Beidou observation data quality analysis method, system and device for dam deformation monitoring and medium

Abstract

The invention discloses a Beidou observation data quality analysis method, system and device for dam deformation monitoring and a medium, and belongs to the technical field of satellite observation data quality analysis, and the method comprises the steps: collecting original observation information at a monitoring point through Beidou monitoring receiving equipment; calculating a data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs of each monitoring point by using full-satellite ephemeris information; calculating a signal-to-noise ratio, and evaluating a cycle slip ratio and a multipath effect in carrier phase measurement; independently considering a data integrity rate, a signal-to-noise ratio, a cycle slip ratio and a multi-path effect to obtain a single evaluation grade; and comprehensively considering the data integrity rate, the signal-to-noise ratio, the cycle slip ratio and the multipath effect, and performing quality evaluation and grading on the original observation information received by each monitoring station. According to the method, the quality of Beidou observation data received by the monitoring points can be comprehensively reflected from multiple angles, and necessary help and support are provided for investigation design and point selection of Beidou automatic monitoring engineering.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite observation data quality analysis, and particularly relates to a Beidou observation data quality analysis method, system, device and medium for dam deformation monitoring. Background Art

[0002] The external deformation monitoring of hydropower projects is an important part of the dam safety monitoring system. The Beidou Global Navigation Satellite System (BDS) has the advantages of high monitoring frequency, continuous and stable monitoring, wide monitoring range, high degree of automation, and being unaffected by weather conditions. Its accuracy can reach the millimeter level and has become an important means in the field of external deformation monitoring of hydropower projects. At the same time, the observation environment around the Beidou monitoring stations of hydropower projects is usually very complex, and satellite signals are easily interfered. Among them, environmental conditions and receiver performance are the main factors affecting the quality of Beidou observation data. The observation environment of Beidou survey stations in the dam safety monitoring scenario is usually relatively complex. For example, there are serious obstructions caused by vegetation or slopes, and multipath effects are seriously affected by buildings or water surfaces, etc. The quality of the monitoring point observation environment directly affects the monitoring accuracy and is a factor that must be fully considered in the design process of the Beidou monitoring scheme.

[0003] The Beidou Global Navigation Satellite System (BDS) is applied to the external deformation monitoring of water conservancy projects by virtue of its advantages of all-weather, continuous, and automated acquisition of high-precision three-dimensional surface deformation. With the completion and continuous development and improvement of the Beidou system, the monitoring service ability of satellite positioning technology in complex environments has been improved, and its application scope in the safety monitoring of water conservancy projects has also become increasingly wide. At present, the Beidou deformation monitoring technology in open environments is relatively mature and can meet the relevant specifications and technical indicators of deformation monitoring, but it requires no vegetation, water bodies, buildings, etc. around that affect the signal quality. However, the actual deformation monitoring environment is usually relatively complex, and key monitoring points usually face situations such as signal occlusion and serious multipath effects near water bodies. Therefore, in the process of survey and design, fully considering the observation environment factors of monitoring points and selecting reasonable measuring points can achieve the expected deformation monitoring accuracy.

[0004] The present invention proposes a Beidou data quality evaluation system, formulates data quality grades, provides a theoretical basis for the site selection of Beidou automated monitoring survey, guarantees the reliability of the Beidou monitoring system service, and improves the stability of monitoring results. Summary of the Invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is: how to solve the problems that the actual deformation monitoring environment is usually relatively complex, and key monitoring points usually face situations such as signal occlusion and serious multipath effects near water bodies.

[0007] To solve the above technical problems, the present invention provides the following technical solution: A method for analyzing the quality of Beidou observation data for dam deformation monitoring, which includes the following steps: collecting original observation information at the monitoring points through Beidou monitoring receiving equipment, and transmitting the original observation information and full satellite ephemeris information to the monitoring station through communication technology; calculating the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs for each monitoring point using the full satellite ephemeris information; calculating the signal-to-noise ratio using the obtained data integrity rate and original observation information, and evaluating the cycle slip ratio and multipath effect in carrier phase measurement; separately considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to obtain a single-item evaluation grade; comprehensively considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to conduct quality assessment and grade division on the original observation information received by each monitoring station.

