A method and device for analyzing satellite positioning errors with reduced storage

Abstract

The present invention discloses a method and device for analyzing satellite positioning errors with reduced storage. The method includes: calculating the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and storing the mean and standard deviation corresponding to at least one historical satellite positioning data; performing mean-standard deviation analysis on all satellite positioning data based on the stored mean and standard deviation corresponding to at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data; and calculating the positioning deviation and confidence level of the current satellite positioning data based on the Chebyshev probability inequality according to the obtained mean and standard deviation of all satellite positioning data. It can not only save storage resources for historical satellite positioning data, improve the efficiency of analysis and calculation, but also perform mean-standard deviation analysis on satellite positioning errors, which is beneficial to the application and development of satellite positioning data.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite positioning and its applications, and particularly relates to a method and device for analyzing satellite positioning errors with reduced storage. Background Art

[0002] Due to the long distance between satellites and ground receivers, the signal propagation between satellites and receivers will be affected by various error sources. Therefore, satellite positioning inevitably has errors. Satellite positioning errors are at least affected by satellite ephemeris errors, satellite clock errors, ionospheric delay, tropospheric delay, multipath effects, receiver noise, and resolution, etc. The probability distribution of satellite positioning and its errors is an important indicator of the integrity of satellite positioning information. The analysis of satellite positioning errors is of great significance in various satellite positioning application systems.

[0003] Generally, due to the influence of numerous factors on positioning errors, according to the central limit theorem, it can be known that positioning errors approximately follow a normal distribution. However, in some specific cases, their distribution may also be non-normal. Also, since the distribution of satellite positioning errors is of great significance for analyzing the accuracy of satellite positioning, when applying satellite positioning functions and positioning data, it is often necessary to conduct a specific analysis of satellite positioning errors.

[0004] In the prior art, in order to analyze satellite positioning errors, it is necessary to collect and store a large amount of satellite positioning data, and then fit the error distribution and conduct hypothesis testing based on these historical data. As a result, a lot of storage and computing resources as well as professional human resources are consumed. In practical applications, there is a need to develop and research a method and device for analyzing satellite positioning errors that are simple, convenient, and sufficient. Summary of the Invention

[0005] The present invention provides a method and device for analyzing satellite positioning errors with reduced storage, which are used to at least solve the technical problem of consuming a lot of storage and computing resources to analyze satellite positioning errors.

[0006] In a first aspect, the present invention provides a method for analyzing satellite positioning errors with reduced storage, including: calculating the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and only storing the mean and standard deviation corresponding to the at least one historical satellite positioning data; performing mean-standard deviation analysis on all satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data to obtain the mean and standard deviation of all satellite positioning data; and calculating the positioning deviation and confidence level of the current satellite positioning data based on the mean and standard deviation of all the obtained satellite positioning data according to the Chebyshev probability inequality.

[0007] Second aspect, the present invention provides a satellite positioning error analysis device for reducing storage, including: a storage module configured to calculate the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and only store the mean and standard deviation corresponding to the at least one historical satellite positioning data; an analysis module configured to perform mean-standard deviation analysis on all satellite positioning data after adding new current satellite positioning data based on the mean and standard deviation corresponding to the at least one stored satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data; an error calculation module configured to calculate the positioning deviation and confidence level of the current satellite positioning data based on the mean and standard deviation of all the obtained satellite positioning data and Chebyshev's probability inequality.

[0008] Third aspect, there is provided an electronic device, which includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the method for analyzing satellite positioning errors with reduced storage according to any embodiment of the present invention.

[0009] Fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program instructions are executed by a processor, the processor is enabled to execute the steps of the method for analyzing satellite positioning errors with reduced storage according to any embodiment of the present invention.

[0010] A method and device for analyzing satellite positioning errors with reduced storage according to the present application do not need to store all satellite positioning data. By only storing the satellite positioning data at the most recent moment, the mean and standard deviation corresponding to the calculated historical satellite positioning data, and the number of the obtained historical satellite positioning data, it is possible to complete the analysis of the positioning error of the current satellite positioning data. This can not only save the storage resources for historical satellite positioning data, improve the efficiency of analysis and calculation, but also perform mean-standard deviation analysis on satellite positioning errors, which is beneficial to the application and development of satellite positioning data. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0012] Figure 1 It is a flowchart of a method for analyzing satellite positioning errors with reduced storage provided by an embodiment of the present invention;

[0013] Figure 2 The structural block diagram of a satellite positioning error analysis device for reducing storage provided by an embodiment of the present invention;

[0014] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0015] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0016] Please refer to Figure 1 , which shows a flowchart of a method for analyzing satellite positioning errors with reduced storage according to the present application.

[0017] As Figure 1 shown, in step S101, calculate the mean value and standard deviation of at least one satellite positioning data obtained according to the time sequence, and only store the mean value and standard deviation corresponding to the at least one historical satellite positioning data;

[0018] In step S102, perform mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean value and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean value and standard deviation of all satellite positioning data;

[0019] In step S103, calculate the positioning deviation and confidence level of the current satellite positioning data based on the mean value and standard deviation of all the obtained satellite positioning data according to the Chebyshev probability inequality.

