Full-digital radio height measurement radar optimization method based on artificial intelligence

Abstract

The invention discloses a full-digital radio height-finding radar optimization method based on artificial intelligence, and relates to the technical field of height-finding radar data processing. The method comprises the following steps: carrying out the first analysis of the natural environment interference effect of the sea-crossing bridge height-finding radar, and carrying out the first optimization of the interference superposition of the sea-crossing bridge height-finding radar; judging and carrying out second analysis on the natural environment interference effect of the sea-crossing bridge height-finding radar, and carrying out second optimization on interference superposition of the sea-crossing bridge height-finding radar; optimized feedback analysis is carried out, and judgment and early warning are carried out. According to the method, the signal-to-noise ratio is reduced by analyzing the notation influence coefficient; if the frequency exceeds the standard, the pulse repetition frequency is adjusted, the bridge vibration and coupling frequency is analyzed, the overlapping type with the vehicle frequency is judged, the cut-off frequency and the pulse repetition frequency of the filter are adjusted accordingly, and the effect of improving the robustness when dealing with nonlinear and strong-coupling multi-physics field interference is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of altimeter radar data processing, and in particular to an artificial intelligence-based full-digital radio altimeter radar optimization method. Background Art

[0002] A radio height radar is a sensor that transmits electromagnetic waves and receives reflected echoes from a target, calculating vertical distance based on signal delay or frequency difference. Its core advantages lie in non-contact measurement and high precision, making it widely used in aviation, drones, and bridge health monitoring. In bridge health monitoring scenarios, radio height radar is considered a low-cost, highly reliable tool for measuring vertical displacement. By measuring the change in vertical distance from the sensor to the bridge deck, it can infer the deformation of the bridge under load. It can also assess the health of the bridge structure through the time and frequency domain characteristics of high-frequency vibration signals. By combining the correlation between vehicle vibration signals and bridge vibration signals, it can indirectly identify the type of vehicle crossing the bridge and the axle load distribution.

[0003] However, the technical characteristics of traditional radio height-finding radars result in significant limitations in monitoring scenarios of cross-sea bridges in complex marine environments, making it difficult to meet long-term, high-reliability monitoring needs. Due to the complexity of the marine environment and the high intensity of vehicle loads, cross-sea bridges place far more stringent requirements on the performance of radio height-finding radars than in conventional scenarios. The limitations of traditional technologies are concentrated in the following aspects: environmental corrosion and insufficient hardware reliability, severe multipath interference and signal aliasing, and dynamic signal aliasing and coupling interference.

[0004] For example, patent publication number CN119940267A discloses a standard module-based integrated design method for an inertial control system. This method involves analyzing requirements, dividing functional modules, and constructing standard modules. It also specifies the internal and external electrical interfaces and mechanical interfaces of standard modules. The structural layout of the integrated inertial control system is determined, and the mechanical and thermal environment adaptability of the integrated inertial control system is analyzed to achieve iterative optimization of the integrated design. This method redefines and divides the functions of traditional discrete electronic equipment such as missile-borne integrated control units, inertial navigation systems, satellite receivers, radio altimeter radars, and barometric altimeter radars, creating standard modules that unify power distribution and management, centralized information processing, and integrated structural design.

[0005] For example, the invention patent announcement with announcement number: CN109992897B discloses a radio altimeter radar simulation method for ground proximity warning equipment, which includes a main control unit, a solver unit and a signal unit. The main control unit is an industrial computer for receiving user instructions and forwarding them to the solver unit after processing. The solver unit is an industrial computer for processing the received commands and sending them to the signal unit. The solver unit contains solver software. The signal unit is a board that can send ARINC429 signals, which is installed in the solver unit to send altimeter radar simulation signals. The user opens the simulation software on the main control unit and inputs the simulated flight altitude information. The simulation software sends the input simulated flight altitude information to the solver software in the solver unit. The solver software processes the simulated altitude information to form simulation information and sends it to the signal unit. The signal unit translates the received simulation information into ARINC429 signals and sends them to the ground proximity warning equipment as simulated altitude information.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, traditional radio height-finding radars are unable to meet complex requirements in vehicle load monitoring scenarios on cross-sea bridges due to their simple signal processing algorithms and weak environmental adaptability. When dealing with environmental corrosion, multipath interference, dynamic signal aliasing, long-term drift and severe weather, the error rate soars significantly. Traditional hardware designs are not optimized for complex marine environments, and signal processing algorithms rely on simple thresholds and linear filtering, resulting in insufficient measurement accuracy and reliability. There is also a problem of insufficient robustness of fully digital radio height-finding radars when dealing with nonlinear, strongly coupled multi-physical field interference. Summary of the Invention

