Pseudorange generalized extension extrapolation method, device, computer equipment and medium

Abstract

The present application relates to a method, device, computer equipment and medium for generalized continuation and extrapolation of pseudorange. The method includes: storing a priori pseudorange observations, and receiving pseudorange and Doppler shift observations at the current moment; calculating the pseudorange change rate, and determining whether an abnormality occurs based on the pseudorange change rate and Doppler shift observations; if so, selecting pseudorange observations of multiple epochs including the current moment from the priori pseudorange observations, and calculating the pseudorange change rate data sequence; determining the abnormal data in the pseudorange observations of multiple epochs based on their medians and median absolute deviations and eliminating the abnormal data; using the pseudorange observations of multiple epochs with the abnormal data eliminated to perform polynomial fitting on the pseudorange observations at the current moment, and then using the generalized continuation and extrapolation model to perform pseudorange extrapolation based on the fitted data. The present method can use a smaller amount of calculation, that is, control the error of the interpolation point.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and in particular to a method, device, computer equipment and medium for generalized extension and extrapolation of pseudorange. Background Art

[0002] Beidou's generalized RDSS service adopts the three-star positioning principle, that is, users need to observe at least a three-star positioning combination constellation, which includes a GEO satellite capable of providing RDSS services and two or more satellites capable of providing RNSS services. The user terminal sends an RDSS service application to the MCC (Measurement Control Center) through the RDSS link. The MCC obtains the RDSS service pseudo-range observation of the user terminal by calculating the transmission delay, and adds the pseudo-range observation information of at least three RNSS pseudo-range observations filled in by the user in the RDSS service message to establish the pseudo-range observation equation group of the user terminal. After the MCC corrects the observation information, it obtains the user's position information and clock error information through the analytical equation group, and sends the position information to the user through the downlink to realize the positioning of the user terminal.

[0003] In the above process, the quality of pseudo-range observations submitted by the user terminal is a key factor affecting the positioning accuracy of generalized RDSS. Since there is a time asynchrony between the RDSS entry time and the RNSS measurement time, that is, the RNSS pseudo-range observation information is received before the RDSS entry time, and the generalized RDSS service needs to fill in the RNSS pseudo-range observation information at the whole second time close to the entry time, it is necessary to accurately extrapolate the RNSS pseudo-range observations, which can generally be done by interpolation and fitting methods. Commonly used interpolation and fitting methods include Lagrange interpolation, Newton interpolation, Chebyshev polynomial fitting, Legendre polynomial fitting, generalized continuation model, etc.

[0004] When using the generalized continuation model to extrapolate pseudorange, when the interpolation point error is large, it will directly lead to a large deviation in extrapolation, thus affecting the generalized RDSS positioning accuracy. Usually, in order to overcome the error caused by the sudden change of the interpolation point value, the average value of the latest several points is selected as the pseudorange observation at the latest moment for constraint. This processing method will artificially introduce a certain error when the pseudorange observation does not have a large deviation; when the pseudorange observation has a large deviation, the obtained pseudorange observation is not accurate enough. Summary of the invention

[0005] Based on this, it is necessary to provide a pseudorange generalized extension extrapolation method, device, computer equipment and medium to address the above technical problems.

[0006] A pseudorange generalized continuation extrapolation method, the method comprising:

[0007] Storing a priori pseudorange observations, and receiving pseudorange and Doppler shift observations at the current moment;

[0008] Calculating a pseudorange change rate according to the pseudorange at the current moment, and determining whether an abnormality occurs in the current pseudorange observation amount according to the pseudorange change rate and the Doppler frequency shift observation amount;

[0009] If yes, then select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence;

[0010] Obtaining the median and median absolute deviation of the pseudorange change rate data sequence, determining abnormal data in pseudorange observations of multiple epochs according to the median and median absolute deviation, and removing the abnormal data;

[0011] The pseudorange observations of multiple epochs without abnormal data are used to perform polynomial fitting on the pseudorange at the current moment to obtain an improved value of the pseudorange observation at the current moment;

[0012] The improved value of the pseudorange observation at the current moment is used as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0013] In one embodiment, the method further includes: setting a threshold ,if , then it is determined that the pseudo-range observation at this moment is normal; otherwise, it is determined that the pseudo-range observation is abnormal. The threshold setting can be determined according to the receiver noise situation, where Indicates satellite exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal.

