A landslide body millimeter-level displacement real-time monitoring method based on beidou-3 double-frequency observation

Abstract

The present application belongs to the technical field of geological disaster monitoring, and particularly relates to a landslide millimeter-level displacement real-time monitoring method based on Beidou No. 3 dual-frequency observation. The method constructs a short baseline network by arranging GNSS monitoring stations in the deformation sensitive area of the landslide and arranging differential reference stations in the stable bedrock area, and synchronously collects Beidou B1C / B2a dual-frequency observation values. The multipath error is suppressed by the dual mechanisms of hardware radius suppression and algorithm correction, the carrier phase observation values are corrected, the localized RTK solution is executed on the embedded platform, the common error is eliminated by combining the wide and narrow lane combination technology and the double difference model, and then the high-precision displacement data is output through the adaptive dynamic filtering based on the PDOP value. The present application realizes millimeter-level monitoring precision, has strong anti-interference ability and environmental adaptability, can accurately capture the early creep of the landslide, and provides reliable support for disaster warning.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of geological disaster monitoring, and particularly relates to a landslide millimeter-level displacement real-time monitoring method based on Beidou-3 dual-frequency observation. BACKGROUND

[0002] Landslide geological disasters pose a serious threat to people's life and property safety, and existing monitoring technologies have multiple limitations. Traditional manual monitoring methods such as total station and range finder require personnel to work on site, are restricted by bad weather and complex terrain, and the sampling frequency is usually limited to once a day, making it difficult to capture transient deformation signals, and the risk of operation in high-risk environments is significant. Although the sensor network scheme such as inclinometer and crack meter can realize automatic monitoring, it can only obtain local point information and cannot fully reflect the overall displacement trend of the landslide body, and it also faces the problems of complex installation and high maintenance cost.

[0003] Satellite navigation technology provides a new way to solve the above problems, but the current widely used single-frequency GNSS system still faces serious challenges in landslide monitoring. Ionospheric delay can significantly amplify positioning errors under certain space weather conditions, and multipath effects caused by signal disturbances in complex mountainous environments are particularly prominent, making it difficult to meet the millimeter-level monitoring requirements of the integrated positioning accuracy, and unable to effectively capture the key evolution stage of early weak creep of landslides. Although the dual-frequency GNSS technology partially overcomes the ionospheric error through multi-frequency combination, the existing scheme still has obvious defects. The dependence on GPS or GLONASS system leads to unstable signal coverage in remote mountainous areas; the data processing relies on cloud servers, causing real-time degradation; the effectiveness of the multipath suppression mechanism is limited in complex terrain; and the fixed design of filter parameters cannot adapt to dynamic environmental changes such as signal obstruction and weather interference. The above technical bottlenecks seriously restrict the early warning capability of landslide disasters, and it is urgent to develop a new monitoring method with self-control, millimeter-level precision and strong anti-interference characteristics. SUMMARY

[0004] The present application proposes a landslide millimeter-level displacement real-time monitoring method based on Beidou-3 dual-frequency observation to solve the technical problems in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present application is as follows:

[0006] S1, arranging GNSS monitoring stations on the surface deformation sensitive area of the landslide body, arranging differential reference stations in the stable geological structure of the bedrock area, and constructing a short baseline monitoring network;

[0007] S2, synchronously collect the original observation values of the Beidou frequency points through the differential reference station and the GNSS monitoring station, realize sub-second time synchronization by adopting the PTP protocol, synchronously acquire the dual-frequency pseudo-range and carrier phase observation values at a sampling rate of 5 Hz, and return the observation data to the monitoring station embedded processing platform in real time;

[0008] S3, suppress the multipath error by the double mechanism of hardware suppression and algorithm correction, and correct the carrier phase observation values;

[0009] The hardware layer adopts a metal suppression plate with a diameter of 40 cm and an edge inclination angle of 15°, which is installed at the bottom of the antenna of the monitoring station to suppress the ground reflected signal;

