Data acquisition device and data acquisition system for civil engineering surveying and mapping

Abstract

The invention discloses a data acquisition device and a data acquisition system for civil engineering surveying and mapping, and relates to the field of surveying and mapping acquisition, and the data acquisition device comprises a surveying and mapping instrument main body which is used for deploying a plurality of sensors and performing original surveying and mapping sensing data acquisition at a preset acquisition angle through the sensors; the analysis unit is used for generating an acquisition correction instruction for the environmental interference factors according to the original sensing data acquired by the surveying instrument main body, and submitting the acquisition correction instruction to the surveying instrument main body for acquiring angle deviation; a submodule is deployed in the lower level of the analysis unit and comprises a distance extraction module used for extracting distance parameters in original data collected by the surveying instrument main body and filtering the distance parameters; according to the method, the interference correction instruction is dynamically generated, and the acquisition angle of the sensor is adjusted to make up errors caused by environmental interference, so that the influence of the environmental interference on surveying and mapping results is effectively reduced, the reliability of data is remarkably improved through an intelligent correction strategy, and errors caused by human or environmental factors are reduced.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping acquisition technology, and in particular to a data acquisition device and a data acquisition system for civil engineering surveying and mapping. Background Art

[0002] With the acceleration of global urbanization and the advancement of science and technology, the demand for infrastructure construction has increased, and the demand for data accuracy in civil engineering surveying and mapping has continued to increase. The performance of various sensors in the background environment also needs to keep pace with the times to meet the needs of modern engineering applications. The improvement of sensor integration and the development of intelligent environmental monitoring technology have prompted the transformation of existing surveying and mapping methods to intelligent and automated ones.

[0003] Civil engineering projects are usually located in various natural and man-made environments such as cities, villages, and mountains. Different environments will lead to different interference factors. In the actual surveying and mapping process, the environment is dynamically changing, such as vehicles passing by, workers' activities, fallen leaves blown by the wind, etc. These background objects can easily interfere with the measurement signal, affecting the signal propagation path or causing signal scattering, resulting in signal attenuation or reflection, thereby affecting the accuracy of the measurement. With the advancement of civil engineering technology and the increase in demand, the requirements for surveying and mapping accuracy are becoming increasingly stringent, forcing the impact of environmental interference to be taken seriously and corrected. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a data acquisition device and a data acquisition system for civil engineering surveying and mapping, which can effectively solve the problems of the prior art.

[0006] (2) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] In a first aspect, the present invention discloses a data acquisition device and a data acquisition system for civil engineering surveying and mapping, comprising:

[0009] The main body of the surveying instrument is used to deploy a number of sensors and collect raw surveying and mapping sensor data at preset collection angles through the sensors;

[0010] The analysis unit is used to generate collection correction instructions for environmental interference factors based on the raw sensor data collected by the surveying instrument body, and submit them to the surveying instrument body to shift the collection angle. The analysis unit is deployed with submodules at the lower level, including:

[0011] The distance extraction module is used to extract the distance parameters from the raw data collected and filtered by the surveying instrument body;

[0012] The factor extraction module is used to monitor the ranging background during the acquisition of the surveying instrument body and extract the background object covering factor data based on the preset interference index;

[0013] The model building module is used to build an environmental interference model through a regression algorithm, input the current background object covering factor data, and output several interference features of the current ranging background;

[0014] The interference integration module is used to extract several interference features output by the model building module, perform quantitative processing, and output an interference factor set;

[0015] The decision-making unit is used to determine whether the interference factor set output by the interference integration module triggers the abnormal threshold. If a triggering behavior occurs, the integrated output compensation strategy is generated;

[0016] The instruction adjustment module is used to receive the compensation strategy of the decision unit, calculate and output the acquisition angle offset instruction of the surveying instrument body based on the ranging target, and adjust the acquisition angle of the surveying instrument body.

[0017] Furthermore, the decision unit is deployed at a lower level with sub-modules, which include: a judgment module, a trigger module and an integrated analysis module. The trigger module is interactively connected to the judgment module and the integrated analysis module through a wireless network. The judgment module is used to set a pre-defined interference threshold. When the interference feature index exceeds the threshold, it is determined that correction is required and a correction trigger signal is output. The trigger module is used to receive the correction trigger signal of the judgment module and match the interference intensity according to the threshold exceeding the range. The integrated analysis module is used to integrate and analyze several current interference features and distance parameters, calculate the correction amount according to the interference intensity, and obtain the adjustment amplitude.