[0008] The embodiments of the present application provide an artificial intelligence-based fully digital radio altimeter optimization method, which solves the problem in the prior art that the fully digital radio altimeter is insufficiently robust when dealing with nonlinear, strongly coupled multi-physical field interference, and achieves the effect of improving the robustness when dealing with nonlinear, strongly coupled multi-physical field interference.

[0009] An embodiment of the present application provides an artificial intelligence-based fully digital radio height-finding radar optimization method, comprising the following steps: performing a first analysis of the natural environment interference effect of the cross-sea bridge height-finding radar, and performing a first optimization of the cross-sea bridge height-finding radar interference superposition; conducting a second analysis of the natural environment interference effect of the cross-sea bridge height-finding radar, and performing a second optimization of the cross-sea bridge height-finding radar interference superposition; performing feedback analysis of the optimization and making judgments and early warnings.

[0010] Furthermore, the first analysis of the natural environment interference effect of the sea-crossing bridge height finding radar is carried out, specifically including: collecting the height finding radar environmental humidity through temperature and humidity sensors; directly obtaining the height finding radar environmental rainfall intensity through the meteorological database; directly extracting the humidity influence coefficient and the rainfall influence coefficient through the radio height finding radar comprehensive database; if the height finding radar environmental humidity is greater than the height finding radar environmental humidity threshold and the height finding radar environmental rainfall intensity is greater than the height finding radar environmental rainfall intensity threshold, then the height finding radar environmental humidity, height finding radar environmental rainfall intensity, humidity influence coefficient and rainfall influence coefficient are comprehensively analyzed to obtain the signal-to-noise ratio degradation analysis value of the sea-crossing bridge height finding radar.

[0011] Furthermore, the first optimization of the interference superposition of the cross-sea bridge height measurement radar is carried out, specifically including: directly extracting the height measurement radar benchmark signal-to-noise ratio through the radio height measurement radar historical database, and comparing and analyzing the height measurement radar benchmark signal-to-noise ratio with the cross-sea bridge height measurement radar signal-to-noise ratio drop analysis value to obtain the cross-sea bridge height measurement radar signal-to-noise ratio fluctuation lower limit; if the cross-sea bridge height measurement radar signal-to-noise ratio fluctuation lower limit is greater than the signal-to-noise ratio failure, the optimization is not triggered; if the cross-sea bridge height measurement radar signal-to-noise ratio fluctuation lower limit is equal to or less than the signal-to-noise ratio failure, the optimization is triggered; directly extracting the height measurement radar pulse repetition frequency minimum value, height measurement radar pulse repetition frequency benchmark value, maximum value through the radio height measurement radar comprehensive database Large signal-to-noise ratio loss threshold; after comparing and analyzing the pulse repetition frequency baseline value of the height measuring radar with the minimum value of the pulse repetition frequency of the height measuring radar, it is recorded as the pulse repetition frequency adjustment range value of the height measuring radar, and the results of the proportion analysis of the unit one and the lower limit value of the signal-to-noise ratio fluctuation of the cross-sea bridge height measuring radar and the maximum signal-to-noise ratio loss threshold are compared and analyzed to obtain the height measuring radar signal-to-noise ratio fluctuation loss coefficient; the minimum value of the pulse repetition frequency of the height measuring radar, the pulse repetition frequency adjustment range value of the height measuring radar and the signal-to-noise ratio fluctuation loss coefficient of the height measuring radar are coupled and analyzed to obtain the optimized value of the pulse repetition frequency of the height measuring radar; trigger optimization is used to determine the pulse repetition frequency output by the height measuring radar according to the optimized value of the pulse repetition frequency of the height measuring radar.

