Control network construction and calculation method based on combination of GNSS and total station

Abstract

The invention belongs to the technical field of engineering measurement, and discloses a GNSS and total station combination-based control network construction and calculation method, which comprises the following steps of: firstly, arranging a GNSS first-level control network in a high intervisibility area, and constructing an encryption control network by using a total station in a non-intervisibility area; then, a GNSS receiver is used for collecting control point data of a non-intervisibility area, and a total station is used for collecting target point data of an intervisibility area; then, cycle slip detection and repair, gross error elimination, error correction and the like are respectively carried out on GNSS and total station data, and formats are unified; then, establishing a unified mathematical model, and solving parameters by using a least square method or robust Kalman filtering to obtain a three-dimensional coordinate of a control point; finally, error analysis is carried out on the resolving result, and iterative optimization is carried out when the precision requirement is not met; through hierarchical construction of the control network, complementary observation, targeted error correction and intelligent calculation, the problem of control point measurement under large-fall and invisible working conditions is effectively solved, and the requirement of high-precision engineering measurement can be met.

Description

Technical Field

[0001] The present invention relates to the field of engineering surveying technology, and in particular to a control network construction and solution method based on the combination of GNSS and a total station. Background Art

[0002] In traditional surveying technology, total stations, as commonly used equipment, rely on line-of-sight conditions between the measuring station and the target point to measure angles and distances. In environments with large elevation differences, such as mountainous areas and canyons, or where there are a large number of obstructions, due to limited line-of-sight requirements, stations and points need to be moved and changed frequently, resulting in low measurement efficiency and serious error accumulation.

[0003] While the Global Positioning System (GNSS) can overcome line-of-sight limitations and rapidly acquire control point coordinates worldwide, its accuracy for elevation measurement is poor, and positioning errors increase significantly in areas where the signal is easily obstructed, such as deep valleys and densely populated areas with tall buildings. GNSS elevation data is particularly difficult to obtain for high-precision engineering surveys, and total stations cannot effectively cover areas without line of sight, making control point data collection difficult and resulting in insufficient solution accuracy.

[0004] At present, the combined application of GNSS and total stations in existing technologies is mostly limited to measurement modes dominated by a single technology. No systematic solution has been formed to the problem of control point measurement under large drop and lack of line of sight conditions. It is difficult to simultaneously meet the requirements of engineering measurement for high precision, high efficiency and strong adaptability. Summary of the Invention

[0005] The purpose of the present invention is to provide a control network construction and solution method based on the combination of GNSS and total station. Through hierarchical construction of the control network, complementary observation, targeted error correction and intelligent solution, it systematically solves the control point measurement problem under large drop and no line of sight conditions, and meets the needs of high-precision engineering measurement.

[0006] The present invention is achieved through the following technical solutions:

[0007] A control network construction and solution method based on the combination of GNSS and total station includes the following steps:

[0008] S1. Deploy a GNSS primary control network in high-altitude areas with line of sight to form a wide-area coordinate reference. In areas without line of sight, perform prism-free measurements using a total station. Simultaneously, construct a dense control network using the free station setup method or the resection method, observing reflective targets at the primary network control points.

[0009] S2. Use a GNSS receiver to collect the three-dimensional coordinates and satellite status information of control points in the non-line-of-sight area of the target area. Simultaneously, use a total station to collect horizontal angle, vertical angle, and slant distance data of target points in the line-of-sight area.

[0010] S3. Perform cycle slip detection and repair, gross error rejection, and systematic error correction on GNSS data, and perform observed value correction, gross error rejection, and format unification on total station data;

[0011] S4. Establish a unified mathematical model including GNSS and total station observation equations, solve parameters through the least squares method or robust Kalman filter, and obtain the three-dimensional coordinates of control points;

[0012] S5. Conduct error analysis on the solution results, evaluate the reliability of the results through accuracy indicators, and iteratively optimize the solution parameters if the requirements are not met.

