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

Abstract

The application discloses a high-precision positioning method and system based on multi-frequency band single Beidou signal, the method receives multi-frequency band signals from a single Beidou satellite, the multi-frequency band includes three frequency bands of B1I, B1C and B2a, pseudo-range measurement values and carrier phase measurement values of signals of each frequency band are extracted, and an observation value model containing multipath error and ionospheric delay is constructed; wavelet transform decomposition is carried out on the multi-frequency band observation value sequence, signal characteristics on different frequency scales are obtained, and based on the wavelet decomposition result, a multipath-ionosphere coupling separation discriminator using the characteristic difference and frequency-dependent relationship of pseudo-range and carrier phase observation values is constructed; the error dominant type is determined according to the size of the discrimination value output by the separation discriminator, and the corresponding error correction strategy is applied to correct the observation value respectively, and the corrected observation value is used for position solution, and a high-precision positioning result is obtained.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and positioning technology, and in particular to a high-precision positioning method and system based on multi-band single BeiDou signals. Background Technology

[0002] Traditional satellite navigation and positioning methods mainly rely on pseudorange measurements from multiple satellites to calculate position. 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, the methods for handling multipath effects and ionospheric delay are typically designed independently: multipath effects are usually mitigated through correlator design, antenna improvements, or signal processing techniques; ionospheric delay is mainly eliminated through broadcast model correction, dual-frequency combination, or ground-based augmentation systems. However, in practical applications, multipath effects and ionospheric delay often coexist and are coupled, making it difficult for traditional independent processing methods to effectively distinguish and eliminate the combined effects of these two error sources, thus limiting positioning accuracy. Furthermore, existing technologies often fail to fully utilize inter-frequency relationships and time-domain characteristics when processing multi-band signals from a single satellite, making it difficult to achieve high-precision positioning.

[0004] With the full completion of the BeiDou-3 system, its multi-band signals (such as B1I, B1C, B2a, etc.) provide new possibilities for solving the above problems. Multi-band signals have different response characteristics to multipath effects and ionospheric delay. If these error sources can be effectively identified and separated and corrected in a targeted manner, the positioning accuracy in complex environments will be significantly improved. Especially when the number of visible satellites is limited, fully exploring the potential of multi-band signals from a single satellite is of great significance for improving the performance of navigation and positioning systems in obstructed environments. Summary of the Invention

[0005] The purpose of this invention is to provide a high-precision positioning method and system based on multi-band single BeiDou signal. By constructing a wavelet transform multi-scale analysis framework and an innovative multi-path-ionospheric 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 objectives, the present invention provides a high-precision positioning method based on a multi-band single BeiDou signal, the method comprising the following steps:

[0007] Step S1: Receive multi-band signals from a single BeiDou satellite. The multi-band signals include three frequency bands: B1I, B1C, and B2a. Extract pseudorange measurements and carrier phase measurements from each frequency band signal to construct an observation model that includes multipath error and ionospheric delay.

[0008] The multi-band signals include B1I (1561.098MHz), B1C (1575.42MHz), and B2a (1176.45MHz) band signals. The observation model is expressed as follows: ;in, and They represent the receivers respectively. Beidou satellite Pseudorange and carrier phase observations; Represents geometric distance; Represents the speed of light; Indicates receiver clock bias; Indicates satellite clock bias; Indicates tropospheric delay; Indicates ionospheric delay; This represents pseudorange multipath error; Indicates carrier phase multipath error; Indicates the carrier wavelength; Indicates phase ambiguity; and These represent pseudorange and carrier phase measurement noise, respectively.

[0009] This embodiment uses a multi-band BeiDou receiver equipped with a multi-band antenna optimized for the B1I / B1C / B2a bands, which can simultaneously receive navigation signals from multiple bands.

[0010] Step S2: Perform wavelet transform decomposition on the multi-band observation sequence to obtain signal features at different frequency scales, and based on the wavelet decomposition results, construct a multipath-ionospheric coupling separation discriminator that utilizes the differences in pseudorange and carrier phase observation characteristics and frequency dependence.