[0014] In one embodiment, it also includes: determining the abnormal data judgment formula as:

[0015] ;

[0016] Indicates satellite exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

[0017] In one embodiment, the method further includes: fitting a linear function based on the principle of minimum sum of square deviations of the pseudorange at the current moment using the pseudorange observations of multiple epochs excluding abnormal data to obtain an improved value of the pseudorange observation at the current moment.

[0018] In one embodiment, the generalized extension and extrapolation model is:

[0019] ;

[0020] in, is the coefficient to be determined, To minimize the optimal objective function, For the current moment, is the number of pseudo-range observations used, st is the boundary point interpolation condition, Indicated in When the pseudo-range at the moment and the pseudo-range observation is normal, For the current The actual pseudo-range observation at the moment; when the pseudo-range observation is abnormal, For the current Improved value of pseudorange observation at time.

[0021] A pseudorange generalized continuation extrapolation device, the device comprising:

[0022] A data storage module, used to store a priori pseudorange observations, and receive pseudorange and Doppler frequency shift observations at the current moment;

[0023] An abnormality judgment module is used to calculate the pseudorange change rate according to the pseudorange at the current moment, and determine whether the current pseudorange observation value is abnormal according to the pseudorange change rate and the Doppler frequency shift observation value;

[0024] a data sequence generating module, configured to select pseudorange observations of a plurality of epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence;

[0025] A data elimination module, used to obtain the median and median absolute deviation of the pseudorange change rate data sequence, determine the abnormal data in the pseudorange observations of multiple epochs according to the median and median absolute deviation, and eliminate the abnormal data;

[0026] The extrapolation module is used to perform polynomial fitting on the pseudorange at the current moment by using the pseudorange observations of multiple epochs with abnormal data removed to obtain an improved value of the pseudorange observation at the current moment; and use the improved value of the pseudorange observation at the current moment as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0027] In one embodiment, the abnormality determination module is also used to set a threshold ,if , then it is determined that the pseudo-range observation quantity at this moment is normal, if not, then it is determined that the pseudo-range observation quantity is abnormal; where, Indicates satellite exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal.

[0028] In one embodiment, the data elimination module is further used to determine the abnormal data judgment formula as follows:

[0029] ;

[0030] Indicates satellite exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

[0031] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0032] Storing a priori pseudorange observations, and receiving pseudorange and Doppler shift observations at the current moment;

[0033] Calculating a pseudorange change rate according to the pseudorange at the current moment, and determining whether an abnormality occurs in the current pseudorange observation amount according to the pseudorange change rate and the Doppler frequency shift observation amount;

[0034] If yes, then select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence;

[0035] Obtaining the median and median absolute deviation of the pseudorange change rate data sequence, determining abnormal data in pseudorange observations of multiple epochs according to the median and median absolute deviation, and removing the abnormal data;

[0036] The pseudorange observations of multiple epochs without abnormal data are used to perform polynomial fitting on the pseudorange at the current moment to obtain an improved value of the pseudorange observation at the current moment;

[0037] The improved value of the pseudorange observation at the current moment is used as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0039] Storing a priori pseudorange observations, and receiving pseudorange and Doppler shift observations at the current moment;

[0040] Calculating a pseudorange change rate according to the pseudorange at the current moment, and determining whether an abnormality occurs in the current pseudorange observation amount according to the pseudorange change rate and the Doppler frequency shift observation amount;

[0041] If yes, then select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence;

[0042] Obtaining the median and median absolute deviation of the pseudorange change rate data sequence, determining abnormal data in pseudorange observations of multiple epochs according to the median and median absolute deviation, and removing the abnormal data;

[0043] The pseudorange observations of multiple epochs without abnormal data are used to perform polynomial fitting on the pseudorange at the current moment to obtain an improved value of the pseudorange observation at the current moment;

