A deformation monitoring method for pseudo-satellite assisted DBD

Abstract

The present invention relates to a deformation monitoring method for pseudo-satellite assisted DBD, comprising the following steps: receiving pseudo-satellite signals and BDS satellite signals through a receiver and classifying them; screening and eliminating the pseudo-satellite signals and BDS signals; selecting the main satellite; constructing double-difference carrier observation equations and double-difference pseudo-range observation equations and performing least squares solution to obtain a floating-point solution; selecting a partial ambiguity-fixed subset; fixing partial ambiguities; and RTK position solution. By using pseudo-satellites to assist the Beidou satellite system for positioning, the position dilution of precision is reduced, the geometric configuration of the satellites is improved, and the positioning accuracy and reliability of deformation monitoring are ensured.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping science and technology, and particularly to a deformation monitoring method for pseudo-satellite assisted DBD. Background Art

[0002] With the construction of modern infrastructure, especially for some facilities with complex structures, GNSS positioning technology is required for deformation monitoring to ensure safety. However, in practical applications, due to the influence of complex surrounding environments on GNSS measurement stations, it is inevitable that the surrounding environment of the measurement station is not good, resulting in insufficient observable satellite numbers, poor satellite geometric configurations, reduced positioning accuracy, measurement errors of GNSS signals, thereby reducing the fixation rate of integer ambiguities and the accuracy of positioning. With China's strong promotion of the use of the single Beidou satellite positioning system, it is difficult to achieve the accuracy requirements for monitoring with a single Beidou satellite positioning system in complex environments. Sufficient satellite numbers and good satellite geometric configurations are the prerequisites for ensuring high-precision RTK relative positioning, which can effectively make up for the shortage of Beidou satellites and improve positioning accuracy, providing more accurate data support for reservoir dam deformation monitoring. Therefore, the present invention is to improve positioning accuracy by constructing pseudo-satellites in the surrounding area under harsh environments. However, in the actual application process, the existing main reference satellite selection strategies mainly select through elevation angles, carrier-to-noise ratios, etc., but they are not applicable in the pseudo-satellite system. For this reason, the present invention constructs a deformation monitoring method applicable to pseudo-satellite assisted DBD. Summary of the Invention

[0003] Aiming at the shortcomings of the above-mentioned prior art, the purpose of the present invention is to provide a deformation monitoring method for pseudo-satellite assisted DBD to solve one or more problems in the prior art.

[0004] To achieve the above purpose, the technical solution of the present invention is as follows:

[0005] A deformation monitoring method for pseudo-satellite assisted DBD includes the following steps: receiving pseudo-satellite signals and BDS satellite signals and classifying them; screening and eliminating pseudo-satellite signals and BDS satellite signals; selecting the main satellite; constructing double-difference carrier observation equations and double-difference pseudorange observation equations and calculating the floating solution; selecting a partial ambiguity fixation subset; partially fixing the ambiguity; and solving the RTK position.

[0006] Further, the screening and elimination of the pseudo-satellite signals include the following steps: obtaining pseudo-satellite observations and pseudo-satellite positions; calculating the difference between pseudo-range observations according to adjacent pseudo-range observations of the pseudo-satellite, and determining whether the difference between adjacent pseudo-range observations is greater than D. If so, deleting the current pseudo-satellite signal; if not, entering the main satellite selection step, where D is a priori threshold obtained through experiments.

[0007] Further, the screening and elimination of the BDS satellite signals include the following steps: determining whether cycle slips occur in the BDS satellite signals; if so, eliminating the current BDS satellite, and if not, entering the main satellite selection step.

[0008] Further, determining whether cycle slips occur in the BDS satellite signals includes the following steps: First cycle slip detection: identifying cycle slips based on the LLI flag. If the LLI has a value, it is determined that cycle slips have occurred. If the LLI has no value, enter the second cycle slip detection; Second cycle slip detection: After filtering the GF combination, if the difference between the predicted value and the observed value is greater than the set threshold, it is determined that cycle slips have occurred. Otherwise, enter the third cycle slip detection; Third cycle slip detection: After filtering the MW combination, if the difference between the predicted value and the observed value is greater than or equal to the set threshold, it is determined that cycle slips have occurred. Otherwise, it is considered that no cycle slips have occurred in the BDS satellite signals.

