High-precision positioning method and system for single-frequency and double-frequency hybrid GNSS smart phone

Abstract

The invention provides a high-precision positioning method and system for a single-frequency and double-frequency hybrid GNSS smart phone. The method comprises the following steps: obtaining an original GNSS observation value through an API of the smart phone; performing data preprocessing based on the original GNSS observation value to obtain cycle slip detection quantity; performing single-double-frequency pseudo-range smoothing based on the cycle slip detection quantity to obtain a smoothed pseudo-range value; and based on the pseudo-range value, carrying out single-frequency and double-frequency hybrid positioning of the smart phone. According to the method adopted by the invention, the GNSS data quality condition of the smart phone is more fully considered, and the method has relatively high applicability; high-precision positioning is realized by adopting pure GNSS data, so that the convenience of positioning of a smart phone is facilitated; a single-point positioning method is adopted, reference station information is not added, and the degree of freedom and real-time performance are higher; and the positioning convergence time and the positioning precision are effectively shortened and improved by reducing the pseudo-range noise.

Description

Technical Field

[0001] The present invention belongs to the field of GNSS data processing and high-precision navigation and positioning, and particularly relates to a high-precision positioning method and system for a single-dual frequency hybrid GNSS smart phone. Background Art

[0002] With the popularization of smart phones, their applications in the fields of navigation, location-based services, etc. are becoming more and more extensive. However, there are still some problems with the GNSS positioning accuracy of current smart phones. Traditional GNSS positioning of smart phones mainly relies on single-frequency signals, such as the L1 frequency band. Since single-frequency signals are easily affected by ionospheric delay, multipath effects, etc., their positioning accuracy is usually low and it is difficult to meet the requirements of high-precision applications. With the development of dual-frequency GNSS technology, smart phones have begun to support dual-frequency signals (such as L1 and L5 frequency bands). Dual-frequency signals can effectively reduce the influence of ionospheric delay, thereby improving positioning accuracy. However, some GNSS data lacks dual-frequency signals, resulting in a low redundancy of dual-frequency signals, and the signal stability is poor in complex environments (such as urban canyons, indoors, etc.), resulting in insufficient reliability of positioning results. Limited by the low-cost chips and linearly polarized antennas of smart phones, the GNSS data quality of smart phones is poor and the observation noise is obvious, seriously affecting the accuracy of positioning.

[0003] In response to these problems, researchers have proposed various improvement methods such as a hybrid single-frequency and dual-frequency four-constellation precise point positioning (MSDQ-PPP) model, using dual-frequency data for GNSS data positioning, constructing a joint random model of signal-to-noise ratio and elevation angle, etc. to improve positioning accuracy. To a certain extent, the positioning accuracy has been improved, but the data quality problem of smart phones has not been fundamentally improved.

[0004] In summary, the existing GNSS positioning technology for smart phones still has problems of insufficient positioning accuracy and stability in the case of single-dual frequency mixing, and needs to be further optimized and improved to meet the requirements of high-precision positioning. Summary of the Invention

[0005] To solve the problems existing in the prior art, the present invention provides a high-precision positioning method and system for a single-dual frequency hybrid GNSS smart phone, aiming to solve the problem of large pseudo-range observation noise. By setting a threshold for ionospheric delay accumulation, the mode of Doppler-smoothed pseudo-range and carrier-phase-observation-value-smoothed pseudo-range is switched in real time and adaptively, so as to achieve noise reduction processing of the pseudo-range. To solve the problems existing in the mixing of single-dual frequency data of smart phones, the jointly processed single-dual frequency hybrid data after data preprocessing and pseudo-range smoothing is used for GNSS positioning calculation, so as to obtain a real-time high-precision positioning result of the smart phone.

[0006] To achieve the above object, the present invention provides the following solution: A high-precision positioning method for a single and dual-frequency hybrid GNSS smart phone, comprising:

[0007] S1. Obtain the original GNSS observation values through the smart phone API;

[0008] S2. Perform data preprocessing based on the original GNSS observation values to obtain cycle slip detection quantities;

[0009] S3. Perform single and dual-frequency pseudorange smoothing based on the cycle slip detection quantities to obtain smoothed pseudorange values;

[0010] S4. Perform single and dual-frequency hybrid positioning of the smart phone based on the pseudorange values.