[0018] Furthermore, the integration analysis module receives the interference factor set output by the interference integration module and the distance parameter extracted by the distance extraction module, and establishes a weight distribution relationship between the interference feature and the distance parameter according to the interference intensity level matched by the trigger module, wherein the weight of the distance parameter decreases as the interference intensity increases;

[0019] Fit the functional relationship between the interference feature and the distance parameter, and output the fitting residual as the initial correction value;

[0020] Based on the initial correction amount and the interference intensity coefficient provided by the trigger module, the final correction amount and the corresponding acquisition angle adjustment range are calculated.

[0021] Furthermore, the calculation formula for the acquisition angle adjustment range is:

[0022]

[0023] Where T represents the adjustment amplitude, k represents the interference intensity coefficient, n represents the total number of interference features, and w i represents the weight of the i-th interference feature, f i Represents the regression function of the i-th interference feature, d i Represents the distance parameter of the i-th interference feature, a i Represents the value of the i-th interference feature.

[0024] Furthermore, during the adjustment range calculation process of the integrated analysis module, dynamic calibration is required, including the following steps:

[0025] monitoring the corrected collected data in real time, and triggering the model building module to update the environmental interference model if the deviation between the newly collected distance parameter and the fitted value exceeds a preset tolerance;

[0026] The updated model parameters are fed back to the threshold setting of the judgment module to adaptively adjust the triggering conditions of the interference threshold.

[0027] Furthermore, the working logic of the factor extraction module is:

[0028] Acquire point cloud data of the sensor scanning area in real time and divide the monitoring grid based on the preset spatial resolution;

[0029] Calculate the signal attenuation rate of each grid unit. When the signal attenuation rate is greater than the set threshold, mark the grid as an occlusion area.

[0030] Count the area and contour features of the continuous region formed by adjacent occlusion grids. When the area of ​​the continuous region is greater than or equal to the minimum effective occlusion area, it is recorded as an effective occlusion object.

[0031] The output is a covering factor dataset containing the center coordinates of the covered object, the equivalent covering area, and the dynamic covering flag.

[0032] Furthermore, the construction process of the environmental interference model in the model construction module is:

[0033] Based on the historical ranging data and the corresponding background object covering factor data, a sample data set is established;

[0034] The multivariate linear regression algorithm is used to fit and generate the initial interference model, with the background object covering factor data as the independent variable and the ranging error value as the dependent variable;

[0035] The weight coefficients of the initial interference model are optimized by the least square method to obtain the target interference model, which satisfies the condition of minimizing the sum of squares of error residuals.

[0036] The current background object covering factor data collected in real time is input into the target interference model, and the corresponding ranging background interference characteristics are output. The interference characteristics include dynamic occlusion correction coefficient, multipath effect intensity and signal-to-noise ratio attenuation.

[0037] Furthermore, the analysis unit is installed on the top of the surveying instrument body, the model construction module is interactively connected with the distance extraction module, the factor extraction module and the interference integration module through a wireless network, and the decision unit is interactively connected with the interference integration module and the instruction adjustment module through a wireless network.

[0038] In a second aspect, the present invention discloses a data acquisition system for civil engineering surveying and mapping, including a ranging mechanism and an adjustment mechanism. The ranging mechanism is located inside the adjustment mechanism, the ranging mechanism is used to send optical sensing scanning signals and read position feedback data, and the adjustment mechanism is used to provide the ranging mechanism with acquisition angle adjustment instructions and receive active adjustment control instructions to operate automatically.

[0039] Furthermore, the ranging mechanism is an optical sensing module that integrates laser ranging and optical encoding feedback, and its model is LDM-4110 laser ranging sensor. The ranging mechanism and the adjustment mechanism transmit control instructions and position feedback data through the RS-485 bus protocol, and the transmission baud rate is configured to be 9600bps to 115200bps.

[0040] (3) Beneficial effects

[0041] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0042] 1. Through the dynamic compensation mechanism of environmental interference, the impact of external factors on the measurement data is analyzed in real time. By extracting interference features and monitoring the occlusion of background objects, the device can dynamically generate interference correction instructions and adjust the sensor's acquisition angle to compensate for the errors caused by environmental interference, thereby effectively reducing the impact of environmental interference on the surveying and mapping results. The intelligent correction strategy significantly improves the reliability of the data and reduces errors caused by human or environmental factors.

