High-precision positioning method and system based on multi-band single Beidou signal

Abstract

The invention discloses a high-precision positioning method and system based on a multi-band single Beidou signal, and the method comprises the steps: receiving a multi-band signal from a single Beidou satellite, the multi-band signal comprises three bands B1I, B1C and B2a, extracting a pseudo-range measurement value and a carrier phase measurement value of the signal of each band, and calculating the pseudo-range measurement value and the carrier phase measurement value of the signal of each band according to the pseudo-range measurement value and the carrier phase measurement value; constructing an observation value model containing multi-path errors and ionosphere delay; performing wavelet transform decomposition on the multi-band observation value sequence to obtain signal characteristics on different frequency scales, and constructing a multi-path-ionosphere coupling separation discriminator using pseudo-range and carrier phase observation value characteristic difference and a frequency dependency relationship based on a wavelet decomposition result; the error dominant type is determined according to the size of the discriminant value output by the separation discriminator, the observation value is corrected by applying a corresponding error correction strategy, the corrected observation value is used for position calculation, and a high-precision positioning result is obtained.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation and positioning technology, and in particular to a high-precision positioning method and system based on a multi-band single Beidou signal. Background Art

[0002] Traditional satellite navigation positioning methods mainly rely on pseudo-range measurements of multiple satellites to achieve position solution. However, in complex environments such as urban canyons, dense forests, and mountainous areas, the number of visible satellites is limited, and the signals are easily affected by error sources such as multipath effects and ionospheric delay, resulting in a significant decrease in positioning accuracy.

[0003] In existing technologies, methods for processing multipath effects and ionospheric delay are usually designed separately: multipath effects are usually mitigated by correlator design, antenna improvements, or signal processing techniques; ionospheric delay is mainly eliminated through broadcast model correction, dual-frequency combination, or ground-based augmentation system assistance. However, in actual application scenarios, multipath effects and ionospheric delay often exist simultaneously and are coupled with each other. Traditional independent processing methods have difficulty in effectively distinguishing and eliminating the mixed effects of these two error sources, resulting in limited positioning accuracy. In addition, when processing multi-band signals from a single satellite, existing technologies often fail to fully utilize the inter-frequency relationship and time domain characteristics, making it difficult to achieve high-precision positioning.

[0004] With the full completion of the BeiDou-3 system, the multi-band signals it provides (such as B1I, B1C, B2a, etc.) have opened up new possibilities for solving the above-mentioned problems. Multi-band signals have different response characteristics to multipath effects and ionospheric delays. If these error sources can be effectively identified and separated, and targeted corrections can be made, the positioning accuracy in complex environments will be significantly improved. Especially when the number of visible satellites is limited, fully tapping the potential of a single satellite's multi-band signals is of great significance to improving the performance of navigation and positioning systems in obscured environments. Summary of the Invention

[0005] The purpose of the present invention is to provide a high-precision positioning method and system based on a multi-band single Beidou signal. By constructing a wavelet transform multi-scale analysis framework and an innovative multipath-ionosphere coupling separation discriminator, the error sources can be accurately identified and separated, significantly improving the positioning accuracy of the Beidou navigation system in complex environments.

[0006] To achieve the above object, the present invention provides a high-precision positioning method based on a multi-band single Beidou signal, the method comprising the following steps: Step S1: Receive multi-band signals from a single BeiDou satellite, where the multi-band signals include B1I, B1C, and B2a. Extract pseudorange and carrier phase measurements from each frequency band, and construct an observation model that includes multipath error and ionospheric delay.

[0007] The multi-band signal includes B1I (1561.098 MHz), B1C (1575.42 MHz) and B2a (1176.45 MHz) frequency band signals. The observation value model is expressed as: ;in, and Respectively represent the receiver Beidou satellite Pseudorange and carrier phase observations; Represents geometric distance; represents the speed of light; Indicates the receiver clock error; represents the satellite clock error; represents the tropospheric delay; represents the ionospheric delay; represents the pseudorange multipath error; represents the carrier phase multipath error; Indicates the carrier wavelength; represents the phase ambiguity; and represent the pseudorange and carrier phase measurement noise, respectively.

[0008] This embodiment uses a BeiDou receiver that supports multiple frequency bands. The receiver is equipped with a multi-frequency antenna optimized for the B1I / B1C / B2a frequency bands and can simultaneously receive navigation signals from multiple frequency bands.