[0044] The improved value of the pseudorange observation at the current moment is used as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0045] The above-mentioned pseudorange generalized continuation extrapolation method, device, computer equipment and storage medium introduce Doppler frequency shift observations to verify the pseudorange observations. When there is no abnormality in the pseudorange observations at the latest time point, the generalized continuation method is directly used to extrapolate the pseudorange through a certain number of stored prior pseudorange observation data, and the amount of calculation will not be increased; when an abnormality occurs, the pseudorange at the current moment is polynomially fitted using the pseudorange observations of multiple epochs with the abnormal data removed to obtain an improved value of the pseudorange observation at the current moment, and then the generalized continuation method is used to extrapolate the pseudorange through a certain number of stored prior pseudorange observation data. The present invention uses a smaller amount of calculation, that is, to control the error of the interpolation point, which not only ensures positioning accuracy, but also ensures real-time performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Schematic diagram of a flow chart of a pseudorange generalized extension extrapolation method in one embodiment;

[0047] Figure 2 Schematic diagram of the overall process of a pseudorange generalized extension extrapolation method in one embodiment;

[0048] Figure 3 It is a structural block diagram of a pseudorange generalized continuation extrapolation device in one embodiment;

[0049] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] In one embodiment, Figure 1 As shown, a pseudorange generalized extension extrapolation method is provided, comprising the following steps:

[0052] Step 102: store the prior pseudorange observations, and receive the pseudorange and Doppler shift observations at the current moment.

[0053] In this step, for each RNSS operational satellite observed, according to the output frequency of the user terminal observation quantity, you can choose to store n A set of prior pseudorange observations.

[0054] Step 104, calculating the pseudorange change rate according to the pseudorange at the current moment, and determining whether the current pseudorange observation value is abnormal according to the pseudorange change rate and the Doppler frequency shift observation value.

[0055] set up A satellite to be observed up to date The pseudo-range observation at the moment, The latest The pseudorange change rate at the moment, The pseudo-range observations are differentiated to calculate the latest The pseudorange change rate at the moment:

[0056] ;

[0057] satellite exist Doppler shift at time Pseudorange change rate The relationship is as follows:

[0058] ;

[0059] in, is the wavelength of the received satellite navigation signal.

[0060] It is worth noting that the basis for whether the current pseudo-range observation is abnormal is to ensure that the Doppler frequency shift Pseudorange change rate Relational consistency.

[0061] Step 106: If yes, then select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate the pseudorange change rate data sequence.

[0062] The value of pseudorange observation is relatively large, which makes it easy to cover up the abnormal data points in the pseudorange observation data. However, the value of the pseudorange change rate data series between adjacent epochs does not change much, which makes it relatively easy to detect abnormal values. At the same time, the pseudorange change rate can eliminate the system and receiver related errors that may exist in the pseudorange observation sequence through a differential processing of the pseudorange observation between adjacent epochs, which is convenient for more accurate data screening preprocessing.

[0063] In this step, the amount of pseudo-range observations of multiple epochs is relatively small, so that the amount of extrapolation calculation is not large.

[0064] Step 108, obtaining the median and median absolute deviation of the pseudorange change rate data sequence, determining abnormal data in the pseudorange observations of multiple epochs according to the median and median absolute deviation, and removing the abnormal data.

[0065] Step 110, using the pseudorange observations of multiple epochs with abnormal data removed to perform polynomial fitting on the pseudorange at the current moment, obtain an improved value of the pseudorange observation at the current moment, and use the improved value of the pseudorange observation at the current moment as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0066] In the above-mentioned pseudorange generalized continuation extrapolation method, Doppler frequency shift observations are introduced to verify the pseudorange observations. When there is no abnormality in the pseudorange observations at the latest time point, the generalized continuation method is directly used to extrapolate the pseudorange through a certain number of stored prior pseudorange observation data, and the amount of calculation will not be increased; when an abnormality occurs, the abnormal data is first eliminated and fitted to obtain the improved value of the pseudorange observation at the current moment, and then the pseudorange observations of multiple epochs with the abnormal data eliminated and the improved value of the pseudorange observation at the current moment are used to extrapolate the pseudorange. The present invention uses a smaller amount of calculation, that is, to control the error of the interpolation point, which not only ensures positioning accuracy, but also ensures real-time performance.

