CN111123303A - Method and device for acquiring positioning error data and processing method - Google Patents
Method and device for acquiring positioning error data and processing method Download PDFInfo
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- CN111123303A CN111123303A CN201910817467.8A CN201910817467A CN111123303A CN 111123303 A CN111123303 A CN 111123303A CN 201910817467 A CN201910817467 A CN 201910817467A CN 111123303 A CN111123303 A CN 111123303A
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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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/23—Testing, monitoring, correcting or calibrating of receiver elements
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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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
- G01S19/27—Acquisition or tracking or demodulation of signals transmitted by the system creating, predicting or correcting ephemeris or almanac data within the receiver
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Abstract
The disclosure relates to the technical field of satellite positioning, and discloses a method for acquiring positioning error data, which comprises the following steps: acquiring first positioning data of the measured locator in a plurality of epochs, acquiring second positioning data of the standard locator in the same plurality of epochs, responding to an instruction for determining a positioning state, and carrying out corresponding processing on a second coordinate value to obtain a standard coordinate value; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; and associating the positioning error value of each epoch with the influence factor data and then storing to obtain a positioning error data set. Some technical effects of this disclosure are: according to the acquisition method, the automation degree of data acquisition and processing is higher, the requirement on the field is relatively lower, and meanwhile, the acquired positioning data can reflect the change of the numerical values of the influence factors of the measured positioner in different states, so that the method can provide help for more fully and dimensionally analyzing the positioning errors.
Description
Technical Field
The present disclosure relates to the field of satellite positioning technologies, and in particular, to a method, an apparatus, and a processing method for acquiring positioning error data.
Background
More and more user terminals (such as mobile phones, portable computers, vehicle navigation devices, etc.) have a satellite positioning function, but in the satellite positioning (hereinafter referred to as "positioning"), due to the influence of external factors, a high-precision positioning result cannot be obtained all the time, and the positioning accuracy of the mobile terminal is affected under the conditions that the relative position of a satellite and the mobile terminal is changed, the satellite signal propagation process is blocked by trees or tall buildings, etc.
In the prior art, the positioning error data is generally acquired by placing a measured positioner on a marker at a known real position (such as the position of a base station or the position of an observation pier), manually recording coordinates obtained by positioning the measured positioner, and comparing the coordinates with the real coordinates to obtain the positioning error data. The defects of the measurement technology are mainly as follows: the obtained data cannot sufficiently reflect the positioning performance of the positioner due to the fact that the data depend on the field and manual operation.
Disclosure of Invention
To solve at least one of the foregoing technical problems, the present disclosure in one aspect provides a method for acquiring positioning error data, including: acquiring first positioning data of a measured locator in a plurality of epochs, wherein the first positioning data comprises influence factor data and a first coordinate value; acquiring second positioning data of the standard locator in the same plurality of epochs, wherein the second positioning data comprises second coordinate values; responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; the positioning state comprises dynamic positioning or static positioning; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; and associating the positioning error value of each epoch with the influence factor data and then storing to obtain a positioning error data set.
Preferably, the instructions are for determining the positioning status as a static positioning; "performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes: and dividing the plurality of epochs into one or more time periods, and selecting a second coordinate value with a fixed solution from the time periods as a standard coordinate value of the time period.
Preferably, the positioning state comprises dynamic positioning or static positioning; the instructions are for determining a location state as a dynamic location; "performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes: and enabling the standard coordinate value to be equal to the second coordinate value of each epoch.
Preferably, the first positioning data and the second positioning data are acquired and processed in a plurality of scenes with different occlusion rates.
Preferably, the impact factor data includes a name and a value of the impact factor; the impact factors include any at least three of a horizontal accuracy factor, an average signal-to-noise ratio, a minimum signal-to-noise ratio, a number of premium satellites, and a number of available satellites.
Preferably, processing the original observation data, and counting according to a preset filtering condition to obtain the number of high-quality satellites suitable for positioning calculation at that time; the filtering condition comprises that the satellite signal frequency, the numerical value of the satellite altitude angle or the pseudo range value is in a preset range.
In yet another aspect, the present disclosure further provides a method of processing positioning error data, comprising the steps of: obtaining the positioning error data set according to the obtaining method; responding to the counting instruction, counting the number of the positioning error data of each influence factor falling into a specific first set interval to obtain the total number of the partitions, and counting the number of the positioning error data falling into a specific first set interval set and a second set interval at the same time to obtain the number of the matched partitions; the first setting interval is a numerical interval set for an influence factor, and the second setting interval is a numerical interval set for the positioning error value; calculating a coincidence proportion according to the total number of the partitions and the coincidence number of the partitions; and associating the first set of setting intervals and the second set of setting intervals with the coincidence proportion higher than the setting threshold value, generating and storing first associated data, wherein the associated data is used for estimating the positioning error.
Preferably, according to the first correlation data, the positioning error estimation value is correlated with the first set of setting intervals, and second correlation data is generated and stored.