[0008] As a preferred solution of the method for analyzing the quality of Beidou observation data for dam deformation monitoring according to the present invention, wherein: the communication technology includes 4G communication protocol or TCP protocol or Lora communication technology; the full satellite ephemeris information includes, at each epoch, calculating the elevation angle of the satellite, i.e., the theoretical elevation angle, according to the broadcast ephemeris, comparing the theoretical elevation angle with the preset cut-off elevation angle, if the theoretical elevation angle is greater than the cut-off elevation angle, it is considered that the satellite is theoretically observed, that is, the number of theoretical observation epochs of the satellite is incremented by 1, and the actual observation epochs are counted according to the actual observation situation.

[0009] As a preferred solution of the method for analyzing the quality of Beidou observation data for dam deformation monitoring according to the present invention, wherein: the data integrity rate is calculated according to the ratio of the actual epoch data volume of the satellite observed by the receiver to the theoretical epoch data volume, expressed as:

[0010]

[0011] wherein, DI f is the data integrity rate of the satellite single-frequency point observation data, n is the total number of satellites observed during the observation period, j is the satellite number observed, A j is the total number of actual observation epochs of the j-th satellite at the f frequency point during the observation period, B j is the total number of theoretical observation epochs of the j-th satellite at the f frequency point during the observation period.

[0012] As a preferred solution of the method for analyzing the quality of Beidou observation data for dam deformation monitoring according to the present invention, wherein: the signal-to-noise ratio is expressed as:

[0013]

[0014] wherein, is the statistical value of the satellite observation signal-to-noise ratio index, N is the total number of satellite observation epochs, ti is the observation epoch serial number of the satellite, SNR j (t i ) is the SNR observation value of satellite j at epoch t i ; The cycle slip ratio is expressed as:

[0015] C = O / S

[0016] where C represents the cycle slip ratio, O is the number of observation values, and S is the number of cycle slips.

[0017] As a preferred solution of the Beidou observation data quality analysis method for dam deformation monitoring according to the present invention, wherein: the multipath effect includes calculating the linear combination of dual-frequency pseudorange and phase observation values, which is expressed as:

[0018]

[0019] where are the multipath effects containing multipath error and integer ambiguity information at frequencies k1 and k2 respectively, are the pseudorange observation values at frequencies k1 and k2 respectively, are the frequencies of the carriers of k1 and k2 respectively, are the carrier phase observation values at frequencies k1 and k2 respectively; for the same satellite, in a continuous observation arc without cycle slips, the ambiguity parameter remains fixed, and the multipath error is calculated as:

[0020]

[0021] where is the multipath error evaluation value of the receiver receiving the signal of frequency k from the satellite, N sw is the number of epochs of the sliding window, MP k (t i ) is the multipath error value of the signal at frequency k at time t i .

[0022] As a preferred solution of a Beidou observation data quality analysis method for dam deformation monitoring according to the present invention, wherein: the single-item evaluation grades include setting a first threshold of data integrity rate, a second threshold of data integrity rate, a third threshold of data integrity rate, a fourth threshold of data integrity rate, a first threshold of signal-to-noise ratio, a second threshold of signal-to-noise ratio, a third threshold of signal-to-noise ratio, a fourth threshold of signal-to-noise ratio, a first threshold of cycle slip ratio, a second threshold of cycle slip ratio, a third threshold of cycle slip ratio, a fourth threshold of cycle slip ratio, a first threshold of multipath effect, a second threshold of multipath effect, a third threshold of multipath effect, and a fourth threshold of multipath effect; the calculated data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect are respectively compared with the corresponding first threshold, second threshold, third threshold, and fourth threshold. If it is less than the first threshold, the single-item evaluation grade is poor. If it is greater than or equal to the first threshold and less than the second threshold, the single-item evaluation grade is normal. If it is greater than or equal to the third threshold and less than the fourth threshold, the single-item evaluation grade is good. If it is greater than or equal to the fourth threshold, the single-item evaluation grade is excellent, and the single scores of different single-item evaluation grades are obtained according to the calculated data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect.

[0023] As a preferred solution of a Beidou observation data quality analysis method for dam deformation monitoring according to the present invention, wherein: comprehensively considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect includes giving priority to the data integrity rate, followed by the cycle slip ratio, and finally the signal-to-noise ratio; if the data integrity rate does not reach excellent, the integrity rate grade is taken as the final grade; in the case where the integrity rate is excellent, the grade of the cycle slip ratio is taken as the final grade; in the case where both the integrity rate and the cycle slip ratio are excellent, the grade of the signal-to-noise ratio is taken as the final grade.