[0067] In one of the embodiments, it is determined whether the pseudorange observation amount at the current moment is abnormal based on the pseudorange change rate and the Doppler frequency shift observation amount.

[0068] Specifically, setting the threshold ,if , then it is determined that the pseudo-range observation at this moment is normal; otherwise, it is determined that the pseudo-range observation is abnormal. The threshold setting can be determined according to the receiver noise situation. Among them, Indicates satellite exist The pseudorange change rate at the moment, Indicates satellite exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal.

[0069] In one embodiment, the abnormal data determination formula is:

[0070] ;

[0071] Indicates satellite exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

[0072] Specifically, a relatively small number of epochs of data are selected from the stored prior pseudo-range observation data. of Moment epoch pseudorange observation data. According to the formula Calculate the pseudorange change rate data series , each pseudorange change rate data Median of the pseudorange change rate data series (MED) k The absolute value of and the sum of multiples of the median absolute deviation (MAD) are compared. If the formula is satisfied , then the pseudorange change rate data is considered to be an abnormal value, and the pseudorange observation data used to calculate the pseudorange change rate data are removed from the pseudorange observation data. In the above formula, , N The value of is determined according to needs, for example, it can be 3.

[0073] The generalized extension extrapolation model is highly dependent on the latest pseudorange observation data, and the reliability of this data is closely related to the generalized RDSS positioning result. Therefore, in one embodiment, the pseudorange at the current moment is fitted with a polynomial using the pseudorange observations of multiple epochs with abnormal data removed to obtain an improved value of the pseudorange observation at the current moment; the improved value of the pseudorange observation at the current moment is used as the interpolation point of the generalized extension extrapolation model to perform pseudorange extrapolation.

[0074] The present invention improves the reliability of interpolation points in the generalized extension method by using a polynomial model to fit the latest time data based on the screening of pseudorange observation data. Since the pseudorange observation data used for fitting are screened, the number is small and the time is short, and the pseudorange change rate data is close to a constant, the pseudorange observation data is more consistent with a first-order polynomial model, that is, a linear model.

[0075] Specifically, since the least square method is simple, the present invention uses the least square method for linear fitting, that is, the linear function is fitted according to the principle of minimum sum of squared deviations, and then the fitted linear function is calculated to obtain Improved value of pseudo-range observation at the moment . Let the linear function expression be , the number of pseudo-range observations after screening is , then according to the principle of least squares method, we can get the following matrix equation:

[0076] ;

[0077] ;

[0078] It can be solved as follows:

[0079] ;

[0080] ;

[0081] Will a, b Substituting the value into the linear function ,calculate Improved value of pseudo-range observation at the moment .

[0082] In one embodiment, the generalized extension model is:

[0083] ;

[0084] in, is the coefficient to be determined, To minimize the optimal objective function, For the current moment, is the number of pseudo-range observations used, and st is the boundary point interpolation condition.

[0085] When there is no abnormality in the pseudorange observation, For the current Actual pseudo-range observation at the moment ; When the pseudorange observation is abnormal, For the current Improved value of pseudo-range observation at the moment .

[0086] Expand the above model and solve it according to the constraints:

[0087] ;

[0088] Substitute the above formula into the minimization objective function for:

[0089] ;

[0090] then Find partial derivatives: ;

[0091] We can get:

[0092] ;

[0093] Arranged into matrix form:

[0094] ;

[0095] in:

[0096] ;

[0097] ;

[0098] ;

[0099] ;

[0100] Available :

[0101] ;

[0102] Will Substitution In the formula, we get :

[0103] ;

[0104] The coefficients to be obtained Substituting the polynomial into the equation, we can obtain the extrapolated pseudorange value of the observed satellite:

[0105] ;

[0106] in, The time is the whole second time adjacent to the generalized RDSS inbound time.