Preferably, the server receives the request information of the user terminal and then analyzes the request information; and determining a corresponding positioning error estimation value according to a first set of setting intervals in which the numerical values of the influence factors in the request information fall, and combining the second associated data, and sending the corresponding positioning error estimation value to the user terminal.
In yet another aspect, the present disclosure provides an apparatus for acquiring positioning error data, including: the data acquisition module is used for acquiring first positioning data of the measured positioner in a plurality of epochs, and the first positioning data comprises influence factor data and a first coordinate value; the data acquisition module is also used for acquiring second positioning data of the standard positioner in a plurality of same epochs, and the second positioning data comprises second coordinate values; a processing module for performing the steps of: responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; correlating the positioning error value of each epoch with the influence factor data to obtain a positioning error data set; a storage module for storing the set of positioning error data.
Some technical effects of this disclosure are: according to the acquisition method, the automation degree of data acquisition and processing is higher, the requirement on the field is relatively lower, and meanwhile, the acquired positioning data can reflect the change of the numerical values of the influence factors of the measured positioner in different states, so that the method can provide help for more fully and dimensionally analyzing the positioning errors.
Drawings
For a better understanding of the technical aspects of the present disclosure, reference may be made to the following drawings, which are included to provide an additional description of the prior art or embodiments. These drawings selectively illustrate articles or methods related to the prior art or some embodiments of the present disclosure. The basic information for these figures is as follows:
FIG. 1 is a diagram illustrating a relationship between a value of an impact factor and a first setting range according to an embodiment;
FIG. 2 is a diagram illustrating a relationship between a second predetermined interval and positioning error data according to an embodiment;
FIG. 3 is a diagram illustrating relationships among some constituent elements of first associated data, according to an embodiment;
FIG. 4 is a diagram illustrating relationships between partial constituent elements of second associated data according to an embodiment.
Detailed Description
The technical means or technical effects referred to by the present disclosure will be further described below, and it is apparent that the examples (or embodiments) provided are only some embodiments intended to be covered by the present disclosure, and not all embodiments. All other embodiments, which can be made by those skilled in the art without any inventive step, will be within the scope of the present disclosure, either explicitly or implicitly based on the embodiments and the text of the present disclosure.
The present disclosure provides, in one aspect, a method for acquiring positioning error data, including: acquiring first positioning data of a measured locator in a plurality of epochs, wherein the first positioning data comprises influence factor data and a first coordinate value; acquiring second positioning data of the standard locator in the same plurality of epochs, wherein the second positioning data comprises second coordinate values; responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; the positioning state comprises dynamic positioning or static positioning; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; and associating the positioning error value of each epoch with the influence factor data and then storing to obtain a positioning error data set.
A position measuring instrument is disclosed. The measured positioner refers to a positioner that needs to be known about performance related to positioning errors, and may be a positioning device used in daily life, or a positioning device used in, for example, industry or other fields. The measured position device includes at least an antenna for receiving satellite signals, but may also include processing circuitry for satellite signals, and may even include circuitry for performing position calculations. Generally, the measured positioners include a mobile phone, a smart band, an entrance card, a navigator, a portable computer, a robot or an auxiliary positioner with satellite positioning function, and generally, these products or devices have an antenna for receiving satellite signals and a positioning chip for processing satellite signals, and these products or devices can also store or receive an algorithm program for position calculation.
With respect to standard locators. The standard positioner should have a higher positioning accuracy than the measured positioner per se, so the former will have superior hardware performance than the latter, or the former will use better algorithms than the latter. Thus, the standard positioner may also be various common positioning devices, such as a mobile phone, an RTK (Real-time kinematic) device, a tablet computer, and the like. Similarly, a standard locator includes at least an antenna for receiving satellite signals, but may also include processing circuitry for satellite signals, and may even include circuitry for performing position calculations.
In some embodiments, the position being measured may be a product to be marketed whose positioning performance needs to be known in advance, such as a cell phone, a navigator, which have a sub-meter level positioning accuracy, and in this case the standard positioner may select an RTK device having a centimeter level positioning accuracy. Alternatively, the standard locator may be a device for performing auxiliary positioning, such as the portable navigation positioning terminal mentioned in the document with the bulletin number CN206235741U entitled "a portable navigation positioning terminal and smart phone for enhancing positioning accuracy of mobile phone"; for example, the positioning terminal is disclosed in the document with publication number CN108204786A, entitled "a beidou measuring system based on mobile phone module". There are still many devices with similar functions, which are not listed here too much.
When the positioning accuracy of the measured locator is in a meter level, the positioning accuracy of the standard locator can be in a sub-meter level or a centimeter level; when the positioning accuracy of the measured locator is in the centimeter level, the positioning accuracy of the standard locator can be in the millimeter level.
