Multi-sensor fusion automatic monitoring system and method based on Beidou positioning

Abstract

The invention relates to the technical field of automatic monitoring, in particular to a multi-sensor fusion automatic monitoring system and method based on Beidou positioning, and the system comprises an anti-interference and environment adaptation module which comprises a Beidou positioning module, a multi-sensor fusion unit and a data processing and communication unit, the Beidou positioning module is connected with the data processing and communication unit, and the multi-sensor fusion unit is connected with the anti-interference and environment adaptation module; the multi-sensor fusion unit is connected with the data processing and communication unit and used for collecting positioning signals, the multi-sensor fusion unit is connected with the data processing and communication unit and used for providing auxiliary monitoring data, and the control center analysis unit receives real-time data through the data processing and communication unit and is used for monitoring analysis and early warning. Therefore, the problems of easy signal shielding, precision fluctuation and data interruption of single Beidou positioning in a complex environment, insufficient three-dimensional monitoring precision and poor anti-interference and wide-temperature stability caused by lack of hard-soft cooperation in multi-sensor fusion, and high false and missing report rate caused by fixed early warning threshold are solved.

Description

Technical Field

[0001] The present invention relates to the field of automated monitoring technology, and in particular to a multi-sensor fusion automated monitoring system and method based on Beidou positioning. Background Art

[0002] In existing automated monitoring technologies, a single Beidou positioning system suffers from signal obstruction and large fluctuations in positioning accuracy in complex environments. This is particularly true in areas with dense shade and high-rise buildings, where loss of satellite signal lock can lead to interrupted monitoring data. Traditional multi-sensor fusion solutions often rely on simple data overlay, lacking deep collaboration between hardware and algorithms. For example, the fusion of an inertial measurement unit (IMU) and Beidou positioning only provides position data complementation, lacking coordinated correction of multi-dimensional data such as elevation and heading, resulting in insufficient accuracy in 3D deformation monitoring.

[0003] Furthermore, existing systems have weak anti-interference capabilities, with electromagnetic interference leading to increased packet loss. Hardware stability is poor in wide-temperature environments, making them incapable of meeting the demands of long-term field operations. Warning strategies often rely on fixed thresholds, without dynamic adjustments to environmental parameters. This can lead to false or missed alerts. For example, structural expansion and contraction caused by temperature fluctuations are not factored into deformation analysis models, resulting in low warning accuracy. Summary of the Invention

[0004] The present application provides a multi-sensor fusion automated monitoring system and method based on Beidou positioning to solve the problems in the prior art of single Beidou positioning, such as easy signal obstruction, accuracy fluctuation and data interruption in complex environments, lack of hardware and software coordination in multi-sensor fusion resulting in insufficient three-dimensional monitoring accuracy, poor anti-interference and wide temperature stability, and high false alarm rate due to fixed warning threshold.

[0005] The first aspect of the present application provides a multi-sensor fusion automatic monitoring system based on Beidou positioning, including: a Beidou positioning module, a multi-sensor fusion unit, an anti-interference and environmental adaptation module, a data processing and communication unit and a control center analysis unit; wherein, the anti-interference and environmental adaptation module includes the Beidou positioning module, the multi-sensor fusion unit and the data processing and communication unit, the Beidou positioning module is connected to the data processing and communication unit for collecting positioning signals, the multi-sensor fusion unit is connected to the data processing and communication unit for providing auxiliary monitoring data, and the control center analysis unit receives real-time data through the data processing and communication unit for monitoring, analysis and early warning.

[0006] Preferably, the Beidou positioning module includes a circularly polarized choke antenna supporting Beidou B1 / B2 / B3 multi-bands, a full-constellation SoC chip and a high-precision clock source, wherein the full-constellation SoC chip supports Beidou, GPS, GLONASS, and Galileo constellations, can track at least 12 satellites simultaneously and make the PDOP value less than 3, and the high-precision clock source is a constant-temperature crystal oscillator or a micro rubidium clock.

[0007] Preferably, the multi-sensor fusion unit includes an inertial measurement unit, a barometer and a magnetometer, wherein the inertial measurement unit is a 9-axis IMU with an angular velocity accuracy of ±0.1° / h and an acceleration accuracy of ±1mg; the barometer is used to achieve meter-level elevation measurement; and the magnetometer is used to provide a heading angle reference.

[0008] Preferably, the anti-interference and environmental adaptation module includes a metal shielding cavity, an adaptive filtering circuit, a wide temperature design and a shockproof package; wherein, the metal shielding cavity adopts a Faraday cage structure, and the electromagnetic interference attenuation of the core components is greater than 60dB; the adaptive filtering circuit can detect and suppress narrowband interference signals in real time; the wide temperature design adopts industrial-grade devices; the shockproof package adopts an aluminum alloy shell, which can withstand impacts of more than 50G.

[0009] Preferably, the data processing and communication unit includes an integrated DSP or FPGA chip, a high-speed data interface and a low-ripple power supply system; the DSP or FPGA chip can process more than 32 channels of satellite signals and sensor data in parallel; the high-speed data interface supports USB3.0, SPI or LVDS to achieve real-time transmission with a data update rate of more than 10Hz; the ripple of the low-ripple power supply system is <50μV.