[0013] In this solution, a GNSS primary control network is deployed in the high-altitude visible area, providing a wide-area coordinate reference for the entire measurement area, solving the large-scale coordinate frame problem. In the non-visible area, a total station prismless measurement and free station method or resection method are used to construct an encrypted control network and observe the reflector targets of the primary network control points, supplementing the measurement data in the non-visible area. Among them, the three-dimensional coordinates of control points in the non-visible area and satellite status information are collected by a GNSS receiver, and the horizontal angle, vertical angle, and inclined distance data of target points in the visible area are collected by a total station, obtaining comprehensive measurement data. Preprocessing operations such as cycle slip detection and repair, gross error rejection, systematic error correction, observed value correction, and format unification are respectively performed on GNSS data and total station data to improve data quality. A unified mathematical model including the observation equations of both is established, and then the least squares method or robust Kalman filter is used to solve parameters to obtain the three-dimensional coordinates of control points. Finally, error analysis is performed on the solution results, the reliability is evaluated based on accuracy indicators, and the solution parameters are iteratively optimized when the requirements are not met, ensuring the accuracy and reliability of the control point solution results and meeting the requirements for high-precision coordinates of control points in various fields such as engineering surveying and topographic mapping.

[0014] Further, in step S1, the GNSS primary control network in the high-altitude visible area adopts a static observation mode, the observation time is not less than 45 minutes, the satellite cut-off elevation angle is set to 15° - 20°, and the point positions of the primary control network should evenly cover the measurement area, and the distance between adjacent points does not exceed 10 km.

[0015] In this solution, the GNSS primary control network in the high-altitude visible area adopts a static observation mode, and it is stipulated that the observation time is not less than 45 minutes, which ensures the stability of satellite signal reception, accumulates sufficient observation data, reduces the influence of random errors, and improves the positioning accuracy; setting the satellite cut-off elevation angle to 15° - 20° can effectively exclude the interference of low-elevation satellite signals, avoid signal occlusion or multipath effects, and ensure the quality of observation data; the point positions of the primary control network evenly cover the measurement area and the distance between adjacent points does not exceed 10 km, which is conducive to constructing a reasonable control network structure, enhancing the integrity and reliability of the control network, and providing a stable and accurate coordinate reference for subsequent measurements.

[0016] Furthermore, when the GNSS is in static observation, the carrier phase observation equation is as follows:

[0017] Wherein, is the carrier phase observation value, f is the carrier frequency, c is the speed of light, ρ is the geometric distance from the satellite to the measuring station, δρ ion and δρ trop are the ionospheric and tropospheric delays respectively, λ is the carrier wavelength, N is the integer ambiguity, is the observation noise.

[0018] Furthermore, in the step S2, when the GNSS receiver collects data, the sampling interval is 15 to 30 seconds, and during the collection process, it is ensured that the number of satellites is not less than 4, the PDOP value is less than 6. The total station collects the horizontal angle by the method of repetition measurement, observes 2 to 3 repetitions, and measures the inclined distance 2 - 3 times and takes the average value.

[0019] In this solution, for the GNSS receiver, setting the sampling interval to 15 to 30 seconds can ensure obtaining sufficient observation data to accurately track the satellite motion trajectory while avoiding generating a large amount of redundant data due to over - dense sampling, thus improving the data processing efficiency. Requiring that the number of satellites is not less than 4 and the PDOP value is less than 6 during the collection process is because a sufficient number of satellites can ensure the strength of the spatial geometric figure, and a small PDOP value means a reasonable satellite distribution. These two together guarantee the accuracy and reliability of GNSS positioning, laying a foundation for accurately collecting the three - dimensional coordinates of control points in non - visible areas. The total station collects the horizontal angle by the method of repetition measurement and observes 2 - 3 repetitions, and measures the inclined distance 2 - 3 times and takes the average value, which is to effectively weaken the accidental errors in the observation process by taking the average of multiple measurements and improve the accuracy of horizontal angle and inclined distance measurement.

[0020] Furthermore, the total station horizontal angle observation equation is β obs = β true + Δβ, the vertical angle observation equation is α obs = α true + Δα, the inclined distance observation equation is S obs = S true + ΔS, where β obs , α obs , S obs are the observation values, β true , α true , S trueis the true value, and Δβ, Δα, and ΔS are the observation errors. During data preprocessing, these equations can be used to correct observations, identifying and eliminating data containing large observation errors, thereby improving data quality. When establishing a unified mathematical model, these equations serve as key components, integrated with the GNSS observation equations to ensure that the model fully reflects the actual measurement situation.

[0021] Furthermore, in step S3, the cycle slip detection of the GNSS data includes a triple difference method and an ionospheric residual method, and is performed by polynomial fitting or Kalman filtering; gross error elimination is processed by a 3σ criterion; and system error correction includes ionospheric error correction and tropospheric error correction;

[0022] Among them, the ionospheric error correction formula is: in, are the carrier phase observation values at different frequencies, f1 and f2 are the corresponding frequencies;

[0023] The tropospheric error correction formula is: Among them, P s is the atmospheric pressure at the measuring station, T s is the station temperature, e s is the water vapor pressure at the measuring station, k1, k2, and k3 are model constants.

