CN114355417B - Three-frequency cycle-slip detection repair method considering pseudo-range multipath, track and data type - Google Patents
Three-frequency cycle-slip detection repair method considering pseudo-range multipath, track and data type Download PDFInfo
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Abstract
The invention discloses a three-frequency cycle-slip detection repair method taking account of pseudo-range multipath, orbit and data types, which comprises the steps of (1) extracting original observation values of a navigation system as original pseudo-ranges, carrier phases and signal-to-noise ratios; preprocessing the original observed values in the step (2): step (3), performing cycle slip detection on the preprocessed observed value; step (4) cycle slip repair; and (5) outputting the repaired observed value. The invention carries out preprocessing on the original observed value from the observation layer, adopts a self-adaptive threshold wavelet packet filtering denoising model based on signal-to-noise ratio constraint to filter random noise, and simultaneously adopts a altitude model based on orbit-division satellite to correct the satellite-end pseudo-range multipath error, thereby reducing the influence of the satellite-end pseudo-range multipath error. And finally, carrying out self-adaptive threshold detection on the detection quantity from the detection layer, reducing the cycle slip false detection rate and improving the detection accuracy.
Description
Technical Field
The invention relates to the technical field of satellite navigation positioning, in particular to a three-frequency cycle slip detection and repair method considering pseudo-range multipath, orbit and data types.
Background
In GNSS high-precision positioning, the precision of the carrier phase directly determines the positioning precision of the final result. The observed quality of the carrier phase has a direct impact on the accuracy of the carrier phase. Therefore, the quality assurance for the observed quantity of the carrier phase is a precondition of high-precision positioning and is one of key research technologies of high-precision positioning. The carrier phase observation value is mainly influenced by cycle slip, and the accuracy of the observation value is sharply reduced due to false detection or repair inaccuracy of the cycle slip, and the parameter estimation error is increased, so that the convergence time and the final positioning accuracy of a subsequent algorithm are influenced. Therefore, detection and repair for cycle slips are the basis for high-precision positioning of GNSS. In addition, the three-frequency cycle slip detection and repair algorithm is researched according to the characteristic that the Beidou satellite navigation system directly broadcasts three-frequency data to a user, so that the method is more suitable for the Beidou navigation system and is also suitable for future multi-frequency multi-system positioning.
At present, a cycle slip detection and repair algorithm based on a three-frequency observation value mainly comprises a code phase combination method, a geometric phase-free combination method, a classification least square method, a mixed phase pseudo-range combination method and the like. However, the code phase combining method and the mixed phase pseudo-range combining method are greatly affected by random noise of observed values and pseudo-range multipath, so that the existing code phase combining method cannot accurately detect and repair small cycle slips. The complexity of the geometric phase combination method is high, and the cycle slip detection instantaneity is low. The classification least square method is only suitable for low-altitude angle satellites and has poor universality.
In addition, the existing cycle slip detection and repair algorithm is mainly researched and improved from a detection layer to an algorithm, and influence on an observation layer is ignored. Meanwhile, the influence of different multi-orbit types of Beidou satellites and different sampling rates of receivers is not considered in the existing algorithm. Considering that the Beidou navigation system is a full three-frequency and multi-orbit satellite type system, a new three-frequency-based Beidou cycle slip detection and repair algorithm is researched, the cycle slip detection accuracy and success rate are improved, and the method has important research significance for high-precision positioning of the Beidou satellite navigation system.
Disclosure of Invention
According to the defects of the prior art, the invention provides a three-frequency cycle slip detection repair method considering pseudo-range multipath, orbit and data types, which can preprocess an original observed value from an observed layer, filter and denoise the original observed value by adopting a self-adaptive threshold wavelet packet filter and denoise model based on signal-to-noise ratio constraint, filter out random noise errors and improve cycle slip detection success rate.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the three-frequency cycle-slip detection and repair method considering pseudo-range multipath, track and data type comprises the following steps of
Extracting an original observed value of a navigation system as an original pseudo-range, a carrier phase and a signal-to-noise ratio;
preprocessing the original observed values in the step (2):
step (2-1), filtering and denoising the original carrier phase and pseudo-range observation value based on adaptive threshold wavelet packet transformation of signal-to-noise ratio constraint, and filtering high-frequency random noise;
step (2-2) performing satellite-end pseudo-range multipath bias correction on the original pseudo-range observation value based on the altitude model corrected by the orbit-dividing satellites respectively;
step (3), performing cycle slip detection on the preprocessed observed value;
step (4) cycle slip repair;
and (5) outputting the repaired observed value.