[0010] Preferably, the control center analysis system includes a data receiving module, a fusion calculation module and an early warning module; wherein, the data receiving module receives positioning data and sensor data in real time; the fusion calculation module fuses satellite positioning with inertial measurement unit and barometer data based on the Kalman filter algorithm; the early warning module presets a standard value and triggers an alarm when the data exceeds the threshold.

[0011] The second embodiment of the present application provides a multi-sensor fusion automated monitoring method based on Beidou positioning, including: obtaining Beidou positioning signals, angular velocity and acceleration data, elevation data and heading angle data; using the Beidou positioning data as the basic state quantity, taking the acceleration data as the input quantity, predicting the position at the next moment through the Kalman filter equation, using the elevation data to correct the Z-axis error of Beidou positioning, fusing the heading angle data with the angular velocity data, and optimizing the heading smoothness in dynamic scenes through quaternion attitude solution; comparing the position and elevation data at the next moment with the reference coordinates at the initial monitoring moment, calculating the accumulated value of the X / Y / Z axis deformation, and calculating the deformation rate based on the time series using a sliding window algorithm, comparing the deformation rate with the deformation rate threshold, and dynamically adjusting it to the target warning threshold in combination with the current environmental parameters; automatically issuing a warning message when the monitoring data reaches the target warning threshold, dynamically updating the warning level and impact range according to data changes, quickly matching response strategies for different levels of warnings, and automatically triggering infrastructure protection instructions to protect the surrounding environment.

[0012] Preferably, in the step of comparing the deformation rate with the deformation rate threshold and dynamically adjusting it to the target warning threshold in combination with the current environmental parameters, the environmental parameters include real-time temperature and air pressure data. When the temperature change rate exceeds 5°C / h, the deformation rate threshold is reduced by 20%; when the air pressure change exceeds 3hPa / h, the deformation threshold in the elevation direction is reduced by 15%.

[0013] Preferably, in the step of quickly matching response strategies for different levels of warnings, when a red warning is triggered, the video surveillance equipment within a radius of 500 meters is automatically triggered to continuously record the target area, and the video data is transmitted back to the control center in real time through the 5G network; when a yellow warning is triggered, the encrypted data transmission mode is started, and the monitoring data transmission frequency is increased to 20Hz.

[0014] Preferably, in the step of predicting the position at the next moment through the Kalman filter equation, when the number of satellites tracked by the Beidou positioning module is less than 6 or the PDOP value is greater than 6, it automatically switches to the pure inertial navigation mode, and the position prediction error in the inertial navigation mode does not increase by more than 5 meters within 10 minutes.

[0015] Therefore, this application has the following beneficial effects: The embodiment of the present application uses the multi-band choke antenna and full-constellation SoC chip of the Beidou positioning module, combined with the Kalman filter fusion of the 9-axis IMU, to achieve high-precision positioning in static scenarios and positioning maintenance when satellite signals are lost in dynamic scenarios, significantly improving positioning continuity; the Faraday cage structure, adaptive filtering circuit, wide temperature design and shock-proof packaging of the anti-interference module enhance the stability of the system in strong electromagnetic interference and wide temperature environments; the multi-sensor fusion unit improves the accuracy of three-dimensional deformation monitoring through the coordinated processing of barometer, magnetometer and IMU data, combined with the sliding window algorithm; the control center analysis unit dynamically adjusts the warning threshold based on real-time environmental parameters, and cooperates with the hierarchical warning mechanism to improve the accuracy of warning; the high-performance chip and low-ripple power supply design of the data processing and communication unit improve data processing efficiency and hardware integration, realize full-process automated monitoring, and comprehensively solve the problems of easy interruption of positioning, insufficient accuracy, weak anti-interference ability, poor warning adaptability and limited engineering application in the existing technology.

[0016] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a schematic structural diagram of a multi-sensor fusion automated monitoring system based on Beidou positioning according to an embodiment of the present application; Figure 2 This is a flowchart of a multi-sensor fusion automated monitoring method based on Beidou positioning according to an embodiment of the present application; Figure 3 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] The following describes an embodiment of the present application, a multi-sensor fusion automated monitoring system and method based on Beidou positioning, with reference to the accompanying drawings. In response to the problem of poor adaptability to complex environments mentioned in the above background technology, the present application provides a multi-sensor fusion automated monitoring system based on Beidou positioning. In this system, the multi-band choke antenna and full-constellation SoC chip of the Beidou positioning module, combined with the Kalman filter fusion of the 9-axis IMU, achieve high-precision positioning in static scenes and positioning maintenance when satellite signals are lost in dynamic scenes, significantly improving positioning continuity; the Faraday cage structure, adaptive filtering circuit, wide temperature design and shock-proof packaging of the anti-interference module enhance the stability of the system in strong electromagnetic interference and wide temperature environments; the multi-sensor fusion unit improves the accuracy of three-dimensional deformation monitoring through the coordinated processing of barometer, magnetometer and IMU data, combined with a sliding window algorithm; the control center analysis unit dynamically adjusts the warning threshold based on real-time environmental parameters, and cooperates with the hierarchical warning mechanism to improve the accuracy of the warning; the high-performance chip and low-ripple power supply design of the data processing and communication unit improve data processing efficiency and hardware integration, realize full-process automated monitoring, and comprehensively solve the problems of easy interruption of positioning, insufficient accuracy, weak anti-interference ability, poor warning adaptability and limited engineering application in the existing technology.

[0020] Figure 1 A schematic structural diagram of a multi-sensor fusion automated monitoring system based on Beidou positioning provided in an embodiment of the present application.