[0024] Cycle slip detection uses the triple-difference method and the ionospheric residual method to keenly capture cycle slips in carrier phase observations. These are then corrected with the aid of polynomial fitting or Kalman filtering to ensure the continuity and accuracy of carrier phase data, making carrier phase-based positioning calculations more reliable. Gross error removal using the 3σ criterion and the median method accurately identifies and removes outliers from the data, preventing them from adversely affecting the solution and improving overall data reliability. Systematic error correction encompasses both ionospheric and tropospheric error correction. The ionospheric error correction formula utilizes carrier phase observations at different frequencies to eliminate the effects of ionospheric delay on measurements. The tropospheric error correction formula uses meteorological parameters such as the station's air pressure, temperature, and water vapor pressure, combined with model constants, to make corrections. This significantly reduces the interference of these two major systematic errors on GNSS measurements, making GNSS measurement data closer to the true value.

[0025] Furthermore, in step S3, the observation value correction of the total station data includes correction of the i angle and the horizontal axis error, and meteorological correction of the slant distance according to the temperature and air pressure at the time of observation, and the elimination of gross errors is processed by the limit difference test method;

[0026] Among them, the i angle correction formula is Where L and R are the vertical angles observed from disk left and disk right, and ρ″ is a constant;

[0027] The meteorological correction formula is: ΔS=Sobs ×(0.000028×(P - 1013.25) - 0.00000012×(T - 20)), where P is the air pressure (Pa) and T is the temperature (°C).

[0028] In this solution, the i - angle is corrected. By calculating the correction amount based on the difference in vertical angles observed in face - left and face - right positions and the formula, it can effectively eliminate the influence of the instrument's i - angle error on vertical - angle measurement, improve the accuracy of vertical - angle measurement, and further enhance the accuracy of trigonometric leveling. The correction of the transverse axis error can ensure more accurate horizontal - angle measurement, making the coordinate calculation based on the horizontal angle more reliable. The meteorological correction of the inclined distance is carried out according to temperature and air pressure. Through an accurate meteorological correction formula, the influence of meteorological factors such as temperature and air pressure on inclined - distance measurement is eliminated or reduced to ensure the accuracy of the inclined - distance measurement value. The gross error rejection uses the limit - difference test method. According to the limits specified in the measurement specifications, the observed values containing gross errors are identified and rejected to avoid the interference of these abnormal data on subsequent calculations.

[0029] Furthermore, in step S4, when establishing a unified mathematical model, the conversion formula is as follows:

[0030] where ΔX, ΔY, and ΔZ are translation parameters, ω x 、ω y 、ω z are rotation parameters, m is the scale factor, and X WGS-84 、Y WGS-84 、Z WGS-84 are the coordinates obtained by GNSS measurement. By introducing translation parameters, rotation parameters, and scale factor, it can accurately transform the coordinates obtained by GNSS measurement into the required coordinate system, unifying the coordinate reference. This makes it feasible to solve parameters based on the unified coordinate system. Whether using the least - squares method or robust Kalman filtering, the three - dimensional coordinates of control points can be calculated more accurately within this unified framework.

[0031] Further, when using the least squares method, the error equation V = BδX - L is iteratively solved until the residual |V| < 3σ and the number of iterations < 10 times, where V is the residual vector, B is the coefficient matrix, δX is the unknown vector, and L is the constant term vector. By iteratively solving the error equation and continuously adjusting the unknown vector, the residual between the calculated value and the observed value gradually decreases. Setting the residual less than 3σ as one of the termination conditions ensures that the error of the final solution result is within a reasonable range. The 3σ criterion is a commonly used standard for measuring the degree of data dispersion and error range, and based on this, the reliability of the solution result can be guaranteed. At the same time, setting the number of iterations less than 10 times can not only avoid low calculation efficiency caused by too many iterations but also prevent the situation of non-convergence of iterations. In this process, the coefficient matrix B reflects the relationship between the observed value and the unknown, and the constant term vector L combines the known information of the observed value and the model. They jointly act on each iterative calculation. On the basis of establishing a unified mathematical model, the least squares method is used for iterative solution to continuously optimize the unknown vector, and then the three-dimensional coordinates of the control points that meet the accuracy requirements are obtained, ultimately ensuring the accuracy and practicability of the entire control point solution method.