Regarding the first positioning data and the second positioning data, the difference in names between the first positioning data and the second positioning data is mainly used to distinguish the acquisition carriers of the positioning data. The first positioning data is multiple, and under normal conditions, each epoch has a corresponding first positioning data, and similarly, the second positioning data is the same. The first positioning data may include a part of the content of the original observation data, or may include the entire content of the original observation data. The first positioning data may also include data processed from the original observation data, such as an average signal-to-noise ratio, a minimum signal-to-noise ratio, and the like. The first positioning data comprises a first coordinate value, namely the position coordinate of the measured locator under a certain epoch; similarly, the second coordinate value is the position coordinate of the standard locator corresponding to the epoch. The satellite positioning involves the constant change of the satellite self state, the positioner self state and the signal propagation medium self state, so the data of a plurality of epochs can more fully reflect the performance problem of the measured positioner in normal use.
Regarding the influencing factor. The influence factors can be understood as variables that influence the positioning accuracy, the values of which variables can generally be obtained directly from the raw observation data. And impact factor data may be understood as data related to an impact factor, such as the name, value, etc. of the impact factor. With respect to the raw observation data of the satellite, which may have different specifications for different satellite navigation positioning system data, for different countries or different organizations, in one embodiment, the raw observation data includes six types of data of NMEA-0183(NMEA is an abbreviation of National Marine Electronics Association, which can be understood as american National Marine Electronics Association) standard: and the time, the position, the precision factor, the number of satellites, the elevation angle, the azimuth angle, the signal-to-noise ratio and other parameters of satellite positioning in unit of epoch can be read from the data. The precision factors include one or more of PDOP (Position precision of precision), TDOP (time precision of clock), HDOP (horizontal precision of horizontal component, or horizontal precision of vertical component), VDOP (vertical precision of vertical component), which belong to the common general knowledge field and are not expanded herein. Therefore, the positioning data under different epochs can reflect the change of the numerical value of the influence factor of the measured positioner under different states, and help can be provided for analyzing the positioning error more fully and dimensionally. Such acquisition and data processing can help to more fully obtain information about the positioning error.
Regarding the positioning status. The positioning state includes dynamic positioning or static positioning (belonging to common knowledge), in general, the former refers to collecting positioning data during movement, and the latter refers to collecting positioning data at a fixed point. The instruction for determining the positioning state may be generated by being triggered by an input device such as a touch interface, a keyboard, or a mouse, or may be generated by automatically detecting the first positioning data or the second positioning data by the system and judging according to a change condition of the first coordinate value or the second coordinate value. According to the method and the device, the second coordinate value is processed differently according to different positioning states during data processing, and a more reasonable positioning error value can be obtained. Under the condition of dynamic positioning, the second coordinate value of each epoch of the standard positioner can be directly used as the standard coordinate value; however, in the case of static positioning, if the second coordinate value has a single-point solution or a floating-point solution, these values may not be considered as standard coordinate values, and only the fixed solution may be used as standard coordinate values (only one fixed solution may be used as standard coordinate values, or a numerical value obtained by averaging the fixed solutions may be used as standard coordinate values), so that the real position of the standard positioner can be reflected relatively truly. That is, in the case of static positioning, only one second coordinate value is required, and a plurality of second coordinate values are not required. According to different positioning states, different data processing modes are adopted, and the data processing amount of the system can be reduced. The system referred to herein may be understood as a positioning error data acquisition system comprising a processor or server performing the relevant steps.
With respect to the positioning error value. The positioning error value can be understood as a difference (including an absolute value of the difference) between coordinates obtained by positioning the measured position device itself and coordinates corresponding to the real position of the measured position device. It should be noted that, when the positioning data is collected, when the distance between the standard locator and the measured locator is in the centimeter level and the positioning accuracy of the measured locator is in the meter level, the real positions of the standard locator and the measured locator can be regarded as being coincident, and this is used as the basis for calculating the positioning error value. In this case, the registration error value refers to a deviation amount of the first coordinate value from the standard coordinate value. Of course, the positioning error value can also be calculated in such a way that the distance between the standard positioner and the measured positioner is measured first, and then the positioning error value is calculated according to the distance, the first coordinate value and the standard coordinate value. When the first positioning data and the second positioning data of a plurality of epochs exist, positioning error values of the plurality of epochs can be obtained.
With respect to the set of positioning error data. The positioning error value of a plurality of epochs and corresponding influence factor data are at least included, and the correlation of the positioning error value and the change of the influence factor data can be facilitated.
In summary, the technical solutions of the present disclosure are different from the prior art in the manner of acquiring the positioning error data, including different manners of acquiring and processing the original observation data. The obtained positioning error data can reflect the positioning error of the measured positioner more fully, comprehensively and truly, and the data processing mode has higher efficiency.
In one embodiment, the instructions are for determining the location state as a static location; "performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes: and dividing the plurality of epochs into one or more time periods, and selecting a second coordinate value with a fixed solution from the time periods as a standard coordinate value of the time period.
In one embodiment, the positioning state comprises dynamic positioning or static positioning; the instructions are for determining a location state as a dynamic location; "performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes: and enabling the standard coordinate value to be equal to the second coordinate value of each epoch.