Preferably, the step (2-1) includes:
1) Selecting a proper wavelet base and constructing a binary discrete orthogonal wavelet packet transformation function;
2) Denoising based on the signal-to-noise ratio;
3) And carrying out signal reconstruction on the denoised wavelet packet coefficient, and outputting a denoised observation value.
Preferably, the step (2-2) includes:
1) Three-frequency observation data are collected by adopting observation stations widely distributed in the world, and on the basis, a pseudo-range multipath deviation model of a satellite terminal is extracted through a carrier pseudo-range multipath deviation combination model;
2) Denoising the collected data, eliminating the influence of combined amplified noise errors, only keeping the deviation amount related to the altitude angle, distinguishing and sequencing the data according to the altitude angle, and fitting the denoised data by adopting a third-order polynomial fitting model;
3) And calculating the altitude of the observation epoch, calculating the pseudo-range deviation of the observation epoch by using the altitude correction model, and correcting the deviation of the corresponding epoch, thereby obtaining the pseudo-range observation value with higher precision.
Preferably, the step (3) includes:
step (3-1) performing three-frequency combination on the accurate observed values pretreated in the step (2) to respectively form three combined observed values of an ultra-wide lane, a wide lane and a narrow lane;
step (3-2) detecting the current observation epoch by taking the three-frequency combined ultra-wide lane combination and the wide lane combination as a first cycle slip detection quantity and a second cycle slip detection quantity;
and (3-3) performing cycle slip detection on the cycle slip detection observed quantity of the third combined narrow lane by adopting the self-adaptive threshold strategy.
Preferably, the step (4) includes:
step (4-1) can effectively detect all cycle slip values through cycle slip detection in step (3), and marks in cycle slip epochs;
in the step (4-2), when three cycle slip detection amounts are detected, the detected combined cycle slip can be effectively calculated, the three combined cycle slips are jointly solved, and the cycle slip value on each frequency can be effectively solved, wherein the solution formula is as follows:
the ambiguity solution of the combined observed value in the above formula can be obtained during cycle slip detection, so that cycle slip values of three frequencies can be respectively calculated, the calculated values are floating point solutions, and then accurate cycle slip values can be obtained through rounding operation;
and (4-3) repairing the cycle slip occurrence epoch by the calculated accurate cycle slip value, updating and storing the subsequent observed value, repeating the process, repairing each cycle slip occurrence epoch observed value, and finally repairing all detected cycle slip epochs effectively.
Preferably, the step (2-1) selects a dB4 wavelet base as a mother function of wavelet packet transformation, and constructs a binary discrete orthogonal wavelet packet transformation function, where the formula is:
preferably, the step (2-1) uses an adjustable threshold strategy based on signal-to-noise ratio weighting to perform denoising, and the expression is:
wherein d j，k Andthe wavelet coefficients and quantized wavelet coefficients, respectively, J represents the current wavelet layer for adjusting the wavelet threshold coefficient, λ is the wavelet threshold, expressed as:
where CNR represents the current average signal-to-noise ratio of the denoising data.
Preferably, in the step (3-3), the threshold value of cycle slip detection needs to be adaptively set, and the specific expression is as follows:
|ΔN (2,-1,0) |>K
wherein K is a threshold weighting coefficient, and in practical application, the weighting coefficient is selected according to the following rule
Where T is the observed data sampling rate, and T generally defaults to a data sampling rate of 15 s.
Preferably, in the step (2-2), the combination model of the multi-path deviation of the beidou carrier pseudo range is expressed as:
where P and φ are the raw pseudorange and carrier phase observations, respectively, and α is expressed asB represents a fixed amount of deviation including ambiguity, which can be eliminated by smoothing;
the fitting formula is expressed as:
wherein E represents the altitude angle of the current epoch observation, b k Represented are polynomial fitting coefficients.
Preferably, in the step (3-1), the three combined observations of the ultra-wide lane, the wide lane and the narrow lane have the following combined coefficients: (0, 1, -1), (1, 0, -1) and (2, -1, 0), the combined model is as follows:
φ c ＝αφ b1 +βφ b2 +γφ b3
wherein, alpha, beta and gamma are respectively the combination coefficients of three frequency bands, phi b1 ，φ b2 And phi b3 And representing the original carrier observation values of the Beidou three frequency bands.