[0032] Further, in step S5, the error analysis includes calculating the mean square error of the point position, and the calculation formula for the mean square error of the point position is where M x and M y are the mean square errors of the control points in the X and Y directions respectively. Calculating the mean square error of the point position can intuitively reflect the accuracy status of the control points in the plane position based on the mean square errors of the control points in the X and Y directions, and judge whether it meets the accuracy requirements of engineering survey.

[0033] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0034] By constructing a hierarchical control network and using GNSS to widely cover the primary control network, the present invention can effectively overcome the line-of-sight obstacle and obtain a wide-area coordinate reference without being restricted by the terrain. The total station uses the prismless measurement technology in the encrypted control network and combines the free station method and the resection method, which can flexibly measure in non-line-of-sight areas, greatly expanding the applicable range of the measurement and enabling the measurement work in complex terrain to be carried out smoothly. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of this application, and do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0036] Figure 1 is the solution flow chart of the control points of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0037] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0038] Example

[0039] Under complex working conditions such as large drop heights and lack of line of sight, traditional single measurement methods are unable to meet the needs of high-precision control point measurement. The control point solution method based on GNSS and total station systematically solves the problems of limited line of sight and insufficient accuracy through the construction of regional control networks, complementary data collection, targeted error processing and joint optimization. The specific implementation examples are as follows:

[0040] This embodiment provides a control network construction and solution method based on the combination of GNSS and total station. Figure 1 As shown, the following steps are included:

[0041] S1. Deploy a GNSS primary control network in high-altitude areas with line of sight to form a wide-area coordinate reference. In areas without line of sight, perform prism-free measurements using a total station. Simultaneously, construct a dense control network using the free station setup method or the resection method, observing reflective targets at the primary network control points.

[0042] Specifically, in high-altitude visibility areas, first select a commanding height with a height difference of ≥20 meters relative to the surrounding terrain, such as a mountain top or a rooftop of a high-rise building with a wide field of view, to ensure good satellite signal reception and at the same time ensure that the number of visible satellites is ≥4. The cut-off altitude angle is set to ≤15° to ensure the effective acquisition of satellite signals, and the distance between adjacent points is controlled between 5-10km. According to the terrain characteristics of the survey area, such as evenly arranged at key locations such as ridge lines and tunnel entrances and exits, the first-level control network can fully and evenly cover the entire survey area, providing a stable basic framework for subsequent measurements; then, the first-level control network adopts a static observation mode, and the observation time of a single period must be ≥45 minutes to ensure the continuity and stability of the observation. In order to achieve more accurate control point solution, when the GNSS is in static observation, the carrier phase observation equation is:

[0043] in, is the carrier phase observation value, f is the carrier frequency, c is the speed of light, ρ is the geometric distance from the satellite to the observation station, δρ ion ,δρ trop are the ionospheric and tropospheric delays, λ is the carrier wavelength, N is the integer ambiguity, is the observation noise.

[0044] Among them, as the coordinate benchmark for the entire survey area, this GNSS primary control network provides initial data for the total station encryption network in non-visible areas, effectively solving the problem of benchmark loss caused by the inability of total stations to have long-distance visibility in large-drop areas. Through the high-precision coordinate transfer of the primary control network, it is ensured that subsequent surveying work is carried out under a unified coordinate system, reducing error accumulation and improving the accuracy and reliability of the survey. After the establishment of the primary control network, its accuracy needs to be evaluated. By means of repeated measurements, comparison with known high-precision control points, etc., the stability and accuracy of the primary control network are tested. If it is found that the accuracy does not meet the requirements, the reasons need to be analyzed, which may be unreasonable point selection, interference during the observation process, etc., and timely adjustments and re-observations are carried out to ensure the quality of the primary control network.