In one embodiment, the first positioning data and the second positioning data are acquired and processed in a plurality of scenes with different occlusion rates. The method comprises the steps of firstly acquiring a plurality of first positioning data and second positioning data in a scene with one occlusion rate, and then acquiring more first positioning data and second positioning data one by one in scenes with other occlusion rates. This has the advantage that positioning error data of the measured position device under different shading rate scenes can be obtained, which can help to judge the positioning performance of the measured position device more comprehensively. Scenes of different occlusion rates include, but are not limited to: under tree shadows, in automobiles, in scenes sheltered by buildings, in open air, and the like.
In one embodiment, the impact factor data includes a name and a value of the impact factor; the impact factors include any at least three of a horizontal accuracy factor, an average signal-to-noise ratio, a minimum signal-to-noise ratio, a number of premium satellites, and a number of available satellites. The average signal-to-noise ratio, the minimum signal-to-noise ratio, the number of good-quality satellites, and the number of available satellites need to be obtained by simply processing the original observation data, that is, in this embodiment, the first positioning data is not equal to the original observation data. Obtaining the first positioning data means that the original observation data is processed in advance.
With respect to average signal-to-noise ratio and minimum signal-to-noise ratio. The average signal-to-noise ratio may be understood as the result of averaging the signal-to-noise ratios of the received satellite signals for that epoch. The minimum signal-to-noise ratio is the signal-to-noise ratio corresponding to the satellite signal with the minimum signal-to-noise ratio among the satellite signals. The satellite signal referred to herein includes a signal of a visible satellite (a satellite signal that can be received by the measurement subject) or a signal of a satellite used for final positioning calculation (a satellite signal that can be received by the measurement subject and is finally selected for positioning calculation).
The number of available satellites and the number of premium satellites. The number of available satellites is the number of satellite signals that can be used for positioning calculation by the algorithm of the positioning chip in the satellite signals of the epoch. Generally, some Positioning algorithms are applicable to beidou Positioning systems, some are applicable to GPS (Global Positioning System, which may be understood as the american Global Positioning System), some are applicable to GLONASS (Global NAVIGATION SATELLITE SYSTEM, which may be understood as the russian Global satellite NAVIGATION System), some are applicable to other NAVIGATION Positioning systems or are applicable to more than two NAVIGATION Positioning systems, and not all signals of visible satellites can be used for Positioning solution.
Generally speaking, the number of satellite signals with better quality can be counted according to a custom rule (the custom rule should objectively reflect that the quality of the screened satellite signals is relatively better). For example, the satellite signal higher than a certain value is regarded as a satellite signal with better quality according to the requirements on indexes such as signal-to-noise ratio, satellite altitude, satellite signal frequency and the like. For example, satellite signals with a signal-to-noise ratio higher than a customized value such as 20 or 25 can be regarded as signals with better quality, and those skilled in the art can set the signals according to specific requirements.
In one embodiment, the original observation data is processed, and the number of high-quality satellites suitable for positioning calculation at that time is obtained through statistics according to preset filtering conditions; the filtering condition comprises that the satellite signal frequency, the numerical value of the satellite altitude angle or the pseudo range value is in a preset range.
The ways of performing statistics on the filtering conditions mainly include, but are not limited to:
(1) the frequency of the satellite signal of different satellite navigation positioning systems is generally different, and some positioning calculation algorithms are only suitable for a plurality of specific satellite navigation positioning systems but not suitable for others, such as Beidou, GPS and Glonass navigation positioning systems but not suitable for Galileo navigation positioning systems. The number of satellites contributing to the positioning solution can be obtained by using the frequency of the satellite signal as a screening basis.
(2) Whether the satellite altitude value is within a set range (such as less than 20 ° or 10 °) is judged, and generally, the greater the number of satellites within the set range, the greater the assistance to improve the positioning accuracy.
(3) And judging whether the value of the signal-to-noise ratio of the satellite is within a set range (such as more than 30).
(4) And judging whether the pseudo-range value is within a set range, and when the calculated pseudo-range value is too high or too low, indicating that the pseudo-range value is obviously not in accordance with the actual condition, and considering the epoch data as data with extremely large noise to further remove the data. For example, if the calculated pseudorange value is less than 2 kilometers or greater than 10 kilometers for the epoch data of the GPS signal, the epoch data may be considered to be particularly noisy and may be rejected.
The data such as satellite signal frequency, satellite altitude angle and the like can be directly obtained from the original observation data or obtained by adopting a known and simple calculation mode, and the actual operation is convenient. Of course, other more filtering conditions may be provided to define the "number of premium satellites".