The invention has the following characteristics and beneficial effects:
by adopting the technical scheme, the influence condition of random bath and pseudo-range multipath on the detection and repair of the three-frequency cycle slip is considered, so that the self-adaptive threshold wavelet packet transformation based on the signal-to-noise ratio constraint is adopted to carry out filtering treatment on the original observed value, the error level of the observed value is effectively reduced, and the detection and repair accuracy of the cycle slip is improved. Meanwhile, the altitude model based on orbit division and satellite division is adopted to correct the satellite end pseudo-range multipath error, so that the influence of the satellite end pseudo-range multipath error is reduced, and the detection success rate of small cycle slip is improved. Aiming at cycle slip detection, the Zhou Tiaojin lines are detected by adopting a self-adaptive threshold adjustment strategy based on the track type and the data sampling rate aiming at different track types and data sampling rates, so that the problem of higher cycle slip false detection rate under normal threshold detection is effectively avoided, and the cycle slip detection accuracy is improved. Finally, by combining three combined detection amounts, the large cycle slip, the small cycle slip and the special combined cycle slip can be effectively detected and repaired, the defects that the false detection rate is high and the small cycle slip detection and repair success rate is low due to random noise, pseudo-range errors and fixed threshold detection in the existing method are overcome, and the small cycle slip detection and repair accuracy and success rate are improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of a three-frequency cycle-slip detection and repair algorithm that accounts for pseudorange multipath, orbit, and data type.
Fig. 2 is a flow chart of an adaptive threshold wavelet packet denoising model based on signal-to-noise ratio constraints.
FIG. 3 is a flow chart of altitude model pseudorange multipath error correction based on separate correction of satellite-by-satellite.
FIG. 4 is a flow chart of an adaptive threshold detection algorithm that takes into account satellite type and data sampling rate.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
The invention provides a three-frequency cycle-slip detection and repair method considering pseudo-range multipath, track and data type, as shown in figure 1, comprising the following steps of
Extracting an original observed value of a navigation system as an original pseudo-range, a carrier phase and a signal-to-noise ratio;
preprocessing the original observed values in the step (2):
step (3), performing cycle slip detection on the preprocessed observed value;
step (4) cycle slip repair;
and (5) outputting the repaired observed value.
In the technical scheme, the original observed value is directly preprocessed from the observed layer, so that the success rate of the late cycle slip detection is greatly improved.
It should be noted that, the technical scheme disclosed in this embodiment is based on the Beidou satellite, but is not limited to the use of the Beidou satellite.
Further, the step (2) comprises
Step (2-1) filtering and denoising the original carrier phase and the pseudo-range observation value based on adaptive threshold wavelet packet transformation of signal-to-noise ratio constraint, wherein the filtering and denoising treatment is mainly used for filtering high-frequency random noise aiming at the influence of the random noise and ensuring the precision of the pseudo-range and the carrier phase observation value;
and (2-2) correcting satellite-end pseudo-range multipath bias on the original pseudo-range observation value based on the altitude model corrected by the orbit-dividing satellites, and extracting a high-precision pseudo-range observation value mainly aiming at the influence of the satellite-end pseudo-range multipath error.
According to the technical scheme, the influence condition of random bath and pseudo-range multipath on the detection and repair of the three-frequency cycle slip is considered, so that the self-adaptive threshold wavelet packet transformation based on the signal-to-noise ratio constraint is adopted to carry out filtering treatment on the original observed value, the error level of the observed value is effectively reduced, and the detection and repair accuracy of the cycle slip is improved. Meanwhile, the altitude model based on orbit division and satellite division is adopted to correct the satellite end pseudo-range multipath error, so that the influence of the satellite end pseudo-range multipath error is reduced, and the detection success rate of small cycle slip is improved.
Specifically, as shown in FIG. 2, the step (2-1) is
1) Selecting proper wavelet base and constructing binary discrete orthogonal wavelet packet transformation function,
it will be appreciated that the appropriate wavelet basis and corresponding wavelet packet transform function are selected based on signal characteristics. Since the GNSS signals are processed in this embodiment, their signal frequencies and noise characteristics are suitable for the dB4 wavelet basis, therefore, this patent selects the dB4 wavelet basis as the mother function of wavelet packet transformation.