[0010] The algorithm layer dynamically calculates the multipath correction amount based on the satellite elevation angle The correction amount formula is: wherein the coefficient k is obtained by 24-hour static calibration on site, and the value range is [0.05, 0.15], and the correction amount is used to correct the carrier phase observation values: wherein is the carrier phase observation value, is the corrected carrier phase observation value;

[0011] S4, execute the localized RTK solution on the monitoring station embedded processing platform, dynamically output the three-dimensional relative displacement amount, and eliminate the common error based on the double difference observation model;

[0012] S5, calculate the instantaneous horizontal displacement from the three-dimensional relative displacement amount obtained by the localized RTK solution, and perform adaptive dynamic filtering processing on the displacement sequence formed by the horizontal displacement to obtain stable and reliable high-precision displacement data.

[0013] As preferred, the distance between the GNSS monitoring station and the differential reference station in step S1 is ≤5 km, the GNSS monitoring station is equipped with a Beidou No. 3 B1C and B2a dual-frequency receiver and an anti-multipath choke coil antenna, and the differential reference station is located to satisfy the satellite signal shielding angle <10° and avoid strong electromagnetic interference sources.

[0014] As preferred, the step S4 of executing the localized RTK solution on the monitoring station embedded processing platform to dynamically output the three-dimensional relative displacement amount and eliminate the common error based on the double difference observation model includes the following specific steps:

[0015] S41, execute the localized RTK solution on the monitoring station embedded platform;

[0016] S42, adopt the wide-narrow lane combination technology, the wide lane combination observation value is: , and the narrow lane combination observation value is: wherein, is the frequency of the B1C frequency point, is a frequency of a B2a frequency point; is a corrected carrier phase observation value of a B1C frequency point, is a corrected carrier phase observation value of a B2a frequency point;

[0017] S43, based on the double-difference observation value, solving the three-dimensional relative displacement component of the monitoring station relative to the reference station.

[0018] As preferred, the step S5 calculates the instantaneous horizontal displacement based on the three-dimensional relative displacement obtained by the localized RTK solution, and the stable and reliable high-precision displacement data is obtained by performing adaptive dynamic filtering processing on the displacement sequence constituted by the horizontal displacement.

[0019] S51, first, based on the dynamic filtering algorithm of the positioning quality evaluation, processing the horizontal displacement, calculating the instantaneous horizontal displacement: , wherein are the relative displacement values of the x-axis and the y-axis, respectively;

[0020] S52, obtaining the positioning quality factor PDOP value, dynamically adjusting the filtering parameters; when PDOP≤2, sliding average filtering is adopted; when 2<PDOP≤5, Kalman filtering is adopted; when PDOP>5, wavelet threshold denoising is enabled;

[0021] S53, finally, performing variable parameter filtering to obtain the displacement , wherein, is a variable filtering coefficient, is the horizontal displacement sequence obtained by performing variable parameter filtering and weighted summation processing at the previous moment.

[0022] Compared with the prior art, the advantages and positive effects of the present application are:

[0023] 1. High monitoring accuracy: using Beidou No. 3 double-frequency signals and short baseline RTK solution, the horizontal displacement monitoring accuracy is improved to millimeter level, which can capture early weak creep of landslides.

[0024] 2. Strong anti-interference ability: by combining the hardware of the diameter plate with the multi-path correction model, the multi-path error in complex mountainous environment is significantly reduced, and the data availability in bad weather is improved.

[0025] 3. Strong environmental adaptability: the adaptive filtering algorithm dynamically adjusts the filtering strength according to the positioning quality, strengthens the noise reduction when the signal is blocked, and retains the true displacement details in open environment, ensuring the monitoring reliability in different environments. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative labor.

[0027] Figure 1 A structural flowchart of a landslide millimeter-level displacement real-time monitoring method based on Beidou No. 3 dual-frequency observation. DETAILED DESCRIPTION

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative labor.

[0029] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, however, the present application can also be implemented in other ways different from the description, therefore, the present application is not limited to the specific embodiments disclosed in the following description.