[0043] 2. By using a regression algorithm to construct an environmental interference model and combining it with real-time extracted parameters for analysis, the device's adaptability to complex backgrounds is further enhanced. By quantifying interference characteristics, the device can comprehensively evaluate various influencing factors and automatically adjust acquisition parameters according to different environmental conditions to ensure the consistency and accuracy of measurement results. It can rely on real-time monitoring data and feedback mechanisms to adaptively adjust interference thresholds and interference characteristics, thereby enhancing its ability to cope with complex environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0045] Figure 1 It is a schematic diagram of the overall three-dimensional structure of the present invention;

[0046] Figure 2 This is a schematic diagram of the overall three-dimensional structure of the present invention from another angle;

[0047] Figure 3 It is a schematic diagram of the overall framework of the present invention;

[0048] Figure 4 This is a schematic diagram of the framework of the surveying and mapping instrument body of the present invention;

[0049] Figure 5 Schematic diagram of the framework of the decision-making unit in the present invention.

[0050] The numbers in the figure represent, respectively, 1. surveying instrument body; 11. distance measuring mechanism; 12. adjustment mechanism; 2. analysis unit; 21. distance extraction module; 22. factor extraction module; 23. model building module; 24. interference integration module; 25. decision unit; 51. judgment module; 52. trigger module; 53. integration analysis module; 26. instruction adjustment module. DETAILED DESCRIPTION

[0051] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] The present invention will be further described below with reference to the embodiments.

[0053] ①Example 1

[0054] A data acquisition device and a data acquisition system for civil engineering surveying and mapping of this embodiment are as follows: Figure 1-Figure 5 Shown, including:

[0055] The surveying instrument body 1 is used to deploy a number of sensors and collect raw surveying and mapping sensor data at a preset collection angle through the sensors;

[0056] The analysis unit 2 is used to generate collection correction instructions for environmental interference factors based on the original sensor data collected by the surveying instrument body 1, and submit them to the surveying instrument body 1 to offset the collection angle. The analysis unit 2 has submodules deployed below, including:

[0057] The distance extraction module 21 is used to extract the distance parameters from the raw data collected and filtered by the surveying and mapping instrument body 1;

[0058] The factor extraction module 22 is used to monitor the ranging background during the acquisition of the surveying instrument body 1 and extract the background object covering factor data based on the preset interference index; the working logic of the factor extraction module 22 is:

[0059] Acquire point cloud data of the sensor scanning area in real time and divide the monitoring grid based on the preset spatial resolution;

[0060] Calculate the signal attenuation rate of each grid cell, the difference between the theoretical received signal strength and the actual received signal strength, and the ratio of the difference to the theoretical received signal strength is the signal attenuation rate. When the signal attenuation rate is greater than the set threshold, mark the grid as an occlusion area;

[0061] Count the area and contour features of the continuous region formed by adjacent occlusion grids. When the area of ​​the continuous region is greater than or equal to the minimum effective occlusion area, it is recorded as an effective occlusion object.

[0062] Output a mask factor dataset containing the center coordinates of the masked object, the equivalent mask area, and the dynamic mask flag.

[0063] The model building module 23 is used to build an environmental interference model through a regression algorithm, input the current background object covering factor data, and output a number of interference features of the current ranging background;

[0064] The construction process of the environmental interference model in the model construction module 23 is as follows:

[0065] Based on the historical distance measurement data and the corresponding background object occlusion factor data, a sample data set is established. The sample data set includes distance measurement values, background object density, occlusion angle, and environmental reflectivity parameters;

[0066] A multiple linear regression algorithm is used. The calculation logic of the multiple linear regression algorithm is as follows: the regression coefficients corresponding to the background object density, occlusion angle and ambient reflectivity are preset, and a weighted calculation is performed to obtain the ranging error value. The background object occlusion factor data is used as the independent variable and the ranging error value is used as the dependent variable to fit and generate the initial interference model.

[0067] The weight coefficients of the initial interference model are optimized by the least squares method to obtain the target interference model, which satisfies the condition of minimizing the sum of squared residual errors. The weight coefficients are iteratively updated by the gradient descent method until the model converges.