[0011] The expression for wavelet transform decomposition of the multi-band observation sequence is as follows:

[0012] ;in, Wavelet coefficients representing pseudorange or carrier phase signals; This represents the original pseudorange or carrier phase time-domain signal; Represents the wavelet mother function; Indicates the scale parameter; This represents the translation parameter.

[0013] The expression for the multipath-ionosphere coupling separation discriminator is:

[0014] ;in, Indicates the multipath ionospheric coupling separation discrimination value; Indicates the first Wavelet coefficients of pseudorange signals at each frequency point; Indicates the first Wavelet coefficients of carrier phase signals at each frequency point; Indicates the first The carrier frequency of each frequency band; The weighting coefficients representing the 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.

[0015] Step S3: Determine the dominant error type based on the magnitude of the discrimination value output by the separation discriminator, and apply the corresponding error correction strategy to correct the observation value. Use the corrected observation value for position calculation to obtain a high-precision positioning result.

[0016] The error dominance type is determined based on the magnitude of the discriminant value output by the separation discriminator as follows:

[0017] when When, it is determined that the multipath effect is dominant; when When, it is determined to be dominated by ionospheric delay; when When this occurs, it is determined to be a coupling effect; among which... and The preset threshold;

[0018] For cases dominated by multiple paths, wavelet threshold filtering is used to eliminate multiple paths. For cases dominated by the ionosphere, three-frequency combination is used to eliminate the first-order ionospheric effect. For coupling effects, adaptive filtering is used for joint estimation and elimination.

[0019] Furthermore, the wavelet mother function The expression is:

[0020] ;in, Indicates the number of wavelet filter coefficients. A higher value indicates higher frequency resolution, and vice versa. The value of is an even number between 4 and 20; This represents the coefficients of the low-pass filter. The scaling function satisfies the two-scale equation: .

[0021] Furthermore, the weighting coefficients for the carrier phase and pseudorange Determined in the following ways: ;in, This represents the variance of pseudorange measurement noise, in square meters, and is obtained through receiver noise level assessment, with a typical range of 0.25 to 4 square meters.

[0022] This represents the carrier phase measurement noise variance, expressed in square cycles, with a typical range of [value missing]. to Square circumference; This indicates the carrier wavelength, measured in meters.

[0023] Furthermore, preset threshold and Dynamically adjusted based on signal-to-noise ratio: ; ;in, This represents the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, and is expressed in dBHz. , The slope parameter has values ​​ranging from 1.2 to 2.0 and from 0.3 to 0.8, respectively. , These 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 first Weights of each frequency band.

[0024] Furthermore, for cases dominated by multiple paths, wavelet threshold filtering is applied for multipath elimination, using an adaptive threshold. :

[0025] ;in, The noise standard deviation estimate is calculated using the median absolute difference (MAD) of the wavelet coefficients. ,in, For the first The first level of decomposition Wavelet coefficients; This indicates the number of samples, i.e., the number of sampling points within the observation window.

[0026] Furthermore, for cases dominated by the ionosphere, a three-frequency combination is applied to eliminate the first-order ionospheric effect, and the three-frequency combination algorithm constructs a geometrically ionosphere-free combination. :

[0027] ;

[0028] in, , , This represents the pseudorange observation values ​​for the three frequency bands, in meters, corresponding to the BeiDou B1I, B1C, and B2a frequency bands. , , This indicates the corresponding carrier frequency, in Hz, corresponding to the BeiDou B1I, B1C, and B2a frequency bands.

[0029] Furthermore, for coupling effects, adaptive filtering is applied for joint estimation and elimination. The state equation of the filtering algorithm... : Observation equation : ; where the state vector Includes position, velocity, receiver clock bias, multipath parameters, and ionospheric parameters: ; The state transition matrix is ​​a block diagonal matrix, in which the position and velocity parts adopt a uniform motion model, the receiver clock error part adopts a second-order Markov process, the multipath parameter part adopts a first-order Gaussian Markov process, and the ionospheric parameter part adopts a random walk model. The observation matrix is ​​used to associate the state vector with the observation vector. Its elements are determined by the satellite position, receiver position, and carrier frequencies of each frequency band. Let the process noise be represented, assuming it follows a mean of 0 and a covariance matrix of... Gaussian distribution; Let the observed noise be represented by a mean of 0, and the covariance matrix be... The Gaussian distribution.