[0030] Embodiment, in order to overcome the problem that the existing landslide monitoring technology cannot realize millimeter-level precision, real-time performance is insufficient, anti-interference ability is weak, and adaptability to complex mountain environment is poor, the present application provides a landslide millimeter-level displacement real-time monitoring method based on Beidou No. 3 dual-frequency observation. The method deploys a short baseline monitoring network, introduces a dual-frequency synchronous observation mechanism, constructs a multi-path suppression model combining hardware and algorithm, realizes local RTK solution, and designs an adaptive dynamic filtering algorithm, so as to achieve the purpose of real-time high-precision displacement monitoring. The specific implementation is as shown in Figure 1 .

[0031] Firstly, the present embodiment arranges a plurality of GNSS monitoring stations in the deformation sensitive area of the landslide body, and arranges a differential reference station in the bedrock area with stable geological structure and high safety level. The distance between the monitoring station and the reference station is limited within ≤5km range, so as to ensure high ambiguity fixing rate of Beidou dual-frequency carrier phase solution and stable baseline solution. The monitoring station is equipped with Beidou No. 3 B1C / B2a dual-frequency receiver and anti-multipath choke coil antenna, and the reference station site selection needs to meet the satellite signal shielding angle <10°.

[0032] The original observation values of Beidou B1C and B2a frequencies are collected by the reference station and the monitoring station synchronously to realize sub-second time synchronization. The dual-frequency pseudo-range and carrier phase observation values are synchronously obtained at a sampling rate of 5 Hz, and the PTP protocol is used to ensure time synchronization, ensuring an error of less than 1 ms. Specifically, the reference station and the monitoring station are respectively equipped with high-precision receivers supporting Beidou-3 B1C and B2a dual-frequency signals, and the simultaneous collection capability of the receivers for dual-frequency carrier phase and pseudo-range observation values is used to ensure the consistency of the observation frequencies at the physical layer. At the same time, the PTP (Precision Time Protocol) precise time service mechanism is deployed in the inter-station communication network to realize the propagation of nanosecond-level time stamps, the calibration of hardware clocks, and the periodic comparison of time synchronization signals, so that the overall time synchronization error of the system is strictly controlled within 1 ms. On the basis of continuous and effective time synchronization, the system obtains the original pseudo-range and carrier phase observation values of B1C and B2a frequencies in real time at a high sampling frequency of 5 Hz, so that the monitoring system can capture the weak dynamic displacement changes and transient disturbances of the landslide body, and the synchronized observation data are returned to the embedded processing platform of the monitoring station with a millisecond-level time delay, realizing real-time and continuous calculation of deformation information. This dual-frequency synchronization, high-speed sampling, and precise time service observation mode ensures the consistency of the data time sequence, and significantly improves the stability and reliability of the subsequent differential calculation.

[0033] In order to effectively suppress the multipath error in a complex mountainous environment and solve the problem that the GNSS monitoring precision is seriously affected by ground reflection and multi-source interference, a double-layer suppression mechanism combining hardware suppression and algorithm correction is adopted in the embodiment. The multipath error is suppressed by the double-layer mechanism of hardware suppression and algorithm correction, and the carrier phase observation values are corrected. The hardware layer adopts a metal suppression plate with a diameter of 40 cm and an edge inclination angle of 15°, which is installed at the bottom of the antenna of the monitoring station to suppress the ground reflected signal. The algorithm layer dynamically calculates the multipath correction value based on the satellite elevation angle The correction value formula is: wherein the coefficient k is obtained by 24-hour static calibration on site, and the value range is [0.05, 0.15], and the carrier phase observation value is corrected by using the correction value: wherein is the carrier phase observation value, is the corrected carrier phase observation value. The hardware suppression reduces the interference of the strong reflection path signal, and the algorithm dynamic correction further compensates for the limitations of the hardware suppression, so that the stability of the carrier phase can be maintained in a low satellite elevation angle and weak signal environment. The double-layer mechanism significantly reduces the carrier phase observation noise, providing reliable input for millimeter-level displacement calculation.

