost GNSS terminal data exception handling method |
| CN114325777A (en) * | 2021-11-11 | 2022-04-12 | 中航机载系统共性技术有限公司 | Cycle slip detection and restoration method, device and equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009229295A (en) * | 2008-03-24 | 2009-10-08 | Fujitsu Ltd | Positional information processor, positional information processing program, and moving object terminal |
| JP2013181802A (en) * | 2012-03-01 | 2013-09-12 | Furuno Electric Co Ltd | Positioning device, signal processing device, gnss receiver, information terminal device for gnss receiver, positioning method and program therefor |
| CN104502889A (en) * | 2014-12-29 | 2015-04-08 | 哈尔滨工业大学 | Reference point maximum range based positioning reliability calculation method in fingerprint positioning |
| CN106123771A (en) * | 2016-05-27 | 2016-11-16 | 南京理工大学 | The Interval Fuzzy evaluation method of wheelset profile measurement results reliability based on laser displacement sensor |
| CN107807371A (en) * | 2017-09-14 | 2018-03-16 | 北京航空航天大学 | Data dependence processing method based on big-dipper satellite observation data |
-
2020
- 2020-04-13 CN CN202010286557.1A patent/CN111505671A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009229295A (en) * | 2008-03-24 | 2009-10-08 | Fujitsu Ltd | Positional information processor, positional information processing program, and moving object terminal |
| JP2013181802A (en) * | 2012-03-01 | 2013-09-12 | Furuno Electric Co Ltd | Positioning device, signal processing device, gnss receiver, information terminal device for gnss receiver, positioning method and program therefor |
| CN104502889A (en) * | 2014-12-29 | 2015-04-08 | 哈尔滨工业大学 | Reference point maximum range based positioning reliability calculation method in fingerprint positioning |
| CN106123771A (en) * | 2016-05-27 | 2016-11-16 | 南京理工大学 | The Interval Fuzzy evaluation method of wheelset profile measurement results reliability based on laser displacement sensor |
| CN107807371A (en) * | 2017-09-14 | 2018-03-16 | 北京航空航天大学 | Data dependence processing method based on big-dipper satellite observation data |
Non-Patent Citations (2)
| Title |
|---|
| 常青 等: "《GPS定位解的可信度研究》", 《航空学报》 * |
| 虞顺 等: "《Galileo导航系统观测值的质量分析》", 《测绘地理信息》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113050135A (en) * | 2021-03-26 | 2021-06-29 | 同济大学 | Low-cost GNSS terminal data exception handling method |
| CN114325777A (en) * | 2021-11-11 | 2022-04-12 | 中航机载系统共性技术有限公司 | Cycle slip detection and restoration method, device and equipment |
| CN114325777B (en) * | 2021-11-11 | 2023-10-13 | 中航机载系统共性技术有限公司 | Cycle slip detection and repair method, device and equipment |
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