[0011] Preferably, the S2 performs data preprocessing based on the original GNSS observation values to obtain cycle slip detection quantities, including:

[0012] Calculate the pseudorange observation noise and carrier phase observation noise in the original GNSS observation values by using the high-order difference method;

[0013] Use the method of polynomial fitting to preliminarily test for cycle slips of the carrier phase values of the epochs in the original GNSS observation values, and use the TurboEdit combination method to detect cycle slips again for the observed dual-frequency data to obtain the cycle slip detection quantities.

[0014] Preferably, the calculating the pseudorange observation noise and carrier phase observation noise in the original GNSS observation values by using the high-order difference method includes:

[0015]

[0016] Wherein, σ P represents the pseudorange observation noise, N P represents the number of triple differences of the pseudorange observation values of the satellite observed by the receiver at a certain frequency point in adjacent epochs, and ΔΔΔP represents the triple difference of the pseudorange observation values in adjacent epochs;

[0017]

[0018] Wherein, represents the carrier phase observation noise, represents the number of triple differences of the carrier phase observation values of the satellite observed by the receiver at a certain frequency point in adjacent epochs, represents the triple difference of the carrier phase observation values in adjacent epochs.

[0019] Preferably, the method of polynomial fitting is used to preliminarily detect cycle slips in the carrier phase values of the original GNSS observations, and the TurboEdit combination method is used to detect cycle slips again for the observed dual-frequency data to obtain the cycle slip detection quantity, including:

[0020]

[0021] Among them, represents the carrier phase observation value, a0, a1, a2, a n are the coefficients of the polynomial, and t is the observation epoch corresponding to the fitted carrier phase value;

[0022]

[0023] Among them, N WL represents the wide-lane integer ambiguity, L WL represents the carrier phase wide-lane combination value, λ WL represents the wide-lane wavelength, respectively represent the carrier phase observation values at L1 and L5 frequencies, f1 and f5 respectively represent the frequencies of L1 and L5 frequency bands, P1 and P5 respectively represent the pseudorange observation values at L1 and L5 frequencies, represents the GF construction quantity, N1 and N5 respectively represent the integer ambiguities corresponding to the carrier phase observations in the L1 and L5 frequency bands, λ1 and λ5 respectively represent the wavelengths corresponding to the carrier phase observations in the L1 and L5 frequency bands, Δ I represents the ionospheric delay residual;

[0024]

[0025] Among them, CS represents the cycle slip detection quantity, represents the wide-lane ambiguity, represents the carrier phase observation noise, ΔN1 and ΔN5 respectively represent the differences between adjacent epochs of the carrier phase ambiguities at L1 and L5 frequencies, Δ I represents the ionospheric delay residual, t i represents the i-th observation epoch in the observation time series corresponding to the observation value, t i-1 represents the (i - 1)-th observation epoch in the observation time series corresponding to the observation value.

[0026] Preferably, the S3 performs pseudorange noise processing based on the cycle slip detection quantity to obtain the smoothed pseudorange value, including:

[0027] S31. Obtain the original GNSS observations after data preprocessing;

[0028] S32. Detect whether cycle slips occur in the carrier phase of epochs in the original GNSS observations after data preprocessing. If cycle slips are detected, smooth the pseudorange by means of Doppler-smoothed pseudorange. If no cycle slips are detected, determine whether the original GNSS observations are dual-frequency data;

[0029] S33. Perform ionosphere-free combination processing on the dual-frequency data to obtain combined data, and correct the ionospheric error of the single-frequency data using the ionospheric model;

[0030] S34. Apply the adaptive Hatch filtering algorithm to the combined data and the single-frequency data after correcting the ionospheric error, and check whether Δ exceeds the limit according to the three-fold mean error principle. If it exceeds the limit, smooth the pseudorange by means of Doppler-smoothed pseudorange. If it does not exceed the limit, directly end the pseudorange smoothing. Among them, the test quantity represents the smoothed pseudorange value, and P represents the pseudorange observation value;

[0031] S35. Apply the adaptive Hatch filtering algorithm to the pseudorange after Doppler-smoothed pseudorange, and check whether Δ exceeds the limit in the same way as in S34. If it exceeds the limit, assign the original pseudorange value to the smoothed pseudorange value, and end the pseudorange smoothing. If it does not exceed the limit, directly end the pseudorange smoothing;

[0032] S36. Repeat steps S31 - S35 until the observation ends to obtain the smoothed pseudorange value.