[0045] In non-visible areas, first use the free station method (resection). Reasonably set up stations in non-visible areas such as inside tunnels and at the bottom of canyons. Specifically, when setting up stations, observe the reflectors of ≥3 primary network control points. To ensure the measurement accuracy, the installation height of the reflectors should be unified to reduce the influence caused by the vertical angle measurement error. The coverage radius of a single station is generally ≤500 meters under normal circumstances. In large-drop areas, considering factors such as complex terrain and great measurement difficulty, the coverage radius is shortened to 300 meters to improve the measurement accuracy and reliability. During the station setup process, precisely level and center the total station. Use professional centering equipment to ensure that the center of the total station coincides with the measurement station, and control the centering error within an extremely small range; at the same time, adjust the level of the total station to make the instrument in a horizontal state to reduce measurement errors; for non-visible points to be measured, use the prismless measurement method, and its ranging accuracy can reach ±2mm + 2ppm. For large-drop targets such as high slopes, due to the long measurement distance and complex terrain, the ranging accuracy is improved by setting up a reflecting prism to ensure the accuracy of the measurement data. During the measurement process, for targets at a relatively long distance, appropriately increase the number of ranging measurements and take the average value to reduce measurement errors.

[0046] Then, construct a network structure of closed traverse or connecting traverse. Among them, the azimuth closure error of the closed traverse needs to be ≤±√(n)″ (n is the number of stations), so as to solve the problem of cumulative station relocation errors of traditional total stations relying on visibility and achieve high-precision local measurement in non-visible areas.

[0047] S2. Collect the three-dimensional coordinates and satellite status information of the control points in the non-visible area through a GNSS receiver in the target area, and at the same time collect the horizontal angle, vertical angle and inclined distance data of the target points through a total station in the visible area;

[0048] Specifically, an RTK receiver with dual-frequency function is selected, the sampling interval is set to 15 seconds, and the number of satellites and PDOP value (Position Dilution of Precision) are recorded in real time. During the measurement process, the PDOP value is strictly monitored to ensure that it is ≤6, and at the same time, the number of satellites is ensured to be ≥4 to obtain stable and reliable satellite signals. In large-drop areas, to reduce the centering error, the receiver antenna is fixed by forced centering with a tripod, and the GNSS receiver is used to collect the three-dimensional coordinates (X WGS-84 、Y WGS-84 、Z WGS-84 ) of the control points in the non-visible area in the WGS-84 coordinate system;

[0049] At the same time, the horizontal angle is observed by the method of repetition measurement. Generally, 2 to 3 repetitions are observed. The total station is placed in the left face position, accurately aimed at the backsight point, and the horizontal circle reading is set to 0°00′00″. Then rotate the telescope clockwise and aim at each target point in turn, read and record the horizontal circle reading. The total station is placed in the right face position, rotate the telescope counterclockwise, and aim at each target point in turn again, read and record the horizontal circle reading. During the observation process, the horizontal angle observation error Δβ is strictly controlled. This observation error β L and β R are the horizontal angles observed in the left face and right face respectively. The circle setting should be carried out between each repetition to weaken the influence of the circle graduation error. After the observation is completed, calculate the horizontal angle observation values of each repetition. If the difference between each repetition is within the specified tolerance (such as the horizontal angle closing error ≤ ±√(n)″, n is the number of stations), then take the average value of each repetition as the final horizontal angle observation value β obs ; if it exceeds the tolerance, re-observation should be carried out, and the corrected horizontal angle is obtained according to the formula β obs =β true +Δβ, where β true is the true value and Δβ is the observation error.

[0050] Similarly, the vertical angle is measured by the method of left face and right face observations. When observing in the left face, aim at the target point and read the vertical circle reading; when observing in the right face, aim at the same target point again and read the vertical circle reading. Here, the i-angle of the total station needs to be corrected to improve the vertical angle measurement accuracy. The i-angle correction formula is where L and R are the vertical angles observed in the left face and right face respectively, ρ″ is a constant, take ρ″ = 206265”), and the corrected vertical angle is obtained according to the formula α obs =α true +Δα to obtain the true value α true , α obsLet \(L\) be the observed value and \(\Delta\alpha\) be the observation error. By correcting the \(i\)-angle, ensure that the vertical angle measurement accuracy reaches \(\pm0.5''\). For targets with large elevation differences (such as elevation difference \(> 200\) meters), reciprocal observations can be added. During reciprocal observations, vertical angle observations are carried out at two survey stations respectively, and the height difference between the forward and backward observations is calculated. The difference between the forward and backward height differences should meet the requirement of \(\leq\pm0.04\sqrt{D}\) meters (\(D\) is the horizontal distance, unit km). If not satisfied, re-observation is required.