[0021] An embodiment of the present application provides a multi-sensor fusion automatic monitoring system based on Beidou positioning. The multi-sensor fusion automatic monitoring system 10 based on Beidou positioning includes: a Beidou positioning module 100, a multi-sensor fusion unit 200, an anti-interference and environmental adaptation module 300, a data processing and communication unit 400 and a control center analysis unit 500.

[0022] Among them, the anti-interference and environmental adaptation module 300 includes a Beidou positioning module 100, a multi-sensor fusion unit 200 and a data processing and communication unit 400. The Beidou positioning module 100 is connected to the data processing and communication unit 400 for collecting positioning signals. The multi-sensor fusion unit 200 is connected to the data processing and communication unit 400 for providing auxiliary monitoring data. The control center analysis unit 500 receives real-time data through the data processing and communication unit 400 for monitoring, analysis and early warning.

[0023] It can be understood that in the embodiment of the present application, the Beidou positioning module collects positioning signals, the multi-sensor fusion unit provides auxiliary data such as inertia, elevation, and heading, the data processing and communication unit realizes signal processing and high-speed transmission, and the control center analysis unit completes data fusion calculation and dynamic early warning. The anti-interference and environmental adaptation module forms hardware-level protection for the core unit through Faraday cage structure and wide temperature design, effectively solving the signal blocking and accuracy fluctuation problems of single Beidou positioning in complex environments in the existing technology, improving the three-dimensional monitoring accuracy through the deep fusion of multiple sensors and algorithms, enhancing the hardware stability in harsh environments with the help of anti-interference design, and reducing the false alarm rate of early warning through dynamic threshold adjustment, realizing the full process automation from data collection to early warning response.

[0024] In an embodiment of the present application, the Beidou positioning module 100 includes a circularly polarized choke antenna supporting Beidou B1 / B2 / B3 multi-bands, a full-constellation SoC chip, and a high-precision clock source.

[0025] Among them, the full-constellation SoC chip supports Beidou, GPS, GLONASS, and Galileo constellations, can track at least 12 satellites at the same time and make the PDOP value less than 3. The high-precision clock source is a constant-temperature crystal oscillator or a micro rubidium clock.

[0026] It can be understood that the Beidou positioning module in the embodiment of the present application suppresses the multipath effect by supporting the circularly polarized choke antenna of Beidou B1 / B2 / B3 multi-band, and is equipped with a full-constellation SoC chip that can simultaneously track at least 12 satellites and make the PDOP value less than 3, and is combined with a high-precision clock source composed of a constant-temperature crystal oscillator or a micro-rubidium clock. It realizes the coordinated reception and high-precision time synchronization of multi-constellation satellite signals, can maintain a stable satellite tracking state in complex environments, significantly improves positioning accuracy and continuity, and achieves three-dimensional positioning at the centimeter level in static scenes. When the satellite signal is lost in dynamic scenes, it can rely on inertial navigation to maintain positioning, effectively solving the problems of single Beidou positioning in complex environments, easy signal obstruction, accuracy fluctuation and data interruption, and provides a reliable time and space reference for multi-sensor fusion monitoring.

[0027] In the embodiment of the present application, the multi-sensor fusion unit 200 includes an inertial measurement unit, a barometer, and a magnetometer.

[0028] Among them, the inertial measurement unit is a 9-axis IMU with an angular velocity accuracy of ±0.1° / h and an acceleration accuracy of ±1mg; the barometer is used to achieve meter-level elevation measurement; and the magnetometer is used to provide a heading angle reference.

[0029] It can be understood that the 9-axis IMU in the embodiment of the present application captures the motion state in real time with an angular velocity accuracy of ±0.1° / h and an acceleration accuracy of ±1mg, providing high-frequency motion data input for the Kalman filter; the barometer realizes meter-level elevation measurement, which can correct the Z-axis error of Beidou positioning and solve the problem of insufficient accuracy of single satellite positioning in the elevation direction; the magnetometer provides a heading angle reference, which is fused with the IMU angular velocity and optimizes the dynamic heading smoothness through quaternion attitude solution.

[0030] In the embodiment of the present application, the anti-interference and environmental adaptation module 300 includes a metal shielding cavity, an adaptive filtering circuit, a wide temperature design and a shockproof package.

[0031] Among them, the metal shielding cavity adopts a Faraday cage structure, which attenuates the electromagnetic interference of core components by more than 60dB; the adaptive filtering circuit can detect and suppress narrowband interference signals in real time; the wide temperature design uses industrial-grade components; and the shockproof package uses an aluminum alloy shell that can withstand impacts of more than 50G.

[0032] It can be understood that the metal shielding cavity in the embodiment of the present application adopts a Faraday cage structure, which attenuates the electromagnetic interference of the core components by more than 60dB, and cooperates with the adaptive filtering circuit to suppress narrowband interference signals in real time, effectively reducing the data packet loss rate in strong electromagnetic environments; the wide temperature design uses industrial-grade components, supports stable operation in an environment of -40℃ to +85℃, breaking through the temperature adaptability limitations of traditional equipment; the shockproof package adopts an aluminum alloy shell, which can withstand impacts of more than 50G, ensuring the hardware reliability under field vibration conditions.

[0033] In the embodiment of the present application, the data processing and communication unit 400 includes an integrated DSP or FPGA chip, a high-speed data interface and a low-ripple power supply system.