Based on the basis set forth above, further, the present disclosure proposes a method of processing positioning error data, comprising the steps of: obtaining the positioning error data set according to the obtaining method; responding to the counting instruction, counting the number of the positioning error data of each influence factor falling into a specific first set interval to obtain the total number of the partitions, and counting the number of the positioning error data falling into a specific first set interval set and a second set interval at the same time to obtain the number of the matched partitions; the first setting interval is a numerical interval set for an influence factor, and the second setting interval is a numerical interval set for the positioning error value; calculating a coincidence proportion according to the total number of the partitions and the coincidence number of the partitions; and associating the first set of setting intervals and the second set of setting intervals with the coincidence proportion higher than the setting threshold value, generating and storing first associated data, wherein the associated data is used for estimating the positioning error.
Considering that the users need to know the situation of the positioning error of the positioning devices such as mobile phones, navigators and the like in the process of using the positioning devices, predicting or estimating the positioning error according to the situation of the influence factors is a feasible solution. That is, data of a plurality of epochs can be collected in advance, a positioning error data set is obtained by a positioning error data acquisition method, the correlation between the numerical value of the influence factor and the positioning error value in the positioning error data set is analyzed, and the correlation and the reliability obtained by analysis are applied to estimation of the positioning error of the positioning equipment such as a collection instrument, a navigator and the like.
Regarding statistical directives. The command may be obtained through input by an input device, or may be automatically generated after the system determines that the data is complete, or of course, there may be other generation manners, and the generation itself is not a key point of the present invention, and is not particularly limited herein.
Regarding the first setting section. The first setting range should be plural, and each first setting range corresponds to a certain value section of a specific certain influence factor. Fig. 1 illustrates an example in detail, in this example, the influence factors include a horizontal accuracy factor, an average signal-to-noise ratio, a minimum signal-to-noise ratio, the number of available satellites, and the number of premium satellites, wherein the first setting section corresponding to the horizontal accuracy factor includes a first setting section a1, a first setting section a2, and a first setting section A3, the first setting section corresponding to the average signal-to-noise ratio includes a first setting section B1, a first setting section B2, and a first setting section B3, and the first setting sections corresponding to the other influence factors can be understood in a similar manner. As for the design of the foregoing numerical value segments, it is necessary to consider the design according to needs and requirements in specific implementation, the numerical value segments may be designed to be wider or narrower, and the number of the numerical value segments may not be limited to the number in the figures, and may be more or less. Since the design of the value section can be very flexible and difficult to be exhaustive, the following is only one example for reference: the values of the first setting interval a1, the first setting interval a2 and the first setting interval A3 are "less than 0.7", "0.7-1.0" and "more than 1.0", respectively; the values of the first setting interval B1, the first setting interval B2 and the first setting interval B3 are "greater than 35", "28-35" and "less than 28", respectively; the values of the first setting interval C1, the first setting interval C2 and the first setting interval C3 are "greater than 30", "25-30" and "less than 25", respectively; the values of the first setting interval D1, the first setting interval D2 and the first setting interval D3 are "greater than 20", "15-20" and "less than 15", respectively; the first setting section E1, the first setting section E2, and the first setting section E3 take values "greater than 18", "12-18", and "less than 12", respectively. Those skilled in the art can easily conceive of various modifications, such as reduction of the range in each numerical range, enlargement of the range in some numerical ranges, and reduction of … …, by designing more numerical ranges, for example, 4 or 5 numerical ranges, for the first set section of a certain influence factor, based on the above-mentioned explicit or implicit descriptions.
Regarding the total number of partitions. "total number of partitions" can be understood as: at least one first setting section (i.e. a specific first setting section) is designated for each influence factor, for example, the specific first setting section for the horizontal precision factor is designated as a first setting section a1, the specific first setting section for the average signal-to-noise ratio is designated as a first setting section B2, the specific first setting section for the minimum signal-to-noise ratio is designated as a first setting section C1, the specific first setting section for the number of available satellites is designated as a first setting section D3, the specific first setting section for the number of premium satellites is designated as a first setting section E4, the influence factors of the first positioning data of how many epochs fall into these specific first sections, and the counted total number is the total number of partitions. The aforementioned set of first setting intervals corresponding to each of the specified impact factors may be understood as a partition, i.e., a set of first setting intervals. Since an influence factor may have a plurality of first setting intervals, a combination of the plurality of first setting intervals of different influence factors may generate a plurality of partitions (i.e., a plurality of first setting interval sets), for example, a partition may be "a combination of a1, B1, C1, D1, E1", may be "a combination of a1, B1, C1, D1, E1", may be "a combination of a1, B2, C1, D1, E1", may be "a combination of a1, B1, C2, D1, E1", may be "a combination of a2, B1, C3, D1, E3", may be "a combination of A4, B2, C3, D1, E1", may be "a combination of A3, B1, C4, D4, E1", and so on.