[0034] Then in order to achieve fast, stable and high-precision displacement calculation in landslide monitoring site, solve the problems of poor real-time performance, dependence on external network and easy to be affected by communication interference of traditional cloud RTK calculation, the embedded local RTK calculation architecture is adopted, the dynamic output three-dimensional relative displacement is output, and the common error is eliminated based on the double difference observation model. Specifically, after the Beidou B1C, B2a double frequency carrier phase observation values after synchronization collection and correction are received by the monitoring station, firstly, the double difference observation model between the reference station and the monitoring station is constructed in the local processing platform, the wide and narrow lane combination technology is adopted, the wide lane combination observation value is: , the narrow lane combination observation value is: , wherein, is the frequency of B1C frequency, is the frequency of B2a frequency; is the corrected carrier phase observation value of B1C frequency, is the corrected carrier phase observation value of B2a frequency; based on the double difference observation value, the three-dimensional relative displacement component of the monitoring station relative to the reference station is calculated, and the common error such as satellite clock error, receiver clock error and ionospheric delay is eliminated, so that the purity of the carrier phase observation value is improved significantly.

[0035] Finally, the three-dimensional relative displacement obtained by local RTK calculation is calculated to obtain stable and reliable high-precision displacement data. The realization is that firstly, the dynamic filtering algorithm based on positioning quality evaluation is used to process the horizontal displacement, and the instantaneous horizontal displacement is calculated: , wherein are the relative displacement values of x-axis and y-axis respectively; the positioning quality factor PDOP value is obtained, and the filtering parameter is dynamically adjusted; when PDOP is less than or equal to 2, sliding average filtering is adopted; when 2 is less than or equal to 5, Kalman filtering is adopted; when PDOP is greater than 5, wavelet threshold denoising is enabled; finally, variable parameter filtering is carried out to obtain displacement , wherein, is the variable filtering coefficient, The horizontal displacement sequence obtained after the previous time's variable parameter filtering and weighted sum processing. Specifically, the system first extracts the plane component from the x, y, z displacement components obtained by RTK calculation, and constructs the instantaneous horizontal displacement from the x, y displacement. This instantaneous horizontal displacement reflects the dynamic change of the landslide body in the plane direction, and is an important basis for determining the weak creep and sudden displacement of the landslide. On this basis, the system introduces the positioning quality factor PDOP as the core adaptive evaluation index of the filtering strategy. Since PDOP can reflect the influence of the current geometric distribution on the positioning accuracy, it is suitable as the basis for dynamically adjusting the filtering strength. When PDOP≤2, it indicates that the distribution is good and the observation accuracy is high, and the system uses sliding average filtering to slightly smooth the instantaneous horizontal displacement, so as to maximize the retention of true displacement details. When 2<PDOP≤5, the stability of the observation data decreases, and the system enables Kalman filtering, which considers the historical displacement state and the current observation value, to suppress random fluctuations while maintaining response speed. When PDOP>5, the observation data structure is significantly deteriorated, the carrier observation noise and jump risk increase, and the system switches to wavelet threshold denoising, which effectively filters sudden noise peaks by decomposing and thresholding the displacement sequence, preventing false displacement information from entering the subsequent monitoring model. After the above multi-strategy filtering is completed, the system performs variable parameter filtering on the smoothed displacement value to ensure the continuity and stability of the sequence. Recursive variable parameter filtering is performed according to PDOP and displacement change rate in real time to optimize the filtering balance point in different environmental conditions. The output of the previous time's variable parameter filtering and weighted sum, used to strengthen the sequence continuity and reduce the jump caused by measurement fluctuations. Through this chain adaptive dynamic filtering mechanism, the ability to stably output high-precision displacement results in complex terrain, weak signal and weather interference background is realized, providing a reliable data basis for early warning of landslides.

[0036] The above is only a preferred embodiment of the present application, and is not intended to limit the present application in other forms. Any skilled person in the art can modify or change the above disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification of the above embodiments without departing from the technical solution content of the present application, according to the technical essence of the present application, still belongs to the protection scope of the present application.