[0012] Furthermore, it is determined that a second analysis of the natural environment interference effect of the height measuring radar of the cross-sea bridge is conducted, specifically including: if the height measuring radar environmental wind speed is less than or equal to the height measuring radar environmental wind speed threshold, the second analysis of the natural environment interference effect of the height measuring radar of the cross-sea bridge is not conducted; if the height measuring radar environmental wind speed exceeds the height measuring radar environmental wind speed threshold, the second analysis of the natural environment interference effect of the height measuring radar of the cross-sea bridge is conducted; the second analysis of the natural environment interference effect of the height measuring radar of the cross-sea bridge includes: directly extracting the Strouhal number, bridge characteristic width and bridge nonlinear stiffness coefficient of the cross-sea bridge through the radio height measuring radar comprehensive database; and collecting the wind speed and direction meter at the top of the radar antenna mast. The sea breeze speed of the sea-crossing bridge is obtained by the inertial measurement sensor installed at the bottom of the bridge box girder, which measures the vibration displacement in real time, extracts the amplitude through fast Fourier transform analysis, and obtains the maximum vibration amplitude of the bridge; the Strouhal number of the sea-crossing bridge is coupled with the sea breeze speed of the sea-crossing bridge and then compared with the characteristic width of the bridge to obtain the linear vibration frequency of the bridge; the coupling result of the unit one and the nonlinear stiffness coefficient of the bridge and the maximum vibration amplitude of the bridge is compared and analyzed, and then a square root analysis is performed to obtain the nonlinear vibration frequency adjustment coefficient of the bridge; the linear vibration frequency of the bridge is coupled with the nonlinear vibration frequency adjustment coefficient of the bridge to obtain the nonlinear vibration frequency of the bridge.

[0013] Furthermore, the second analysis of the natural environment interference effect of the height-finding radar on the cross-sea bridge also includes: directly extracting the bridge mass, bridge stiffness and fitted damping ratio through the radio height-finding radar comprehensive database; obtaining the total average mass of vehicles on the bridge in real time through the vehicle weighing system installed at the entrance and exit of the bridge; after identifying the specific vehicle model, directly obtaining the corresponding vehicle stiffness through the radio height-finding radar comprehensive database and then summing and averaging them to obtain the total average vehicle stiffness; coupling the fitted damping ratio with the bridge mass and the total average vehicle mass and then taking the square root analysis result to obtain the total coupling damping coefficient of the bridge vehicle ; After comparing and analyzing the bridge stiffness with the total average stiffness of the vehicle, the bridge stiffness is coupled with the total coupling damping coefficient of the bridge and vehicle and then squared, which is recorded as the total coupling attenuation coefficient of the bridge and vehicle; after coupling the bridge stiffness and the total average stiffness of the vehicle, the bridge stiffness is compared with the total coupling attenuation coefficient of the bridge and vehicle, and then the coupling result with the bridge mass and the total average mass of the vehicle is analyzed to obtain the basic value of the bridge-vehicle coupling frequency; after square root processing of the basic value of the bridge-vehicle coupling frequency, it is coupled with the predefined coefficient to obtain the bridge-vehicle coupling frequency; the frequency coupling degree is analyzed according to the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency.

[0014] Furthermore, the frequency coupling degree is analyzed according to the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the vehicle coupling frequency of the bridge, specifically including: directly extracting the main frequency of vehicle vibration from the comprehensive database of radio height sounding radar; comparing and analyzing the overlapping interval length of any two frequencies with the maximum coverage length of the three frequency couplings of the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the vehicle coupling frequency, and obtaining the overlapping degree of the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration, the overlapping degree of the vehicle coupling frequency and the main frequency of vehicle vibration, and the overlapping degree of the nonlinear vibration frequency of the bridge and the vehicle coupling frequency; if the overlapping degree of the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration is greater than the overlapping degree of the vehicle coupling frequency and the main frequency of vehicle vibration and If the degree of overlap between the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration is greater than the degree of overlap between the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency, it is judged that the bridge and the vehicle are dominantly overlapping; if the degree of overlap between the bridge-vehicle coupling frequency and the main frequency of vehicle vibration is greater than the degree of overlap between the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration, and the degree of overlap between the bridge-vehicle coupling frequency and the main frequency of vehicle vibration is greater than the degree of overlap between the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency, it is judged that the bridge-vehicle coupling and the vehicle are dominantly overlapping; if the degree of overlap between the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration, the degree of overlap between the bridge-vehicle coupling frequency and the main frequency of vehicle vibration, and the degree of overlap between the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency are all greater than the overlap judgment threshold, it is judged that there is full-band overlap.