[0009] Step S2: Perform wavelet transform decomposition on the multi-band observation value sequence to obtain signal characteristics at different frequency scales. Based on the wavelet decomposition results, a multipath-ionosphere coupling separation discriminator is constructed that utilizes the characteristic differences and frequency dependence of pseudorange and carrier phase observation values.

[0010] The expression for performing wavelet transform decomposition on the multi-band observation value sequence is: ;in, Wavelet coefficients representing pseudorange or carrier phase signals; Represents the original pseudorange or carrier phase time domain signal; represents the wavelet mother function; represents the scale parameter; Represents the translation parameter.

[0011] The expression of the multipath-ionosphere coupling separation discriminator is: ;in, represents the multipath ionospheric coupling separation discrimination value; Indicates the Wavelet coefficients of pseudo-range signals at each frequency point; Indicates the The wavelet coefficients of the carrier phase signal at each frequency point; Indicates the The carrier frequency of each frequency band; Represents the weight coefficient of carrier phase and pseudorange; Indicates the number of frequency bands, In this embodiment, the measurement accuracy of the pseudorange is approximately 0.5 meters, and the measurement accuracy of the carrier phase is approximately 0.5 centimeters.

[0012] In step S3, the error-dominant type is determined according to the size of the discriminant value output by the separation discriminator, and the corresponding error correction strategy is applied to correct the observation value, and the corrected observation value is used for position solution to obtain a high-precision positioning result.

[0013] The error dominant type is determined according to the discriminant value output by the separation discriminator: when When , it is determined that the multipath effect is dominant; when When , it is determined that the ionospheric delay is dominant; when When , it is determined to be a coupling effect; and is the preset threshold; For the case where multipath is dominant, wavelet threshold filtering is applied to eliminate multipath. For the case where ionosphere is dominant, three-frequency combination is applied to eliminate the first-order effect of ionosphere. For the coupling effect, adaptive filtering is applied for joint estimation and elimination.

[0014] Furthermore, the wavelet mother function The expression is: ;in, represents the number of wavelet filter coefficients, The higher the value of , the higher the frequency resolution, and vice versa, the higher the time resolution. The value range of is an even number between 4 and 20; represents the low-pass filter coefficient, Represents the scaling function, satisfying the two-scaling equation: .

[0015] Furthermore, the weight coefficient of the carrier phase and pseudorange Determined by: ;in, The noise variance of the pseudorange measurement is expressed in square meters. It is obtained by evaluating the noise level of the receiver and has a typical value range of 0.25 to 4 square meters. Indicates the carrier phase measurement noise variance in square cycles, with a typical value range of to Square Week; Indicates the carrier wavelength in meters.

[0016] Furthermore, a preset threshold and Dynamic adjustment based on signal-to-noise ratio: ; ;in, Indicates the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, in dBHz; , is the slope parameter, with values ​​ranging from 1.2 to 2.0 and 0.3 to 0.8 respectively; , are bias parameters, with values ​​ranging from 0.8 to 1.5 and 0.2 to 0.5 respectively; The calculation formula is: ,in For the The weight of each frequency band.

[0017] Furthermore, for the case of multipath dominance, wavelet threshold filtering is applied to eliminate multipath. Wavelet threshold filtering uses an adaptive threshold : ;in, Represents the estimated value of the noise standard deviation, which is calculated by the median absolute difference MAD of the wavelet coefficients: ,in, For the Level 1 decomposition wavelet coefficients; Represents the number of samples, that is, the number of sampling points in the observation window.

[0018] Furthermore, for the case where the ionosphere is dominant, the three-frequency combination is applied to eliminate the first-order effect of the ionosphere, and the three-frequency combination algorithm constructs a geometric ionosphere-free combination. : ; in, , , Represents the pseudorange observation values ​​of the three frequency bands, in meters, corresponding to the BeiDou B1I, B1C and B2a frequency bands; , , Indicates the corresponding carrier frequency in Hz, corresponding to the Beidou B1I, B1C, and B2a frequency bands.