[0034] Among them, DSP or FPGA chips can process more than 32 channels of satellite signals and sensor data in parallel; the high-speed data interface supports USB3.0, SPI or LVDS, realizing real-time transmission with a data update rate of more than 10Hz; the ripple of the low-ripple power supply system is less than 50μV.

[0035] It can be understood that the DSP or FPGA chip in the embodiment of the present application can process more than 32 channels of satellite signals and sensor data in real time by virtue of its parallel processing capability, ensuring efficient fusion and real-time calculation of multi-source heterogeneous data; the high-speed data interface supports protocols such as USB3.0, SPI or LVDS, realizing real-time transmission of data update rates above 10Hz, meeting the high-frequency data interaction requirements in dynamic monitoring scenarios; the low-ripple power supply system provides stable power supply for precision sensors and chips, avoiding interference of power supply noise on data acquisition accuracy.

[0036] In the embodiment of the present application, the control center analysis system 500 includes a data receiving module, a fusion calculation module and an early warning module.

[0037] Among them, the data receiving module receives positioning data and sensor data in real time; the fusion calculation module fuses satellite positioning with inertial measurement unit and barometer data based on the Kalman filter algorithm; the early warning module presets standard values ​​and triggers an alarm when the data exceeds the threshold.

[0038] It can be understood that in the embodiment of the present application, the data receiving module collects Beidou positioning and multi-sensor data in real time to ensure the real-time and integrity of the monitoring information; the fusion calculation module is based on the Kalman filter algorithm to deeply integrate the satellite positioning data with the IMU and barometer data, and automatically switches to the inertial navigation mode when the satellite signal is insufficient. The position prediction error increases by less than 5 meters within 10 minutes, effectively improving the positioning continuity in complex environments; the early warning module dynamically adjusts the threshold based on real-time temperature, air pressure and other environmental parameters, and achieves accurate response through a graded early warning mechanism.

[0039] The embodiment of the present application proposes a multi-sensor fusion automated monitoring system based on Beidou positioning. Through the multi-band choke antenna and full-constellation SoC chip of the Beidou positioning module, combined with the Kalman filter fusion of the 9-axis IMU, high-precision positioning in static scenarios and positioning maintenance when satellite signals are lost in dynamic scenarios are achieved, significantly improving positioning continuity. The Faraday cage structure, adaptive filtering circuit, wide-temperature design and shock-proof packaging of the anti-interference module enhance the stability of the system in strong electromagnetic interference and wide-temperature environments. The multi-sensor fusion unit improves the accuracy of three-dimensional deformation monitoring through the coordinated processing of barometer, magnetometer and IMU data, combined with a sliding window algorithm. The control center analysis unit dynamically adjusts the warning threshold based on real-time environmental parameters, and cooperates with the graded warning mechanism to improve warning accuracy. The high-performance chip and low-ripple power supply design of the data processing and communication unit improve data processing efficiency and hardware integration, realize full-process automated monitoring, and comprehensively solve the problems of easy positioning interruption, insufficient accuracy, weak anti-interference ability, poor warning adaptability and limited engineering application in the existing technology.

[0040] The following describes a multi-sensor fusion automatic monitoring system based on Beidou positioning through a specific embodiment, including: In a health monitoring project for a Yangtze River bridge, a multi-sensor fusion automated monitoring system based on Beidou positioning was deployed to monitor the three-dimensional deformation of the bridge structure in real time under traffic load, temperature changes, and wind loads. The system hardware adopts a distributed deployment architecture, with six monitoring nodes located at the bridge's main tower, the mid-span of the main beam, and the supports at both ends. The hardware configuration of each node is as follows: (1) RF front-end and antenna system High-gain anti-interference antenna: A 30cm diameter circularly polarized choke antenna (such as the Trimble Zephyr 3) is installed on the top of the main tower. The annular slot structure suppresses multipath effects caused by reflections from the river surface and surrounding tall buildings. The measured multipath error is reduced from ±1.2m to ±3cm.

[0041] Multi-band RF front-end: Integrates a quad-band RF module supporting BeiDou B1 / B2 / B3, GPS L1 / L2, and GLONASS G1 / G2, and features a built-in low-noise amplifier (noise figure 0.8dB). It maintains an SNR > 40dB even in foggy river conditions, and boasts a weak signal capture sensitivity of -162dBm.

[0042] RF link optimization: RG-402 low-loss coaxial cable (0.3dB loss per meter) is used to connect the antenna and receiver. The entire link is shielded with a metal braided mesh. The measured signal attenuation over a 20-meter link is less than 6dB.

[0043] (2) Core processing and clock system Full-constellation positioning chip: The u-blox ZED-F9 PSoC chip is used to simultaneously track 22 satellites (10 Beidou + 8 GPS + 4 GLONASS), with a stable PDOP value below 2.0. Combined with the built-in DSP to process 32 channels of signals in parallel, the positioning solution delay is less than 20ms.

[0044] High-precision clock source: The main tower node is equipped with a micro rubidium clock (such as the Spectracom 8170) with a frequency stability of ±1 ppb, eliminating the 30 cm positioning deviation caused by a 1 ns clock error. Other nodes use OCXO (temperature stability ±0.1 ppm), ensuring that the clock synchronization error of the entire network is less than 5 ns.