[0020] In this embodiment, there is no need to store all satellite positioning data. By only storing the satellite positioning data at the most recent moment, the mean value and standard deviation corresponding to the historical satellite positioning data obtained by calculation, and the number of historical satellite positioning data that have been obtained, the mean value and standard deviation corresponding to all satellite positioning data after adding the new current satellite positioning data can be obtained, so that the approximate accurate value of the location of the satellite positioning device in the current satellite positioning data (i.e., the coordinate mean value corresponding to all satellite positioning data) can be determined, and the positioning deviation of the location of the satellite positioning device in the current satellite positioning data (i.e., the difference between the coordinate value of the satellite positioning device in the current satellite positioning data and the coordinate mean value corresponding to all satellite positioning data) can be determined, and the confidence level of the positioning deviation of the current satellite positioning data can be calculated according to the Chebyshev probability inequality.

[0021] The method of this embodiment can save the storage resources for historical satellite positioning data, improve the efficiency of analysis and calculation, and at the same time can perform mean-standard deviation analysis on satellite positioning errors, which is beneficial to the application and development of satellite positioning data by only storing the satellite positioning data at the most recent moment, the mean and standard deviation corresponding to the calculated historical satellite positioning data, and the number of historical satellite positioning data obtained.

[0022] In a specific embodiment, when the first satellite positioning data (t1, lon1, lat1) is received, it is stored as (t1, lon1, lat1), and the mean lon of the satellite positioning data is stored μ = lon1, lat μ = lat1 and the standard deviation lon σ = 0, lat σ = 0. At the same time, record the number n of the received satellite positioning data stored. At this time, n = 1.

[0023] When the second satellite positioning data (t2, lon2, lat2) is received, the original storage (t1, lon1, lat1) is overwritten with (t2, lon2, lat2), and the mean and standard deviation are recalculated according to the mean-standard deviation algorithm, and the originally stored mean lon μ , lon μ and the standard deviation lon σ , lon σ are overwritten and updated. At the same time, update and record the number n of the received satellite positioning data stored in this invention device. At this time, n = 2. And so on. When the nth satellite positioning data (t n , lon n , lat n ) is received, the storage space stores only the nth satellite positioning data (t n , lon n , lat n ), the mean lon μ of the received n satellite positioning data, lat μ and the standard deviation lon σ , lat σ , and the number n of the received satellite positioning data.

[0024] If a new satellite positioning data is added, denoted as (t, lon, lat), and denote the new mean of all satellite positioning data after adding this new satellite positioning data as The new standard deviation is The update algorithm is deduced as follows:

[0025] The updated mean is:

[0026]

[0027] Similar

[0028] In the formula, is the standard deviation of the longitudes of all satellite positioning data, lon σ is the standard deviation of the longitudes of all historical satellite positioning data, lon is the longitude of the current satellite positioning data, is the standard deviation of the latitudes of all satellite positioning data, lat σ is the standard deviation of the latitudes of all historical satellite positioning data, lat is the latitude of the current satellite positioning data, and n is the number of historical satellite positioning data.

[0029] Among them, the definition of the mean value is:

[0030]

[0031] In the formula, lon n is the longitude of the nth satellite positioning data, lat n is the latitude of the nth satellite positioning data.

[0032] The updated standard deviation is:

[0033]

[0034] That is

[0035] Similar

[0036] In the formula, is the mean value of the longitudes of all satellite positioning data, lon μ is the mean value of the longitudes of all historical satellite positioning data, lon is the longitude of the current satellite positioning data, is the mean value of the latitudes of all satellite positioning data, lat μ is the mean value of the latitudes of all historical satellite positioning data, lat is the latitude of the current satellite positioning data, and n is the number of historical satellite positioning data.

[0037] Among them, the definition of the standard deviation is:

[0038]

[0039]

[0040] According to the law of large numbers, to determine the approximately accurate satellite positioning data of the specified point where the satellite positioning device is located, that is (lon μ , latμ )

[0041] Determine the positioning deviation of the new satellite positioning data (t, lon, lat), that is:

[0042] (lon, lat) - (lon μ , lat μ ) = (lon - lon μ , lat - lat μ ),

[0043] Determine the confidence level of the deviation corresponding to the new satellite positioning data, that is, the maximum probability that the positioning error exceeds a given number

[0044] The principle of estimating the deviation confidence level is explained as follows:

[0045] Although the specific distribution of the satellite positioning error is not known, Chebyshev's probability inequality generally holds where ε is an arbitrarily given positive number, and considering that the probability is always less than or equal to 1;

[0046] Then can be used as the maximum probability that the new satellite positioning error will exceed ε. For example, take Then:

[0047]

[0048] That is, the probability that the new satellite positioning error exceeds does not exceed 25%.

[0049] Take Then:

[0050]

[0051] Note that the left side in the above formula is a notation representing the satellite positioning error, while the right side is a specified definite value. Although the notations are the same, their meanings are significantly different.

[0052] That is, the probability that the new satellite positioning error exceeds does not exceed

[0053] Please refer to Figure 2 , which shows the structural block diagram of a satellite positioning error analysis device for reducing storage according to the present application.