[0024] Another object of the present invention is to provide a Beidou observation data quality analysis system for dam deformation monitoring, and the present invention solves the problem of satellite observation data quality analysis.

[0025] As a preferred solution of a Beidou observation data quality analysis system for dam deformation monitoring according to the present invention, it is characterized in that it includes a data acquisition module, a data integrity rate calculation module, a calculation module, a single-item average module and a comprehensive average module; the data acquisition module is used to collect original observation information at the monitoring point through a Beidou monitoring receiving device, and transmit the original observation information and full satellite ephemeris information to the monitoring station through communication technology; the data integrity rate calculation module is used to calculate the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs of each monitoring point by using the full satellite ephemeris information; the calculation module is used to calculate the signal-to-noise ratio by using the obtained data integrity rate and original observation information, and evaluate the cycle slip ratio and multipath effect in carrier phase measurement; the single-item average module is used to separately consider the data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect to obtain a single-item evaluation grade; the comprehensive average module is used to comprehensively consider the data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect to conduct quality evaluation and grade division on the original observation information received by each monitoring station.

[0026] A computer device includes a memory and a processor, and the memory stores a computer program. It is characterized in that when the processor executes the computer program, the steps of a Beidou observation data quality analysis method for dam deformation monitoring as described above are realized.

[0027] A computer-readable storage medium stores a computer program thereon. It is characterized in that when the computer program is executed by a processor, the steps of a Beidou observation data quality analysis method for dam deformation monitoring as described above are realized.

[0028] The beneficial effects of the present invention: By introducing the full satellite ephemeris information, the present invention can calculate the satellites not observed by the observation network, so as to obtain the azimuth of all Beidou satellites relative to the monitoring point. If the satellites within the specified azimuth range are not observed, it is considered that the receiver tracking fails or there is occlusion in the environment. On the premise that the receiver performance remains stable, the finally calculated data integrity rate index can intuitively reflect the occlusion factor in the measuring point environment.

[0029] The present invention calculates multiple quality analysis indicators including data integrity rate, signal-to-noise ratio, cycle slip ratio, multipath effect, pseudorange noise, phase noise, and ionospheric change rate. The indicators are very rich and comprehensive, and can comprehensively reflect the quality of Beidou observation data received at the monitoring point from multiple angles, providing necessary help and support for the survey design and point selection of the Beidou automatic monitoring project.

[0030] In the initial stage of the Beidou satellite original observation data access system, the present invention fully draws on the advantages of traditional offline processing solutions, conducts independent research and adaptive optimization and transformation, applies it to the real-time monitoring framework, and constructs a real-time evaluation and grading system for Beidou observation data and a real-time evaluation business processing flow for Beidou data quality.

[0031] The present invention adopts a timed task scheduling method to process the quality evaluation of real-time observation data, organizes and schedules tasks for Beidou observation data of a specified duration, and rolls to process the main data quality indicators of each task period. For the real-time data quality evaluation system of the real-time data stream, it can realize the real-time output of data quality indicators within any period, so as to timely evaluate the data quality during the mutation period of the solution results, and can avoid the jump of the results caused by the deterioration of data quality and further lead to false early warnings. At the same time, the project can make a unified analysis of the time series of quality evaluation indicators in a past period to judge whether there are outliers in the observation data. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0033] Figure 1 It is the overall flowchart of a method for analyzing the quality of Beidou observation data for dam deformation monitoring provided by an embodiment of the present invention.

[0034] Figure 2 It is the flowchart of the observation epoch of a method for analyzing the quality of Beidou observation data for dam deformation monitoring provided by an embodiment of the present invention.

[0035] Figure 3 It is the quality analysis diagram of a method for analyzing the quality of Beidou observation data for dam deformation monitoring provided by an embodiment of the present invention.

[0036] Figure 4 It is the system scheme module diagram of a system for analyzing the quality of Beidou observation data for dam deformation monitoring provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] To make the above objects, features, and advantages of the present invention more apparent and understandable, the following provides a detailed description of the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0038] Example 1. Refer to Figures 1 to 3 , which is the first embodiment of the present invention. This embodiment provides a method for analyzing the quality of Beidou observation data for dam deformation monitoring, including: collecting original observation information at the monitoring points through Beidou monitoring receiving equipment, and transmitting the original observation information and full satellite ephemeris information to the monitoring station through communication technology; calculating the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs for each monitoring point using the full satellite ephemeris information; calculating the signal-to-noise ratio using the obtained data integrity rate and original observation information, and evaluating the cycle slip ratio and multipath effect in carrier phase measurement; separately considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to obtain a single-item evaluation grade; comprehensively considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to conduct quality assessment and grade division on the original observation information received by each monitoring station.