[0009] Further, in the construction of the double-difference carrier observation equation and the double-difference pseudorange observation equation, the relationship between the geometric distance between the satellite and the receiver and the pseudorange is as follows:

[0010]

[0011] In the formula, ρ represents the pseudorange, c represents the speed of light, τ R represents the time delay of the receiver, represents the time delay of the satellite, V ion represents the ionospheric delay, V trop represents the tropospheric delay, E i represents other noises, R i represents the geometric distance between the satellite and the receiver, represents the position coordinates of satellite i, (X R , Y R , Z R ) represents the receiver position.

[0012] Further, in the construction of the double-difference carrier observation equation and the double-difference pseudorange observation equation, the relationship between the geometric distance between the satellite and the receiver and the carrier is as follows:

[0013]

[0014] In the formula, λ represents the wavelength of the carrier, N i represents the integer ambiguity of satellite i, is the carrier phase observation value of satellite i.

[0015] Further, the floating-point solution calculation formula is as follows:

[0016]

[0017] In the formula, Let \(W\) denote the weight matrix, \(G\) n×3 denote the coefficient matrix, \(\Delta P\) denote the position correction vector, and \(\hat{N}\) denote the floating-point solution of the integer ambiguity.

[0018] Furthermore, the selection rules for the partial ambiguity subsets are as follows: For BDS satellites, sequentially eliminate the satellite signals with the lowest elevation angle; sequentially eliminate the satellite signals with the lowest signal-to-noise ratio; sequentially eliminate the satellites with the largest least-squares solution residuals; eliminate satellites respectively until the integer ambiguity is fixed or stop eliminating when the number of eliminated satellites exceeds half of the total number of satellites; select the one with the fewest eliminated satellites as the final subset.

[0019] Furthermore, the integer ambiguity fixing includes the following steps: Obtain the integer ambiguity; perform integer estimation on the integer ambiguity; obtain the fixed solution.

[0020] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0021] By setting up pseudolites to assist the Beidou satellite system in positioning, the position dilution of precision is reduced, the geometric configuration of the satellites is improved, and the positioning accuracy and reliability of deformation monitoring are guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 FIG. shows the flowchart of a deformation monitoring method for pseudolite-assisted DBD according to an embodiment of the present invention.

[0023] Figure 2 FIG. shows the flowchart of the LAMBDA algorithm of a deformation monitoring method for pseudolite-assisted DBD according to an embodiment of the present invention.

[0024] Figure 3 FIG. shows the format diagram of the pseudolite telegram frame of a deformation monitoring method for pseudolite-assisted DBD according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the following further elaborates in detail a deformation monitoring method for pseudo-satellite assisted DBD proposed by the present invention in conjunction with the accompanying drawings and specific embodiments. According to the following description, the advantages and features of the present invention will be clearer. It should be noted that the accompanying drawings are in a very simplified form and all use non-precise scales, only for conveniently and clearly assisting in explaining the objectives of the embodiments of the present invention. In order to make the objectives, features and advantages of the present invention more obvious and understandable, please refer to the accompanying drawings. It should be noted that the structures, scales, sizes, etc. shown in the drawings of this specification are only used to cooperate with the content disclosed in the specification for those familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the present invention. Therefore, they do not have technical substantive significance. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effects that the present invention can produce and the objectives that can be achieved, should still fall within the scope covered by the technical content disclosed by the present invention.

[0026] The deformation monitoring method for pseudo-satellite assisted DBD in this embodiment includes the following steps:

[0027] Step 1, please refer to Figure 1 , receive pseudo-satellite signals and BDS satellite signals through a receiver and classify and collect them. The receiver includes a measurement station receiver and a reference station receiver;

[0028] Step 2, please continue to refer to Figure 1 , screen and eliminate the received pseudo-satellite signals and BDS signals.

[0029] Step 2.1, screening and elimination of pseudo-satellite signals.

[0030] Step 2.1.1, specifically, obtain pseudo-satellite observations and pseudo-satellite positions through decoding of pseudo-satellite navigation messages. The pseudo-satellite decodes the navigation message to obtain the position of the pseudo-satellite and the fixed time delay of the system, preparing for subsequent positioning and solution.