[0019] Furthermore, for the coupling effect, adaptive filtering is applied for joint estimation and elimination. The state equation of the filtering algorithm is : , the observation equation : ; where the state vector Contains position, velocity, receiver clock error, multipath parameters and ionospheric parameters: ; represents the state transfer matrix, which is a block diagonal matrix. The position and velocity parts adopt the uniform motion model, the receiver clock error part adopts the second-order Markov process, the multipath parameter part adopts the first-order Gaussian Markov process, and the ionospheric parameter part adopts the random walk model; Represents the observation matrix, which associates the state vector with the observation vector. Its elements are determined by the satellite position, the receiver position and the carrier frequency of each frequency band; Represents process noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution; Represents observation noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution.

[0020] Furthermore, the method also includes a BeiDou B1I, B1C, and B2a three-frequency signal quality assessment step, where the signal quality is calculated using the following indicators: ; in, Indicates the The quality index of the signal in each frequency band, The preset maximum carrier-to-noise ratio threshold is 50dBHz; represents the multipath strength estimate, Indicates the rate of change of the ionosphere in TECU / minute. and represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate, respectively; , , represents the weight coefficient, , , ; When the signal quality indicator When it is lower than 0.3, the corresponding frequency band signal will be eliminated.

[0021] In the second aspect, the present invention provides a high-precision positioning system based on a multi-band single Beidou signal, which is used to execute the method of the first aspect. The system includes: a signal receiving module, an observation value extraction module, a wavelet decomposition module, a multi-path ionosphere discrimination module and an error correction module.

[0022] The signal receiving module is used to receive multi-band signals from a single Beidou satellite. The signal receiving module includes a multi-band antenna unit, a radio frequency front-end unit and a digital signal processing unit. The multi-band antenna unit can simultaneously receive B1I, B1C and B2a band signals. The radio frequency front-end unit amplifies and filters the signals of each band. The digital signal processing unit converts the analog signal into a digital signal and performs baseband processing.

[0023] The observation value extraction module is used to extract pseudorange and carrier phase observation values ​​from the received signal. The observation value extraction module includes a navigation message decoding unit, a pseudorange calculation unit and a carrier phase calculation unit. The navigation message decoding unit analyzes the satellite clock and orbit parameters, the pseudorange calculation unit calculates the pseudorange value based on the code correlation technology, and the carrier phase calculation unit tracks and measures the carrier phase through the phase-locked loop technology.

[0024] The wavelet decomposition module is used to perform wavelet transform decomposition on multi-band observation values. The wavelet decomposition module includes a filter preprocessing unit, a wavelet coefficient calculation unit and a multi-scale analysis unit, wherein the filter preprocessing unit performs low-pass filtering on the original observation values ​​to reduce high-frequency noise interference, the wavelet coefficient calculation unit implements the discrete wavelet transform algorithm, and the multi-scale analysis unit analyzes the time-frequency characteristics of the wavelet coefficients.

[0025] The multipath ionosphere discrimination module is used to construct a discriminator and perform error source classification. The multipath ionosphere discrimination module includes a discriminator construction unit, a threshold calculation unit and a classification decision unit, wherein the discriminator construction unit calculates the discrimination value according to the formula, the threshold calculation unit dynamically determines the threshold based on the signal-to-noise ratio, and the classification decision unit determines the error-dominant type according to the comparison result between the discrimination value and the threshold.

[0026] The error correction module is used to select an appropriate algorithm to eliminate errors according to the discrimination results. The error correction module includes a wavelet filtering unit, a three-frequency combination unit and an adaptive filtering unit, wherein the wavelet filtering unit is used to eliminate multipath errors, the three-frequency combination unit is used to eliminate ionospheric delays, and the adaptive filtering unit is used for joint estimation of coupling effects.

[0027] The positioning solution module is used to calculate the receiver position based on the corrected observation values. The positioning solution module includes a least squares estimation unit, a weighted solution unit and a quality control unit, wherein the least squares estimation unit is used to calculate the initial position solution, the weighted solution unit weights the observation values ​​according to the signal quality index, and the quality control unit monitors the reliability of the solution results and eliminates outliers.