[0030] Furthermore, the method also includes a three-frequency signal quality assessment step for BeiDou B1I, B1C, and B2a, calculating signal quality using the following indicators:

[0031] ;

[0032] in, Indicates the first Quality indicators of signals in each frequency band The preset maximum carrier-to-noise ratio threshold is set to 50 dBHz. This represents the multipath intensity estimate. This represents the rate of change of the ionosphere, measured in TECU / minute. and represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate, respectively; , , Indicates the weighting coefficient. , , When signal quality indicators When the value is below 0.3, the corresponding frequency band signal will be removed.

[0033] In a second aspect, the present invention provides a high-precision positioning system based on a multi-band single BeiDou signal for performing the method of the first aspect. The system includes: a signal receiving module, an observation extraction module, a wavelet decomposition module, a multipath ionospheric discrimination module, and an error correction module.

[0034] 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 signals from the B1I, B1C, and B2a bands. The radio frequency front-end unit amplifies and filters the signals from each band. The digital signal processing unit converts analog signals into digital signals and performs baseband processing.

[0035] The observation extraction module is used to extract pseudorange and carrier phase observations from the received signal. The observation extraction module includes a navigation message decoding unit, a pseudorange calculation unit, and a carrier phase calculation unit. The navigation message decoding unit parses the satellite clock and orbit parameters, the pseudorange calculation unit calculates the pseudorange value based on code correlation technology, and the carrier phase calculation unit tracks and measures the carrier phase through phase-locked loop technology.

[0036] The wavelet decomposition module is used to perform wavelet transform decomposition on multi-frequency band observations. The wavelet decomposition module includes a filtering preprocessing unit, a wavelet coefficient calculation unit, and a multi-scale analysis unit. The filtering preprocessing unit performs low-pass filtering on the original observations to reduce high-frequency noise interference. The wavelet coefficient calculation unit implements the discrete wavelet transform algorithm. The multi-scale analysis unit analyzes the time-frequency characteristics of the wavelet coefficients.

[0037] The multipath ionospheric discrimination module is used to construct a discriminator and perform error source classification. The multipath ionospheric discrimination module includes a discriminator construction unit, a threshold calculation unit, and a classification decision unit. 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 dominant error type based on the comparison result between the discrimination value and the threshold.

[0038] The error correction module is used to select an appropriate algorithm to eliminate errors based on the discrimination result. The error correction module includes a wavelet filtering unit, a three-frequency combination unit, and an adaptive filtering unit. The wavelet filtering unit is used for multipath error elimination, the three-frequency combination unit is used for ionospheric delay elimination, and the adaptive filtering unit is used for joint estimation of coupling effects.

[0039] The positioning solution module is used to calculate the receiver position based on the corrected observations. The positioning solution module includes a least squares estimation unit, a weighted solution unit, and a quality control unit. The least squares estimation unit is used to calculate the initial position solution. The weighted solution unit weights the observations according to the signal quality index. The quality control unit monitors the reliability of the solution results and removes outliers.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] This invention proposes a multipath-ionospheric coupling separation discriminator based on wavelet transform, which can effectively distinguish between multipath effects and ionospheric delay contributions in signals, solving the problem of difficulty in separating error sources in traditional methods; it adopts differentiated correction strategies according to different error types, achieving targeted and efficient error elimination, and improving positioning accuracy when the number of visible satellites is limited. Attached Figure Description

[0042] Figure 1 This is a flowchart of the high-precision positioning method based on multi-band single BeiDou signal of the present invention;

[0043] Figure 2 This is a schematic diagram of the high-precision positioning system based on multi-band single BeiDou signal of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of this invention, not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0045] Example 1

[0046] like Figure 1 As shown, this embodiment provides a high-precision positioning method based on a multi-band single BeiDou signal, the method including the following steps:

[0047] Step S1: Receive multi-band signals from a single BeiDou satellite. The multi-band signals include three frequency bands: B1I, B1C, and B2a. Extract pseudorange measurements and carrier phase measurements from each frequency band signal to construct an observation model that includes multipath error and ionospheric delay.