[0107] In summary, if Figure 2As shown, the present invention first stores pseudorange and Doppler frequency shift observation data for a period of time, and then verifies whether the latest pseudorange observation is abnormal through the relationship between Doppler frequency shift and pseudorange change rate. When the pseudorange observation is normal, the generalized extension method is directly used to extrapolate the pseudorange through a certain number of stored prior pseudorange observation data; when an abnormality occurs, the abnormal data is removed and a smaller number of prior data are used for fitting to correct the latest pseudorange observation, and then the pseudorange observation of multiple epochs with the abnormal data removed and the improved value of the pseudorange observation at the current time are used to extrapolate the pseudorange. The method verifies whether the latest pseudorange observation is abnormal by comparing the pseudorange change rate obtained by the Doppler frequency shift data and the pseudorange difference between the epochs according to the relationship between the two. When there is no abnormality, the amount of calculation will not be increased; when an abnormality occurs, the abnormal data is removed and the latest pseudorange observation is corrected by the fitting method before the generalized extension extrapolation is performed, which improves the accuracy of the interpolation point, thereby improving the generalized RDSS positioning accuracy.

[0108] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0109] In one embodiment, Figure 3 As shown, a pseudorange generalized continuation extrapolation device is provided, comprising: a data storage module 302, an abnormality judgment module 304, a data sequence generation module 306, a data elimination module 308 and an extrapolation module 310, wherein:

[0110] The data storage module 302 is used to store the prior pseudorange observations and receive the pseudorange and Doppler shift observations at the current moment;

[0111] The abnormality judgment module 304 is used to calculate the pseudorange change rate according to the pseudorange at the current moment, and determine whether the current pseudorange observation value is abnormal according to the pseudorange change rate and the Doppler frequency shift observation value;

[0112] A data sequence generating module 306 is configured to select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence;

[0113] A data elimination module 308 is used to obtain the median and median absolute deviation of the pseudorange change rate data sequence, determine the abnormal data in the pseudorange observations of multiple epochs according to the median and median absolute deviation, and eliminate the abnormal data;

[0114] The extrapolation module 310 is used to perform polynomial fitting on the pseudorange at the current moment by using the pseudorange observations of multiple epochs with abnormal data removed to obtain an improved value of the pseudorange observation at the current moment; and use the improved value of the pseudorange observation at the current moment as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

[0115] In one embodiment, the data elimination module 308 is further configured to determine the abnormal data judgment formula as follows:

[0116] ;

[0117] Indicates satellite exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

[0118] In one embodiment, the abnormality determination module 304 is also used to set a threshold ,if , then it is determined that the pseudo-range observation at this moment is normal; otherwise, it is determined that the pseudo-range observation is abnormal. The threshold setting can be determined according to the receiver noise situation. Among them, Indicates satellite exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal.

[0119] In one embodiment, the extrapolation module 310 is further used to fit a linear function to the pseudorange at the current moment based on the principle of minimum sum of square deviations using pseudorange observations of multiple epochs excluding abnormal data, to obtain an improved value of the pseudorange observation at the current moment.

[0120] In one embodiment, the generalized extension and extrapolation model is:

[0121] ;

[0122] in, is the coefficient to be determined, To minimize the optimal objective function, For the current moment, is the number of pseudo-range observations used, and st is the boundary point interpolation condition. Indicated in When the pseudorange observation is normal, For the current The actual pseudo-range observation at the moment; when the pseudo-range observation is abnormal, For the current Improved value of pseudorange observation at time.

[0123] For the specific definition of the pseudorange generalized extension extrapolation device, please refer to the definition of the pseudorange generalized extension extrapolation method above, which will not be repeated here. Each module in the above-mentioned pseudorange generalized extension extrapolation device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0124] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store historical clock difference and frequency difference data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a pseudo-range generalized extension extrapolation method is implemented.

[0125] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0126] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the above embodiment when executing the computer program.

[0127] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in the above embodiment are implemented.