2) Denoising is performed based on the signal-to-noise ratio, and because the signal is a discrete signal, a binary discrete orthogonal wavelet packet transformation function is constructed, and the formula is:
it can be understood that, since the wavelet packet transform denoising mainly depends on the selection of the threshold, and the correlation between the signal-to-noise ratio of the signal and the noise is strong, denoising is performed by adopting an adjustable threshold strategy based on signal-to-noise ratio weighting in this embodiment, which is expressed as:
wherein d j，k Andthe wavelet coefficients and quantized wavelet coefficients, respectively. J denotes the current wavelet layer, used to adjust the wavelet threshold coefficients. λ is the wavelet threshold, expressed as:
where CNR represents the current average signal-to-noise ratio of the denoising data.
It can be seen that if the signal-to-noise ratio is lower, the denoising threshold value is smaller, so that noise is better filtered, and the signal precision is improved.
3) And carrying out signal reconstruction on the denoised wavelet packet coefficient, and outputting a denoised observation value.
Specifically, as shown in fig. 3, the step (2-2) includes:
1) And (3) acquiring Beidou three-frequency observation data, in particular Beidou second-generation observation data, by adopting MGEX (Multi-GNSS Experiment) observation stations widely distributed in the world. On the basis, a pseudo-range multipath deviation model of a Beidou satellite end is extracted through a carrier pseudo-range multipath deviation combination model, and the Beidou carrier pseudo-range multipath deviation combination model is expressed as:
where P and φ are the raw pseudorange and carrier phase observations, respectively, and α is expressed asB represents a fixed amount of deviation including ambiguity, and can be eliminated by smoothing.
2) Denoising the collected data, eliminating the influence of combined amplified noise errors, only keeping the deviation amount related to the altitude angle, distinguishing and sorting the data according to the altitude angle, and fitting the denoised data by adopting a third-order polynomial fitting model, wherein the fitting model is expressed as:
where E represents the altitude of the current epoch observations. b k Represented are polynomial fitting coefficients. It should be noted that, here, the satellite is separately modeled as a satellite-orbit satellite, so as to improve the accuracy of the pseudo-range observation value of each satellite.
3) Calculating the altitude of the observation epoch, calculating the pseudo-range deviation of the observation epoch by using the altitude correction model, and correcting the deviation of the corresponding epoch, thereby obtaining a pseudo-range observation value with higher precision, and further laying a foundation for improving the precision of the follow-up cycle slip detection.
As shown in fig. 4, the step (3) further includes:
step (3-1) performing three-frequency combination on the accurate observed values pretreated in the step (2) to respectively form three combined observed values of an ultra-wide lane, a wide lane and a narrow lane;
wherein, three kinds of combination observations in ultra wide lane, wide lane and narrow lane, its combination coefficient is respectively: (0, 1, -1), (1, 0, -1) and (2, -1, 0), the combined model is as follows:
φ c ＝αφ b1 +βφ b2 +γφ b3 (6)
wherein, alpha, beta and gamma are respectively the combination coefficients of three frequency bands, phi b1 ，φ b2 And phi b3 And representing the original carrier observation values of the Beidou three frequency bands.
And (3-2) adopting a three-frequency combination ultra-wide lane (0, 1-1) combination and a wide lane (1, 0-1) as a first cycle slip detection quantity and a second cycle slip detection quantity to detect the current observation epoch, wherein the step can effectively detect large cycle slips and some cycle slips with medium size. The detected cycle slip epoch is marked. And simultaneously, storing the estimated value detected by cycle slip.
And (3-3) performing cycle slip detection on the cycle slip detection observed quantity of the third combined narrow lane by adopting the self-adaptive threshold strategy.