The number of partitions matching. For each particular partition, there will generally be a plurality of first positioning data values for which the impact factor falls within the partition, and these first positioning data values will have different first coordinate values, i.e. corresponding to different values of positioning error. At this time, if it is to count how many first positioning data fall into a certain positioning error range, it is necessary to count the number of the partition coincidence. For example, if the value of the influence factor of 1 ten thousand first positioning data falls within the range of a first setting section set "first setting section a1, first setting section B2, first setting section C1, first setting section D3, and first setting section E4", and the positioning error value corresponding to 9 thousand first positioning data falls within the range of a second setting section (the positioning error value is less than 10 meters), the coincidence ratio can be calculated to be 90%. If the set threshold of the coincidence ratio is 80%, it can be determined that such a situation is beyond the set threshold. Then, the first setting section (i.e., "first setting section a1, first setting section B2, first setting section C1, first setting section D3, and first setting section E4") and the second setting section (i.e., "the positioning error value is less than 10 meters") may be associated with each other to form correlated data, and the correlated data may be stored. The above-mentioned 9 thousand are the number of the partition matching.
Regarding the second setting section. The second setting interval refers to a numerical interval in which the positioning error value is set. Fig. 2 shows an example in which the second setting interval X1 corresponds to a plurality of epochs of data (i.e., a plurality of epochs of positioning error data), that is, positioning error values corresponding to the epoch W1 data, the epoch W2 data, and the epoch W3 data all fall within the second setting interval X1. The second setting section X2 corresponds to more epochs of data, and it can be seen that the second setting section X2 has a larger range than the first setting section X1. For example, the first setting section X1 may take "less than 1 meter", and correspondingly, the second setting section X2 may take "less than 5 meters"; the first setting interval X1 may take "less than 0.5 m", and correspondingly, the second setting interval X2 may take "less than 10 m"; the first setting interval X1 may be "less than 10 meters", and correspondingly, the second setting interval X2 may be "less than 20 meters" … …, and specific values thereof may be customized according to specific requirements. Fig. 2 is merely an example for the convenience of visual understanding, and the second setting interval may be more, and is not redundant.
"generating the first related data by associating the first set of setting sections and the second set of setting sections having the matching ratio higher than the set threshold" can be understood as follows: for a partition, the corresponding positioning error data is multiple, each positioning error data may have different positioning error values, a second setting interval is given (that is, the positioning error value is divided into a numerical value interval), if the number of the positioning error data falling into the second setting interval is more, the numerical value interval of the impact factor corresponding to the first setting interval may be considered to have higher correlation with the second setting interval, at this time, the first setting interval set may be associated with the second setting interval for estimating the positioning error, for example, when the value of the impact factor in the original observation data observed by the positioning device (such as a mobile phone) falls into the partition, the positioning error of the positioning device at this time may be estimated to fall into the second setting interval. The higher the fit ratio, the higher the confidence in the positioning error estimate. More specifically, for example, in the prior statistics, the influence factors corresponding to 1 ten thousand positioning error data fall into the following ranges, that is, the first setting interval (less than 0.8) of the horizontal accuracy factor, the first setting interval (more than 30) of the average signal-to-noise ratio, the first setting interval (more than 25) of the minimum signal-to-noise ratio, and the first setting interval (more than 18) of the number of quality satellites, the first setting intervals constitute a first setting interval set (i.e., the aforementioned partitions), the positioning error value corresponding to each positioning data is not identical, wherein the positioning error value corresponding to 0.95 ten thousand positioning error data falls into the second setting interval (the positioning error value is less than 1 meter), the coincidence ratio (i.e., the reliability) is 0.95/1 ═ 95%, and if the setting threshold of the coincidence ratio is 90%, the first setting interval of each influence factor can be associated with the second setting interval at the same time, first association data is generated. Such association data may be used to help make the following decisions: when the ue performs positioning later, when the value of the influence factor in the positioning error data falls within the aforementioned first set of setting intervals, the positioning error value of the epoch will have a probability of 95% falling within the second set of setting intervals. I.e. can be used to estimate a positioning error value.
Fig. 3 shows a relationship of data types of the first associated data in one case. The first setting section set U1 includes one first setting section for each influence factor, for example, "first setting section a1, first setting section B2, first setting section C1, first setting section D3, and first setting section E4". The first setting section set U1 is different from the first setting section set U2 in that one first setting section corresponding to at least one influence factor in the latter is different from the former. The first related data represents the relationship between the first set of setting sections U1 and the second set of setting sections X1, and represents the relationship between the first set of setting sections U2 and the second set of setting sections X2. In one embodiment, according to the first correlation data, when the influence factor of the positioning error data of a certain epoch obtained by processing during positioning of the positioning device falls into the first set of setting intervals U1, it can be estimated that the positioning error value of the epoch falls into the second set interval X1, and such estimation result is beneficial for the user to know the current positioning quality in time. In view of data processing, the first related data describes the association relationship between the sections, and has an advantage that it is difficult to replace the first related data in terms of data processing speed and data storage.
Similarly, the estimated positioning error value may be associated with the first set of setting intervals based on the first associated data, and second associated data may be generated and stored. The second setting interval is a value interval of the positioning error value, which may be associated with a positioning error estimate, for example, if the second setting interval is "less than 1 meter", the positioning error estimate may be set to "1 meter"; for another example, if the second set interval is "less than 5 meters", the positioning error estimation value may be set to "5 meters". This allows for a compact display on the display interface of the pointing device. The estimated positioning error value may be obtained systematically by inputting it through an input device, or may be a value within the second set interval (for example, a value at an end point or a value in the middle) according to a simple algorithm.