[0051] And then, measure the slope distance of the target point 2 - 3 times. Each time of measurement should ensure that the line of sight between the total station and the target prism is clear and unobstructed. After the measurement is completed, take the average value of each measurement value as the final observed value \(S\) of the slope distance. obs . While measuring the slope distance, use a thermometer and a barometer to record the temperature and air pressure on site. Obtain the observation error \(\Delta S = S\) obs \(\times(0.000028\times(P - 1013.25)-0.00000012\times(T - 20))\) (where \(P\) is the air pressure, unit hPa; \(T\) is the temperature, unit \(^{\circ}C\)) to perform meteorological correction on the slope distance. The corrected vertical angle is calculated according to the formula \(S\) obs \(= S\) true +\(\Delta S\) to obtain the true value \(S\) true , so as to eliminate the influence of temperature and air pressure changes on the slope distance measurement.

[0052] S3. Perform cycle slip detection and repair, gross error rejection, and systematic error correction on GNSS data, and perform observed value correction, gross error rejection, and format unification on total station data;

[0053] Specifically, the cycle slip detection of GNSS data includes the triple-difference method and the ionospheric residual method. The triple-difference method detects cycle slips by performing three differences on the carrier phase observations between different epochs and different satellites. First, perform single-difference, that is, subtract the carrier phase observations of different satellites at the same epoch to eliminate the receiver clock error; then perform double-difference, that is, subtract the single-difference observations of different epochs to further eliminate the satellite clock error; finally, perform triple-difference, that is, subtract the double-difference observations of different satellite pairs. When the triple-difference observations show abnormal changes (usually exceeding a certain threshold, such as 3 times the standard deviation of the observation noise), it is considered that there may be a cycle slip; of course, due to the different influences of the ionosphere on the carrier phase observations of different frequencies, this characteristic can also be used to detect cycle slips by calculating the ionospheric residuals. For dual-frequency GNSS receivers, the carrier phase observations of the two frequencies and satisfy a certain relationship. When there is a cycle slip, the ionospheric residual will show abnormalities. Set a reasonable threshold (such as greater than 5 cycles). When the ionospheric residual exceeds this threshold, it is determined that there is a cycle slip.

[0054] For cycle slips that occur within a short period of time, the method of polynomial fitting can be adopted. Based on the epoch data without cycle slips, a polynomial for the variation of the carrier phase observation with time is fitted, and then the carrier phase value of the epoch with cycle slips is predicted using this polynomial. The difference between the predicted value and the observed value is used as the estimated value of the cycle slip for repair. Or it can be repaired through Kalman filtering. Taking the carrier phase observation as the state variable, by establishing the state equation and the observation equation, Kalman filtering is used to estimate and repair the cycle slip in real time. For cycle slips caused by long-term loss of lock, Kalman filtering can make full use of historical data and the dynamic information of the system to accurately repair the cycle slip.

[0055] For the rejection of gross errors in GNSS data, it can be processed through the 3σ criterion and the median method. Calculate the mean of the GNSS observations and the standard deviation σ. For each observation calculate the difference between it and the mean When it is considered that this observation is a gross error and it is rejected.

[0056] Meanwhile, the systematic error correction includes ionospheric error correction and tropospheric error correction. Since this embodiment uses a dual-frequency GNSS receiver, the ionospheric error can be eliminated by combining the carrier phase observations of the two frequencies. The commonly used combination method is to form an ionosphere-free combined observation where are the carrier phase observations of different frequencies, and f1, f2 are the corresponding frequencies. This combination method can effectively eliminate the influence of the first-order term of the ionosphere. The tropospheric error correction formula is where P s is the station pressure, T s is the station temperature, e s is the station water vapor pressure, and k1, k2, k3 are model constants.

[0057] For the rejection of gross errors in total station data, it is judged whether there are gross errors in the observations by setting the limits of the horizontal angle closure error or the difference in angular values between sets of observations. For the measurement of interior angles of a closed traverse or polygon, calculate the horizontal angle closure error f β =∑β obs -∑β 理论 where ∑β obs is the sum of the horizontal angle observations, and the sum of the horizontal angle theoretical values ∑β 理论 =(n - 2)×180°, n is the number of sides of the polygon. Compare f β with the specified limit (such as ±√n×angular measurement mean error). If |f β |>limit, it is considered that there are gross errors in the observed data and re-observation is required.

[0058] S4. Establish a unified mathematical model containing GNSS and total station observation equations, solve for parameters through the least squares method or robust Kalman filtering, and obtain the three-dimensional coordinates of the control points;

[0059] For the GNSS observation equation, it can be derived from the aforementioned carrier phase observation equation and linearized for subsequent calculations in practical applications. Taking the solution of the control point coordinates (X, Y, Z) as an example, the geometric distance ρ can be expressed as where (X S , Y S , Z S ) are the coordinates of the satellite (which can be obtained from ephemeris data).

