Pseudo-range multipath error processing method, electronic equipment and storage medium

Abstract

The invention discloses a pseudo-range multipath error processing method, which comprises the following steps: receiving an observation sequence sent by a satellite navigation system, carrying out cycle slip detection on an original carrier phase observation value sequence in the observation sequence, obtaining a cycle slip detection result, obtaining a carrier phase sequence and a pseudo-range sequence from the observation sequence based on the cycle slip detection result, and sending the pseudo-range multipath error to the satellite navigation system. The method comprises the following steps: acquiring a carrier phase sequence and a pseudo-range sequence, acquiring a CMCD sequence based on the carrier phase sequence and the pseudo-range sequence, acquiring a pseudo-range multi-path error estimator sequence, constructing a pseudo-range multi-path error measurement coefficient and a pseudo-range multi-path error significant detection quantity based on the CMCD sequence and the pseudo-range multi-path error estimator sequence, and determining the pseudo-range multi-path error according to the pseudo-range multi-path error significant detection quantity. And when it is detected that the pseudo-range multi-path effect is significant, dynamically adjusting the variance of the pseudo-range observation value in the pseudo-range sequence based on the pseudo-range multi-path error measurement coefficient so as to suppress the pseudo-range multi-path error. According to the method, pseudo-range multipath errors can be suppressed, the method can adapt to low-cost chip sets and dynamic positioning requirements, and the cost-benefit ratio is relatively high.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite navigation, in particular to a pseudo-range multipath error processing method, an electronic device and a storage medium. BACKGROUND

[0002] Multipath error refers to that, in the process of satellite signal being transmitted from a satellite antenna to a receiver antenna, a reflected signal is generated due to reflection of a signal by a reflecting object near the receiver, and the reflected signal and a direct signal from the satellite form a superimposed signal at the receiver antenna. The reflected signal causes an additional time delay error to an observation value, and this phenomenon is referred to as multipath error, and the error caused thereby is referred to as multipath (effect) error.

[0003] At present, the method for weakening multipath error has the following problems: the traditional site selection and hardware suppression method has limited effect in a dynamic environment, and is difficult to adapt to the changing environmental requirements. The data post-processing algorithm is usually complex in operation, and it is difficult to meet the real-time high-precision application requirements. The hardware suppression method has a high cost, which limits the popularization of low-cost chipsets in high-precision positioning. SUMMARY

[0004] In order to solve the above problems, the present application provides a pseudo-range multipath error processing method, an electronic device and a storage medium, which can dynamically adjust the variance of pseudo-range observation values of satellites with significant pseudo-range multipath effects based on an algorithm at a software level, so as to suppress the pseudo-range multipath error, and can adapt to the requirements of low-cost chipsets and dynamic positioning, thereby providing a good cost-benefit ratio.

[0005] The present application provides a pseudo-range multipath error processing method, which comprises the following steps: receiving an observation sequence sent by a satellite navigation system; performing cycle slip detection on an original carrier phase observation value sequence in the observation sequence, and obtaining a cycle slip detection result; obtaining a carrier phase sequence and a pseudo-range sequence from the observation sequence based on the cycle slip detection result; obtaining a CMCD sequence based on the carrier phase sequence and the pseudo-range sequence; obtaining a pseudo-range multipath error estimation sequence; constructing a pseudo-range multipath error measurement coefficient and a pseudo-range multipath error significant detection quantity based on the CMCD sequence and the pseudo-range multipath error estimation sequence; and when it is detected that the pseudo-range multipath effect of a satellite is significant according to the pseudo-range multipath error significant detection quantity, dynamically adjusting the variance of pseudo-range observation values in the pseudo-range sequence based on the pseudo-range multipath error measurement coefficient, so as to suppress the pseudo-range multipath error.

[0006] In an embodiment, based on the cycle slip detection result, the step of obtaining a carrier phase sequence and a pseudo-range sequence from the observation sequence comprises: identifying an epoch at which a cycle slip occurs in the original carrier phase observation sequence based on the cycle slip detection result, and taking the epoch as a segmentation point; segmenting the original carrier phase observation sequence into continuous carrier phase segments based on the segmentation point, and combining all the carrier phase segments into a carrier phase sequence; performing synchronous pseudo-range segment processing on the original pseudo-range observation sequence in the observation sequence based on the segmentation point to obtain continuous pseudo-range segments, and combining all the pseudo-range segments into a pseudo-range sequence.

[0007] In an embodiment, based on the carrier phase sequence and the pseudo-range sequence, the step of obtaining a CMCD sequence comprises: extracting carrier phase observations and pseudo-range observations at the same time and the same frequency in the carrier phase sequence and the pseudo-range sequence; obtaining CMC observations based on the carrier phase observations and the pseudo-range observations at the same time and the same frequency; combining all the CMC observations into a CMC sequence; and obtaining a CMCD sequence by difference operation based on the CMC sequence.