[0031] Step 2.1.2, if there are large changes in the carrier observations and pseudo-range observations of the pseudo-satellite between the previous and subsequent epochs, that is, the difference between the previous and subsequent epochs exceeds D = 1, then eliminate the pseudo-satellite signals of this epoch. If not, enter the selection of the main satellite. The D is a priori threshold obtained through experiments. The navigation message format of the pseudo-satellite is set as follows: The pseudo-satellite message adopts a BDS-like message design. The message rate is 50 bps. Every 6 seconds, 300 bits are broadcast as 1 sub-frame, with a total of 5 sub-frames. Considering subsequent expandability, sub-frames 1 to 3 and sub-frame 5 are reserved. The coordinates and system time delay of the pseudo-satellite are broadcast through sub-frame 4. The first 60 bits of the message frame are TLM and HOW. Bits 20 to 22 of HOW are the sub-frame numbers. When bits 20 to 22 are 100, this sub-frame is a pseudo-satellite message frame.

[0032] Please continue reading Figure 3 The pseudo-satellite message frame format is shown in the figure below. X, Y, Z are pseudo-satellite coordinates, TGD is the system fixed delay, and the CRC calculation range is 236 bits starting from PRN (including PRN, X, Y, Z, TGD and reserve), and the reserve bit is fixedly filled with 0.

[0033]

[0034] Step 2.2: Further, the BDS signal is screened and eliminated by judging whether a cycle slip occurs, and the judgment of whether a cycle slip occurs is performed three times.

[0035] Step 2.2.1, specifically, the first cycle slip judgment is to first identify the cycle slip through the LLI identifier. The LLI is the loss of lock identifier in the original GNSS observation data, which is located in the fourth decimal place after the carrier phase observation value. The value range of LLI is 0 to 7, usually 0 or a space, indicating normal or unknown; if LLI has a value, it means that a loss of lock has occurred between the previous epoch and the current epoch, that is, a cycle slip may have occurred. Therefore, cycle slip detection can be performed directly based on LLI. When an LLI cycle slip is found, the satellite is assigned an LLI cycle slip mark for subsequent processing.

[0036] Furthermore, two observation combination models are:

[0037] The geometry-free combination (GF combination) is shown in equation 1:

[0038]

[0039] In the formula, λ1 represents the wavelength of the first frequency, λ2 represents the wavelength of the second frequency, represents the carrier phase observation value of the first frequency, represents the carrier phase observation value of the second frequency, f1 represents the carrier frequency of the first frequency, f2 represents the carrier frequency of the second frequency, V ion represents the ionospheric delay. N1 represents the integer ambiguity of the first frequency, and N2 represents the integer ambiguity of the second frequency.

[0040] The standard phase-pseudocode combination (MW combination) is shown in equation 2 below:

[0041]

[0042] Where ρ represents the pseudorange observation value, A = -40.3∫ s Neds, Ne represents the ionospheric electron density.

[0043] The GF combination eliminates the influences of orbital errors, receiver clock errors, satellite clock errors, and tropospheric errors, and only includes the influences of ionospheric residuals and the real-time ambiguity combination of two carriers. The MW combination eliminates the influences of ionosphere, satellite clock errors, receiver clock errors, and geometric distance errors from the satellite to the receiver. When there are no cycle slips in the phase observations, the combined ambiguity is theoretically a constant. Due to the influence of observation noise, the combined ambiguity sequence fluctuates around a certain value. Since both the GF combination and the MW combination eliminate the influence of the geometric distance from the satellite to the receiver, that is, they are independent of the motion state of the receiver, these two combinations are applicable to cycle slip detection of dynamic data.

[0044] Step 2.2.2, Second cycle slip judgment. For the GF combination, polynomial fitting is used for filtering. First, the predicted value of the next epoch i + 1 is calculated using the observations and prior information of the current epoch i and several previous epochs, and the fitting standard deviation σ is obtained at the same time. When the observation value at epoch i + 1 is received, the predicted value is compared with the GF combination observation value. If the difference between the two is greater than the set threshold (±3σ), it is determined that there is a cycle slip in epoch i + 1; if the predicted value is within the threshold, it indicates that there is no cycle slip in this epoch.

[0045] Step 2.2.3, Third cycle slip judgment. For the MW combination, a recursive formula is used for filtering. As follows

[0046] Shown in Equations 3 and 4:

[0047]

[0048]

[0049] Among them, <N σ > i is the average value of the ambiguity difference N σ ; N i σ is the ambiguity difference of the i-th epoch; is the variance of the ambiguity difference N σ of the i-th epoch. If it is necessary to detect the (i + 1)-th epoch, first calculate the average value <N σ of the ambiguity differences N σ > i of the previous i epochs, and compare the observation value MW combination of the (i + 1)-th epoch with the predicted value <N σ > i . When is greater than or equal to the threshold (±3σ), it is determined that a cycle slip occurs in epoch i + 1.