Specifically, the cycle slip detection is carried out on the cycle slip detection observed quantity of the third combined narrow lane (2, -1, 0) by adopting an adaptive threshold strategy. In order to avoid the influence of ionospheric delay fluctuation on cycle slip detection as much as possible, a three-frequency combination with the minimum ionospheric delay coefficient, namely (2, -1, 0) combination is adopted, and the influence of the ionosphere can be minimized at the moment, so that the cycle slip detection success rate is improved, and the method is specifically expressed as:
where η represents the ionospheric delay amplification factor. It can be seen that although the above combination can reduce the residual ripple caused by ionospheric delay errors to some extent, there is still a small residual value. Therefore, further processing is required, especially when the receiver sampling interval is large. Therefore, the cycle slip detection threshold setting process needs to be performed on equation (7). Normally, the cycle slip detection threshold is set to 0.5 weeks. However, considering the difference of satellite characteristics of the beidou satellite in different satellite orbits, for example, the GEO satellite is a stationary orbit satellite, when the receiver is also in a stationary state, the random error fluctuation is very small, so the detection threshold should be properly reduced. Furthermore, when the sampling interval is large, the detection threshold should be enlarged in consideration of the influence of ionospheric delay errors. Therefore, the threshold value needs to be adaptively set here, which is specifically expressed as:
|ΔN (2,-1,0) |＞K (8)
where K is a threshold weighting coefficient. In practical application, the weighting coefficients are selected according to the following rule
Where T is the observed data sampling rate, and T generally defaults to a data sampling rate of 15 s. It can be seen that when the data sampling rate is less than 15s, it is shown that the receiver data frequency is relatively high, the time interval is reduced and the ionospheric error delay is small. Therefore, cycle slip can be effectively detected by using 0.5 week as a detection threshold. When the sampling interval is larger, the judgment threshold value must be increased appropriately, otherwise, erroneous judgment is generated.
It will be appreciated that S then represents a different satellite type. Because the GEO is a static satellite, the error is small, so the cycle slip detection for the GEO satellite needs to reduce the cycle slip detection threshold value, and the success rate of the cycle slip detection is ensured. For IGSO and MEO satellites, the detection threshold is improved because of larger errors, the cycle slip false detection rate is reduced, and finally the cycle slip detection accuracy and success rate are ensured.
Further, the step (4) includes:
step (4-1) can effectively detect all cycle slip values through cycle slip detection in step (3), and marks in cycle slip epochs;
in the step (4-2), when three cycle slip detection amounts are detected, the detected combined cycle slip can be effectively calculated, the three combined cycle slips are jointly solved, the cycle slip value on each frequency can be effectively solved, and the solution model is as follows:
the ambiguity solution of the combined observed value in the above formula can be obtained during cycle slip detection, so that cycle slip values of three frequencies can be respectively calculated, the calculated values are floating point solutions, and then accurate cycle slip values can be obtained through rounding operation;
and (4-3) repairing the cycle slip occurrence epoch by the calculated accurate cycle slip value, updating and storing the subsequent observed value, repeating the process, repairing each cycle slip occurrence epoch observed value, and finally repairing all detected cycle slip epochs effectively.
According to the technical scheme, for cycle slip detection, the Zhou Tiaojin line is detected by adopting the self-adaptive threshold adjustment strategy based on the track type and the data sampling rate for different track types and data sampling rates, so that the problem of higher cycle slip false detection rate under normal threshold detection is effectively avoided, and the cycle slip detection accuracy is improved. Finally, by combining three combined detection amounts, the large cycle slip, the small cycle slip and the special combined cycle slip can be effectively detected and repaired, the defects that the false detection rate is high and the small cycle slip detection and repair success rate is low due to random noise, pseudo-range errors and fixed threshold detection in the existing method are overcome, and the small cycle slip detection and repair accuracy and success rate are improved.
The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments, including the components, without departing from the principles and spirit of the invention, yet fall within the scope of the invention.