Fig. 4 shows an example of the correlation between the first setting range and the estimated value of the positioning error and the reliability. That is, the estimated positioning error value and the reliability may be associated with the first set interval, and second associated data may be generated and stored. For example, "the first setting section a1, the first setting section B2, the first setting section C1, the first setting section D3, and the first setting section E4" may be associated with the estimated value of positioning error Y1 and the confidence level Z1 as the first setting section set U1. The second associated data essentially records the association relationship between the value segment of the influence factor and the estimated value and reliability of the positioning error, so that the situation of the positioning error can be reflected more fully, and the data can be used as the estimation of the positioning error conveniently.
In some embodiments, the first setting interval set may also be designed according to the specific situation of the actually obtained positioning error data set, for example, when in a certain scenario, the positioning error value with the average signal-to-noise ratio above 28 is obviously different from the positioning error value with the average signal-to-noise ratio below 25, the first setting interval of the average signal-to-noise ratio may be designed according to the pattern shown in fig. 1 as follows: the first setting interval B1 is less than 25, the first setting interval B2 is 25-28, and the first setting interval B3 is greater than 28. Similarly, the first setting section of the other influence factors may be designed in such a manner.
Based on the above explanation, a method for providing a positioning service for a user terminal can be obtained, so that the user terminal can obtain estimation information of positioning error values of some epochs and can provide more dimensional references for subsequent decisions such as navigation. Such a method may be such that: the server analyzes the request information of the user terminal after receiving the request information; and determining a corresponding positioning error estimation value according to a first set of setting intervals in which the numerical values of the influence factors in the request information fall, and combining the second associated data, and sending the corresponding positioning error estimation value to the user terminal. A user terminal may be understood herein as a positioning device for use by a user.
In yet another aspect, the present disclosure provides an apparatus for acquiring positioning error data, including: the data acquisition module is used for acquiring first positioning data of the measured positioner in a plurality of epochs, and the first positioning data comprises influence factor data and a first coordinate value; the data acquisition module is also used for acquiring second positioning data of the standard positioner in a plurality of same epochs, and the second positioning data comprises second coordinate values; a processing module for performing the steps of: responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; correlating the positioning error value of each epoch with the influence factor data to obtain a positioning error data set; a storage module for storing the set of positioning error data.
In fact, the first set of setting intervals may include the type information of the device in addition to the value intervals set for the impact factors, so that the content of the formed first associated data or second associated data is richer and more accurate for performing the positioning error estimation.
Expressions in the forms such as a1, B1, C1, D1, E1, W1, X1, Y1, Z1, etc. in the foregoing and in the drawings can be understood only as symbols of different styles, which do not have more concepts per se.
It will be understood by those skilled in the art that all or part of the steps in the embodiments may be implemented by hardware instructions associated with a computer program, and the program may be stored in a computer readable medium, which may include various media capable of storing program code, such as a flash memory, a removable hard disk, a read-only memory, a random access memory, a magnetic or optical disk, and the like.
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 skill of the disclosed technology, as will be understood or inferred by those skilled in the art from the figures and above.
Moreover, the descriptions of the various embodiments are expanded upon with varying emphasis, and where not already described, may be had by reference to the prior art or other related descriptions herein.
It is emphasized that the above-mentioned embodiments, which are typical and preferred embodiments of the present disclosure, are only used for explaining and explaining the technical solutions of the present disclosure in detail for the convenience of the reader, and do not limit the protection scope or application of the present disclosure. Any modifications, equivalents, improvements and the like which come within the spirit and principle of the disclosure are intended to be covered by the scope of the disclosure.
Claims (10)
1. A method for acquiring positioning error data, comprising the steps of:
acquiring first positioning data of a measured locator in a plurality of epochs, wherein the first positioning data comprises influence factor data and a first coordinate value;
acquiring second positioning data of the standard locator in the same plurality of epochs, wherein the second positioning data comprises second coordinate values;
responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; the positioning state comprises dynamic positioning or static positioning;
calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value;
and associating the positioning error value of each epoch with the influence factor data and then storing to obtain a positioning error data set.
2. The acquisition method according to claim 1,
the instructions are for determining a positioning state as a static positioning;
"performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes:
and dividing the plurality of epochs into one or more time periods, and selecting a second coordinate value with a fixed solution from the time periods as a standard coordinate value of the time period.
3. The acquisition method according to claim 1,
the positioning state comprises dynamic positioning or static positioning;
the instructions are for determining a location state as a dynamic location;
"performing corresponding processing on the second coordinate value to obtain a standard coordinate value" includes: and enabling the standard coordinate value to be equal to the second coordinate value of each epoch.