[0039] In view of the common monitoring environments of Beidou automated deformation monitoring in current hydropower projects, such as complex and harsh environmental factors like half-side blockage of slopes, double-side blockage of canyons, and water-facing surfaces, the present invention comprehensively analyzes Beidou observation data from the perspectives of single quality indicators and multi-quality comprehensive scoring, and evaluates and grades it to indicate the quality of the observation environment at the monitoring points. In terms of single quality indicators, multiple quality indicators such as data integrity rate, signal-to-noise ratio, cycle slip ratio, multipath effect, pseudorange noise, phase noise, and ionospheric change rate are calculated successively.

[0040] S1. Collect original observation information at the monitoring points through Beidou monitoring receiving equipment, and transmit the original observation information and full satellite ephemeris information to the monitoring station through communication technology.

[0041] Transmit the original observation information of the Beidou monitoring receiving equipment for hydropower projects to the relevant server through the 4G communication protocol or TCP protocol (optical fiber + Ethernet) or Lora communication technology.

[0042] After summarizing the original observation information and full satellite ephemeris information of the monitoring points in the server, perform calculations.

[0043] S2. Calculate the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs for each monitoring point using the full satellite ephemeris information.

[0044] The data integrity rate refers to the ratio of the actual epoch data volume of the satellites observed by the receiver to the theoretical epoch data volume. Complete observation data is a prerequisite for data processing and other applications. The data integrity rate is affected by the working performance of the receiver, the working performance of the satellites, and the surrounding environment of the monitoring point. Therefore, it can reflect the quality of the receiver performance and the observation environment, and is a comprehensive indicator that intuitively reflects the quality of the observation data. The higher the data integrity rate, the better the receiver performance and the observation conditions. The calculation formula is as follows:

[0045]

[0046] Among them, DI f is the data integrity rate of the satellite's single-frequency point observation, n is the total number of satellites observed during the observation period, j is the observed satellite number, A j is the total number of actual observation epochs of the j-th satellite at the f frequency point during the observation period, B j is the total number of theoretical observation epochs of the j-th satellite at the f frequency point during the observation period.

[0047] The data integrity rate can reflect the quality of the receiver performance and the observation environment. The data integrity rate calculated in this solution uses the full satellite ephemeris information, and can calculate the blocked satellites, so as to accurately judge the occlusion situation of the satellites. As Figure 2 shown, at each epoch, calculate the elevation angle of the satellite according to the broadcast ephemeris, that is, the theoretical elevation angle. Note that all satellites in the system are processed, and this satellite may not be observed at this epoch. Compare the theoretical elevation angle with the cut-off elevation angle. If the former is greater than the latter, then it is considered that the satellite should be observed theoretically, that is, the number of theoretical observation epochs of this satellite is incremented by 1. The actual observation epochs are counted according to the actual observation situation. Finally, divide the actual observation epochs by the theoretical observation epochs to obtain the data integrity rate calculated in this solution.

[0048] S3. Use the obtained data integrity rate and the original observation information to calculate the signal-to-noise ratio, and evaluate the cycle slip ratio and multipath effect in the carrier phase measurement.

[0049] The signal-to-noise ratio (SNR) is the ratio of the signal power to the noise power, usually expressed in decibels (dB). The signal-to-noise ratio reflects the receiver's ability to search and track satellite signals, and is an important parameter in GNSS data processing. The larger the signal-to-noise ratio, the better the quality of the satellite observation data. The calculation formula is as follows:

[0050]

[0051] Among them, is the statistical value of the satellite observation signal-to-noise ratio index, N is the total number of satellite observation epochs, t iis the observation epoch serial number of the satellite, SNR j (t i ) is the SNR observation value of satellite j at epoch t i , with the unit of dB.

[0052] When the receiver performs carrier phase measurement, the phenomenon that the integer cycle count is incorrect while the fractional part remains correct is called cycle slip, abbreviated as CS. Cycle slip is an important parameter in GNSS data processing. The cycle slip ratio (CSR) is the ratio of the number of observations to the number of cycle slips, which can reflect the quality of the carrier phase observation data and the receiver's ability to repair cycle slips. The larger the cycle slip ratio, the fewer the number of cycle slips, and the better the quality of the observation data. The calculation formula is as follows:

[0053] C = O / S

[0054] where C represents the cycle slip ratio, O is the number of observations, and S is the number of cycle slips.