[0050] When none of the three schemes detects cycle slips, it is determined that there are no cycle slips for that satellite. When at least one of the three schemes detects cycle slips, that BDS satellite is excluded.

[0051] Step 3, please continue to refer to Figure 1 , furthermore, select the master satellite. The selection rules for the master reference satellite are different for the pseudolite system and the BDS system. The selection of the master reference satellite in the pseudolite system is determined by the Doppler observations of each pseudolite. Since the positions of the pseudolites and the receiver are stationary during deformation monitoring, the Doppler observations should be 0. However, due to the existence of system noise, the Doppler observations are not 0. Therefore, the pseudolite with the minimum Doppler observation value is selected as the master reference satellite in the pseudolite system. The selection of the master reference satellite in the BDS satellite system is determined by the elevation angle of the satellite. The higher the elevation angle, the smaller the errors such as ionospheric delay and tropospheric delay. Therefore, the satellite with the highest elevation angle is selected as the master reference satellite in the BDS satellite system.

[0052] Step 4, please continue to refer to Figure 1 , furthermore, construct the double-difference carrier observation equation and the double-difference pseudorange observation equation and perform least squares solution to obtain the floating-point solution. Based on the influence of different factors in the actual measurement results, the relationship between the geometric distance between the satellite and the receiver and the pseudorange is established as shown in Equations 5 and 6 below:

[0053]

[0054] In the formula, ρ represents the pseudorange, c represents the speed of light, τ R represents the time delay of the receiver, represents the time delay of the satellite, V ion represents the ionospheric delay, V trop represents the tropospheric delay, E i represents other noises, R i represents the geometric distance between the satellite and the receiver, represents the position coordinates of satellite i, (X R , Y R , Z R ) represents the receiver position.

[0055] The relationship between the geometric distance between the satellite and the receiver and the carrier is established as shown in Equation 7 below:

[0056]

[0057] In the formula, λ represents the wavelength of the carrier, N i represents the integer ambiguity of satellite i, is the carrier phase observation value of satellite i.

[0058] Further, by assuming that satellites P and Q simultaneously transmit satellite signals to receivers A and B, the single-difference expression between receivers is established as shown in Equation 8 below:

[0059]

[0060] After simplification, we get Equation 9 below:

[0061]

[0062] In the case of short baselines, the reference station and the measurement station are very close, so we get Equation 10 below:

[0063]

[0064] On this basis, by taking a single difference between satellites, the double-difference observation equation can be obtained, which can be expressed as Equation 11 below:

[0065]

[0066] After simplification, we get Equation 12 below:

[0067]

[0068] Further, the RTK relative positioning theoretical model is Equation 13 below:

[0069]

[0070] In the formula, W represents the weight matrix, G n×3 represents the coefficient matrix, ΔP represents the position correction vector, represents the floating-point solution of the integer ambiguity.

[0071] Further, through least squares solution, the floating-point solution can be obtained as shown in Equation 14 below:

[0072]

[0073] Step 5, please continue to refer to Figure 1 , further, select a partial ambiguity-fixed subset. Because when fixing the integer ambiguity, if all the floating-point solutions are fixed, the success rate of fixing the integer ambiguity is low and the positioning accuracy is reduced. Therefore, a partial ambiguity-fixed strategy needs to be adopted, which involves the selection of a subset.

[0074] Specifically, the rules for selecting subsets are as follows: for BDS satellites, the satellite signal with the smallest elevation angle is sequentially excluded, the satellite signal with the lowest signal-to-noise ratio is sequentially excluded, and the satellite with the largest least-squares solution residual is sequentially excluded. Through the above three strategies until the ambiguity is fixed, or stop when the number of excluded satellites exceeds half of the total number of satellites.

[0075] Step 6, please continue to refer to Figure 1 , and part of the ambiguity is fixed. The floating-point solution obtained above is usually not an integer value, but the true value of the ambiguity should be an integer value. Therefore, the floating-point solution must be further processed, which is called ambiguity fixing. The LAMBDA algorithm is an algorithm that uses the integer least-squares principle to perform integer estimation on the ambiguity.

[0076] Please continue to refer to Figure 1 and Figure 2 , the LAMBDA algorithm first calculates the sequential conditional least-squares ambiguity, and then constructs an objective function through the sequential conditional least-squares ambiguity and minimizes it to obtain the integer estimation of the ambiguity.