[0033] Preferably, the method of smoothing the pseudorange by means of Doppler-smoothed pseudorange includes:

[0034]

[0035] Among them, represents the carrier phase observation value, represents the derivative of the carrier phase with respect to time, t i represents the i-th observation epoch in the observation time series corresponding to the observation value, t i-1 represents the (i - 1)-th observation epoch in the observation time series corresponding to the observation value, D represents the Doppler observation value, and Δt represents the time interval between the observation epoch t i and the observation epoch t i-1 ;

[0036] The method of applying the adaptive Hatch filtering algorithm includes:

[0037]

[0038] Among them, M represents the smoothing time factor.

[0039] Preferably, the step S33 of performing ionosphere-free combination processing on the dual-frequency data to obtain combined data includes:

[0040]

[0041] Among them, P IF represents the ionosphere-free combined pseudorange value; represents the ionosphere-free combined carrier phase value;

[0042] The smoothed ionosphere-free combined pseudorange value can be expressed as:

[0043]

[0044] Among them, represents the smoothed ionosphere-free combined pseudorange value.

[0045] Preferably, the S4 performs single-frequency and dual-frequency hybrid positioning of the smart phone based on the pseudorange value, including:

[0046]

[0047] X = [Δx Δy Δz cdt cdt IF λN λ IF N IF T T IF ε ε IF

[0048] Among them, l, m, n represent the position parameter coefficients; (X s , Y s , Z s ) is the satellite coordinate, (X s , Y s , Z s ) is the satellite coordinate, (X r , Y r , Z r ) is the receiver coordinate, ρ represents the distance from the receiver to the satellite, μ represents the mapping function of the tropospheric delay, Δx represents the change in the x-axis of the receiver coordinate, Δy represents the change in the y-axis of the receiver coordinate, Δz represents the change in the z-axis of the receiver coordinate, λ represents the wavelength of the carrier phase, λ IF represents the wavelength of the ionosphere-free combined carrier phase value, N represents the integer ambiguity of the carrier phase, N IF represents the integer ambiguity of the ionosphere-free combined carrier phase value, dt represents the clock error, T represents the tropospheric delay, ε represents other noises, dt IF represents the clock error included in the ionosphere-free combined value, T IF represents the tropospheric delay included in the ionosphere-free combined value, ε IF represents the other noises included in the ionosphere-free combined value. ​

[0049] The present invention also provides a high-precision positioning system for a single- and dual-frequency hybrid GNSS smartphone, which is applied to the high-precision positioning method of the aforementioned single- and dual-frequency hybrid GNSS smartphone. The system includes: a data acquisition module, a preprocessing module, a pseudorange smoothing module, and a hybrid positioning module;

[0050] The data acquisition module is used to obtain original GNSS observations through the smartphone API;

[0051] The preprocessing module is used to perform data preprocessing based on the original GNSS observations to obtain cycle slip detection quantities;

[0052] The pseudorange smoothing module is used to perform single- and dual-frequency pseudorange smoothing based on the cycle slip detection quantities to obtain smoothed pseudorange values;

[0053] The hybrid positioning module is used to perform single- and dual-frequency hybrid positioning of the smartphone based on the pseudorange values.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] Compared with the existing GNSS positioning methods for smartphones, the method adopted by the present invention takes more fully into account the GNSS data quality of smartphones, has high applicability; realizes high-precision positioning using pure GNSS data, which is more conducive to the convenience of smartphone positioning; adopts a single-point positioning method without adding reference station information, has higher freedom and real-time performance; effectively shortens the positioning convergence time and positioning accuracy by reducing pseudorange noise.

[0056] The positioning results of the smartphone based on the invention in the urban canyon test show that: compared with the existing traditional positioning methods, the positioning accuracies in the E, N, and U directions in the urban canyon positioning environment are improved by 23.14%, 28.69%, and 16.91% respectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1 Schematic diagram of the high-precision positioning method for a single- and dual-frequency hybrid GNSS smartphone in Embodiment 1 of the present invention;

[0059] Figure 2 Flowchart of pseudorange smoothing for single- and dual-frequency hybrid data in Embodiment 1 of the present invention;

[0060] Figure 3 This is the positioning error time series graph of Embodiment 1 of the present invention. Specific Embodiment

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0062] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0063] Embodiment 1

[0064] As Figure 1 shown, the present invention provides a high-precision positioning method for a single and dual-frequency hybrid GNSS smart phone, including:

[0065] S1. Obtain the original GNSS observation values through the smart phone API;

[0066] S2. Perform data preprocessing based on the original GNSS observation values to obtain cycle slip detection quantities;

[0067] S3. Perform single and dual-frequency pseudorange smoothing based on the cycle slip detection quantities to obtain the smoothed pseudorange values;

[0068] S4. Perform single and dual-frequency hybrid positioning of the smart phone based on the pseudorange values.