Claims (6)
1. The three-frequency cycle-slip detection and repair method taking account of pseudo-range multipath, track and data type is characterized by comprising the following steps of
Extracting an original observed value of a navigation system as an original pseudo-range, a carrier phase and a signal-to-noise ratio;
preprocessing the original observed values in the step (2):
step (2-1) filtering and denoising the original carrier phase and pseudo-range observation value based on adaptive threshold wavelet packet transformation of signal-to-noise ratio constraint, and filtering high-frequency random noise, wherein the specific method comprises the following steps:
1) Selecting a proper wavelet base and constructing a binary discrete orthogonal wavelet packet transformation function;
2) Denoising based on the signal-to-noise ratio;
3) Carrying out signal reconstruction on the denoised wavelet packet coefficient, and outputting a denoised observation value;
and (2-2) correcting satellite-end pseudo-range multipath deviation of an original pseudo-range observation value based on a altitude model corrected by the orbit-dividing satellites, wherein the method comprises the following steps of:
1) Three-frequency observation data are collected by adopting observation stations widely distributed in the world, and on the basis, a pseudo-range multipath deviation model of a satellite terminal is extracted through a carrier pseudo-range multipath deviation combination model;
2) Denoising the collected data, eliminating the influence of combined amplified noise errors, only keeping the deviation amount related to the altitude angle, distinguishing and sequencing the data according to the altitude angle, and fitting the denoised data by adopting a third-order polynomial fitting model;
3) Calculating the altitude of an observation epoch, calculating the pseudo-range deviation of the observation epoch by using the altitude correction model, and correcting the deviation of the corresponding epoch, thereby obtaining a pseudo-range observation value with higher precision;
and (3) performing cycle slip detection on the preprocessed observed value, wherein the specific method comprises the following steps of:
step (3-1) performing three-frequency combination on the accurate observed values pretreated in the step (2) to respectively form three combined observed values of an ultra-wide lane, a wide lane and a narrow lane;
step (3-2) detecting the current observation epoch by taking the three-frequency combined ultra-wide lane combination and the wide lane combination as a first cycle slip detection quantity and a second cycle slip detection quantity;
step (3-3) performing cycle slip detection on the cycle slip detection observed quantity of the third combined narrow lane by adopting the self-adaptive threshold strategy,
the specific expression is as follows:
|αN (2,-1,0) |＞K
wherein K is a threshold weighting coefficient, and in practical application, the weighting coefficient is selected according to the following rule
Wherein T is the observed data sampling rate, and T generally defaults to a data sampling rate of 15 s;
step (4) cycle slip repair;
and (5) outputting the repaired observed value.
2. The method of three-frequency cycle-slip probe repair taking account of pseudorange multipath, orbit and data type of claim 1, wherein said step (4) comprises:
step (4-1) can effectively detect all cycle slip values through cycle slip detection in step (3), and marks in cycle slip epochs;
in the step (4-2), when three cycle slip detection amounts are detected, the detected combined cycle slip can be effectively calculated, the three combined cycle slips are jointly solved, the cycle slip value on each frequency can be effectively solved, and the solution model is as follows:
the ambiguity solution of the combined observed value in the above formula can be obtained during cycle slip detection, so that cycle slip values of three frequencies can be respectively calculated, the calculated values are floating point solutions, and then accurate cycle slip values can be obtained through rounding operation;
and (4-3) repairing the cycle slip occurrence epoch by the calculated accurate cycle slip value, updating and storing the subsequent observed value, repeating the process, repairing each cycle slip occurrence epoch observed value, and finally repairing all detected cycle slip epochs effectively.
3. The method of three-frequency cycle slip detection and repair taking account of pseudo-range multipath, orbit and data type as claimed in claim 1, wherein said step (2-1) selects dB4 wavelet basis as a mother function of wavelet packet transformation and constructs a binary discrete orthogonal wavelet packet transformation function with the formula:
4. the method of three-frequency cycle-slip probe repair taking account of pseudorange multipath, orbit and data type according to claim 3, wherein the step (2-1) uses an adjustable threshold strategy based on signal-to-noise ratio weighting for denoising, and the expression is:
wherein d j，k Andthe wavelet coefficients and quantized wavelet coefficients, respectively, J represents the current wavelet layer for adjusting the wavelet threshold coefficient, λ is the wavelet threshold, expressed as:
where CNR represents the current average signal-to-noise ratio of the denoising data.
5. The method of three-frequency cycle-slip sounding repair taking account of pseudorange multipaths, orbits and data types of claim 1, wherein in step (2-2), the carrier pseudorange multipath bias combination model is expressed as:
where P and φ are the raw pseudorange and carrier phase observations, respectively, and α is expressed asB represents a fixed amount of deviation including ambiguity, which can be eliminated by smoothing;
the fitting formula is expressed as:
wherein E represents the altitude angle of the current epoch observation, b k Represented are polynomial fitting coefficients.
6. The method of three-frequency cycle-slip detection and repair according to claim 1, wherein in the step (3-1), three combined observations of ultra-wide lane, wide lane and narrow lane have the following combination coefficients: (0, 1, -1), (1, 0, -1) and (2, -1, 0), the combined formula is as follows:
φ c ＝αφ b1 +βφ b2 +γφ b3
wherein, alpha, beta and gamma are respectively the combination coefficients of three frequency bands, phi b1 ，φ b2 And phi b3 And representing the original carrier observation values of the Beidou three frequency bands.
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