[0008] In an embodiment, the step of obtaining a pseudo-range multipath error estimation sequence comprises: determining a calculation method based on the data type of the carrier phase sequence and the data type of the pseudo-range sequence; and determining the pseudo-range multipath error estimation sequence corresponding to the carrier phase sequence and the pseudo-range sequence by using the calculation method.

[0009] In an embodiment, the data type comprises at least one of single-frequency data, double-frequency data, and non-difference non-combined data. The step of determining a calculation method based on the data type of the carrier phase sequence and the data type of the pseudo-range sequence comprises: if the data type of the carrier phase observations and the pseudo-range observations at the same time and the same frequency in the carrier phase sequence and the pseudo-range sequence is single-frequency data, determining that the calculation method is an interpolation algorithm; if the data type of the carrier phase observations and the pseudo-range observations at the same time and the same frequency in the carrier phase sequence and the pseudo-range sequence is double-frequency data, determining that the calculation method is a first algorithm; and if the data type of the carrier phase observations and the pseudo-range observations at the same time and the same frequency in the carrier phase sequence and the pseudo-range sequence is non-difference non-combined data, determining that the calculation method is a second algorithm.

[0010] In an embodiment, the step of constructing the pseudo-range multipath error measurement coefficient and the pseudo-range multipath error significant detection quantity based on the CMCD sequence and the pseudo-range multipath error estimator sequence comprises: obtaining the mean and variance of the CMCD observation in the CMCD sequence; obtaining the mean and variance of the pseudo-range multipath error estimator in the pseudo-range multipath error estimator sequence; obtaining the pseudo-range multipath error significant detection quantity based on the mean and variance of the CMCD observation and the mean and variance of the pseudo-range multipath error estimator; and obtaining the pseudo-range multipath error measurement coefficient based on the pseudo-range multipath error estimator sequence.

[0011] In an embodiment, the pseudo-range multipath error significant detection quantity comprises a CMCD significant detection quantity and a multipath error significant detection quantity; and the step of constructing the pseudo-range multipath error measurement coefficient and the pseudo-range multipath error significant detection quantity based on the CMCD sequence and the pseudo-range multipath error estimator sequence comprises: obtaining the CMCD significant detection quantity based on the mean and variance of the CMCD observation; and obtaining the multipath error significant detection quantity based on the mean and variance of the pseudo-range multipath error estimator.

[0012] In an embodiment, when the pseudo-range multipath effect of the satellite is detected to be significant according to the pseudo-range multipath error significant detection quantity, the step of dynamically adjusting the variance of the pseudo-range observation in the pseudo-range sequence based on the pseudo-range multipath error measurement coefficient to suppress the pseudo-range multipath error comprises: detecting whether the pseudo-range multipath effect of the satellite on each frequency point is significant based on the CMCD sequence, the pseudo-range multipath error estimator sequence, the CMCD significant detection quantity and the multipath error significant detection quantity; when the pseudo-range multipath effect of the satellite on a frequency point is detected to be significant, if the pseudo-range multipath error measurement coefficient is less than a measurement threshold, the corresponding satellite is set as a first satellite, and the variance of the pseudo-range observation of the first satellite is maximally de-weighted; and when the pseudo-range multipath effect of the satellite on a frequency point is detected to be significant, if the pseudo-range multipath error measurement coefficient is greater than the measurement threshold, the corresponding satellite is set as a second satellite, and the variance of the pseudo-range observation of the second satellite is proportionally de-weighted.

[0013] In an embodiment, the method comprises: if the proportion of the number of the first satellites at the same time and on the same frequency point in the available satellites at the same time exceeds a preset proportion, the variance of the pseudo-range observation of the second satellite is not proportionally de-weighted.

[0014] The present invention also provides an electronic device, comprising: a memory for storing instructions executed by one or more processors of the electronic device, and a processor, one of the processors of the electronic device, for executing a processing method for pseudorange multipath error as described in any of the preceding claims.

[0015] The present invention also provides a storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the pseudorange multipath error processing method described above.

[0016] This invention provides a method, electronic device, and storage medium for processing pseudorange multipath errors. The method receives observation sequences sent by a satellite navigation system, performs cycle slip detection on the original carrier phase observation sequence, and obtains the cycle slip detection results. Based on the cycle slip detection results, it obtains a carrier phase sequence and a pseudorange sequence from the observation sequence. Based on the carrier phase sequence and the pseudorange sequence, it obtains a CMCD sequence and a pseudorange multipath error estimate sequence. Based on the CMCD sequence and the pseudorange multipath error estimate sequence, it constructs a pseudorange multipath error measurement coefficient and a pseudorange multipath error significance detection quantity. According to the pseudorange multipath error significance detection quantity, when a significant pseudorange multipath effect of a satellite is detected, it dynamically adjusts the variance of the pseudorange observations in the pseudorange sequence based on the pseudorange multipath error measurement coefficient to suppress pseudorange multipath errors. This invention can dynamically adjust the variance of pseudorange observations of satellites with significant pseudorange multipath effects based on software-level algorithms to suppress pseudorange multipath errors. It can adapt to low-cost chipsets and dynamic positioning requirements, providing a good cost-effectiveness ratio. Attached Figure Description

[0017] Figure 1 This is a flowchart of a pseudorange multipath error processing method according to an embodiment of the present invention.