[0077] Step 7, please continue to refer to Figure 1 , after the ambiguity fixing is successful, using the ambiguity-fixed solution and the corresponding covariance, update the floating-point solution of the baseline parameters to the fixed solution to obtain the RTK position solution.

[0078] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as these combinations of technical features do not conflict, they should be considered as falling within the scope described in this specification.

[0079] The above-described embodiments only represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent should be subject to the appended claims.

Claims

1. A deformation monitoring method for pseudo-satellite assisted DBD, characterized in that It includes the following steps: Receiving and classifying pseudolite signals and BDS satellite signals; Screening and eliminating pseudolite signals and BDS satellite signals; Selecting the main satellite, where the main reference satellite of the pseudolite selects the pseudolite with the minimum Doppler observation value as the main reference satellite, and the main reference satellite of the BDS satellite system selects the satellite with the highest elevation angle as the main reference satellite; Constructing double-difference carrier observation equations and double-difference pseudorange observation equations and calculating the floating solution, where the relationship between the geometric distance between the satellite and the receiver and the pseudorange is as follows: where ρ represents the pseudorange, c represents the speed of light, and τ R represents the time delay of the receiver, represents the time delay of the satellite, V ion represents the ionospheric delay, V trop represents the tropospheric delay, E i represents other noises, R i represents the geometric distance between the satellite and the receiver, represents the position coordinates of satellite i, (X R , Y R , Z R ) represents the receiver position, Where the relationship between the geometric distance between the satellite and the receiver and the carrier is as follows: where λ represents the wavelength of the carrier wave, and N i represents the integer ambiguity of satellite i, is the carrier phase observation of satellite i, Where, the calculation formula of the floating solution is as follows: In the formula, W represents the weight matrix, G n×3 represents the coefficient matrix, and ΔP represents the position correction vector, represents the floating-point solution of the integer ambiguity; Selecting a partial ambiguity-fixed subset; Partially fixing the ambiguity; RTK position solution.

2. The deformation monitoring method of pseudo-satellite-assisted DBD according to claim 1, characterized in that: The screening and elimination of the pseudolite signals includes the following steps: Obtaining pseudolite observations and pseudolite positions; According to the adjacent pseudorange observations of the pseudolite, calculating the difference between the pseudorange observations, and determining whether the difference between the adjacent pseudorange observations is greater than D. If so, deleting the current pseudolite signal. If not, entering the main satellite selection step, where D is a priori threshold obtained through experiments.

3. A deformation monitoring method for pseudo-satellite assisted DBD according to claim 1, characterized in that: The screening and elimination of the BDS satellite signals includes the following steps: Determining whether a cycle slip occurs in the BDS satellite signal; if so, eliminating the current BDS satellite. If not, entering the main satellite selection step.

4. The deformation monitoring method of pseudo-satellite assisted DBD according to claim 3, characterized in that: Determining whether a cycle slip occurs in the BDS satellite signal includes the following steps: First cycle slip detection: Identifying the cycle slip according to the LLI flag. If the LLI has a value, it is determined that a cycle slip has occurred. If the LLI has no value, entering the second cycle slip detection; Second cycle slip detection: After filtering the GF combination, if the difference between the predicted value and the observed value is greater than the set threshold, it is determined that a cycle slip has occurred. Otherwise, entering the third cycle slip detection; Third cycle slip detection: After filtering the MW combination, if the difference between the predicted value and the observed value is greater than or equal to the set threshold, it is determined that a cycle slip has occurred. Otherwise, the BDS satellite signal has not had a cycle slip.

5. A deformation monitoring method for pseudo-satellite assisted DBD according to claim 1, characterized in that: The selection rules of the partial ambiguity subset are as follows: For BDS satellites, sequentially eliminating the satellite signals with the minimum elevation angle; Sequentially eliminating the satellite signals with the lowest signal-to-noise ratio; Sequentially eliminating the satellites with the largest least squares solution residuals; Eliminating satellites respectively until the integer ambiguity is fixed or stopping eliminating when the number of eliminated satellites exceeds half of the total number of satellites; Selecting the one with the fewest eliminated satellites as the final subset.

6. The deformation monitoring method of a pseudo-satellite assisted DBD according to claim 5, characterized in that: The ambiguity fixing includes the following steps: Obtaining the integer ambiguity; Performing integer estimation on the integer ambiguity; Obtaining the fixed solution.

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