[0055] After the satellite signal is reflected by the reflectors near the measuring station (reflected wave), it enters the receiver antenna and interferes with the signal directly from the satellite (direct wave), resulting in the deviation of the observation value from the true value. This effect is called the multipath effect, and the measurement error caused by it is called the multipath error. The multipath effect is mainly affected by the surrounding environment of the receiver. Reflectors such as large calm water surfaces and high-rise buildings have strong reflection capabilities, and the stations near them are more severely affected by the multipath effect. The anti-multipath performance is an important indicator to evaluate the performance of the receiver. The smaller the value of the multipath effect, the better the observation environment of the monitoring point and the anti-multipath performance of the receiver, and the higher the quality of the observation data. First, calculate the linear combination of dual-frequency pseudorange and phase observations:

[0056]

[0057] where are the multipath effects containing multipath error and integer ambiguity information at frequencies k1 and k2 respectively, are the pseudorange observations at frequencies k1 and k2 respectively, are the frequencies of the k1 and k2 carriers respectively, are the carrier phase observations at frequencies k1 and k2 respectively;

[0058] For the same satellite, in the continuous observation arc without cycle slips, the ambiguity parameter remains fixed. The multipath error is calculated using the following formula:

[0059]

[0060] where is the multipath error evaluation value of the receiver receiving the signal of satellite k frequency, Nsw is the number of epochs of the sliding window, MP k (t i ) is the multipath error value at the signal frequency k at time t i

[0061] The above can obtain a value (temporarily called the original value) at each moment. Here is equivalent to using the sliding window method to find the smoothed value of the original value within the window, aiming to weaken the influence of pseudorange noise.

[0062] The signal-to-noise ratio reflects the receiver's ability to search for and track satellite signals and is an important parameter for Beidou data processing; the cycle slip ratio can reflect the quality of the carrier phase observation data and directly affects the deformation monitoring accuracy; the path effect is mainly affected by the surrounding environment of the receiver. Reflective objects such as large calm water surfaces and high-rise buildings have strong reflection capabilities, and the stations near them are also severely affected by the multipath effect. Through comprehensive processing of various indicators for data quality assessment, the present invention divides the available levels of the observed data under the premise of considering the characteristics of the deformation monitoring scenario of the hydropower project and relevant adaptation technical indicators, so as to clarify the health status and available level of the data collected by the GNSS receiver at the specified monitoring point, and provide important reference information for real-time system operation and maintenance and the adaptation of the optimal solution algorithm mode.

[0063] S4. Consider the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect separately to obtain single-item evaluation grades.

[0064] First, calculate for each single-quality index such as the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect for each monitoring station, then conduct joint analysis and calculation for the combined reference station - monitoring station pair, and finally calculate the comprehensive evaluation of the multi-quality assessment index to evaluate and grade the quality of the Beidou observation data received by each monitoring station. As Figure 3 shown.

[0065] The single-item evaluation grades include setting the first threshold of the data integrity rate, the second threshold of the data integrity rate, the third threshold of the data integrity rate, the fourth threshold of the data integrity rate, the first threshold of the signal-to-noise ratio, the second threshold of the signal-to-noise ratio, the third threshold of the signal-to-noise ratio, the fourth threshold of the signal-to-noise ratio, the first threshold of the cycle slip ratio, the second threshold of the cycle slip ratio, the third threshold of the cycle slip ratio, the fourth threshold of the cycle slip ratio, the first threshold of the multipath effect, the second threshold of the multipath effect, the third threshold of the multipath effect, and the fourth threshold of the multipath effect.

[0066] ​The calculated data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect are respectively compared with the corresponding first threshold, second threshold, third threshold, and fourth threshold. If it is less than the first threshold, the single-item evaluation level is poor; if it is greater than or equal to the first threshold and less than the second threshold, the single-item evaluation level is normal; if it is greater than or equal to the third threshold and less than the fourth threshold, the single-item evaluation level is good; if it is greater than or equal to the fourth threshold, the single-item evaluation level is excellent. And the single-item scores of different single-item evaluation levels are obtained based on the calculated data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect. As shown in Table 1.