[0048] The observation model is represented as follows: ;in, and They represent the receivers respectively. Pseudorange and carrier phase observations of BeiDou satellites; Represents geometric distance; Represents the speed of light; Indicates receiver clock bias; Indicates satellite clock bias; Indicates tropospheric delay; Indicates ionospheric delay; This represents pseudorange multipath error; Indicates carrier phase multipath error; Indicates the carrier wavelength; Indicates phase ambiguity; and These represent pseudorange and carrier phase measurement noise, respectively.

[0049] Step S2: Perform wavelet transform decomposition on the multi-band observation sequence to obtain signal features at different frequency scales, and based on the wavelet decomposition results, construct a multipath-ionospheric coupling separation discriminator that utilizes the differences in pseudorange and carrier phase observation characteristics and frequency dependence.

[0050] The expression for wavelet transform decomposition of the multi-band observation sequence is as follows:

[0051] ;in, Wavelet coefficients representing pseudorange or carrier phase signals; This represents the original pseudorange or carrier phase time-domain signal; Represents the wavelet mother function; Indicates the scale parameter; This represents the translation parameter.

[0052] The expression for the multipath-ionosphere coupling separation discriminator is:

[0053] ;in, Indicates the multipath ionospheric coupling separation discrimination value; Indicates the first Wavelet coefficients of pseudorange signals at each frequency point; Indicates the first Wavelet coefficients of carrier phase signals at each frequency point; Indicates the first The carrier frequency of each frequency band; the weighting coefficients representing the carrier phase and pseudorange; Indicates the number of frequency bands. .

[0054] Step S3: Determine the dominant error type based on the magnitude of the discrimination value output by the separation discriminator, and apply the corresponding error correction strategy to correct the observation value. Use the corrected observation value for position calculation to obtain a high-precision positioning result.

[0055] The error dominance type is determined based on the magnitude of the discriminant value output by the separation discriminator as follows:

[0056] when When, it is determined that the multipath effect is dominant; when When, it is determined to be dominated by ionospheric delay; when When this occurs, it is determined to be a coupling effect; among which... and The preset threshold;

[0057] For cases dominated by multiple paths, wavelet threshold filtering is used to eliminate multiple paths. For cases dominated by the ionosphere, three-frequency combination is used to eliminate the first-order ionospheric effect. For coupling effects, adaptive filtering is used for joint estimation and elimination.

[0058] The expression for the wavelet mother function is:

[0059] ;in, Indicates the number of wavelet filter coefficients. A higher value indicates higher frequency resolution, and vice versa. The value of is an even number between 4 and 20; This represents the coefficients of the low-pass filter. The scaling function satisfies the two-scale equation: .

[0060] The wavelet decomposition is implemented using discrete wavelet transform, and the decomposition series is... Based on signal sampling rate and the minimum frequency required for analysis Sure: ,in This represents the floor function, typically with values ​​of 3 to 5; the decomposition process produces a series of approximation coefficients. and detail coefficient The detail coefficients correspond to the signal fluctuation characteristics at different frequency scales.

[0061] The weighting coefficients of the carrier phase and pseudorange Determined in the following ways: ;in, This represents the variance of pseudorange measurement noise, in square meters, and is obtained through receiver noise level assessment, with a typical range of 0.25 to 4 square meters. This represents the carrier phase measurement noise variance, expressed in square cycles, with a typical range of [value missing]. to Square circumference; This indicates the carrier wavelength, measured in meters.

[0062] The weighting coefficient Given a frequency-dependent vector, calculate the corresponding values ​​for the three frequency bands B1I, B1C, and B2a of the BeiDou system. Values ​​are adjusted to achieve optimal multipath and ionospheric effect separation; when the receiving environment changes, The value can be updated in real time through the receiver's signal-to-noise ratio. The specific update formula is as follows:

[0063] ;in, This is a smoothing coefficient, with a value ranging from 0.01 to 0.1. is the carrier-to-noise ratio of the i-th frequency band, in dBHz.