[0018] Figure 2 for Figure 1 The flowchart for step S12.

[0019] Figure 3 for Figure 1 The flowchart for step S13.

[0020] Figure 4 for Figure 1 The flowchart for step S14.

[0021] Figure 5 This is a schematic diagram of a semi-celestial grid division according to an embodiment of the present invention.

[0022] Figure 6 for Figure 1 The flowchart for step S15.

[0023] Figure 7Structure diagram of an electronic device according to an embodiment of the present application.

[0024] Reference signs: processor - 70; memory - 71; network interface - 72; bus system - 73. DETAILED DESCRIPTION

[0025] Technical explanation: CMC: Code-Minus-Carrier / carrier-pseudorange combined observation.

[0026] CMCD: Code-Minus-Carrier Delta-range / carrier-pseudorange combined change observation.

[0027] The foregoing and other technical contents, features and effects of the present application will be apparent from the following detailed description of the preferred embodiments, which is given by reference to the accompanying drawings. Through the description of the specific embodiments, the technical means and effects taken by the present application to achieve the predetermined purposes can be understood more deeply and specifically. However, the accompanying drawings are provided for reference and illustration only, and are not intended to limit the present application.

[0028] To further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the present application is described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0029] The present application is applied to GNSS receivers or satellite signal receiving and / or processing devices.

[0030] Figure 1 Flow chart of the method for processing pseudorange multipath error according to an embodiment of the present application.

[0031] As shown in Figure 1 The method for processing pseudorange multipath error provided by the present embodiment includes the following steps: Step S11: receiving an observation sequence sent by a satellite navigation system, performing cycle slip detection on a raw carrier phase observation value sequence in the observation sequence, and obtaining a cycle slip detection result.

[0032] Specifically, before step S11, a specific signal is sent to the sky by the GNSS receiver to guide the satellite navigation system to send a corresponding observation sequence to the GNSS receiver.

[0033] Specifically, by receiving observation sequences from a satellite navigation system via GNSS, cycle slip detection algorithms (such as double-difference methods, single-difference methods, DOP checks, or phase-to-pseudorange comparisons) are used to detect cycle slips in the original carrier phase observation sequence. The cycle slip detection results are then used to identify the epochs in which cycle slips occur within the original carrier phase observation sequence. The observation sequence includes both the original carrier phase observation sequence and the original pseudorange observation sequence. A cycle slip refers to a complete cycle jump in the carrier phase observation between consecutive measurement time points. This can disrupt the continuity of carrier phase information, often caused by GNSS receiver lock-in, multipath effects, or unexpected orbital errors in the satellite orbit.

[0034] Step S12: Based on the cycle slip detection results, obtain the carrier phase sequence and pseudorange sequence from the observation sequence.

[0035] like Figure 2 Step S12 shown includes: Step S121: Identify the epochs in the original carrier phase observation sequence where cycle slips occur based on the cycle slip detection results, and use the epochs as segmentation points.

[0036] Specifically, the epoch of the cycle slip is identified based on the cycle slip detection results, and this epoch is set as a segmentation point, indicating that there is a discontinuity between the observations before and after this epoch.

[0037] Step S122: Based on the segmentation points, the original carrier phase observation sequence is segmented into multiple consecutive carrier phase segments, and all the carrier phase segments are combined into a carrier phase sequence.

[0038] Specifically, independent carrier phase sequence segments are established before and after the segmentation point. Data smoothing and interpolation techniques are used to process the carrier phase observations of each continuous segment, making them more continuous and accurate. All processed continuous carrier phase segments are then combined to form a new carrier phase sequence. It is understandable that segmenting the carrier phase sequence allows for better processing of the data within each continuous segment, reducing or eliminating errors caused by cycle slips.

[0039] Step S123: Based on the segmentation points, the original pseudorange observation sequence in the observation sequence is processed into continuous pseudorange segments by synchronous pseudorange segment processing, and all the pseudorange segments are combined into a pseudorange sequence.

[0040] Specifically, at each segment point, the pseudorange observations are recalculated or adjusted to ensure that the pseudorange data and carrier phase data within each segment remain synchronized; techniques such as pseudorange smoothing or filtering are used to reduce the impact of multipath errors on the pseudorange sequence; and all processed pseudorange segments are recombined to form a continuous pseudorange sequence.

[0041] Through the above steps 121 to 123, in the technical solution of the present disclosure, the carrier phase and the pseudo-range need to be processed synchronously because of the direct relationship between them. Through the segmented processing and synchronous adjustment, the multipath error in the pseudo-range can be better processed, and the continuity of the carrier phase observation value is improved. The purpose of the segmented processing and the recombination sequence is to reduce the error propagation and improve the quality of the observation value, so as to achieve higher accuracy in the final positioning or navigation application. In the GNSS real-time positioning or precise point positioning (PPP), these steps can help to monitor and correct the measurement error in real time, and ensure the continuity and accuracy of the positioning.