[0028] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a multipath-ionosphere coupling separation discriminator based on wavelet transform, which can effectively distinguish the multipath effect and ionospheric delay contribution in the signal, solving the problem of difficulty in separating error sources in traditional methods; it adopts differentiated correction strategies according to different error types, realizes targeted and efficient error elimination, and improves positioning accuracy when the number of visible satellites is limited. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of the high-precision positioning method based on multi-band single Beidou signal of the present invention; Figure 2 This is a schematic diagram of the composition of the high-precision positioning system based on multi-band single Beidou signal of the present invention. DETAILED DESCRIPTION

[0030] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only part of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0031] Example 1 like Figure 1 As shown, this embodiment provides a high-precision positioning method based on a multi-band single Beidou signal, the method comprising the following steps: Step S1: Receive multi-band signals from a single BeiDou satellite, where the multi-band signals include B1I, B1C, and B2a. Extract pseudorange and carrier phase measurements from each frequency band, and construct an observation model that includes multipath error and ionospheric delay.

[0032] The observation model is expressed as: ;in, and Respectively represent the receiver Pseudorange and carrier phase observations of BeiDou satellites; Represents geometric distance; represents the speed of light; Indicates the receiver clock error; represents the satellite clock error; represents the tropospheric delay; represents the ionospheric delay; represents the pseudorange multipath error; represents the carrier phase multipath error; Indicates the carrier wavelength; represents the phase ambiguity; and represent the pseudorange and carrier phase measurement noise, respectively.

[0033] Step S2: Perform wavelet transform decomposition on the multi-band observation value sequence to obtain signal characteristics at different frequency scales. Based on the wavelet decomposition results, a multipath-ionosphere coupling separation discriminator is constructed that utilizes the characteristic differences and frequency dependence of pseudorange and carrier phase observation values.

[0034] The expression for performing wavelet transform decomposition on the multi-band observation value sequence is: ;in, Wavelet coefficients representing pseudorange or carrier phase signals; Represents the original pseudorange or carrier phase time domain signal; represents the wavelet mother function; represents the scale parameter; Represents the translation parameter.

[0035] The expression of the multipath-ionosphere coupling separation discriminator is: ;in, represents the multipath ionospheric coupling separation discrimination value; Indicates the Wavelet coefficients of pseudo-range signals at each frequency point; Indicates the The wavelet coefficients of the carrier phase signal at each frequency point; Indicates the The carrier frequency of each frequency band; the weight coefficient of the carrier phase and pseudorange; Indicates the number of frequency bands, .

[0036] In step S3, the error-dominant type is determined according to the size of the discriminant value output by the separation discriminator, and the corresponding error correction strategy is applied to correct the observation value, and the corrected observation value is used for position solution to obtain a high-precision positioning result.

[0037] The error dominant type is determined according to the discriminant value output by the separation discriminator: when When , it is determined that the multipath effect is dominant; when When , it is determined that the ionospheric delay is dominant; when When , it is determined to be a coupling effect; and is the preset threshold; For the case where multipath is dominant, wavelet threshold filtering is applied to eliminate multipath. For the case where ionosphere is dominant, three-frequency combination is applied to eliminate the first-order effect of ionosphere. For the coupling effect, adaptive filtering is applied for joint estimation and elimination.

[0038] The expression of the wavelet mother function is: ;in, represents the number of wavelet filter coefficients, The higher the value of , the higher the frequency resolution, and vice versa, the higher the time resolution. The value range of is an even number between 4 and 20; represents the low-pass filter coefficient, Represents the scaling function, satisfying the two-scaling equation: .

[0039] The wavelet decomposition is realized by discrete wavelet transform, and the decomposition level According to the signal sampling rate and the minimum frequency of analysis required Sure: ,in Represents a rounding-up operation, typically with values ​​of 3 to 5; the decomposition process produces a series of approximation coefficients and detail coefficient , the detail coefficient corresponds to the signal fluctuation characteristics at different frequency scales.

[0040] The weight coefficient of the carrier phase and pseudorange Determined by: ;in, The pseudorange measurement noise variance is expressed in square meters and is derived from the receiver noise level assessment. Typical values ​​range from 0.25 to 4 square meters. Indicates the carrier phase measurement noise variance in square cycles, with a typical value range of to Square Week; Indicates the carrier wavelength in meters.

[0041] The weight coefficient is a vector that changes with frequency. For the three BeiDou frequency bands B1I, B1C and B2a, the corresponding value to achieve the best separation effect of multipath and ionospheric effect; when the receiving environment changes, The value can be updated in real time through the receiver signal-to-noise ratio. The specific update formula is: ;in, is the smoothing coefficient, ranging from 0.01 to 0.1, is the carrier-to-noise ratio of the ith frequency band, in dBHz.