[0064] Preset threshold and Dynamically adjusted based on signal-to-noise ratio: ; ;in, This represents the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, and is expressed in dBHz. , The slope parameter has values ​​ranging from 1.2 to 2.0 and from 0.3 to 0.8, respectively. , These 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 first Weights of each frequency band.

[0065] This dynamic threshold mechanism can adapt to the characteristics of received signals under different environmental conditions. It adopts stricter discrimination criteria in high signal-to-noise ratio environments and relaxes the discrimination criteria in low signal-to-noise ratio environments, thereby achieving more robust separation of multipath and ionospheric effects.

[0066] The threshold also varies with the length of the observation time window. Adjustments will be made, and the specific formula is as follows: ;in, This is a reference window length, typically 60 seconds. The actual observation window length is in seconds, i=1,2.

[0067] For cases dominated by multiple paths, wavelet threshold filtering is applied to eliminate multiple paths. The wavelet threshold filtering uses an adaptive threshold. :

[0068] ;in, The noise standard deviation estimate is calculated using the median absolute difference (MAD) of the wavelet coefficients. ,in, For the first The first level of decomposition Wavelet coefficients; This indicates the number of samples, i.e., the number of sampling points within the observation window.

[0069] The wavelet threshold filtering employs a soft thresholding method for the wavelet coefficients. Perform the following processing:

[0070]

[0071] in, Represents a symbolic function. These are the processed wavelet coefficients; after filtering, the signal is reconstructed using inverse wavelet transform to eliminate high-frequency fluctuations caused by multipath effects. The expression for the reconstructed signal is:

[0072]

[0073] in, The approximation coefficients are the coarsest scale. and These are the scaling function and the wavelet function, respectively.

[0074] For cases dominated by the ionosphere, a three-frequency combination algorithm is applied to eliminate the first-order ionospheric effect. The algorithm constructs a geometrically ionosphere-free combination. :

[0075]

[0076] in, , , This represents the pseudorange observation values ​​for the three frequency bands, in meters, corresponding to the BeiDou B1I, B1C, and B2a frequency bands. , , This indicates the corresponding carrier frequency, in Hz, corresponding to the BeiDou B1I, B1C, and B2a frequency bands.

[0077] The BeiDou B1I frequency is 1561.098MHz, the B1C frequency is 1575.42MHz, and the B2a frequency is 1176.45MHz. This three-frequency combination can eliminate first- and second-order ionospheric delay effects, significantly improving positioning accuracy. Simultaneously, to reduce the amplification effect of combined noise, weighted smoothing processing is introduced.

[0078]

[0079] in, This is a smoothing factor, with a value ranging from 0.1 to 0.5. and These represent the smoothed geometrically ionospherically de-ionized combination values ​​for the current and previous time points, respectively. For carrier phase observations, a similar three-frequency combination method is used to construct the ionospherically de-ionized combination:

[0080]

[0081] in, This represents the carrier phase observations for the three frequency bands, in cycles.

[0082] Furthermore, for coupling effects, adaptive filtering is applied for joint estimation and elimination. The state equation of the filtering algorithm... : Observation equation :; where the state vector Includes position, velocity, receiver clock bias, multipath parameters, and ionospheric parameters: ; The state transition matrix is ​​a block diagonal matrix, in which the position and velocity parts adopt a uniform motion model, the receiver clock error part adopts a second-order Markov process, the multipath parameter part adopts a first-order Gaussian Markov process, and the ionospheric parameter part adopts a random walk model. The observation matrix is ​​used to associate the state vector with the observation vector. Its elements are determined by the satellite position, receiver position, and carrier frequencies of each frequency band. Let the process noise be represented, assuming it follows a mean of 0 and a covariance matrix of... Gaussian distribution; Let the observed noise be represented by a mean of 0, and the covariance matrix be... The Gaussian distribution.