[0068] The real-time collected data on the current background object occlusion factor is input into the target interference model, and the corresponding ranging background interference characteristics are output. The interference characteristics include dynamic occlusion correction coefficient, multipath effect intensity, and signal-to-noise ratio attenuation. The interference model constructed through the regression algorithm can quantify the dynamic impact of environmental factors on ranging. Combined with real-time data input, it can accurately output interference characteristics, such as the occlusion correction coefficient, providing a calculable parameter basis for subsequent compensation strategies, thereby improving the robustness of data acquisition in complex environments.

[0069] The interference integration module 24 is used to extract a number of interference features output by the model building module 23, perform quantification processing, and output an interference factor set;

[0070] The decision unit 25 is used to determine whether the interference factor set output by the interference integration module 24 triggers an abnormal threshold. If a triggering behavior occurs, the integrated output compensation strategy is output. The decision unit 25 is deployed at the lower level. The submodules include: a judgment module 51, a trigger module 52, and an integrated analysis module 53. The trigger module 52 is interactively connected with the judgment module 51 and the integrated analysis module 53 via a wireless network. The judgment module 51 is used to set a predefined interference threshold. When the interference feature index exceeds the threshold, it is determined that correction is required and a correction trigger signal is output. The trigger module 52 is used to receive the correction trigger signal from the judgment module 51 and match the interference intensity according to the threshold exceeding the range. The integrated analysis module 53 is used to integrate and analyze several current interference features and distance parameters, calculate the correction amount according to the interference intensity, and obtain the adjustment amplitude. When the integrated analysis module 53 interacts with the trigger module 52 via the wireless network, an encryption protocol is used to transmit the interference intensity and correction amount data to ensure the integrity and real-time performance of the instructions.

[0071] The instruction adjustment module 26 is used to receive the compensation strategy of the decision unit 25, calculate and output the acquisition angle offset instruction of the surveying instrument body 1 based on the ranging target, and adjust the acquisition angle of the surveying instrument body 1.

[0072] As a preferred implementation in this embodiment, Figure 3 As shown, the analysis unit 2 is installed at the top of the surveying instrument body 1, the model building module 23 is interactively connected with the distance extraction module 21, the factor extraction module 22 and the interference integration module 24 through a wireless network, and the decision unit 25 is interactively connected with the interference integration module 24 and the instruction adjustment module 26 through a wireless network.

[0073] Compared with existing technologies, through a multi-level interference detection and correction mechanism, it can monitor and analyze environmental interference factors in real time, effectively improve the accuracy and reliability of ranging data, and use regression algorithms to build a dynamic environmental interference model to achieve adaptive correction and flexible angle adjustment, greatly enhancing the adaptability to surveying and mapping tasks in complex environments, reducing deviations caused by occlusion and interference, and thus optimizing the overall surveying and mapping efficiency and accuracy.

[0074] ②Example 2

[0075] At other levels, a data acquisition system for civil engineering surveying and mapping in this embodiment, such as Figure 1 and Figure 2 As shown, it includes a distance measuring mechanism 11 and an adjustment mechanism 12. The distance measuring mechanism 11 is located inside the adjustment mechanism 12. The distance measuring mechanism 11 is used to send optical sensor scanning signals and read position feedback data. The adjustment mechanism 12 is used to provide the distance measuring mechanism 11 with an acquisition angle adjustment instruction and automatically operate upon receiving an active adjustment control instruction.

[0076] The ranging mechanism 11 is an optical sensing module that integrates laser ranging and optical encoding feedback. Its model is LDM-4110 laser ranging sensor. The ranging mechanism 11 and the adjustment mechanism 12 transmit control instructions and position feedback data through the RS-485 bus protocol. The transmission baud rate is configured to be 9600bps to 115200bps.

[0077] ③Example 3

[0078] In this embodiment, the integration analysis module 53 receives the interference factor set output by the interference integration module 24 and the distance parameter extracted by the distance extraction module 21, and establishes a weight distribution relationship between the interference feature and the distance parameter based on the interference intensity level matched by the trigger module 52, wherein the weight of the distance parameter decreases as the interference intensity increases;

[0079] Fit the functional relationship between the interference feature and the distance parameter, and output the fitting residual as the initial correction value;

[0080] Based on the initial correction amount, the interference intensity coefficient provided by the trigger module 52 is superimposed to calculate the final correction amount and the corresponding acquisition angle adjustment range;