[0042] In an embodiment, step S12 comprises: performing abnormal identification and elimination on the pseudo-range observation value which is abnormal in the segment, has a sudden deviation, or is inconsistent with the difference result of the carrier phase, based on the segmented result.

[0043] Step S13: obtaining a CMCD sequence based on the carrier phase sequence and the pseudo-range sequence.

[0044] As shown in step S13: Figure 3 Step S131: extracting all carrier phase observation values and pseudo-range observation values at the same time and the same frequency point in the carrier phase sequence and the pseudo-range sequence. Specifically, the carrier phase observation value

[0045] is obtained by formula 1, and the pseudo-range observation value is obtained by formula 2, and formula 1 and formula 2 are as follows: (1) (2) Wherein represents a satellite; represents a frequency point; represents the geometric distance between the satellite and the current GNSS receiver, and the unit is meter; The satellite clock error, the GNSS receiver clock error and the tropospheric delay error have been included in the above formula; represents the ionospheric delay error in the signal propagation process of the satellite at the frequency point, and the unit is meter; represents the wavelength of the signal at the frequency point, and the unit is meter; represents the ionospheric delay error in the signal propagation process of the satellite at the frequency point, and the unit is meter; represents the wavelength of the signal at the frequency point, and the unit is meter; represents the ionospheric delay error in the signal propagation process of the satellite at the frequency point, and the unit is meter; represents the wavelength of the signal at the frequency point, and the unit is meter; represents the ionospheric delay error in the signal propagation process of the satellite at the frequency point, and the unit is meter; represents the wavelength of the signal at the frequency point, and the unit is meter; ​​​carrier phase ambiguity parameter between the current GNSS receiver and the reference station, in cycle; carrier phase multipath error on frequency point , in meter; pseudorange multipath error on frequency point , in meter; denotes the noise term of the carrier phase; denotes the noise term of the pseudorange, and contains the observation noise and other unmodeled error terms.

[0046] Step S132: Obtain the CMC observation value based on the carrier phase observation value and the pseudorange phase observation value at the same time and on the same frequency point.

[0047] Specifically, the CMC observation value is obtained by formula 3 , and formula 3 is as follows: (3) wherein, denotes the time; is the CMC observation value on frequency point at time , in meter; is the pseudorange observation value on frequency point at time , in meter; is the carrier phase observation value on frequency point at time , in meter; is the ionospheric delay error on frequency point at time , in meter; is the pseudorange multipath error on frequency point at time , in meter; is the carrier phase ambiguity parameter on frequency point at time , in cycle; is the carrier phase multipath error on frequency point at time , in meter; is the CMC noise term on frequency point at time .

[0048] Step S133: Group all the CMC observation values to form a CMC sequence.

[0049] Specifically, all the obtained CMC observation values The CMC sequence is combined.

[0050] Step S134: obtaining a CMC D sequence through a difference operation based on the CMC sequence.

[0051] Specifically, since the multipath (effect) error on the carrier phase is much smaller than the multipath error on the pseudo-range, the term in Formula 3 can be ignored, and Formula 4 is obtained as follows: (4) A difference operation is performed on Formula 4, and Formula 5 is obtained, and the CMC D observation value is obtained based on Formula 5. All the CMC D observation values are combined into a CMC D sequence, and Formula 5 is as follows: (5) Wherein, t represents the time interval between the time t and the time t + Δt; represents the ionospheric change rate at the time t, which is generally a very small value; represents the pseudo-range multipath change rate; and represents the observation value noise change term. According to the CMC D observation value, it can be known that, in the case that the carrier phase observation ambiguity parameter of the satellite at the frequency point does not jump, the CMC D observation value can reflect the change state of the pseudo-range multipath error.

[0052]

[0053] Step S14: obtaining a pseudo-range multipath error estimation sequence.

[0054] As shown in FIG. 14, the step S14 includes: Figure 4 Step S141: determining a calculation mode based on the data type of the carrier phase sequence and the data type of the pseudo-range sequence.

[0055] ​​​​​​​​​​​​​​Specifically, the data types include at least one of single-frequency data, dual-frequency data, and non-differential, non-combined data. Single-frequency data refers to pseudorange and carrier phase observations acquired by a GNSS receiver at a single frequency point. Dual-frequency data refers to pseudorange and carrier phase observations acquired simultaneously by a GNSS receiver at two different frequency points. Non-differential, non-combined data refers to data where, during the observation modeling process, no differential (e.g., single-difference, double-difference) or linear combination (e.g., wide-lane combination, ionospheric-free combination) processing is performed on the pseudorange or carrier phase observations; instead, the original observations are directly used to establish a Precise Point Positioning (PPP) model for solution. The calculation involves obtaining pseudorange and carrier phase observations. If the data type of the carrier phase and pseudorange observations at the same time and frequency in the carrier phase and pseudorange sequences is single-frequency data, the calculation method is determined to be interpolation algorithm. If the data type of the carrier phase and pseudorange observations at the same time and frequency in the carrier phase and pseudorange sequences is dual-frequency data, the calculation method is determined to be the first algorithm. If the data type of the carrier phase and pseudorange observations at the same time and frequency in the carrier phase and pseudorange sequences is non-difference and non-combined data, the calculation method is determined to be the second algorithm.