[0083] The covariance matrix and For adaptive and dynamic adjustment, the specific adjustment method is as follows:

[0084] ;in, This is the forgetting factor, with a value ranging from 0.95 to 0.99. To predict residuals; ;in, The forgetting factor ranges from 0.97 to 0.995, and the state vector update amount is used. The Kalman filter adopts a progressive structure, first estimating and compensating for ionospheric delay, then estimating and compensating for multipath error, and finally estimating position, velocity, and receiver clock error parameters.

[0085] The method also includes a signal quality assessment step for BeiDou B1I, B1C, and B2a tri-frequency signals, calculating signal quality using the following indicators:

[0086] ;

[0087] Wherein, it represents the first Quality indicators of signals in each frequency band The preset maximum carrier-to-noise ratio threshold is set to 50 dBHz. This represents the multipath intensity estimate. This represents the rate of change of the ionosphere, measured in TECU / minute. and represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate, respectively; , , Indicates the weighting coefficient. , , When signal quality indicators When the value is below 0.3, the corresponding frequency band signal will be removed.

[0088] The signal quality metrics are used for observation weighting and satellite selection: ;in, The observation weights are E, where E is the satellite elevation angle in radians; when the signal quality index... When the value is below 0.3, the corresponding frequency band signal will be removed to avoid the adverse effect of low-quality signal on the positioning solution.

[0089] 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, achieved a horizontal positioning accuracy of 2.5 meters and a vertical accuracy of 3.8 meters, which is about 65% higher than traditional methods.

[0090] Example 2

[0091] like Figure 2 The diagram shows the components 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 multi-path ionosphere discrimination module, and an error correction module.

[0092] 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 signals from the B1I, B1C, and B2a bands. The radio frequency front-end unit amplifies and filters the signals from each band. The digital signal processing unit converts analog signals into digital signals and performs baseband processing.

[0093] The observation extraction module is used to extract pseudorange and carrier phase observations from the received signal. The observation extraction module includes a navigation message decoding unit, a pseudorange calculation unit, and a carrier phase calculation unit. The navigation message decoding unit parses the satellite clock and orbit parameters, the pseudorange calculation unit calculates the pseudorange value based on code correlation technology, and the carrier phase calculation unit tracks and measures the carrier phase through phase-locked loop technology.

[0094] The wavelet decomposition module is used to perform wavelet transform decomposition on multi-frequency band observations. The wavelet decomposition module includes a filtering preprocessing unit, a wavelet coefficient calculation unit, and a multi-scale analysis unit. The filtering preprocessing unit performs low-pass filtering on the original observations to reduce high-frequency noise interference. The wavelet coefficient calculation unit implements the discrete wavelet transform algorithm. The multi-scale analysis unit analyzes the time-frequency characteristics of the wavelet coefficients.

[0095] The multipath ionospheric discrimination module is used to construct a discriminator and perform error source classification. The multipath ionospheric discrimination module includes a discriminator construction unit, a threshold calculation unit, and a classification decision unit. 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 dominant error type based on the comparison result between the discrimination value and the threshold.

[0096] The error correction module is used to select an appropriate algorithm to eliminate errors based on the discrimination result. The error correction module includes a wavelet filtering unit, a three-frequency combination unit, and an adaptive filtering unit. The wavelet filtering unit is used for multipath error elimination, the three-frequency combination unit is used for ionospheric delay elimination, and the adaptive filtering unit is used for joint estimation of coupling effects.

[0097] The positioning solution module is used to calculate the receiver position based on the corrected observations. The positioning solution module includes a least squares estimation unit, a weighted solution unit, and a quality control unit. The least squares estimation unit is used to calculate the initial position solution. The weighted solution unit weights the observations according to the signal quality index. The quality control unit monitors the reliability of the solution results and removes outliers.