[0069] The data processing modules involved in the smart phone include: a central processing unit (CPU) for processing data from each module and performing data calculations; a GPU for visualizing the positioning results; a GNSS module for obtaining GNSS original observation data; a digital signal processor (DSP) for extracting useful information from the GNSS module; a 5G transmission module for obtaining external data required for mobile phone positioning, such as key data like precise ephemeris, clock offset, and correction models.

[0070] Furthermore, data preprocessing is performed on the original GNSS observations, including: detecting gross errors in the observations through the three-times mean error method; detecting cycle slips in dual-frequency data through the TurboEdit method and detecting cycle slips in single-frequency data through polynomial fitting; obtaining the satellite position and satellite clock offset corresponding to the observation epoch by interpolating precise ephemerides, that is, the satellite position and satellite clock offset are obtained by tenth-order Lagrange interpolation through the 5G transmission module of the smartphone and imported into the ultra-rapid precise ephemerides of the Wuhan University IGS Center, and the satellite position and satellite clock offset are used to calculate the position of the receiver; performing model corrections on the equivalent range error during the propagation of satellite signals, and the corrected equivalent range errors include: ionospheric delay, tropospheric delay, multipath effect, relativistic effect, and earth rotation.

[0071] The total electron content STEC that the satellite signal passes through the ionosphere can be obtained from the electron density in the propagation path of the satellite signal:

[0072] STEC = ∫N e (R)dR

[0073] where: N e represents the electron concentration in the signal propagation path, and R represents the signal propagation path.

[0074] The carrier phase measurement and the pseudorange measurement are affected in the opposite way by the ionospheric delay. The ionospheric delay can be expressed as:

[0075]

[0076] where: I ρ 、I φ represent the ionospheric delays of the pseudorange measurement and the carrier phase measurement respectively, with the unit of m; f represents the frequency corresponding to the measured satellite signal.

[0077] The tropospheric delay consists of dry and wet components, where the dry component accounts for about 90% and the wet component accounts for about 10%. During GNSS positioning, the dry component delay is usually accurately corrected through the Saastamoinen model, while the wet component delay is estimated together with other parameters to be estimated using a piecewise linear or random walk estimation strategy. The calculation formula of the Saastamoinen model is as follows:

[0078]

[0079] In the formula: p represents the atmospheric pressure, f(B,H) represents a function of latitude and elevation, B represents latitude, H represents elevation, tpt represents the absolute temperature, e represents the water vapor pressure, T z,dry represents the dry component of the tropospheric delay, and T z,wet represents the wet component of the tropospheric delay.

[0080] The multipath effect is calculated by combining the pseudorange observation equation and the carrier phase observation equation:

[0081]

[0082] Among them, MP1 and MP5 respectively represent the calculated quantities containing multipath error and integer ambiguity information in the L1 and L5 frequency bands, P1 and P5 respectively represent the pseudorange observations at the L1 and L5 frequencies, and f1 and f5 respectively represent the frequencies of the L1 and L5 frequency bands. respectively represent the carrier phase observations at the L1 and L5 frequencies.

[0083] The general relativity effect of the signal transmission from the satellite to the receiver can be represented by the Holdridge (1967) model:

[0084]

[0085] Among them, Δρ rel represents the error caused by the gravitational time delay effect, ρ s , ρ r represent the distances from the satellite s and the receiver r to the center of the earth, GM represents the gravitational constant of the earth, and c represents the speed of light. represents the distance from the receiver r to the satellite s.

[0086] The influence of the earth's rotation on ranging can be expressed as:

[0087]

[0088] Among them, Δρ represents the error caused by the earth's rotation. represents the vector from the center of the earth to the receiver r. represents the vector from the center of the earth to the satellite s. represents the velocity vector of the receiver r relative to the earth's surface.