[0056] Step S142: Use the calculation method to determine the pseudorange multipath error estimation sequence corresponding to the carrier phase sequence and the pseudorange sequence.

[0057] Specifically, when the carrier phase observations and pseudorange observations at the same time and frequency are of single-frequency data, the time is interpolated within the semi-celestial grid. The pseudorange multipath error estimate at the corresponding frequency point, i.e., at time t. The upper hemisphere centered on the antenna of the receiving device, intersecting with the plane containing the cutoff elevation angle, forms a hemisphere, which is divided according to a preset gradient. Figure 5 The hemispherical grid shown is used, and then the time is obtained by interpolation algorithm based on the reference error data at the grid nodes. The pseudorange multipath error estimate at the corresponding frequency point is obtained, thus acquiring the carrier phase observation and pseudorange observation values ​​at the same time and frequency point under single-frequency data conditions, and the corresponding pseudorange multipath error estimate. .

[0058] Specifically, when the carrier phase observations and pseudorange observations at the same time and frequency are of dual-frequency data type, the carrier phase observations and pseudorange observations at the current frequency are obtained, along with the associated carrier phase observations and associated pseudorange observations at different frequencies at the same time. Based on the carrier phase observations and pseudorange observations at the current frequency and Equation 6, the pseudorange multipath error estimates corresponding to the carrier phase observations and pseudorange observations at the current frequency are obtained. , based on the carrier phase observation value of the associated frequency point, the pseudo-range observation value of the associated frequency point and formula 7, the pseudo-range multipath error estimation of the carrier phase observation value of the associated frequency point and the pseudo-range observation value of the associated frequency point is obtained , formula 6 and formula 7 are as follows: (6) (7) wherein the frequency point characterizes the current frequency point, and the frequency point characterizes the associated frequency point; and include the carrier phase parameter and the unmodeled noise term , ; , .

[0059] from and , it can be seen that the carrier phase observation value of the satellite at the frequency point , at the time should be consistent with the corresponding value at the time ; if the ambiguity at the frequency point , is not found to have a cycle slip from the time to the time , the time change state of the satellite can be reflected by the right side of formula 6 and formula 7.

[0060] Specifically, formula 6 and formula 7 are the first algorithm.

[0061] Specifically, when the data types of the carrier phase observation value and the pseudo-range observation value at the same time and the same frequency point are non-difference non-combination data, the pseudo-range multipath error estimation of the carrier phase observation value and the pseudo-range observation value at the time at the corresponding frequency point is obtained by the second algorithm as shown in formula 8. (8) wherein and can be obtained based on a non-difference non-combination filter.

[0062] The pseudorange multipath error estimate obtained by the second algorithm is more consistent with the non-differential non-combined filter, and can more accurately reflect the degree of influence of the current signal on the pseudorange multipath effect. This makes the acquisition of the pseudorange multipath error estimate more flexible, no longer dependent on whether the carrier phase observation value and the pseudorange observation value are single-frequency data or dual-frequency data. At the same time, it can also make the acquired pseudorange multipath error estimate have lower signal noise.

[0063] The pseudorange multipath error estimates obtained through the above calculation methods are combined into a pseudorange multipath error estimate sequence.

[0064] Based on the data types of carrier phase sequence and pseudorange sequence, different calculation methods are used to obtain pseudorange multipath error estimation sequences. This enables adaptive processing of different types of observation data and improves the accuracy and robustness of pseudorange multipath error estimation.

[0065] Step S15: Based on the CMCD sequence and the pseudorange multipath error estimation sequence, construct the pseudorange multipath error measurement coefficient and the pseudorange multipath error significant detection quantity.

[0066] like Figure 6 As shown, step S15 includes: Step S151: Obtain the mean and variance of the CMCD observations in the CMCD sequence.

[0067] Specifically, the mean of CMCD observations is calculated recursively using a sliding window method. With variance The width of the sliding window The setting is based on the number of time points in the CMCD observations. For the number of window moments, the preferred method is... When recursively calculating the mean and variance of CMCD observations, the initial values ​​of the mean and variance of CMCD observations are selected based on the accuracy of the pseudorange observations.

[0068] Step S152: Obtain the mean and variance of the pseudorange multipath error estimates in the pseudorange multipath error estimate sequence.

[0069] Specifically, multipath effects not only affect satellite observations but also their signal-to-noise ratio (SNR). When multipath effects occur, the SNR of satellite observations during that time period will change accordingly, thus affecting the calculation time. Time, frequency Mean of the upper pseudorange multipath error estimator sequence At that time, the carrier-to-noise ratio weighted algorithm shown in Equation 9 is used, based on the time... The weights are determined by the reciprocal of the carrier-to-noise ratio (CNR) and the CNR difference at all times, to achieve weighted enhancement for observation times with high CNR, thereby obtaining more robust mean estimation results; in the calculation time... Time, frequency Variance of the upper pseudorange multipath error estimator sequence In this case, the recursive algorithm shown in Equation 10 is used, replacing the traditional root mean square method with a weighted average of the squared residuals for recursive calculation, thereby reducing the impact of abnormal moments or abrupt observations on variance estimation. Equations 9 and 10 are shown below: (9) (10) in, For satellite At frequency ,time The weighting coefficients, It is obtained through Equation 11, which is: (11) in, For satellite At frequency ,time The carrier-to-noise ratio.