[0098] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment 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 within 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, receiving multi-band signals from a single Beidou satellite, the multi-band including three frequency bands of B1I, B1C and B2a, extracting pseudo-range measurement values and carrier phase measurement values of each frequency band signal, and constructing an observation value model containing multipath error and ionospheric delay; The observation model is expressed as: ; wherein, and represent the pseudorange and carrier phase observations of the receiver to the Beidou satellite ; represents the geometric range; represents the speed of light; represents the receiver clock bias; represents the satellite clock bias; represents the tropospheric delay; represents the ionospheric delay; represents the pseudorange multipath error; represents the carrier phase multipath error; represents 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 characteristics at different frequency scales, and based on the wavelet decomposition result, constructing a multipath-ionosphere coupling separation discriminator using the characteristics difference and frequency dependence of pseudo-range and carrier phase observation values; The expression of the wavelet transform decomposition on the multi-band observation value sequence is: ; wherein denotes a wavelet coefficient of a pseudorange or carrier phase signal; denotes an original pseudorange or carrier phase time domain signal; denotes a wavelet mother function; denotes a scale parameter; denotes a translation parameter; The expression of the multipath-ionosphere coupling separation discriminator is: ; wherein, represents a multi-path ionosphere coupling separation discrimination value; represents a wavelet coefficient of a pseudo-range signal of an th frequency point; represents a wavelet coefficient of a carrier phase signal of an th frequency point; represents a carrier frequency of an th frequency band; represents a weight coefficient of a carrier phase and a pseudo-range; represents a number of frequency bands, ; Step S3, determining the error dominant type according to the size of the discrimination value output by the separation discriminator, and respectively applying corresponding error correction strategies to correct the observation values, and using the corrected observation values for position solution to obtain a high-precision positioning result; Determining the error dominant type according to the size of the discrimination value output by the separation discriminator is specifically: When , it is determined that multipath effects dominate; when , it is determined that ionospheric delay dominates; when , it is determined that coupling effects dominate; where and are preset threshold values; For the case of multipath dominance, wavelet threshold filtering is applied for multipath elimination, for the case of ionospheric dominance, three-frequency combination is applied to eliminate ionospheric first-order effects, and for the coupling effect, adaptive filtering is applied for joint estimation and elimination.

2. The method of claim 1, wherein, The mother wavelet function The expression is: ; wherein, represents the number of wavelet filter coefficients, the higher the value of the frequency resolution, and vice versa, the value of is an even number between 4 and 20; represents the low-pass filter coefficients, represents a scaling function, satisfying: .

3. The method of claim 2, wherein, The weight coefficient of the carrier phase and the pseudo range Determined by the following way: ; wherein, Indicates the pseudo range measurement noise variance, the unit is square meter, which is evaluated by the receiver noise level, and the typical value range is 0.25 to 4 square meters; denotes the carrier phase measurement noise variance in square weeks, with a typical value range of to square weeks; denotes the carrier wavelength in meters.

4. The method of claim 3, wherein, Preset threshold and Dynamically adjusted based on signal-to-noise ratio: ; ;in, It represents the carrier-to-noise ratio, which is the weighted average of the carrier-to-noise ratios of multi-band signals, and the unit is dBHz; , The slope parameter has values ​​ranging from 1.2 to 2.0 and from 0.3 to 0.8, respectively. , These are bias parameters, with values ​​ranging from 0.8 to 1.5 and from 0.2 to 0.5, respectively. The calculation formula is: ,in For the first Weights of each frequency band.

5. The method of claim 4, wherein, For the case of multipath dominance, wavelet threshold filtering is applied for multipath mitigation, and the wavelet threshold filtering adopts an adaptive threshold : ; wherein denotes the noise standard deviation estimate, calculated by the absolute median difference MAD of the wavelet coefficients: , wherein is the wavelet coefficient of the decomposition; denotes the number of samples, i.e. the number of sampling points within the observation window.

6. The method of claim 5, wherein, For ionosphere dominant case, the first order ionosphere effect is eliminated by using triple-frequency combination, and the geometry ionosphere-free combination is constructed by triple-frequency combination algorithm : ； wherein, , , represents the pseudo-range observation value of three frequency bands, in meters, corresponding to the Beidou B1I, B1C and B2a frequency bands; , , represents the corresponding carrier frequency, in Hz, corresponding to the Beidou B1I, B1C and B2a frequency bands.