[0042] Preset threshold and Dynamic adjustment based on signal-to-noise ratio: ; ;in, Indicates the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, in dBHz; , is the slope parameter, with values ​​ranging from 1.2 to 2.0 and 0.3 to 0.8 respectively; , are bias parameters, with values ​​ranging from 0.8 to 1.5 and 0.2 to 0.5 respectively; The calculation formula is: ,in For the The weight of each frequency band.

[0043] This dynamic threshold mechanism can adapt to the characteristics of received signals under different environmental conditions, adopt stricter discrimination criteria in high signal-to-noise ratio environments, and relax the discrimination criteria in low signal-to-noise ratio environments, thereby achieving more robust separation of multipath and ionospheric effects.

[0044] The threshold also varies with the length of the observation time window Make adjustments, the specific formula is: ;in, is the reference window length, typically 60 seconds, is the actual observation window length used, in seconds, i=1,2.

[0045] For the case of multipath dominance, wavelet threshold filtering is applied to eliminate multipath. Wavelet threshold filtering uses an adaptive threshold : ;in, Represents the estimated value of the noise standard deviation, which is calculated by the median absolute difference MAD of the wavelet coefficients: ,in, For the Level 1 decomposition wavelet coefficients; Represents the number of samples, that is, the number of sampling points in the observation window.

[0046] The wavelet threshold filtering adopts the soft threshold processing method to process the wavelet coefficients Perform the following processing: in, represents the symbolic function, is the processed wavelet coefficient; after filtering, the signal is reconstructed by inverse wavelet transform to eliminate the high-frequency fluctuation caused by the multipath effect. The expression of the reconstructed signal is: in, is the coarsest scale approximation coefficient, and are scaling function and wavelet function respectively.

[0047] For the ionosphere-dominated situation, the three-frequency combination is applied to eliminate the first-order effect of the ionosphere, and the three-frequency combination algorithm is used to construct a geometric ionosphere-free combination. : in, , , Represents the pseudorange observation values ​​of the three frequency bands, in meters, corresponding to the BeiDou B1I, B1C and B2a frequency bands; , , Indicates the corresponding carrier frequency in Hz, corresponding to the Beidou B1I, B1C, and B2a frequency bands.

[0048] The BeiDou B1I frequency is 1561.098 MHz, the B1C frequency is 1575.42 MHz, and the B2a frequency is 1176.45 MHz. This three-frequency combination can eliminate the first- and second-order ionospheric delay effects, significantly improving positioning accuracy. At the same time, to reduce the combined noise amplification effect, a weighted smoothing process is introduced: in, is the smoothing factor, ranging from 0.1 to 0.5, and Represent the smoothed geometric ionosphere-free combination values ​​at the current moment and the previous moment respectively. For the carrier phase observation value, a similar three-frequency combination method is used to construct the ionosphere-free combination: in, Represents the carrier phase observation values ​​of the three frequency bands, in cycles.

[0049] Furthermore, for the coupling effect, adaptive filtering is applied for joint estimation and elimination. The state equation of the filtering algorithm is : , the observation equation :; where the state vector Contains position, velocity, receiver clock error, multipath parameters and ionospheric parameters: ; represents the state transfer matrix, which is a block diagonal matrix. The position and velocity parts adopt the uniform motion model, the receiver clock error part adopts the second-order Markov process, the multipath parameter part adopts the first-order Gaussian Markov process, and the ionospheric parameter part adopts the random walk model; Represents the observation matrix, which associates the state vector with the observation vector. Its elements are determined by the satellite position, the receiver position and the carrier frequency of each frequency band; Represents process noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution; Represents observation noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution.

[0050] The covariance matrix and For adaptive dynamic adjustment, the specific adjustment method is: ;in, is the forgetting factor, ranging from 0.95 to 0.99, is the prediction residual; ;in, is the forgetting factor, ranging from 0.97 to 0.995, and is the state vector update amount; the Kalman filter adopts a progressive structure, first estimating and compensating the ionospheric delay, then estimating and compensating the multipath error, and finally estimating the position, velocity and receiver clock error parameters.