[0070] Step S153: Based on the mean and variance of the CMCD observations and the mean and variance of the pseudorange multipath error estimate, obtain the significant detection quantity of the pseudorange multipath error.

[0071] Specifically, the pseudorange multipath error significant detection quantity includes the CMCD significant detection quantity and the multipath error significant detection quantity. The CMCD significant detection quantity is shown in Equation 12, and the multipath error significant detection quantity is shown in Equation 13. Equations 12 and 13 are: (12) in, CMCD observations scale factor ( ).

[0072] (13) in, For pseudorange multipath error estimation scale factor ( ); It is a dynamic value related to the (filtering) solution process, and is related to the accuracy of the pseudorange observations and the convergence state of the corresponding satellite's (filtering) parameters.

[0073] In one embodiment, the scale factor of CMCD observations is obtained based on measured data. Alternatively, the scale factor of CMCD observations can be determined based on a piecewise function of the elevation angle. The piecewise function of the elevation angle is shown in Equation 14, which is: (14) in, For reference satellite elevation angle, it is generally... ; For a moment The actual satellite elevation angle.

[0074] Step S154: Based on the pseudorange multipath error estimation sequence, obtain the pseudorange multipath error measurement coefficient.

[0075] Specifically, the pseudorange multipath error measurement coefficient is obtained through Equation 15. Equation 15 is shown below: (15) in, For the window On frequency The mean; For satellite , The strength of the correlation between time series is indicated by the value; the higher the value, the stronger the correlation between satellites.

[0076] Step S16: When a significant pseudorange multipath effect of a satellite is detected based on the pseudorange multipath error significant detection quantity, the variance of the pseudorange observations in the pseudorange sequence is dynamically adjusted based on the pseudorange multipath error measurement coefficient to suppress the pseudorange multipath error.

[0077] Specifically, if any one or more of the relationships in Equations 12 and 13 are satisfied, then the pseudorange multipath effect of the corresponding satellite at one frequency point is determined to be significant; when a significant pseudorange multipath effect of the satellite at one frequency point is detected, if the pseudorange multipath error measurement coefficient is... If the value is less than the measurement threshold, the corresponding satellite is designated as the first satellite, and the variance of the pseudorange observations of the first satellite is weighted by maximum reduction. When a significant pseudorange multipath effect is detected at a satellite at a specific frequency, if the pseudorange multipath error measurement coefficient is... If the measurement threshold is greater than the threshold, the corresponding satellite is set as a second satellite, and the variance of the pseudo-range observation value of the second satellite is proportionally reduced in weight (the proportionally reduced weight scheme considers multiple factors such as convergence time, signal-to-noise ratio, and the like); if the number of the first satellites under the same time and the same frequency point accounts for more than a preset proportion in the available satellites under the same time, the variance of the pseudo-range observation value of the second satellite is not proportionally reduced in weight, and only the first satellite is maximally reduced in weight. The available satellites include satellites with significant pseudo-range multipath effects and satellites without significant pseudo-range multipath effects.

[0078] The pseudo-range multipath error processing method provided by the application comprises the following steps: receiving an observation sequence sent by a satellite navigation system; performing cycle slip detection on an original carrier phase observation value sequence in the observation sequence and obtaining a cycle slip detection result; obtaining a carrier phase sequence and a pseudo-range sequence from the observation sequence based on the cycle slip detection result; obtaining a CMCD sequence based on the carrier phase sequence and the pseudo-range sequence; obtaining a pseudo-range multipath error estimator sequence; constructing a pseudo-range multipath error measurement coefficient and a pseudo-range multipath error significant detection quantity based on the CMCD sequence and the pseudo-range multipath error estimator sequence; and when the pseudo-range multipath effect of a satellite is detected according to the pseudo-range multipath error significant detection quantity, dynamically adjusting the variance of a pseudo-range observation value in the pseudo-range sequence based on the pseudo-range multipath error measurement coefficient to suppress the pseudo-range multipath error. The application can dynamically adjust the variance of the pseudo-range observation value of the satellite with significant pseudo-range multipath effect based on the algorithm at the software level to suppress the pseudo-range multipath error, can adapt to low-cost chipsets and dynamic positioning requirements, and has a good cost-benefit ratio. The dynamically adjusted variance of the pseudo-range observation value enables the processing of the multipath error to be adjusted in real time according to changes in the observation environment and adapt to dynamic application environments.