4. The acquisition method according to claim 1,
the first positioning data and the second positioning data are acquired and processed in a plurality of scenes with different occlusion rates.
5. The acquisition method according to claim 1,
the influence factor data comprises names and numerical values of influence factors;
the impact factors include any at least three of a horizontal accuracy factor, an average signal-to-noise ratio, a minimum signal-to-noise ratio, a number of premium satellites, and a number of available satellites.
6. The acquisition method according to claim 5,
processing the original observation data, and counting according to a preset filtering condition to obtain the number of high-quality satellites suitable for positioning calculation at that time;
the filtering condition comprises that the satellite signal frequency, the numerical value of the satellite altitude angle or the pseudo range value is in a preset range.
7. A method of processing positioning error data, comprising the steps of:
the acquisition method according to any one of claims 1 to 6, obtaining the set of positioning error data;
responding to the counting instruction, counting the number of the positioning error data of each influence factor falling into a specific first set interval to obtain the total number of the partitions, and counting the number of the positioning error data falling into a specific first set interval set and a second set interval at the same time to obtain the number of the matched partitions;
the first setting interval is a numerical interval set for an influence factor, and the second setting interval is a numerical interval set for the positioning error value;
calculating a coincidence proportion according to the total number of the partitions and the coincidence number of the partitions;
and associating the first set of setting intervals and the second set of setting intervals with the coincidence proportion higher than the setting threshold value, generating and storing first associated data, wherein the associated data is used for estimating the positioning error.
8. The method of processing positioning error data of claim 7, wherein:
and according to the first correlation data, correlating the estimated positioning error value with the first set interval set to generate and store second correlation data.
9. The method of processing positioning error data of claim 8, wherein:
the server analyzes the request information of the user terminal after receiving the request information;
and determining a corresponding positioning error estimation value according to a first set of setting intervals in which the numerical values of the influence factors in the request information fall, and combining the second associated data, and sending the corresponding positioning error estimation value to the user terminal.
10. An apparatus for acquiring positioning error data, comprising:
the data acquisition module is used for acquiring first positioning data of the measured positioner in a plurality of epochs, and the first positioning data comprises influence factor data and a first coordinate value; the data acquisition module is also used for acquiring second positioning data of the standard positioner in a plurality of same epochs, and the second positioning data comprises second coordinate values;
a processing module for performing the steps of: responding to the instruction for determining the positioning state, and performing corresponding processing on the second coordinate value to obtain a standard coordinate value; calculating to obtain a positioning error value of the measured positioner in a plurality of epochs according to the first coordinate value and the standard coordinate value; correlating the positioning error value of each epoch with the influence factor data to obtain a positioning error data set;
a storage module for storing the set of positioning error data.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114355397A (en) * | 2022-03-21 | 2022-04-15 | 中国汽车技术研究中心有限公司 | Positioning sensor simulation method and device, electronic equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101576617A (en) * | 2009-06-18 | 2009-11-11 | 北京航空航天大学 | System and method thereof for obtaining positioning information of satellite navigation system |
| CN102103210A (en) * | 2009-12-17 | 2011-06-22 | 中国石油大学(北京) | System for evaluating performance of satellite navigation system |
| CN102981170A (en) * | 2012-11-19 | 2013-03-20 | 中国人民解放军国防科学技术大学 | Test method for multimode processing capacity of satellite navigation terminal |
| CN108121001A (en) * | 2017-12-29 | 2018-06-05 | 湖南北斗微芯产业发展有限公司 | The quasi-static scene positioning accuracy optimization method differentiated based on fixed solution continuity |
| CN108828630A (en) * | 2018-04-18 | 2018-11-16 | 交通运输部水运科学研究所 | Baseband chip performance estimating method and device |
-
2019
- 2019-08-30 CN CN201910817467.8A patent/CN111123303B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101576617A (en) * | 2009-06-18 | 2009-11-11 | 北京航空航天大学 | System and method thereof for obtaining positioning information of satellite navigation system |
| CN102103210A (en) * | 2009-12-17 | 2011-06-22 | 中国石油大学(北京) | System for evaluating performance of satellite navigation system |
| CN102981170A (en) * | 2012-11-19 | 2013-03-20 | 中国人民解放军国防科学技术大学 | Test method for multimode processing capacity of satellite navigation terminal |
| CN108121001A (en) * | 2017-12-29 | 2018-06-05 | 湖南北斗微芯产业发展有限公司 | The quasi-static scene positioning accuracy optimization method differentiated based on fixed solution continuity |
| CN108828630A (en) * | 2018-04-18 | 2018-11-16 | 交通运输部水运科学研究所 | Baseband chip performance estimating method and device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114355397A (en) * | 2022-03-21 | 2022-04-15 | 中国汽车技术研究中心有限公司 | Positioning sensor simulation method and device, electronic equipment and medium |
| CN114355397B (en) * | 2022-03-21 | 2022-06-17 | 中国汽车技术研究中心有限公司 | Positioning sensor simulation method and device, electronic equipment and medium |
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