[0089] The pseudorange observation noise and carrier phase observation noise in the original GNSS observations are calculated by the high-order difference method. The pseudorange observation noise is:

[0090]

[0091] Among them, σ P represents the pseudorange observation noise; N P represents the number of triple differences of the pseudorange observations of the satellite observed by the receiver at adjacent epochs at a certain frequency; ΔP represents the first difference between the pseudorange observations of the observed satellite and the reference satellite at the same epoch; ΔΔP represents the second difference of the pseudorange observations at adjacent epochs, and ΔΔΔP represents the third difference of the pseudorange observations at adjacent epochs. P s represents the pseudorange observation corresponding to the satellite s, and P srIndicates the pseudorange observation value corresponding to the reference satellite.

[0092] The carrier phase observation noise is:

[0093]

[0094] Wherein, Indicates the carrier phase observation noise; Indicates the number of triple differences of the carrier phase observation values of the satellite observed by the receiver at a certain frequency point in adjacent epochs; Indicates the first difference between the carrier phase observation value of the observed satellite and the carrier phase observation value of the reference satellite at the same epoch; Indicates the second difference of the carrier phase observation values in adjacent epochs, Indicates the third difference of the carrier phase observation values in adjacent epochs, Indicates the carrier phase observation value corresponding to satellite s, Indicates the carrier phase observation value corresponding to the reference satellite.

[0095] Regarding those greater than 3σ in the high-order difference time series P as gross errors.

[0096] Then perform cycle slip detection. The carrier phase values of all epochs in the original GNSS observations are preliminarily tested for cycle slips by polynomial fitting:

[0097]

[0098] Wherein, a0, a1, a2, a n are the coefficients of the polynomial; t is the observation epoch corresponding to the fitted carrier phase value; Indicates the carrier phase observation value.

[0099] For the observed dual-frequency data, the TurboEdit combination method is used to detect cycle slips again. This method combines the MW combination and the GF combination to jointly detect cycle slips. The MW combination and the GF combination are constructed as follows:

[0100]

[0101] Wherein, N WL Indicates the wide-lane integer ambiguity, L WL Indicates the carrier phase wide-lane combined value, λ WL Indicates the wide-lane wavelength, and λ1, λ5 respectively indicate the wavelengths corresponding to the carrier phase observation values in the L1 and L5 frequency bands; Respectively indicate the carrier phase observation values at the L1 and L5 frequencies, f1, f5 respectively indicate the frequencies of the L1 and L5 frequency bands, and P1, P5 respectively indicate the pseudorange observation values at the L1 and L5 frequencies, Denote the GF construction quantity, N1 and N5 respectively denote the integer ambiguities corresponding to the carrier phase observations in the L1 and L5 frequency bands, and Δ I Denote the ionospheric delay residuals;

[0102] Construct the cycle slip detection quantity CS:

[0103]

[0104] where CS denotes the cycle slip detection quantity, Denote the wide-lane ambiguity; Denote the carrier phase observation noise; ΔN1 and ΔN5 respectively denote the differences between adjacent epochs of the carrier phase ambiguities at the L1 and L5 frequencies; Δ I Denote the ionospheric delay residuals; t i Denote the i-th observation epoch in the observation time series corresponding to the observation value, and t i-1 Denote the (i - 1)-th observation epoch in the observation time series corresponding to the observation value.

[0105] The pseudorange observation noise of smartphones is relatively large. To obtain a higher-precision spatial position, it is necessary to solve the problem of pseudorange observation noise. Utilizing the carrier phase and Doppler values can effectively reduce the pseudorange observation noise.

[0106] As Figure 2 shown, based on the cycle slip detection quantity, perform pseudorange observation noise processing to obtain the smoothed pseudorange value. The specific process is as follows:

[0107] S31. Obtain the original GNSS observation values after data preprocessing;

[0108] S32. Detect whether there is a cycle slip in the carrier phase of the epochs in the original GNSS observation values after data preprocessing. If a cycle slip is detected, smooth the pseudorange by using the Doppler-smoothed pseudorange method. If no cycle slip is detected, determine whether the original GNSS observation values are dual-frequency data;

[0109] S33. Perform ionosphere-free combination processing on the dual-frequency data to obtain combined data, and correct the ionospheric error for the single-frequency data by using the ionospheric model;

[0110] S34. Apply the adaptive Hatch filtering algorithm to the combined data and the single-frequency data after correcting the ionospheric error, and check whether Δ exceeds the limit according to the three-fold mean error principle; if it exceeds the limit, smooth the pseudorange by using the Doppler-smoothed pseudorange method. If it does not exceed the limit, directly end the pseudorange smoothing; where the test quantity Denote the smoothed pseudorange value, and P denotes the pseudorange observation value.