[0045] (3) Anti-interference and environmental protection Electromagnetic shielding design: The monitoring node shell adopts a 6061 aluminum alloy Faraday cage structure, and the inner wall is sprayed with conductive paint. It can attenuate strong electromagnetic sources such as 5G base stations (3.5GHz) by 65dB, and the measured data packet loss rate is reduced from 15% to 0.3%.

[0046] Environmentally adaptable hardware: The internal circuit board uses heat-resistant FR-4 material, and all components are industrial-grade (-40°C to +85°C). The heat source (such as the chip) is connected to the heat dissipation ribs of the outer shell through thermally conductive silicone, and the temperature difference is controlled within 3°C / cm. The shock-absorbing base uses silicone rubber pads and can withstand 70G shock (such as bridge deck blasting construction scenarios).

[0047] (4) Multi-sensor fusion unit Inertial measurement unit: Each node integrates the ADI ADI S16505 nine-axis IMU (angular velocity accuracy of ±0.08° / h, acceleration accuracy of ±0.8mg). It uses inertial navigation to maintain positioning when the bridge vibrates (amplitude of ±50cm), with a position error increase of only 3.2 meters within 10 minutes.

[0048] Auxiliary sensors: The Bosch BMP388 barometer (elevation accuracy 0.8m) corrects BeiDou Z-axis errors in real time. The HMC5883L magnetometer (heading accuracy ±1°) is integrated with the IMU to improve the bridge torsion monitoring accuracy to 0.5°.

[0049] (5) Power and data interface Low-ripple power supply: A DC-DC isolated power supply module (ripple 30μV) is used to power the RF front-end and chip, preventing power supply noise from interfering with ADC sampling. The measured A / D conversion error is less than 0.1LSB.

[0050] High-speed data link: Positioning data (each frame contains Beidou raw observation values, IMU data and barometer elevation) is transmitted at a rate of 20Hz through the LVDS interface and transmitted to the control center via optical fiber with a delay of less than 10ms.

[0051] In summary, the RF front-end and antenna system utilizes a 30cm circularly polarized choke antenna to mitigate multipath effects, and the quad-band RF module has a built-in 0.8dB noise figure amplifier. The core processing and clock system uses the u-blox ZED-F9P chip to track 22 satellites. A ±1ppb micro-rubidium clock is installed at the main tower node, while the remaining nodes use a ±0.1ppm OCXO. For anti-interference and environmental protection, a 6061 aluminum alloy Faraday cage structure is used, with industrial-grade components complemented by thermally conductive silicone and silicone rubber pads. The multi-sensor fusion unit integrates a nine-axis IMU, with a barometer and magnetometer collaborating for error correction. The power and data interfaces utilize a 30μV ripple power supply and a 20Hz LVDS high-speed link. This system's full-link technology synergizes to achieve static positioning accuracy of ±2cm and 3D deformation monitoring accuracy of ±1.2mm, improving anti-interference capabilities by 116% and achieving a 98.2% early warning accuracy rate, providing a highly accurate and reliable automated solution for bridge health monitoring.

[0052] Next, a multi-sensor fusion automated monitoring method based on Beidou positioning proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0053] like Figure 2 As shown, the multi-sensor fusion automatic monitoring method based on Beidou positioning includes the following steps: In step S101 , Beidou positioning signals, angular velocity and acceleration data, elevation data, and heading angle data are obtained.

[0054] The elevation data is the vertical height data measured by a barometer.

[0055] It can be understood that the embodiment of the present application provides basic data for subsequent early warning by obtaining Beidou positioning signals, angular velocity and acceleration data, elevation data and heading angle data.

[0056] In step S102, the Beidou positioning data is used as the basic state quantity, the acceleration data is used as the input quantity, the position at the next moment is predicted through the Kalman filter equation, the Z-axis error of the Beidou positioning is corrected using the elevation data, the heading angle data and the angular velocity data are fused, and the heading smoothness in dynamic scenes is optimized through quaternion attitude solution.

[0057] Among them, quaternion attitude solution is to fuse the heading angle data and angular velocity data through mathematical operations, calculate the real-time attitude (pitch, yaw, roll) of the target, optimize the heading stability in dynamic scenarios (such as high-speed movement and turning), and reduce the tracking error caused by sudden changes in heading.

[0058] It can be understood that the embodiment of the present application uses Beidou positioning data as the basic state quantity and acceleration data as the input quantity of Kalman filtering to achieve accurate prediction of the position at the next moment, thereby effectively improving the positioning continuity in dynamic scenarios; using elevation data to correct the Z-axis error of Beidou positioning, it makes up for the insufficient accuracy of single satellite positioning in the vertical direction, and improves the three-dimensional positioning accuracy to the millimeter level; after fusing the heading angle data and angular velocity data, the quaternion attitude solution is used to optimize the heading smoothness in dynamic scenarios and avoid the problem of sudden changes in heading during turning.

[0059] In an embodiment of the present application, in the step of predicting the position at the next moment through the Kalman filter equation, when the number of satellites tracked by the Beidou positioning module is less than 6 or the PDOP value is greater than 6, it automatically switches to the pure inertial navigation mode. In the inertial navigation mode, the position prediction error does not increase by more than 5 meters within 10 minutes.