[0079] As shown in Figure 7 The application further provides an electronic device, which comprises a processor 70 and a memory 71 storing a computer program; wherein, Figure 7 The processor 70 in the figure is not used to indicate that the number of the processor 70 is one, but is only used to indicate the positional relationship of the processor 70 relative to other devices, and in actual application, the number of the processor 70 can be one or more; similarly, Figure 7 The memory 71 in the figure also has the same meaning, that is, only used to indicate the positional relationship of the memory 71 relative to other devices, and in actual application, the number of the memory 71 can be one or more. When the processor 70 runs the computer program, the pseudo-range multipath error processing method described above is realized.

[0080] The electronic device may also include at least one network interface 72. Various components in the electronic device are coupled together via a bus system 73. It is understood that the bus system 73 is used to implement communication between these components. In addition to a data bus, the bus system 73 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general labeled all buses as Bus System 73.

[0081] The memory 71 can be a volatile memory or a non-volatile memory, and can include both a volatile memory and a non-volatile memory. The non-volatile memory can be a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a Compact Disc Read-Only Memory (CD-ROM). The magnetic surface memory can be a magnetic disk memory or a magnetic tape memory. The volatile memory can be a Random Access Memory (RAM) used as an external cache. By way of example and not limitation, many forms of RAM can be used, such as a Static Random Access Memory (SRAM), a Synchronous Static Random Access Memory (SSRAM), a Dynamic Random Access Memory (DRAM), a Synchronous Dynamic Random Access Memory (SDRAM), a Double Data Rate Synchronous Dynamic Random Access Memory (DDR SDRAM), an Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), a Sync Link Dynamic Random Access Memory (SLDRAM), a Direct Rambus Random Access Memory (DRRAM).The memory 71 described in the embodiments of the present application is intended to include, but not limited to, these and any other suitable types of memory.

[0082] The memory 71 in the embodiments of the present application is used to store various types of data to support the operation of the electronic device. Examples of these data include: any computer programs for operating on the electronic device, such as operating systems and application programs; contact data; phonebook data; messages; pictures; videos; etc. The operating system contains various system programs, such as framework layer, core library layer, driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application programs can contain various application programs, such as media players, browsers, etc., for implementing various application services. Here, the program implementing the pseudo-range multipath error processing method of the embodiments of the present application can be contained in the application programs.

[0083] The present application also provides a storage medium, wherein the storage medium stores computer execution instructions, and the computer execution instructions are used to implement the pseudo-range multipath error processing method of any one of the above when executed by a processor.

[0084] The pseudo-range multipath error processing method, electronic device and storage medium provided by the present application receive an observation sequence sent by a satellite navigation system, perform cycle slip detection on a raw carrier phase observation value sequence in the observation sequence, and obtain a cycle slip detection result. Based on the cycle slip detection result, a carrier phase sequence and a pseudo-range sequence are obtained from the observation sequence. Based on the carrier phase sequence and the pseudo-range sequence, a CMCD sequence is obtained. A pseudo-range multipath error estimator sequence is obtained. Based on the CMCD sequence and the pseudo-range multipath error estimator sequence, a pseudo-range multipath error measurement coefficient and a pseudo-range multipath error significant detection quantity are constructed. When the pseudo-range multipath effect of a satellite is significant according to the pseudo-range multipath error significant detection quantity, the variance of the pseudo-range observation value in the pseudo-range sequence is dynamically adjusted based on the pseudo-range multipath error measurement coefficient, so as to suppress the pseudo-range multipath error. The present application can dynamically adjust the variance of the pseudo-range observation value of the satellite with significant pseudo-range multipath effect based on the algorithm at the software level, so as to suppress the pseudo-range multipath error. The present application can adapt to low-cost chipsets and dynamic positioning requirements, and provides a good cost-benefit ratio.

[0085] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content without departing from the technical solution range of the present application, and the equivalent embodiments with equivalent changes are equivalent. Any simple modification, equivalent change and modification of the above embodiments based on the technical essence of the present application are still within the scope of the technical solution of the present application.

Claims

1. A method for processing pseudorange multipath error, characterized in that, The method includes: Receive the observation sequence sent by the satellite navigation system, perform cycle slip detection on the original carrier phase observation sequence in the observation sequence, and obtain the cycle slip detection results; Based on the cycle slip detection results, the carrier phase sequence and pseudorange sequence are obtained from the observation sequence; Based on the carrier phase sequence and the pseudorange sequence, obtain the CMCD sequence; Obtain the pseudorange multipath error estimate sequence; Based on the CMCD sequence and the pseudorange multipath error estimation sequence, construct the pseudorange multipath error measurement coefficient and the pseudorange multipath error significant detection quantity; Based on the significant detection of pseudorange multipath error, when a significant pseudorange multipath effect of a satellite is detected, the variance of the pseudorange observations in the pseudorange sequence is dynamically adjusted based on the pseudorange multipath error measurement coefficient to suppress pseudorange multipath error.