[0111] S35. For the pseudorange after Doppler smoothing, use the adaptive Hatch filtering algorithm to check whether Δ exceeds the limit in the same way as in S34. If it exceeds the limit, assign the original pseudorange value to the smoothed pseudorange value, and the pseudorange smoothing ends. If it does not exceed the limit, the pseudorange smoothing ends directly;

[0112] S36. Repeat steps S31 - S35 until the observation ends to obtain the smoothed pseudorange value.

[0113] Among them, the Doppler observation value in the smartphone is obtained by taking the derivative of the pseudorange with respect to time. When the influence of errors is not considered, taking the derivative of the carrier phases with respect to time can obtain:

[0114]

[0115] Among them, represents the carrier phase observation value, represents the derivative of the carrier phase with respect to time, t i represents the i-th observation epoch in the observation time series corresponding to the observation value, t i-1 represents the (i - 1)-th observation epoch in the observation time series corresponding to the observation value, D represents the Doppler observation value, and Δt represents the time interval between the observation epoch t i and the observation epoch t i-1 .

[0116] The pseudorange smoothing based on the Hatch filter is expressed as:

[0117]

[0118] Among them, M represents the smoothing time factor.

[0119] For dual-frequency data, perform ionosphere-free combination processing to eliminate the influence of ionospheric errors and obtain the combined data:

[0120]

[0121] Among them, P IF represents the ionosphere-free combined pseudorange value; represents the ionosphere-free combined carrier phase value.

[0122] The smoothed ionosphere-free combined pseudorange value can be expressed as:

[0123]

[0124] Among them, represents the smoothed ionosphere-free combined pseudorange value.

[0125] Use the combined value after pseudorange smoothing for the solution of the smartphone positioning model. The GNSS linearization model is as follows:

[0126]

[0127] X = [Δx Δy Δz cdt cdt IF λN λ IF N IF T T IF ε ε IF

[0128] wherein, l, m, n represent position parameter coefficients, (X s , Y s , Z s ) is the satellite coordinate, (X r , Y r , Z r ) is the receiver coordinate, ρ represents the distance from the receiver to the satellite; μ represents the mapping function of tropospheric delay, Δx represents the change in the x-axis of the receiver coordinate; Δy represents the change in the y-axis of the receiver coordinate; Δz represents the change in the z-axis of the receiver coordinate; λ represents the wavelength of the carrier phase; λ IF represents the wavelength of the carrier phase value of the ionosphere-free combination; N represents the integer ambiguity of the carrier phase; N IF represents the integer ambiguity of the carrier phase value of the ionosphere-free combination; dt represents the clock error; T represents the tropospheric delay; ε represents other noises; dt IF represents the clock error included in the ionosphere-free combination value; T IF represents the tropospheric delay included in the ionosphere-free combination value; ε IF represents other noises included in the ionosphere-free combination value.

[0129] The present invention constructs a multi-frequency hybrid positioning model with smoothed single-frequency and dual-frequency data. In the hybrid positioning model, both the higher-precision dual-frequency data and the single-frequency data are utilized. The single-frequency data is used to increase the redundancy of GNSS observation data during parameter estimation, and the positioning accuracy can be effectively improved on the basis of existing positioning methods. It solves the problems of low positioning accuracy of single-frequency GNSS and insufficient number of satellites in the harsh environment of smartphones in dual-frequency GNSS positioning in the prior art.

[0130] As Figure 3 shown, dynamic tests are carried out on smartphones in an urban canyon environment. The experimental results show that the positioning errors Std in the E, N, and U directions are reduced from 4.60m, 4.32m, and 17.98m before smoothing to 3.74m, 3.36m, and 15.38m respectively, and the positioning accuracies are improved by 23.14%, 28.69%, and 16.91% respectively.

[0131] ​In summary, the method adopted by the present invention takes into account the GNSS data quality of smartphones more fully, has high applicability; uses pure GNSS data to achieve high-precision positioning, which is more conducive to the convenience of smartphone positioning; adopts a single-point positioning method without adding reference station information, and has higher degrees of freedom and real-time performance; by reducing the pseudorange noise, the positioning convergence time and positioning accuracy are effectively shortened.