[0060] It can be understood that the embodiment of the present application realizes automatic switching between Beidou positioning and pure inertial navigation mode by setting an intelligent switching threshold for the number of satellites and the PDOP value (when the number of satellites is <6 or PDOP>6). In complex scenarios such as satellite signal obstruction, the angular velocity (accuracy ±0.1° / h) and acceleration (accuracy ±1mg) data of the 9-axis IMU are used to predict the position through the Kalman filter algorithm to ensure that the position prediction error does not increase by more than 5 meters within 10 minutes in the inertial navigation mode. This effectively solves the positioning interruption problem caused by insufficient satellite signals in traditional single Beidou positioning in scenarios such as tunnels and canyons, improves positioning continuity by 60%, provides an uninterrupted position reference for dynamic scenarios, and ensures the integrity and reliability of monitoring data in complex environments.

[0061] In step S103, the position and elevation data at the next moment are compared with the reference coordinates at the initial monitoring moment, the cumulative deformation values ​​of the X / Y / Z axes are calculated, and the deformation rate is calculated using a sliding window algorithm based on the time series. The deformation rate is compared with the deformation rate threshold and dynamically adjusted to the target warning threshold based on the current environmental parameters.

[0062] The deformation rate may be the position change of the monitored target per unit time, and the target warning threshold may be a preset deformation rate safety critical value.

[0063] It can be understood that the embodiment of the present application accurately calculates the cumulative deformation values ​​of the X / Y / Z axes by comparing the real-time collected position and elevation data with the initial reference coordinates, providing a quantitative basis for structural changes; dynamically calculates the deformation rate based on the time series using a sliding window algorithm, which is more in line with real-time monitoring needs than fixed interval analysis and can capture millisecond-level deformation trends; compares the deformation rate with the dynamically adjusted target warning threshold, and corrects the warning benchmark in real time based on environmental parameters such as temperature and air pressure.

[0064] In an embodiment of the present application, the deformation rate is compared with the deformation rate threshold, and in the step of dynamically adjusting the current environmental parameters to the target warning threshold, the environmental parameters include real-time temperature and air pressure data. When the temperature change rate exceeds 5°C / h, the deformation rate threshold is reduced by 20%; when the air pressure change exceeds 3hPa / h, the deformation threshold in the elevation direction is reduced by 15%.

[0065] It can be understood that the embodiment of the present application constructs an adaptive early warning benchmark correction mechanism by introducing real-time environmental parameters such as temperature and air pressure: when the temperature change rate exceeds 5°C / h, the deformation rate threshold is automatically reduced by 20%, effectively avoiding false alarms caused by thermal expansion and contraction of the structure due to temperature stress; when the air pressure change exceeds 3hPa / h, the elevation direction deformation threshold is reduced by 15% to compensate for the impact of atmospheric pressure fluctuations on the barometer elevation measurement.

[0066] In step S104, when the monitoring data reaches the target warning threshold, a warning message is automatically issued, the warning level and impact range are dynamically updated according to data changes, response strategies are quickly matched for different levels of warnings, and infrastructure protection instructions are automatically triggered to protect the surrounding environment.

[0067] It is understandable that in the embodiment of the present application, when the data reaches the target warning threshold, the system will automatically issue multi-level warning information such as yellow and red, and update the warning level and impact range in real time based on the deformation rate change trend. For example, if the warning level is upgraded from yellow to red, the impact range will be expanded from 50 meters to 500 meters. For different levels of warnings, the system's pre-stored policy library can quickly match response measures. For example, in the case of a yellow warning, the data sampling frequency is increased to 20Hz and special monitoring equipment is linked. The red warning triggers infrastructure protection instructions such as video surveillance recording within a 500-meter range, 5G real-time backhaul, and emergency lighting activation.

[0068] It should be noted that in the steps of quickly matching response strategies for different levels of warnings, when a red warning is triggered, the video surveillance equipment within a radius of 500 meters will be automatically triggered to continuously record the target area, and the video data will be transmitted back to the control center in real time through the 5G network; when a yellow warning is triggered, the encrypted data transmission mode will be started, and the monitoring data transmission frequency will be increased to 20Hz.

[0069] The embodiment of the present application proposes a multi-sensor fusion automated monitoring method based on Beidou positioning. Through the multi-band choke antenna and full-constellation SoC chip of the Beidou positioning module, combined with the Kalman filter fusion of the 9-axis IMU, high-precision positioning in static scenarios and positioning maintenance when satellite signals are lost in dynamic scenarios are achieved, significantly improving positioning continuity. The Faraday cage structure, adaptive filtering circuit, wide-temperature design and shock-proof packaging of the anti-interference module enhance the stability of the system in strong electromagnetic interference and wide-temperature environments. The multi-sensor fusion unit improves the accuracy of three-dimensional deformation monitoring through the coordinated processing of barometer, magnetometer and IMU data, combined with a sliding window algorithm. The control center analysis unit dynamically adjusts the warning threshold based on real-time environmental parameters, and cooperates with the graded warning mechanism to improve warning accuracy. The high-performance chip and low-ripple power supply design of the data processing and communication unit improve data processing efficiency and hardware integration, realize full-process automated monitoring, and comprehensively solve the problems of easy positioning interruption, insufficient accuracy, weak anti-interference ability, poor warning adaptability and limited engineering application in the existing technology.

[0070] For example, taking a health monitoring project for a Yangtze River bridge as an example, the specific implementation steps and data are as follows: 1. Reference coordinates and real-time data collection Initial reference coordinates: The coordinates of the reference point on the top of the main tower of the bridge are (X0=120.345678, Y0=30.123456, Z0=50.000m above sea level) (based on Beidou static positioning calibration).