[0067] Table 1 GNSS Single-Item Data Quality Rating System for Stations

[0068]

[0069]

[0070] S5. Considering the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect comprehensively, the quality assessment and grading of the original observation information received by each monitoring station are carried out.

[0071] The combined analysis is to analyze using the common-view satellites of the reference station - monitoring station, extract the common observation epochs of the reference station and the monitoring station (i.e., the same observation time), and take out the satellites that are commonly observed in the common observation epochs, which are the common-view satellites. For the common-view satellites, the quality analysis of the above data integrity rate, signal-to-noise ratio, cycle slip ratio, multipath effect, etc. is carried out.

[0072] When comprehensively grading the stations, the data integrity rate is considered first, the cycle slip ratio is considered second, and the signal-to-noise ratio is considered last: that is, if the integrity rate does not reach excellent, the integrity rate level is taken as the final level. In the case where the integrity rate is excellent, the cycle slip ratio level is taken as the final level. In the case where both the integrity rate and the cycle slip ratio are excellent, the signal-to-noise ratio level is taken as the final level. It should be noted that in the case where there is no cycle slip in the receiver carrier phase measurement value and the surrounding electromagnetic environment is relatively clean, MP1 and MP2 mainly reflect the pseudorange multipath effect, and in the actual solution, they are mainly used to assist steps such as cycle slip detection and ambiguity search of the carrier phase, and can not be used as the main indicators.

[0073] Embodiment 2 is the second embodiment of the present invention, which is different from the previous two embodiments in that:

[0074] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0075] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0076] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or more wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0077] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0078] Example 3, referring to Figure 4 , which is the third embodiment of the present invention. This embodiment provides a Beidou observation data quality analysis system for dam deformation monitoring, including a data acquisition module, a data integrity rate calculation module, a calculation module, a single-item average module, and a comprehensive average module.

[0079] The data acquisition module is used to collect original observation information at the monitoring points through a Beidou monitoring receiving device, and transmit the original observation information and full satellite ephemeris information to the monitoring station through communication technology.

[0080] The data integrity rate calculation module is used to calculate the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs for each monitoring point by using the full satellite ephemeris information.

[0081] The calculation module is used to calculate the signal-to-noise ratio by using the obtained data integrity rate and the original observation information, and evaluate the cycle slip ratio and multipath effect in carrier phase measurement.

[0082] The single-item average module is used to separately consider the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to obtain a single-item evaluation grade.

[0083] The comprehensive average module is used to comprehensively consider the data integrity rate, signal-to-noise ratio, cycle slip ratio, and multipath effect to perform quality evaluation and grading on the original observation information received by each monitoring station.

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A Beidou observation data quality analysis method for dam deformation monitoring, characterized in that: including collecting original observation information at a monitoring point through a Beidou monitoring and receiving device, and transmitting the original observation information and full satellite ephemeris information to a monitoring station through communication technology; calculating the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs at each monitoring point by using the full satellite ephemeris information; calculating the signal-to-noise ratio by using the obtained data integrity rate and original observation information, and evaluating the cycle slip ratio and multipath effect in carrier phase measurement; individually considering the data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect to obtain a single-item evaluation grade; comprehensively considering the data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect to conduct quality assessment and grade division on the original observation information received by each monitoring station.

2. The Beidou observation data quality analysis method for dam deformation monitoring according to claim 1, characterized in that: The communication technology includes a 4G communication protocol or a TCP protocol or a Lora communication technology; The full satellite ephemeris information includes, at each epoch, calculating the elevation angle of a satellite according to the broadcast ephemeris, i.e., the theoretical elevation angle, comparing the theoretical elevation angle with a preset cut-off elevation angle. If the theoretical elevation angle is greater than the cut-off elevation angle, it is considered that the satellite is theoretically observed, i.e., the number of theoretical observation epochs of the satellite is incremented by 1, and the actual observation epochs are counted according to the actual observation situation.

3. A Beidou observation data quality analysis method for dam deformation monitoring according to claim 2, characterized in that: The data integrity rate includes calculating according to the ratio of the actual epoch data volume of the satellite observed by the receiver to the theoretical epoch data volume, expressed as Among them, DI f is the integrity rate of satellite single-frequency point observation data, n is the total number of satellites observed during the observation period, j is the satellite number of observation, A j is the total number of actual observation epochs of the j-th satellite at the f frequency point during the observation period, B j is the total number of theoretical observation epochs of the j-th satellite at the f frequency point during the observation period.