[0128] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0129] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A pseudorange generalized extension extrapolation method, characterized in that: The method comprises: Storing a priori pseudorange observations, and receiving pseudorange and Doppler shift observations at the current moment; Calculating a pseudorange change rate according to the pseudorange at the current moment, and determining whether an abnormality occurs in the current pseudorange observation amount according to the pseudorange change rate and the Doppler frequency shift observation amount; If yes, then select pseudorange observations of multiple epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence; Obtaining the median and median absolute deviation of the pseudorange change rate data sequence, determining abnormal data in pseudorange observations of multiple epochs according to the median and median absolute deviation, and removing the abnormal data; The pseudorange observations of multiple epochs without abnormal data are used to perform polynomial fitting on the pseudorange at the current moment to obtain an improved value of the pseudorange observation at the current moment; The improved value of the pseudorange observation at the current moment is used as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

2. The method according to claim 1, characterized in that Determining whether a current pseudorange observation value is abnormal according to the pseudorange change rate and the Doppler frequency shift observation value includes: Setting Thresholds ,if , then it is determined that the pseudo-range observation quantity at this moment is normal, if not, then it is determined that the pseudo-range observation quantity is abnormal; where, Indicates satellite j exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal, Indicates satellite j exist The pseudorange changing rate at each moment.

3. The method according to claim 1, characterized in that Determining abnormal data in pseudorange observations of multiple epochs according to the median and the median absolute deviation includes: The formula for determining abnormal data is: ； Indicates satellite j exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

4. The method according to claim 1, characterized in that The pseudorange observations of multiple epochs with abnormal data removed are used to perform polynomial fitting on the pseudorange at the current moment to obtain the improved value of the pseudorange observation at the current moment, including: The pseudorange observations of multiple epochs with abnormal data removed are used to fit a linear function based on the principle of minimum sum of square deviations of the pseudorange at the current moment, and the improved value of the pseudorange observation at the current moment is obtained.

5. The method according to any one of claims 1 to 4, characterized in that: The generalized extension and extrapolation model is: ； in, is the coefficient to be determined, To minimize the optimal objective function, For the current moment, n is the number of pseudo-range observations used, st is the boundary point interpolation condition, Indicated in When the pseudo-range at the moment and the pseudo-range observation is normal, For the current The actual pseudo-range observation at the moment; when the pseudo-range observation is abnormal, For the current Improved value of pseudorange observation at time.

6. A pseudorange generalized continuation extrapolation device, characterized in that: The device comprises: A data storage module, used to store a priori pseudorange observations, and receive pseudorange and Doppler frequency shift observations at the current moment; An abnormality judgment module is used to calculate the pseudorange change rate according to the pseudorange at the current moment, and determine whether the current pseudorange observation value is abnormal according to the pseudorange change rate and the Doppler frequency shift observation value; a data sequence generating module, configured to select pseudorange observations of a plurality of epochs including the current moment from the prior pseudorange observations, and calculate a pseudorange change rate data sequence; A data elimination module, used to obtain the median and median absolute deviation of the pseudorange change rate data sequence, determine the abnormal data in the pseudorange observations of multiple epochs according to the median and median absolute deviation, and eliminate the abnormal data; The extrapolation module is used to perform polynomial fitting on the pseudorange at the current moment by using the pseudorange observations of multiple epochs with abnormal data removed to obtain an improved value of the pseudorange observation at the current moment; and use the improved value of the pseudorange observation at the current moment as an interpolation point of the generalized continuation extrapolation model to perform pseudorange extrapolation.

7. The device according to claim 6, characterized in that The abnormal judgment module is also used to set the threshold ,if , then it is determined that the pseudo-range observation quantity at this moment is normal, if not, then it is determined that the pseudo-range observation quantity is abnormal; where, Indicates satellite j exist The Doppler shift observation at time , is the wavelength of the received satellite navigation signal, Indicates satellite j exist The pseudorange changing rate at each moment.

8. The device according to claim 6, characterized in that The data elimination module is also used to determine the abnormal data judgment formula: ； Indicates satellite j exist The pseudorange change rate at the moment, represents the median, represents the median absolute deviation, Indicates multiples.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

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

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