[0060] For total station observations, the relative position relationship between control points can be calculated based on the calculated horizontal angle, vertical angle, and slope distance, and then the connection with the control point coordinates can be established. For example, given the station coordinates (X0, Y0, Z0), horizontal angle β true , vertical angle α true , and slope distance S true , the coordinates of the target point (X, Y, Z) can be calculated as follows:

[0061] X = X0 + S true × cosα true × cosβ true

[0062] Y = Y0 + S true × cosα true × sinβ true

[0063] Z = Z0 + S true × sinα true

[0064] When establishing the unified mathematical model, the conversion formula is:

[0065] where ΔX, ΔY, and ΔZ are translation parameters, ω x , ω y , ω z are rotation parameters, m is the scale factor, and X WGS-84 , Y WGS-84 , Z WGS-84 are the coordinates obtained from GNSS measurements. These seven parameters can be solved to convert the WGS-84 coordinates measured by GNSS to the local coordinate system coordinates that are the same as those measured by the total station, achieving the unification of the coordinate system.

[0066] After linearizing the observation equations of GNSS and total station, the error equation V = BδX - L can be constructed, where V is the residual vector, B is the coefficient matrix, δX is the unknown vector, and L is the constant term vector. The parameters are solved by the least squares method or robust Kalman filtering. The goal of the least squares method is to minimize the sum of the squares of the elements of the residual vector V, that is, V T PV is minimized, where P is the weight matrix determined according to the measurement accuracies of GNSS and total station. Solution steps: Give the initial value of the unknown vector δX. According to the initial value and the observation data, calculate the coefficient matrix B and the constant term vector L. Construct the normal equation NδX = W, where N = B T PB, W = B T PL, solve the normal equation to obtain the corrected value of the unknown vector δX. Repeat the above steps with the corrected δX for iterative solution until |V| < 3σ and the number of iterations < 10 times, where σ is the standard deviation of the observed values.

[0067] After solving the unknown vector δX by the least squares method or robust Kalman filtering, the three-dimensional coordinates of the control points can be obtained. Specifically, the corresponding elements in the unknown vector δX are the X, Y, and Z coordinate values of the control points in the unified coordinate system. At the same time, error analysis needs to be carried out on the solution results to check whether they meet the requirements of plane accuracy of ±5 cm and elevation accuracy of ±3 cm. If the requirements are not met, it may be necessary to recheck the data quality, the rationality of the model, or adjust the solution method.

[0068] S5. Conduct error analysis on the solution results, evaluate the reliability of the results through accuracy indicators, and if the requirements are not met, iterate and optimize the solution parameters.

[0069] Error analysis includes calculating the mean square error of the point position. The formula for calculating the mean square error of the point position is where M x and M y are the mean square errors of the control points in the X and Y directions respectively. By calculating the mean square error of the point position and based on the mean square errors of the control points in the X and Y directions, the accuracy status of the control points in the plane position can be intuitively reflected, and it can be judged whether they meet the accuracy requirements of engineering surveying. In actual calculations, M x and M y can be calculated according to the cofactor matrix obtained during the solution process of the least squares method or robust Kalman filtering. For example, in the least squares method, the elements corresponding to the X and Y directions on the diagonal of the cofactor matrix Q xx are combined with the mean square error of unit weight μ0 respectively to calculate M x and M y , that is After completing the data check and parameter adjustment, use the adjusted parameters and data to re-perform the solution, and conduct error analysis and accuracy evaluation again until the solution results meet the accuracy requirements.

[0070] The specific embodiments described above further elaborate on the object, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A control network construction and solution method based on the combination of GNSS and total station, characterized in that The steps include: S1. Deploy a GNSS primary control network in high-altitude areas with line of sight to form a wide-area coordinate reference. In areas without line of sight, perform prism-free measurements using a total station. Simultaneously, construct a dense control network using the free station setup method or the resection method, observing reflective targets at the primary network control points. S2. Use a GNSS receiver to collect the three-dimensional coordinates and satellite status information of control points in the non-line-of-sight area of the target area. Simultaneously, use a total station to collect horizontal angle, vertical angle, and slant distance data of target points in the line-of-sight area. S3. Perform cycle slip detection and repair, gross error elimination, and systematic error correction on GNSS data; perform observation value correction, gross error elimination, and format unification on total station data; S4. Establish a unified mathematical model that includes the GNSS and total station observation equations, solve the parameters using the least squares method or robust Kalman filtering, and obtain the three-dimensional coordinates of the control points; S5. Perform error analysis on the solution results and evaluate the reliability of the results through accuracy indicators. If the requirements are not met, iteratively optimize the solution parameters.