4. The Beidou observation data quality analysis method for dam deformation monitoring according to claim 3, characterized in that: The signal-to-noise ratio is expressed as Among them, is the statistical value of the satellite observation signal-to-noise ratio index, N is the total number of satellite observation epochs, and t i is the serial number of the satellite observation epoch, and SNR j (t i ) is the signal-to-noise ratio observation value of satellite j at epoch t i ; The cycle slip ratio is expressed as C = O / S where C represents the cycle slip ratio, O is the number of observation values, and S is the number of cycle slips.

5. The Beidou observation data quality analysis method for dam deformation monitoring according to claim 4, wherein: The multipath effect includes calculating the linear combination of dual-frequency pseudorange and phase observation values, expressed as Among them, are the multipath effects containing multipath error and integer ambiguity information at frequencies k1 and k2 respectively, are the pseudorange observations at frequencies k1 and k2 respectively, are the frequencies of the carriers at k1 and k2 respectively, are the carrier phase observations at frequencies k1 and k2 respectively; For the same satellite, in a continuous observation arc without cycle slips, the ambiguity parameter remains fixed, and the multipath error is calculated, expressed as Among them, is the multipath error evaluation value of the receiver receiving the frequency signal from satellite k, N sw is the number of epochs of the sliding window, MP k (t i ) is the multipath error value on signal frequency k at time t i moment.

6. The Beidou observation data quality analysis method for dam deformation monitoring according to claim 4, characterized in that: The single-item evaluation grade includes setting a first threshold, a second threshold, a third threshold, a fourth threshold for the data integrity rate, a first threshold, a second threshold, a third threshold, a fourth threshold for the signal-to-noise ratio, a first threshold, a second threshold, a third threshold, a fourth threshold for the cycle slip ratio, a first threshold, a second threshold, a third threshold, a fourth threshold for the multipath effect; Using the calculated data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect to compare with the corresponding first threshold, second threshold, third threshold, fourth threshold respectively. If it is less than the first threshold, the single-item evaluation grade is poor. If it is greater than or equal to the first threshold and less than the second threshold, the single-item evaluation grade is normal. If it is greater than or equal to the third threshold and less than the fourth threshold, the single-item evaluation grade is good. If it is greater than or equal to the fourth threshold, the single-item evaluation grade is excellent, and the single-item scores of different single-item evaluation grades are obtained according to the calculated data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect.

7. The Beidou observation data quality analysis method for dam deformation monitoring according to claim 4, wherein: The comprehensive consideration of the data integrity rate, signal-to-noise ratio, cycle slip ratio and multipath effect includes giving priority to the data integrity rate, followed by the cycle slip ratio, and finally the signal-to-noise ratio; If the data integrity rate fails to reach excellent, the integrity rate grade is taken as the final grade; In the case where the integrity rate is excellent, the grade of the cycle slip ratio is taken as the final grade; When both the integrity rate and the cycle slip ratio are excellent, the signal-to-noise ratio level is used as the final level.

8. A Beidou observation data quality analysis system for dam deformation monitoring, which applies a Beidou observation data quality analysis method for dam deformation monitoring as described in any one of claims 1 to 7, characterized in that, Including: A data acquisition module, a data integrity rate calculation module, a calculation module, a single-item averaging module, and a comprehensive averaging module; The data acquisition module is used to collect original observation information at the monitoring point through the Beidou monitoring receiving device, and transmit the original observation information and the full satellite ephemeris information to the monitoring station through communication technology; The data integrity rate calculation module is used to calculate the data integrity rate between the total number of theoretical observation epochs and the total number of actual observation epochs at each monitoring point by using the full satellite ephemeris information; The calculation module is used to calculate the signal-to-noise ratio by using the obtained data integrity rate and the original observation information, and evaluate the cycle slip ratio and the multipath effect in the carrier phase measurement; The single-item averaging module is used to separately consider the data integrity rate, the signal-to-noise ratio, the cycle slip ratio, and the multipath effect to obtain a single-item evaluation level; The comprehensive averaging module is used to comprehensively consider the data integrity rate, the signal-to-noise ratio, the cycle slip ratio, and the multipath effect to perform quality evaluation and level division on the original observation information received by each monitoring station.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of a Beidou observation data quality analysis method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of a Beidou observation data quality analysis method according to any one of claims 1 to 7 are implemented.

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