2. The method for processing pseudorange multipath error as described in claim 1, characterized in that, Based on the cycle slip detection results, the steps of obtaining the carrier phase sequence and pseudorange sequence from the observation sequence include: Based on the cycle slip detection results, the epochs in which cycle slips occur in the original carrier phase observation sequence are identified, and these epochs are used as segmentation points. Based on the segmentation points, the original carrier phase observation sequence is divided into multiple consecutive carrier phase segments, and all the carrier phase segments are combined into a carrier phase sequence. Based on the segmentation points, the original pseudorange observation sequence in the observation sequence is processed into continuous pseudorange segments through synchronous pseudorange segmentation, and all the pseudorange segments are combined into a pseudorange sequence.

3. The method for processing pseudorange multipath error as described in claim 1, characterized in that, The step of obtaining the CMCD sequence based on the carrier phase sequence and the pseudorange sequence includes: Extract all carrier phase observations and pseudorange observations at the same time and frequency from the carrier phase sequence and the pseudorange sequence; CMC observations are obtained based on carrier phase observations and pseudorange phase observations at the same time and frequency. All CMC observations are combined into a CMC sequence; The CMCD sequence is obtained by differential operation based on the CMC sequence.

4. The method for processing pseudorange multipath error as described in claim 1, characterized in that, The process of obtaining the pseudorange multipath error estimate sequence includes: The calculation method is determined based on the data type of the carrier phase sequence and the data type of the pseudorange sequence; The pseudorange multipath error estimation sequence corresponding to the carrier phase sequence and the pseudorange sequence is determined using the calculation method described above.

5. The method for processing pseudorange multipath error as described in claim 4, characterized in that, The data type includes at least one of single-frequency data, dual-frequency data, and non-differential non-combined data. Based on the data type of the carrier phase sequence and the data type of the pseudorange sequence, the calculation method is determined, including: If the carrier phase observation value and pseudorange observation value at the same time and frequency point in the carrier phase sequence and the pseudorange sequence are of single-frequency data, then the calculation method is determined to be an interpolation algorithm. If the carrier phase observation value and pseudorange observation value at the same time and frequency point in the carrier phase sequence and the pseudorange sequence are of dual-frequency data, then the calculation method is determined to be the first algorithm. If the data type of the carrier phase observation value and the pseudorange observation value at the same time and frequency point in the carrier phase sequence and the pseudorange sequence is non-difference non-combined data, then the calculation method is determined to be the second algorithm.

6. The method for processing pseudorange multipath error as described in claim 1, characterized in that, The steps for constructing the pseudorange multipath error measurement coefficient and the pseudorange multipath error significant detection quantity based on the CMCD sequence and the pseudorange multipath error estimation sequence include: Obtain the mean and variance of the CMCD observations in the CMCD sequence; Obtain the mean and variance of the pseudorange multipath error estimates in the pseudorange multipath error estimate sequence; Based on the mean and variance of the CMCD observations, and the mean and variance of the pseudorange multipath error estimate, the significant detection quantity of the pseudorange multipath error is obtained. Based on the pseudorange multipath error estimation sequence, the pseudorange multipath error measurement coefficient is obtained.

7. The method for processing pseudorange multipath error as described in claim 6, characterized in that, The pseudorange multipath error significant detection quantity includes CMCD significant detection quantity and multipath error significant detection quantity; The steps for constructing the pseudorange multipath error measurement coefficient and the pseudorange multipath error significant detection quantity based on the CMCD sequence and the pseudorange multipath error estimation sequence include: Based on the mean and variance of the CMCD observations, the CMCD significant detection quantity is obtained; Based on the mean and variance of the pseudorange multipath error estimate, the significant detection quantity of the multipath error is obtained.

8. The method for processing pseudorange multipath error as described in claim 7, characterized in that, The step of dynamically adjusting the variance of pseudorange observations in the pseudorange sequence to suppress pseudorange multipath error when a significant pseudorange multipath effect of a satellite is detected based on the pseudorange multipath error measurement coefficient includes: Based on the CMCD significant detection quantity and the multipath error significant detection quantity, detect whether the pseudorange multipath effect of the satellite is significant at each frequency point; When a significant pseudorange multipath effect is detected when a satellite is at a certain frequency, if the pseudorange multipath error measurement coefficient is less than the measurement threshold, the corresponding satellite is set as the first satellite, and the variance of the pseudorange observation value of the first satellite is reduced by the maximum weight. When a significant pseudorange multipath effect is detected when a satellite is at a certain frequency, if the pseudorange multipath error measurement coefficient is greater than the measurement threshold, the corresponding satellite is set as the second satellite, and the variance of the pseudorange observations of the second satellite is proportionally reduced in weight.

9. The method for processing pseudorange multipath error as described in claim 8, characterized in that, The method includes: If the number of the first satellites at the same time and frequency exceeds the pre-defined proportion of available satellites at the same time, then the variance of the pseudorange observations of the second satellite will not be proportionally reduced.

10. An electronic device, characterized in that, include: A memory for storing instructions executed by one or more processors of an electronic device, and a processor, one of the processors of the electronic device, for executing the pseudorange multipath error processing method according to any one of claims 1 to 9.

11. A storage medium, characterized in that, The storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the pseudorange multipath error processing method as described in any one of claims 1 to 9.

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