2. The control network construction and solution method based on the combination of GNSS and total station according to claim 1, characterized in that, In step S1, the GNSS primary control network in the high-altitude visibility area adopts a static observation mode, the observation time is not less than 45 minutes, the satellite cut-off elevation angle is set to 15°-20°, and the point distribution of the primary control network should evenly cover the measurement area, and the distance between adjacent points should not exceed 10km.

3. A control network construction and solution method based on the combination of GNSS and total station according to claim 2, characterized in that, When GNSS is in static observation, the carrier phase observation equation is: Among them, is the carrier phase observation value, f is the carrier frequency, c is the speed of light, ρ is the geometric distance from the satellite to the measuring station, and δρ ion , δρ trop are the ionospheric and tropospheric delays respectively, λ is the carrier wavelength, N is the integer ambiguity, is the observation noise.

4. A control network construction and solution method based on the combination of GNSS and total station according to claim 3, characterized in that, In step S2, the sampling interval of the GNSS receiver when collecting data is 15 to 30 seconds, and during the collection process, the number of satellites is ensured to be no less than 4 and the PDOP value is less than 6. The total station collects the horizontal angle by the back measurement method, observes 2 to 3 back measurements, and measures the slant distance 2-3 times and takes the average value.

5. A control network construction and solution method based on the combination of GNSS and total station according to claim 4, characterized in that, The horizontal angle observation equation of the total station is β abs = β true ++Δβ, and the vertical angle observation equation is α obs = α true +Δα, and the inclined distance observation equation is S obs = S true +ΔS, where β obs , α obs , S obs are the observed values, β true , α true , S true are the true values, and Δβ, Δα, and ΔS are the observation errors.

6. The control network construction and solution method based on the combination of GNSS and total station according to claim 5, characterized in that, In step S3, the cycle slip detection of GNSS data includes a triple difference method and an ionospheric residual method, and is performed by polynomial fitting or Kalman filtering; gross error elimination is processed by a 3σ criterion; and system error correction includes ionospheric error correction and tropospheric error correction; Among them, the ionospheric error correction formula is Among them, are carrier phase observations at different frequencies, and f1, f2 are the corresponding frequencies; Among them, the tropospheric error correction formula is Among them, P s is the station pressure, T s is the station temperature, e s is the station water vapor pressure, and k1, k2, and k3 are model constants.

7. A control network construction and solution method based on the combination of GNSS and total station according to claim 6, characterized in that In step S3, the observation value correction of the total station data includes correction of the i angle and the horizontal axis error, as well as meteorological correction of the slant distance according to the temperature and air pressure at the time of observation. The gross error elimination is processed by the limit difference test method; Among them, the i - angle correction formula is where L and R are the vertical angles observed in the left - hand and right - hand positions respectively, and ρ″ is a constant; Among them, the meteorological correction formula is ΔS = S obs ×(0.000028×(P - 1013.25) - 0.00000012×(T - 20)), where P is the air pressure (Pa) and T is the temperature (°C).

8. A control network construction and solution method based on the combination of GNSS and total station according to claim 7, characterized in that In step S4, when establishing a unified mathematical model, the conversion formula is: Among them, ΔX, ΔY, and ΔZ are translation parameters, ω x , ω y , ω z are rotation parameters, m is a scale factor, and X WGS-84 , Y WGS-84 , Z WGS-84 are coordinates obtained by GNSS measurement.

9. A control network construction and solution method based on the combination of GNSS and total station according to claim 8, characterized in that, When the least squares method is used, the error equation is solved iteratively: V = BδX-L until the residual |V| is less than 3σ and the number of iterations is less than 10 times, where V is the residual vector, B is the coefficient matrix, δX is the unknown vector, and L is the constant term vector.

10. A control network construction and solution method based on the combination of GNSS and total station according to claim 8, characterized in that, In the step S5, the error analysis includes calculating the mean square error of points, and the calculation formula for the mean square error of points is where M x , M y are the mean square errors of the control points in the X and Y directions respectively.

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