[0051] The method also includes a BeiDou B1I, B1C, and B2a tri-frequency signal quality assessment step, where the signal quality is calculated using the following indicators: ; Among them, it represents the The quality index of the signal in each frequency band, The preset maximum carrier-to-noise ratio threshold is 50dBHz; represents the multipath strength estimate, Indicates the rate of change of the ionosphere in TECU / minute. and represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate, respectively; , , represents the weight coefficient, , , ; When the signal quality indicator When it is lower than 0.3, the corresponding frequency band signal will be eliminated.

[0052] The signal quality index is used for observation weighting and satellite selection: ;in, is the observation weight, E is the satellite altitude angle, in radians; when the signal quality index When it is lower than 0.3, the corresponding frequency band signal will be eliminated to avoid the adverse effects of low-quality signals on the positioning solution.

[0053] In a mountainous environment where only a single Beidou GEO satellite signal can be received, the satellite's B1I, B1C and B2a frequency band signals, combined with precise point positioning (PPP) technology, were used to achieve a positioning accuracy of 2.5 meters in the horizontal direction and 3.8 meters in the vertical direction, an improvement of approximately 65% ​​compared to traditional methods.

[0054] Example 2 like Figure 2 As shown in the figure, it is a schematic diagram of the composition of the high-precision positioning system based on multi-band single Beidou signal of the present invention. The system includes: a signal receiving module, an observation value extraction module, a wavelet decomposition module, a multipath ionosphere discrimination module and an error correction module.

[0055] The signal receiving module is used to receive multi-band signals from a single Beidou satellite. The signal receiving module includes a multi-band antenna unit, a radio frequency front-end unit and a digital signal processing unit. The multi-band antenna unit can simultaneously receive B1I, B1C and B2a band signals. The radio frequency front-end unit amplifies and filters the signals of each band. The digital signal processing unit converts the analog signal into a digital signal and performs baseband processing.

[0056] The observation value extraction module is used to extract pseudorange and carrier phase observation values ​​from the received signal. The observation value extraction module includes a navigation message decoding unit, a pseudorange calculation unit and a carrier phase calculation unit. The navigation message decoding unit analyzes the satellite clock and orbit parameters, the pseudorange calculation unit calculates the pseudorange value based on the code correlation technology, and the carrier phase calculation unit tracks and measures the carrier phase through the phase-locked loop technology.

[0057] The wavelet decomposition module is used to perform wavelet transform decomposition on multi-band observation values. The wavelet decomposition module includes a filter preprocessing unit, a wavelet coefficient calculation unit and a multi-scale analysis unit, wherein the filter preprocessing unit performs low-pass filtering on the original observation values ​​to reduce high-frequency noise interference, the wavelet coefficient calculation unit implements the discrete wavelet transform algorithm, and the multi-scale analysis unit analyzes the time-frequency characteristics of the wavelet coefficients.

[0058] The multipath ionosphere discrimination module is used to construct a discriminator and perform error source classification. The multipath ionosphere discrimination module includes a discriminator construction unit, a threshold calculation unit and a classification decision unit, wherein the discriminator construction unit calculates the discrimination value according to the formula, the threshold calculation unit dynamically determines the threshold based on the signal-to-noise ratio, and the classification decision unit determines the error-dominant type according to the comparison result between the discrimination value and the threshold.

[0059] The error correction module is used to select an appropriate algorithm to eliminate errors according to the discrimination results. The error correction module includes a wavelet filtering unit, a three-frequency combination unit and an adaptive filtering unit, wherein the wavelet filtering unit is used to eliminate multipath errors, the three-frequency combination unit is used to eliminate ionospheric delays, and the adaptive filtering unit is used for joint estimation of coupling effects.

[0060] The positioning solution module is used to calculate the receiver position based on the corrected observation values. The positioning solution module includes a least squares estimation unit, a weighted solution unit and a quality control unit, wherein the least squares estimation unit is used to calculate the initial position solution, the weighted solution unit weights the observation values ​​according to the signal quality index, and the quality control unit monitors the reliability of the solution results and eliminates outliers.