Claims

1. A method for real-time monitoring of millimeter-level displacement of landslides based on dual-frequency observation of BeiDou-3, characterized in that, It includes the following steps: S1. Install GNSS monitoring stations in the deformation-sensitive areas on the surface of the landslide body, and install differential reference stations in the bedrock areas with stable geological structures to construct a short-baseline monitoring network; S2. Synchronously collect the original observation values of Beidou frequency points through the differential reference stations and GNSS monitoring stations, use the PTP protocol to achieve sub-second time synchronization, synchronously obtain dual-frequency pseudorange and carrier phase observation values at a sampling rate of 5Hz, and transmit the observation data back to the monitoring station embedded processing platform in real time; S3. Suppress the multipath error through a dual mechanism of hardware multipath suppression and algorithm correction, and correct the carrier phase observation values; At the hardware layer, a metal multipath suppression plate with a diameter of 40 cm and an edge inclination angle of 15° is installed at the bottom of the monitoring station antenna to suppress the ground reflection signal; The algorithm layer is based on satellite elevation angle. The multipath correction amount is calculated dynamically, and the correction amount formula is as follows: The coefficient k is obtained through 24-hour static calibration on-site, with a value range of [0.05, 0.15], and the correction amount is used to correct the carrier phase observation value. ,in For carrier phase observations, For the corrected carrier phase observations; S4. Perform local RTK solution at the monitoring station embedded processing platform, dynamically output the three-dimensional relative displacement, and eliminate the common error based on the double-difference observation model; S5. Calculate the instantaneous horizontal displacement from the three-dimensional relative displacement obtained by the local RTK solution, and perform adaptive dynamic filtering on the displacement sequence composed of the horizontal displacement to obtain stable and reliable high-precision displacement data.

2. The method for real-time monitoring of millimeter-level displacement of landslides based on BeiDou-3 dual-frequency observation as described in claim 1, characterized in that, In step S1, the distance between the GNSS monitoring station and the differential reference station is ≤ 5 km. The GNSS monitoring station is equipped with a Beidou-3 B1C and B2a dual-frequency receiver and an anti-multipath choke ring antenna. The location selection of the differential reference station satisfies that the satellite signal occlusion angle < 10° and avoids strong electromagnetic interference sources.

3. The method for real-time monitoring of millimeter-level displacement of landslides based on BeiDou-3 dual-frequency observation as described in claim 1, characterized in that, The specific steps of performing local RTK solution at the monitoring station embedded processing platform in step S4 to dynamically output the three-dimensional relative displacement and eliminate the common error based on the double-difference observation model include: S41. Perform local RTK solution at the monitoring station embedded platform; S42. Using the wide-narrow lane combination technique, the observed value for the wide lane combination is: The observed values ​​for the narrow alley combination are: ,in, The frequency of the B1C point, This refers to the frequency of point B2a. The corrected carrier phase observation value for the B1C frequency point. The corrected carrier phase observation value for frequency B2a; S43. Based on the double-difference observations, solve the three-dimensional relative displacement components of the monitoring station relative to the reference station.

4. The method for real-time monitoring of millimeter-level displacement of landslides based on BeiDou-3 dual-frequency observation as described in claim 1, characterized in that, The implementation of calculating the instantaneous horizontal displacement from the three-dimensional relative displacement obtained by the local RTK solution in step S5 and performing adaptive dynamic filtering on the displacement sequence composed of the horizontal displacement to obtain stable and reliable high-precision displacement data is as follows: S51. First, the horizontal displacement is processed based on the dynamic filtering algorithm of the positioning quality assessment to calculate the instantaneous horizontal displacement: ,in These are the relative displacement values ​​along the x-axis and y-axis, respectively. S52. Obtain the positioning quality factor PDOP value and dynamically adjust the filtering parameters; when PDOP ≤ 2, use moving average filtering; when 2 < PDOP ≤ 5, use Kalman filtering; when PDOP > 5, enable wavelet threshold denoising; S53. Finally, variable parameter filtering is performed to obtain the displacement. ,in, For variable filter coefficients, This is the horizontal displacement sequence obtained from the previous time step after variable parameter filtering and weighted summation.

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