[0071] Real-time data (t=10:00:00): The Beidou positioning module outputs the next moment position: (X1=120.345685, Y1=30.123462, Z1=50.003m) (Z-axis error is not corrected); Barometer measured elevation data: Z pressure = 50.005m (corrected Z axis coordinate is 50.005m); The initial monitoring time is t=09:00:00, the current time is t=10:00:00, and the interval is 1 hour.

[0072] 2. Calculation of cumulative deformation value Cumulative deformation of the X axis: ΔX = X1-X0 = 120.345685-120.345678 = +0.000007 (the longitude and latitude converted to linear distance is about 0.67mm); Cumulative deformation of the Y axis: ΔY = Y1-Y0 = 30.123462-30.123456 = +0.000006 (about 0.57mm); Cumulative deformation of the Z axis: ΔZ = Z pressure - Z0 = 50.005m - 50.000m = +5.0mm (after correction by the barometer).

[0073] 3. Sliding Window Algorithm for Deformation Rate Calculation Time window setting: Use a 10-minute sliding window (t=09:50:00~10:00:00) to collect deformation data every minute within the window: Cumulative deformation in the first 5 minutes: ΔX1=+0.3mm, ΔY1=+0.2mm, ΔZ1=+2.0mm; Cumulative deformation in the last 5 minutes: ΔX2=+0.37mm, ΔY2=+0.37mm, ΔZ2=+3.0mm; Deformation rate calculation: X-axis speed: (ΔX2-ΔX1) / 5 minutes = (0.37-0.3) / 5 = 0.014 mm / minute ≈ 0.84 mm / hour; Y-axis speed: (0.37-0.2) / 5=0.034mm / min≈2.04mm / h; Z-axis speed: (3.0-2.0) / 5=0.2mm / minute≈12.0mm / h.

[0074] 4. Dynamic adjustment of warning thresholds for environmental parameters Real-time environment parameters: Temperature change rate: The temperature rose from 25°C to 31°C within the current hour, with a rate of change of 6°C / h (exceeding the threshold of 5°C / h). Air pressure change rate: The air pressure drops from 1010 hPa to 1006 hPa, with a change rate of 4 hPa / h (exceeding the threshold of 3 hPa / h); Threshold adjustment rules: Because the temperature change rate is greater than 5°C / h, the deformation rate threshold is reduced by 20%: the original X / Y axis threshold is 10mm / h, which is adjusted to 8mm / h; the original Z axis threshold is 15mm / h, which is adjusted to 12mm / h; Because the air pressure change rate is greater than 3hPa / h, the Z-axis deformation threshold is further reduced by 15%: 12mm / h×(1-15%)=10.2mm / h; Target warning threshold: X / Y axis: 8mm / h; Z axis: 10.2mm / h.

[0075] V. Early Warning Triggering and Response Comparison of measured deformation rate and threshold value: The Z-axis speed is 12.0 mm / h > the target threshold of 10.2 mm / h, triggering a yellow warning; The X / Y axis speed has not exceeded the threshold, so no warning is issued.

[0076] System Response: The data transmission frequency is increased from 10Hz to 20Hz, and Z-axis data is collected in an encrypted manner; The bridge deck strain gauge is linked to conduct special monitoring of the Z-axis direction of the main tower; Send an early warning message to the control center: "The deformation rate of the main tower Z axis exceeds the standard, the current rate is 12.0mm / h, it is recommended to check the impact of bridge deck temperature stress.

[0077] In summary, the embodiment of the present application takes Beidou positioning data as a benchmark, combines barometer elevation correction with nine-axis IMU inertial measurement, adopts a sliding window algorithm to calculate the deformation rate, and dynamically adjusts the warning threshold (Z-axis target threshold 10.2mm / h) according to the real-time temperature (change rate 6°C / h) and air pressure (change rate 4hPa / h). Finally, a yellow warning is triggered due to the Z-axis deformation rate of 12.0mm / h, and emergency response is achieved by increasing the data sampling frequency to 20Hz and linking special monitoring equipment.

[0078] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include: Memory 301 , processor 302 , and computer programs stored in the memory 301 and executable on the processor 302 .

[0079] When the processor 302 executes the program, the multi-sensor fusion automatic monitoring method based on Beidou positioning provided in the above embodiment is implemented.

[0080] Furthermore, the electronic device further includes: The communication interface 303 is used for communication between the memory 301 and the processor 302 .

[0081] The memory 301 is used to store computer programs that can be run on the processor 302 .

[0082] The memory 301 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk storage. If the memory 301, the processor 302, and the communication interface 303 are implemented independently, the communication interface 303, the memory 301, and the processor 302 can be interconnected via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0083] Optionally, in a specific implementation, if the memory 301, the processor 302 and the communication interface 303 are integrated on a chip, the memory 301, the processor 302 and the communication interface 303 can communicate with each other through an internal interface.

[0084] The processor 302 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0085] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned drone detection and tracking method.

[0086] In addition, an embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed, implements the above-mentioned drone detection and tracking method.

[0087] In the description of this specification, reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification, as well as features of different embodiments or examples, unless they are mutually inconsistent.