[0061] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-precision positioning method based on multi-band single Beidou signal, characterized in that: The method comprises the following steps: Step S1: Receive multi-band signals from a single BeiDou satellite, where the multi-band signals include B1I, B1C, and B2a, extract pseudorange and carrier phase measurements from each frequency band, and construct an observation model that includes multipath error and ionospheric delay. The observation model is expressed as: ;in, and Respectively represent the receiver Beidou satellite Pseudorange and carrier phase observations; Represents geometric distance; represents the speed of light; Indicates the receiver clock error; represents the satellite clock error; represents the tropospheric delay; represents the ionospheric delay; represents the pseudorange multipath error; represents the carrier phase multipath error; Indicates the carrier wavelength; represents the phase ambiguity; and represent the pseudorange and carrier phase measurement noise respectively; Step S2: performing wavelet transform decomposition on the multi-band observation value sequence to obtain signal features at different frequency scales, and based on the wavelet decomposition results, constructing a multipath-ionosphere coupling separation discriminator that utilizes the characteristic differences and frequency dependence of pseudorange and carrier phase observation values; The expression for performing wavelet transform decomposition on the multi-band observation value sequence is: ;in, Wavelet coefficients representing pseudorange or carrier phase signals; Represents the original pseudorange or carrier phase time domain signal; represents the wavelet mother function; represents the scale parameter; represents the translation parameter; The expression of the multipath-ionosphere coupling separation discriminator is: ;in, represents the multipath ionospheric coupling separation discrimination value; Indicates the Wavelet coefficients of pseudo-range signals at each frequency point; Indicates the The wavelet coefficients of the carrier phase signal at each frequency point; Indicates the The carrier frequency of each frequency band; Represents the weight coefficient of carrier phase and pseudorange; Indicates the number of frequency bands, ; Step S3, determining the error-dominant type based on the discriminant value output by the separation discriminator, and applying the corresponding error correction strategy to correct the observation value, and using the corrected observation value for position calculation to obtain a high-precision positioning result; The error dominant type is determined according to the discriminant value output by the separation discriminator: when When , it is determined that the multipath effect is dominant; when When , it is determined that the ionospheric delay is dominant; when When , it is determined to be a coupling effect; and is the preset threshold; For the case where multipath is dominant, wavelet threshold filtering is applied to eliminate multipath. For the case where ionosphere is dominant, three-frequency combination is applied to eliminate the first-order effect of ionosphere. For the coupling effect, adaptive filtering is applied for joint estimation and elimination.

2. The method according to claim 1, characterized in that The wavelet mother function The expression is: ;in, represents the number of wavelet filter coefficients, The higher the value of , the higher the frequency resolution, and vice versa, the higher the time resolution. The value range of is an even number between 4 and 20; represents the low-pass filter coefficient, Represents the scaling function, satisfying the two-scaling equation: .

3. The method according to claim 2, characterized in that The weight coefficient of the carrier phase and pseudorange Determined by: ;in, The pseudorange measurement noise variance is expressed in square meters and is derived from the receiver noise level assessment. Typical values ​​range from 0.25 to 4 square meters. Indicates the carrier phase measurement noise variance in square cycles, with a typical value range of to Square Week; Indicates the carrier wavelength in meters.

4. The method according to claim 3, characterized in that Preset threshold and Dynamic adjustment based on signal-to-noise ratio: ; ;in, Indicates the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, in dBHz; , is the slope parameter, with values ​​ranging from 1.2 to 2.0 and 0.3 to 0.8 respectively; , are bias parameters, with values ​​ranging from 0.8 to 1.5 and 0.2 to 0.5 respectively; The calculation formula is: ,in For the The weight of each frequency band.

5. The method according to claim 4, characterized in that For the case of multipath dominance, wavelet threshold filtering is applied to eliminate multipath. Wavelet threshold filtering uses an adaptive threshold : ;in, Represents the estimated value of the noise standard deviation, which is calculated by the median absolute difference MAD of the wavelet coefficients: ,in, For the The wavelet coefficient of the level decomposition; Represents the number of samples, that is, the number of sampling points in the observation window.

6. The method according to claim 5, characterized in that For the ionosphere-dominated situation, the three-frequency combination is applied to eliminate the first-order effect of the ionosphere, and the three-frequency combination algorithm is used to construct a geometric ionosphere-free combination. : ； in, , , Represents the pseudorange observation values ​​of the three frequency bands, in meters, corresponding to the BeiDou B1I, B1C and B2a frequency bands; , , Indicates the corresponding carrier frequency in Hz, corresponding to the Beidou B1I, B1C, and B2a frequency bands.