[0081] The calculation formula for the acquisition angle adjustment range is:

[0082]

[0083] Where T represents the adjustment amplitude, k represents the interference intensity coefficient, n represents the total number of interference features, and w i represents the weight of the i-th interference feature, f i Represents the regression function of the i-th interference feature, di Represents the distance parameter of the i-th interference feature, a i represents the value of the i-th interference feature;

[0084] During the adjustment range calculation process of the integrated analysis module 53, dynamic calibration is required, which includes the following steps:

[0085] Real-time monitoring of the corrected collected data. If the deviation between the newly collected distance parameter and the fitted value exceeds a preset tolerance, the model building module 23 is triggered to update the environmental interference model.

[0086] The updated model parameters are fed back to the threshold setting of the judgment module 51 to adaptively adjust the triggering conditions of the interference threshold.

[0087] Compared with the existing technology, by establishing a dynamic weight distribution relationship between interference characteristics and distance parameters, and using a linear regression model for function fitting, the correction amount and adjustment amplitude can be accurately calculated. By introducing real-time monitoring and adaptive calibration mechanisms, this module can ensure continuous optimization of acquisition accuracy in complex environments, significantly improving the reliability and adaptability of data acquisition, thereby ensuring the accuracy and efficiency of civil engineering surveying and mapping, realizing intelligent correction of environmental interference, and overcoming the limitations of traditional methods in dealing with complex interference backgrounds.

[0088] Working principle: The surveying instrument body 1 is deployed in the measurement area and collects raw surveying data at a preset angle. The distance extraction module 21 extracts and filters distance parameters from it. The factor extraction module 22 scans the ranging background in real time, identifies obstructions through grid analysis, and outputs obstruction factor data. The model construction module 23 constructs an environmental interference model based on historical data, inputs the current obstruction data, and outputs interference features such as dynamic obstruction correction coefficients. The interference integration module 24 quantifies these features to generate an interference factor set. The decision unit 25 determines whether the interference factor exceeds a threshold, wherein: the judgment module 51 sets the threshold and triggers the correction signal, the trigger module 52 matches the interference intensity level, and the integration analysis module 53 calculates the correction amount and angle adjustment amplitude through weight distribution and function fitting;

[0089] The instruction adjustment module 26 feeds back the adjustment instruction to the surveying instrument body 1, dynamically corrects the sensor acquisition angle, and the device continuously optimizes the acquisition accuracy through the real-time calibration of the module model construction module 23 and the occlusion monitoring of the factor extraction module 22.

[0090] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A data acquisition device for civil engineering surveying and mapping, characterized in that: include: The main body of the surveying instrument is used to deploy a number of sensors and collect raw surveying and mapping sensor data at preset collection angles through the sensors; An analysis unit is used to generate acquisition correction instructions for environmental interference factors based on the original sensor data collected by the surveying instrument body, and submit them to the surveying instrument body to shift the acquisition angle; The analysis unit is deployed with submodules at the lower level, and the submodules include: The distance extraction module is used to extract the distance parameters from the raw data collected and filtered by the surveying instrument body; The factor extraction module is used to monitor the ranging background during the acquisition of the surveying instrument body and extract the background object covering factor data based on the preset interference index; The model building module is used to build an environmental interference model through a regression algorithm, input the current background object covering factor data, and output several interference features of the current ranging background; The interference integration module is used to extract several interference features output by the model building module, perform quantitative processing, and output an interference factor set; The decision-making unit is used to determine whether the interference factor set output by the interference integration module triggers the abnormal threshold. If a triggering behavior occurs, the integrated output compensation strategy is generated; The instruction adjustment module is used to receive the compensation strategy of the decision unit, calculate and output the acquisition angle offset instruction of the surveying instrument body based on the ranging target, and adjust the acquisition angle of the surveying instrument body.

2. A data acquisition device for civil engineering surveying and mapping according to claim 1, characterized in that: The decision unit is deployed at a lower level with submodules, which include: a judgment module, a trigger module and an integrated analysis module. The trigger module is interactively connected to the judgment module and the integrated analysis module via a wireless network. The judgment module is used to set a predefined interference threshold. When the interference feature index exceeds the threshold, it is determined that correction is required and outputs a correction trigger signal. The trigger module is used to receive the correction trigger signal from the judgment module and match the interference intensity according to the threshold exceeding the range. The integrated analysis module is used to integrate and analyze several current interference features and distance parameters, calculate the correction amount according to the interference intensity, and obtain the adjustment amplitude.