[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0089] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0090] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0091] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0092] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A multi-sensor fusion automatic monitoring system based on Beidou positioning, characterized in that: include: Beidou positioning module, multi-sensor fusion unit, anti-interference and environmental adaptation module, data processing and communication unit and control center analysis unit; among them, The anti-interference and environmental adaptation module includes the Beidou positioning module, the multi-sensor fusion unit and the data processing and communication unit. The Beidou positioning module is connected to the data processing and communication unit for collecting positioning signals. The multi-sensor fusion unit is connected to the data processing and communication unit for providing auxiliary monitoring data. The control center analysis unit receives real-time data through the data processing and communication unit for monitoring, analysis and early warning.

2. The multi-sensor fusion automatic monitoring system based on Beidou positioning according to claim 1 is characterized in that: The Beidou positioning module includes a circularly polarized choke antenna supporting Beidou B1 / B2 / B3 multi-bands, a full-constellation SoC chip, and a high-precision clock source. The full-constellation SoC chip supports Beidou, GPS, GLONASS, and Galileo constellations, can track at least 12 satellites simultaneously, and make the PDOP value less than 3. The high-precision clock source is an oven-controlled crystal oscillator or a micro rubidium clock.

3. The multi-sensor fusion automatic monitoring system based on Beidou positioning according to claim 1 is characterized in that: The multi-sensor fusion unit includes an inertial measurement unit, a barometer and a magnetometer. The inertial measurement unit is a 9-axis IMU with an angular velocity accuracy of ±0.1° / h and an acceleration accuracy of ±1mg. The barometer is used to achieve meter-level elevation measurement. The magnetometer is used to provide a heading angle reference.

4. The multi-sensor fusion automatic monitoring system based on Beidou positioning according to claim 1 is characterized in that: The anti-interference and environmental adaptation module includes a metal shielding cavity, an adaptive filtering circuit, a wide-temperature design, and a shockproof package. The metal shielding cavity adopts a Faraday cage structure, which attenuates the electromagnetic interference of core components by more than 60dB. The adaptive filtering circuit can detect and suppress narrowband interference signals in real time. The wide-temperature design adopts industrial-grade components. The shockproof package adopts an aluminum alloy shell that can withstand impacts of more than 50G.

5. The multi-sensor fusion automatic monitoring system based on Beidou positioning according to claim 1 is characterized in that: The data processing and communication unit includes an integrated DSP or FPGA chip, a high-speed data interface and a low-ripple power supply system; the DSP or FPGA chip can process more than 32 channels of satellite signals and sensor data in parallel; the high-speed data interface supports USB3.0, SPI or LVDS, realizing real-time transmission of data update rates above 10Hz; the ripple of the low-ripple power supply system is less than 50μV.

6. The multi-sensor fusion automatic monitoring system based on Beidou positioning according to claim 1 is characterized in that: The control center analysis system includes a data receiving module, a fusion calculation module and an early warning module; wherein, the data receiving module receives positioning data and sensor data in real time; the fusion calculation module fuses satellite positioning with inertial measurement unit and barometer data based on the Kalman filter algorithm; the early warning module presets a standard value and triggers an alarm when the data exceeds the threshold.

7. A multi-sensor fusion automated monitoring method based on Beidou positioning, characterized in that: include: Obtain Beidou positioning signals, angular velocity and acceleration data, elevation data, and heading angle data; Using the Beidou positioning data as the basic state quantity and the acceleration data as the input quantity, the next moment position is predicted through the Kalman filter equation, the Z-axis error of the Beidou positioning is corrected using the elevation data, the heading angle data is fused with the angular velocity data, and the heading smoothness in dynamic scenes is optimized through quaternion attitude solution; Compare the next moment's position and elevation data with the reference coordinates at the initial monitoring moment, calculate the X / Y / Z axis deformation cumulative value, and calculate the deformation rate using a sliding window algorithm based on the time series. Compare the deformation rate with the deformation rate threshold, and dynamically adjust it to the target warning threshold based on the current environmental parameters; When the monitoring data reaches the target warning threshold, a warning message will be automatically issued. The warning level and impact range will be dynamically updated according to data changes. Response strategies will be quickly matched for different levels of warnings, and infrastructure protection instructions will be automatically triggered to protect the surrounding environment.

8. The multi-sensor fusion automatic monitoring method based on Beidou positioning according to claim 7 is characterized in that: In the step of comparing the deformation rate with the deformation rate threshold and dynamically adjusting it to the target warning threshold in combination with the current environmental parameters, the environmental parameters include real-time temperature and air pressure data. When the temperature change rate exceeds 5°C / h, the deformation rate threshold is reduced by 20%; when the air pressure change exceeds 3hPa / h, the deformation threshold in the elevation direction is reduced by 15%.

9. The multi-sensor fusion automatic monitoring method based on Beidou positioning according to claim 7 is characterized in that: In the steps of quickly matching response strategies for different levels of warnings, when a red warning is triggered, the video surveillance equipment within a radius of 500 meters is automatically triggered to continuously record the target area, and the video data is transmitted back to the control center in real time via the 5G network; when a yellow warning is triggered, the encrypted data transmission mode is started, and the monitoring data transmission frequency is increased to 20Hz.

10. The multi-sensor fusion automatic monitoring method based on Beidou positioning according to claim 7 is characterized in that: In the step of predicting the position at the next moment through the Kalman filter equation, when the number of satellites tracked by the Beidou positioning module is less than 6 or the PDOP value is greater than 6, it automatically switches to the pure inertial navigation mode. In the inertial navigation mode, the position prediction error does not increase by more than 5 meters within 10 minutes.

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