[0054] Such as Figure 2 ​As shown, the satellite positioning error analysis device 200 includes a storage module 210, an analysis module 220, and an error calculation module 230.

[0055] Among them, the storage module 210 is configured to calculate the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and only store the mean and standard deviation corresponding to the at least one historical satellite positioning data; the analysis module 220 is configured to perform mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data; the error calculation module 230 is configured to calculate the positioning deviation and confidence of the current satellite positioning data based on the Chebyshev probability inequality according to the mean and standard deviation of the obtained current satellite positioning data.

[0056] It should be understood that Figure 2 The modules described in Figure 1 correspond to the respective steps in the method described in Figure 2 Therefore, the operations, features, and corresponding technical effects described above for the method also apply to

[0057] In some other embodiments, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor executes the method for reducing the stored satellite positioning error in any of the above method embodiments;

[0058] As an implementation manner, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are set as:

[0059] Calculate the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and store the mean and standard deviation corresponding to the at least one historical satellite positioning data;

[0060] Perform mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data;

[0061] Calculate the positioning deviation and confidence of the current satellite positioning data based on the Chebyshev probability inequality according to the mean and standard deviation of the obtained current satellite positioning data.

[0062] A computer-readable storage medium may include a program storage area and a data storage area. Among them, the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created according to the use of the satellite positioning error analysis device with reduced storage, etc. In addition, the computer-readable storage medium may include high-speed random access memory, and may also include a memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the computer-readable storage medium may optionally include a memory remotely provided with respect to the processor, and these remote memories may be connected to the satellite positioning error analysis device with reduced storage through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0063] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. As Figure 3 shown, the device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330, and the output device 340 may be connected through a bus or other means, Figure 3 taking connection through a bus as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running non-volatile software programs, instructions, and modules stored in the memory 320, that is, implements the satellite positioning error analysis method with reduced storage in the above method embodiment. The input device 330 may receive input digital or character information, and generate key signal inputs related to user settings and function controls of the satellite positioning error analysis device with reduced storage. The output device 340 may include a display device such as a display screen.

[0064] The above electronic device may execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.

[0065] As an implementation manner, the above electronic device is applied to a satellite positioning error analysis device with reduced storage and is used for a client, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0066] calculate the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and store the mean and standard deviation corresponding to the at least one historical satellite positioning data;

[0067] Perform mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data.

[0068] Based on the mean and standard deviation of the obtained current satellite positioning data, calculate the positioning deviation and confidence level of the current satellite positioning data based on the Chebyshev probability inequality.

[0069] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on such an understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0070] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or equivalently replace some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for analyzing satellite positioning errors with reduced storage, characterized in that, including: Calculating the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and only storing the mean and standard deviation corresponding to the at least one historical satellite positioning data; Performing mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data, wherein the expression for calculating the standard deviation of all satellite positioning data is: ， In the formula, is the standard deviation of the longitudes of all satellite positioning data, is the standard deviation of the longitudes of all historical satellite positioning data, is the longitude of the current satellite positioning data, is the standard deviation of the latitudes of all satellite positioning data, is the standard deviation of the latitudes of all historical satellite positioning data, is the latitude of the current satellite positioning data, is the number of historical satellite positioning data; Based on the mean and standard deviation of all the obtained satellite positioning data, calculating the positioning deviation and confidence level of the current satellite positioning data based on the Chebyshev probability inequality.

2. The method for analyzing satellite positioning errors for reducing storage according to claim 1, characterized in that, Wherein, The expression for calculating the mean of all satellite positioning data is: ， In the formula, is the average longitude of all satellite positioning data, is the average longitude of all historical satellite positioning data, is the longitude of the current satellite positioning data, is the average latitude of all satellite positioning data, is the average latitude of all historical satellite positioning data, is the latitude of the current satellite positioning data, is the number of historical satellite positioning data.

3. A satellite positioning error analysis device for reducing storage, characterized in that, including: A storage module configured to calculate the mean and standard deviation of at least one satellite positioning data obtained in chronological order, and only store the mean and standard deviation corresponding to the at least one historical satellite positioning data; An analysis module configured to perform mean-standard deviation analysis on all satellite positioning data after adding the new current satellite positioning data based on the mean and standard deviation corresponding to the stored at least one satellite positioning data, so as to obtain the mean and standard deviation of all satellite positioning data, wherein the expression for calculating the standard deviation of all satellite positioning data is: ， Wherein, is the standard deviation of the longitudes of all satellite positioning data, is the standard deviation of the longitudes of all historical satellite positioning data, is the longitude of the current satellite positioning data, is the standard deviation of the latitudes of all satellite positioning data, is the standard deviation of the latitudes of all historical satellite positioning data, is the latitude of the current satellite positioning data, is the quantity of historical satellite positioning data; An error calculation module configured to calculate the positioning deviation and confidence level of the current satellite positioning data based on the Chebyshev probability inequality according to the mean and standard deviation of all the obtained satellite positioning data.

4. An electronic device, characterized in that, including: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the method according to any one of claims 1 to 2 is implemented.

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