3. The data acquisition device for civil engineering surveying and mapping according to claim 2, characterized in that: The integration analysis module receives the interference factor set output by the interference integration module and the distance parameter extracted by the distance extraction module, and establishes a weight distribution relationship between the interference feature and the distance parameter according to the interference intensity level matched by the trigger module, wherein the weight of the distance parameter decreases as the interference intensity increases; Fit the functional relationship between the interference feature and the distance parameter, and output the fitting residual as the initial correction value; Based on the initial correction amount and the interference intensity coefficient provided by the trigger module, the final correction amount and the corresponding acquisition angle adjustment range are calculated.

4. The data acquisition device for civil engineering surveying and mapping according to claim 3, characterized in that: The calculation formula of the acquisition angle adjustment range is: Where T represents the adjustment amplitude, k represents the interference intensity coefficient, n represents the total number of interference features, and w i represents the weight of the i-th interference feature, f i Represents the regression function of the i-th interference feature, d i Represents the distance parameter of the i-th interference feature, a i Represents the value of the i-th interference feature.

5. The data acquisition device for civil engineering surveying and mapping according to claim 3, characterized in that: During the adjustment range calculation process of the integrated analysis module, dynamic calibration is required, including the following steps: monitoring the corrected collected data in real time, and triggering the model building module to update the environmental interference model if the deviation between the newly collected distance parameter and the fitted value exceeds a preset tolerance; The updated model parameters are fed back to the threshold setting of the judgment module to adaptively adjust the triggering conditions of the interference threshold.

6. The data acquisition device for civil engineering surveying and mapping according to claim 1, characterized in that: The working logic of the factor extraction module is: Acquire point cloud data of the sensor scanning area in real time and divide the monitoring grid based on the preset spatial resolution; Calculate the signal attenuation rate of each grid unit. When the signal attenuation rate is greater than the set threshold, mark the grid as an occlusion area. Count the area and contour features of the continuous region formed by adjacent occlusion grids. When the area of ​​the continuous region is greater than or equal to the minimum effective occlusion area, it is recorded as an effective occlusion object. The output is a covering factor dataset containing the center coordinates of the covered object, the equivalent covering area, and the dynamic covering flag.

7. The data acquisition device for civil engineering surveying and mapping according to claim 1, characterized in that: The construction process of the environmental interference model in the model construction module is as follows: Based on the historical ranging data and the corresponding background object covering factor data, a sample data set is established; The multivariate linear regression algorithm is used to fit and generate the initial interference model, with the background object covering factor data as the independent variable and the ranging error value as the dependent variable; The weight coefficients of the initial interference model are optimized by the least square method to obtain the target interference model, which satisfies the condition of minimizing the sum of squares of error residuals. The current background object covering factor data collected in real time is input into the target interference model, and the corresponding ranging background interference characteristics are output. The interference characteristics include dynamic occlusion correction coefficient, multipath effect intensity and signal-to-noise ratio attenuation.

8. The data acquisition device for civil engineering surveying and mapping according to claim 1, characterized in that: The analysis unit is installed on the top of the surveying instrument body, the model building module is interactively connected with the distance extraction module, the factor extraction module and the interference integration module through a wireless network, and the decision unit is interactively connected with the interference integration module and the instruction adjustment module through a wireless network.

9. A data acquisition system for civil engineering surveying and mapping, the system being a system equipped with a data acquisition device for civil engineering surveying and mapping according to any one of claims 1 to 8, characterized in that: It includes a distance measuring mechanism and an adjustment mechanism. The distance measuring mechanism is located inside the adjustment mechanism and is used to send optical sensing scanning signals and read position feedback data. The adjustment mechanism is used to provide the distance measuring mechanism with an acquisition angle adjustment instruction and automatically operate upon receiving an active adjustment control instruction.

10. The data acquisition system for civil engineering surveying and mapping according to claim 9, characterized in that: The distance measuring mechanism is an optical sensing module that integrates laser ranging and optical encoding feedback, and its model is LDM-4110 laser ranging sensor. The distance measuring mechanism and the adjustment mechanism transmit control instructions and position feedback data via the RS-485 bus protocol, and the transmission baud rate is configured to be 9600bps to 115200bps.

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