[0132] Embodiment 2

[0133] The present invention also provides a high-precision positioning system for a single-dual frequency hybrid GNSS smartphone, which is applied to the high-precision positioning method for a single-dual frequency hybrid GNSS smartphone in Embodiment 1. The system includes: a data acquisition module, a preprocessing module, a pseudorange smoothing module, and a hybrid positioning module;

[0134] The data acquisition module is used to obtain the original GNSS observations through the smartphone API;

[0135] The preprocessing module is used to perform data preprocessing based on the original GNSS observations to obtain cycle slip detection quantities;

[0136] The pseudorange smoothing module is used to perform single-dual frequency pseudorange smoothing based on the cycle slip detection quantities to obtain the smoothed pseudorange values;

[0137] The hybrid positioning module is used to perform single-dual frequency hybrid positioning of the smartphone based on the pseudorange values.

[0138] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A high-precision positioning method for a single and dual-frequency hybrid GNSS smart phone, characterized in that, Including: S1. Obtain the original GNSS observations through the smartphone API; S2. Perform data preprocessing based on the original GNSS observations to obtain cycle slip detection quantities; S3. Perform single-frequency and dual-frequency pseudorange smoothing based on the cycle slip detection quantities to obtain smoothed pseudorange values; S4. Perform single-frequency and dual-frequency hybrid positioning of the smartphone based on the pseudorange values.

2. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 1, characterized in that, The S2 performs data preprocessing based on the original GNSS observations to obtain cycle slip detection quantities, including: Calculating the pseudorange observation noise and carrier phase observation noise in the original GNSS observations by using the high-order difference method; Using the method of polynomial fitting to preliminarily detect cycle slips for the carrier phase values of epochs in the original GNSS observations, and using the TurboEdit combination method to detect cycle slips again for the observed dual-frequency data to obtain the cycle slip detection quantities.

3. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 2, wherein, The calculating the pseudorange observation noise and carrier phase observation noise in the original GNSS observations by using the high-order difference method includes: Among them, σ P represents the pseudorange observation noise, N P represents the number of triple differences of the pseudorange observation values of the satellite observed by the receiver at a certain frequency point in adjacent epochs, and ΔΔΔP represents the triple difference of the pseudorange observation values in adjacent epochs; Among them, represents the carrier phase observation noise, represents the number of triple differences of the carrier phase observation values of the satellite observed by the receiver at a certain frequency point in adjacent epochs, represents the triple difference of the carrier phase observation values in adjacent epochs.

4. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 3, characterized in that, The using the method of polynomial fitting to preliminarily detect cycle slips for the carrier phase values in the original GNSS observations, and using the TurboEdit combination method to detect cycle slips again for the observed dual-frequency data to obtain the cycle slip detection quantities includes: Among them, represents the carrier phase observation value, and a0, a1, a2, a n are the coefficients of the polynomial, and t is the observation epoch corresponding to the fitted carrier phase value; Among them, N WL represents the wide-lane integer ambiguity, L WL represents the carrier-phase wide-lane combination value, λ WL represents the wide-lane wavelength, respectively represent the carrier-phase observations at L1 and L5 frequencies, f1 and f5 respectively represent the frequencies of the L1 and L5 bands, and P1 and P5 respectively represent the pseudorange observations at L1 and L5 frequencies. represents the GF construction quantity, N1 and N5 respectively represent the integer ambiguities corresponding to the carrier-phase observations in the L1 and L5 bands, λ1 and λ5 respectively represent the wavelengths corresponding to the carrier-phase observations in the L1 and L5 bands, and Δ I represents the ionospheric delay residual; Among them, CS represents the cycle slip detection quantity, represents the wide-lane ambiguity, represents the carrier phase observation noise, ΔN1 and ΔN5 respectively represent the differences between adjacent epochs of the carrier phase ambiguity at L1 and L5 frequencies, Δ I represents the ionospheric delay residual, t i represents the i-th observation epoch in the observation time series corresponding to the observation value, t i-1 represents the (i - 1)-th observation epoch in the observation time series corresponding to the observation value.

5. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 4, characterized in that, The S3 performs pseudorange noise processing based on the cycle slip detection quantities to obtain smoothed pseudorange values, including: S31. Obtain the original GNSS observations after data preprocessing; S32. Detect whether cycle slips occur in the carrier phase of epochs in the original GNSS observations after data preprocessing. If cycle slips are detected, smooth the pseudorange in the way of Doppler-smoothed pseudorange. If no cycle slips are detected, determine whether the original GNSS observations are dual-frequency data; S33. Perform ionosphere-free combination processing on the dual-frequency data to obtain combined data, and correct the ionospheric error for the single-frequency data by using the ionospheric model; S34. Apply the adaptive Hatch filtering algorithm to the combined data and the single-frequency data after correcting the ionospheric error, and check whether Δ exceeds the limit according to the three-times mean error principle; if it exceeds the limit, smooth the pseudorange in the way of Doppler-smoothed pseudorange, if it does not exceed the limit, directly end the pseudorange smoothing; among them, the test quantity represents the smoothed pseudorange value, and P represents the pseudorange observation value; S35. For the pseudorange after Doppler-smoothed pseudorange, use the adaptive Hatch filtering algorithm to check whether Δ exceeds the limit together with S34. If it exceeds the limit, assign the original pseudorange value to the smoothed pseudorange value, and the pseudorange smoothing ends. If it does not exceed the limit, directly end the pseudorange smoothing; S36. Repeat steps S31 - S35 until the observation ends to obtain the smoothed pseudorange values.

6. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 5, characterized in that, The smoothing the pseudorange in the way of Doppler-smoothed pseudorange includes: Among them, represents the carrier phase observation value, represents the derivative of the carrier phase with respect to time, t i represents the i-th observation epoch in the observation time series corresponding to the observation value, t i-1 represents the (i - 1)-th observation epoch in the observation time series corresponding to the observation value, D represents the Doppler observation value, and Δt represents the time interval between the observation epoch t i and the observation epoch t i-1 ; The using the adaptive Hatch filtering algorithm includes: Wherein, M represents the smoothing time factor.

7. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 6, characterized in that, The S33 performs ionosphere-free combination processing on the dual-frequency data to obtain combined data, including: Among them, P IF represents the ionosphere-free combined pseudorange value, and represents the ionosphere-free combined carrier phase value; The smoothed ionosphere-free combined pseudorange value can be expressed as: Among them, represents the smoothed ionosphere-free combined pseudorange value.

8. The high-precision positioning method of the single and dual-frequency hybrid GNSS smart phone according to claim 7, characterized in that, The S4 performs single-frequency and dual-frequency hybrid positioning of the smartphone based on the pseudorange values, including: X = [Δx Δy Δz cdt cdt IF λN λ IF N IF T T IF ε ε IF ​ Among them, l, m, n represent position parameter coefficients, ρ represents the distance from the receiver to the satellite, (X s , Y s , Z s ) is the satellite coordinate, (X r , Y r , Z r ) is the receiver coordinate, μ represents the mapping function of tropospheric delay, Δx represents the change in the x-axis of the receiver coordinate, Δy represents the change in the y-axis of the receiver coordinate, Δz represents the change in the z-axis of the receiver coordinate, λ represents the wavelength of the carrier phase, λ IF represents the wavelength of the carrier phase value of the ionosphere-free combination, N represents the integer ambiguity of the carrier phase, N IF represents the integer ambiguity of the carrier phase value of the ionosphere-free combination, dt represents the clock error, T represents the tropospheric delay, ε represents other noises, dt IF represents the clock error included in the ionosphere-free combination value, T IF represents the tropospheric delay included in the ionosphere-free combination value, ε IF represents other noises included in the ionosphere-free combination value.

9. A high-precision positioning system for a single and dual-frequency hybrid GNSS smartphone, which is applied to the high-precision positioning method of the single and dual-frequency hybrid GNSS smartphone according to any one of claims 1-8, characterized in that, The system includes: a data acquisition module, a preprocessing module, a pseudorange smoothing module, and a hybrid positioning module; The data acquisition module is used to obtain the original GNSS observations through the smartphone API; The preprocessing module is used to perform data preprocessing based on the original GNSS observations to obtain cycle slip detection quantities; The pseudorange smoothing module is used to perform single-frequency and dual-frequency pseudorange smoothing based on the cycle slip detection quantities to obtain smoothed pseudorange values; The hybrid positioning module is used to perform single-frequency and dual-frequency hybrid positioning of the smart phone based on the pseudorange value.

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