7. The method according to claim 1, characterized in that For the coupling effect, adaptive filtering is applied for joint estimation and elimination. The state equation of the filtering algorithm is : , the observation equation : ; where the state vector Contains position, velocity, receiver clock error, multipath parameters and ionospheric parameters: ; represents the state transfer matrix, which is a block diagonal matrix. The position and velocity parts adopt the uniform motion model, the receiver clock error part adopts the second-order Markov process, the multipath parameter part adopts the first-order Gaussian Markov process, and the ionospheric parameter part adopts the random walk model; Represents the observation matrix, which associates the state vector with the observation vector. Its elements are determined by the satellite position, the receiver position and the carrier frequency of each frequency band; Represents process noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution; Represents observation noise, assuming it obeys mean 0, and the covariance matrix is Gaussian distribution.

8. The method according to claim 1, characterized in that It also includes the Beidou B1I, B1C and B2a three-frequency signal quality assessment steps, and calculates the signal quality through the following indicators: ； in, Indicates the The quality index of the signal in each frequency band, The preset maximum carrier-to-noise ratio threshold is 50dBHz; represents the multipath strength estimate, Indicates the rate of change of the ionosphere in TECU / minute. and They represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate respectively; , , represents the weight coefficient, , , ; When the signal quality indicator When it is lower than 0.3, the corresponding frequency band signal will be eliminated.

9. A high-precision positioning system based on a multi-band single BeiDou signal, used to execute the method according to any one of claims 1 to 8, characterized in that: The system comprises: Signal receiving module, observation value extraction module, wavelet decomposition module, multipath ionosphere discrimination module and error correction module; The signal receiving module is used to receive multi-band signals from a single Beidou satellite. The signal receiving module includes a multi-band antenna unit, a radio frequency front-end unit, and a digital signal processing unit. The multi-band antenna unit can simultaneously receive B1I, B1C, and B2a frequency band signals. The radio frequency front-end unit amplifies and filters the signals of each frequency band. The digital signal processing unit converts the analog signal into a digital signal and performs baseband processing. The observation value extraction module is used to extract pseudorange and carrier phase observation values ​​from the received signal. The observation value extraction module includes a navigation message decoding unit, a pseudorange calculation unit and a carrier phase calculation unit, wherein the navigation message decoding unit analyzes the satellite clock and orbit parameters, the pseudorange calculation unit calculates the pseudorange value based on the code correlation technology, and the carrier phase calculation unit tracks and measures the carrier phase through the phase-locked loop technology; The wavelet decomposition module is used to perform wavelet transform decomposition on multi-band observation values. The wavelet decomposition module includes a filter preprocessing unit, a wavelet coefficient calculation unit and a multi-scale analysis unit, wherein the filter preprocessing unit performs low-pass filtering on the original observation values ​​to reduce high-frequency noise interference, the wavelet coefficient calculation unit implements a discrete wavelet transform algorithm, and the multi-scale analysis unit analyzes the time-frequency characteristics of the wavelet coefficients; The multipath ionosphere discrimination module is used to construct a discriminator and perform error source classification. The multipath ionosphere discrimination module includes a discriminator construction unit, a threshold calculation unit, and a classification decision unit, wherein the discriminator construction unit calculates a discrimination value according to a formula, the threshold calculation unit dynamically determines a threshold based on a signal-to-noise ratio, and the classification decision unit determines the error dominant type according to a comparison result between the discriminant value and the threshold; The error correction module is used to select an appropriate algorithm to eliminate errors according to the discrimination results. The error correction module includes a wavelet filtering unit, a three-frequency combination unit and an adaptive filtering unit, wherein the wavelet filtering unit is used to eliminate multipath errors, the three-frequency combination unit is used to eliminate ionospheric delays, and the adaptive filtering unit is used for joint estimation of coupling effects.

10. The system according to claim 9, characterized in that The system also includes a positioning solution module, which is used to calculate the receiver position based on the corrected observation values. The positioning solution module includes a least squares estimation unit, a weighted solution unit and a quality control unit, wherein the least squares estimation unit is used to calculate the initial position solution, the weighted solution unit weights the observation values ​​according to the signal quality index, and the quality control unit monitors the reliability of the solution results and eliminates outliers.

Images