7. The method of claim 1, wherein, For coupling effects, adaptive filtering is applied for joint estimation and cancellation, the state equation of the filtering algorithm : , the observation equation : ; wherein the state vector contains position, velocity, receiver clock bias, multipath parameter and ionosphere parameter: ; represents the state transition matrix, which is a block diagonal matrix, wherein the position and velocity parts adopt the uniform motion model, the receiver clock bias part adopts the second-order Markov process, the multipath parameter part adopts the first-order Gauss Markov process, and the ionosphere parameter part adopts the random walk model; represents the observation matrix, which associates the state vector with the observation vector, and the elements thereof are determined by the satellite position, the receiver position and the carrier frequency of each frequency band; represents the process noise, which is assumed to follow a Gaussian distribution with a mean of 0 and a covariance matrix ; represents the observation noise, which is assumed to follow a Gaussian distribution with a mean of 0 and a covariance matrix .

8. The method of claim 1, wherein, It also includes a Beidou B1I, B1C and B2a three-frequency signal quality evaluation step, and the signal quality is calculated through the following indexes: ； in, Indicates the first Quality indicators of signals in each frequency band The preset maximum carrier-to-noise ratio threshold is set to 50 dBHz. This represents the multipath intensity estimate. This represents the rate of change of the ionosphere, measured in TECU / minute. and These represent the historical maximum multipath intensity estimate and the historical maximum ionospheric change rate, respectively. , , Indicates the weighting coefficient. , , When signal quality indicators When the value is below 0.3, the corresponding frequency band signal will be removed.

9. A high-precision positioning system based on multi-band single Beidou signal, used for executing the method in any one of claims 1 to 8, characterized in that, The system comprises: a signal receiving module, an observation value extraction module, a wavelet decomposition module, a multipath-ionosphere discrimination module and an error correction module; The signal receiving module is used for receiving multi-band signals from a single Beidou satellite, and the signal receiving module comprises a multi-band antenna unit, a radio frequency front-end unit and a digital signal processing unit, wherein the multi-band antenna unit can simultaneously receive B1I, B1C and B2a frequency band signals, the radio frequency front-end unit amplifies and filters each frequency band signal, and the digital signal processing unit converts the analog signal into a digital signal and performs baseband processing; The observation value extraction module is used for extracting pseudo-range and carrier phase observation values from the received signals, and the observation value extraction module comprises a navigation message decoding unit, a pseudo-range calculation unit and a carrier phase calculation unit, wherein the navigation message decoding unit analyzes satellite clock and orbit parameters, the pseudo-range calculation unit calculates pseudo-range values based on code correlation technology, and the carrier phase calculation unit tracks and measures carrier phase through a phase-locked loop technology; The wavelet decomposition module is used for wavelet transform decomposition on the multi-band observation value, and the wavelet decomposition module comprises a filtering preprocessing unit, a wavelet coefficient calculation unit and a multi-scale analysis unit, wherein the filtering preprocessing unit performs low-pass filtering on the original observation value 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 multi-path ionosphere discrimination module is configured to construct a discriminator and perform error source classification, and comprises 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 value based on a signal-to-noise ratio, and the classification decision unit determines an error dominant type according to a comparison result of the discrimination value and the threshold value; The error correction module is configured to select a suitable algorithm to eliminate errors according to a discrimination result, and comprises a wavelet filtering unit, a three-frequency combination unit and an adaptive filtering unit, wherein the wavelet filtering unit is configured to eliminate multi-path errors, the three-frequency combination unit is configured to eliminate ionosphere delay, and the adaptive filtering unit is configured to jointly estimate coupling effects.

10. The system of claim 9, wherein, The system further comprises a positioning solution module configured to calculate a receiver position based on the corrected observation values, and the positioning solution module comprises a least squares estimation unit, a weighted solution unit and a quality control unit, wherein the least squares estimation unit is configured to calculate an initial position solution, the weighted solution unit is configured to weight the observation values according to a signal quality index, and the quality control unit is configured to monitor the reliability of a solution result and eliminate outliers.

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