[0015] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is carried out, specifically including: if it is determined that the bridge and the vehicle are dominantly overlapping, the results of the comparative analysis of the vehicle vibration main frequency and the first frequency of the safety interval and the results of the coupling analysis of the bridge nonlinear vibration pseudo-peak frequency and the first frequency of the safety interval are processed by the maximum function to obtain the multipath suppression filter cutoff adjustment first frequency, and the height measurement radar multipath suppression filter cutoff frequency is determined according to the multipath suppression filter cutoff adjustment first frequency; the threshold first adjustment coefficient, the overlap degree of the bridge vehicle coupling frequency and the vehicle vibration main frequency and the coupling result of unit one are processed by the logarithmic function to obtain the inspection and adjustment detection value, the radar original detection threshold is compared and analyzed with the inspection and adjustment detection value to obtain the radar adjustment detection threshold, and the height measurement radar adjustment detection threshold is determined according to the radar adjustment detection threshold.

[0016] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is performed, which also includes: if it is determined that the bridge-vehicle coupling and the vehicle-dominant overlap, the results of the coupling analysis of the vehicle vibration main frequency and the first frequency of the safety interval and the results of the comparative analysis of the bridge-vehicle coupling frequency and the second frequency of the safety interval are processed by the minimum function to obtain the second frequency of the multipath suppression filter cutoff adjustment, and the height measurement radar multipath suppression filter cutoff frequency is determined according to the second frequency of the multipath suppression filter cutoff adjustment; the height measurement radar pulse repetition frequency adjustment first frequency is obtained through the height measurement radar pulse repetition frequency reference value, the pulse repetition frequency adjustment coefficient, the overlap degree of the bridge-vehicle coupling frequency and the vehicle vibration main frequency and the unit-one coupling analysis, and the height measurement radar pulse repetition frequency adjustment first frequency is adjusted according to the height measurement radar pulse repetition frequency adjustment first frequency.

[0017] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is performed, which also includes: if it is determined that the full frequency band overlaps, the nonlinear vibration frequency of the bridge, the bridge vehicle coupling frequency and the main frequency of the vehicle vibration are processed by the median function to obtain the third frequency of the multipath suppression filter cutoff adjustment; the band-stop filter frequency of the height measurement radar multipath suppression filter is determined according to the second frequency of the multipath suppression filter cutoff adjustment; the second adjustment coefficient of the threshold, the frequency overlap of the three and the coupling result of unit one are processed by the logarithmic function, recorded as the three frequency coupling adjustment coefficient, to obtain the first test adjustment detection value, the original detection threshold of the radar is compared and analyzed with the first test adjustment detection value to obtain the first threshold of the radar adjustment detection, and the height measurement radar adjustment detection threshold is determined according to the first threshold of the radar adjustment detection; the first frequency of the height measurement radar pulse repetition frequency adjustment is obtained by analyzing the reference value of the height measurement radar pulse repetition frequency, the first coefficient of the pulse repetition frequency adjustment, the frequency overlap of the three and the coupling of unit one, and the height measurement radar pulse repetition frequency is adjusted according to the first frequency of the pulse repetition frequency adjustment.

[0018] Furthermore, optimized feedback analysis is conducted and judgment and early warning are carried out, specifically including: after optimization and adjustment, if the final signal-to-noise ratio of the cross-sea bridge height measurement radar is less than the preset signal-to-noise ratio effective threshold, or the final false detection rate of vehicle detection is still greater than the preset false detection rate target value, or the overlap of the bridge-vehicle coupling frequency is still greater than the preset safety overlap threshold, then the sound and light alarm device of the radar system is activated, an email is simultaneously pushed to the maintenance personnel terminal, and the execution results of all current adjustment steps, environmental parameters, and bridge-vehicle coupling parameters are stored in the non-volatile memory.

[0019] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0020] 1. This optimization method addresses the interference issues of the natural environment and vehicle-bridge coupling in a step-by-step manner, focusing on the anti-interference requirements of cross-sea bridge height-finding radars. First, ambient humidity and rainfall intensity are obtained using temperature and humidity sensors and a meteorological database. The humidity and rainfall influence coefficients are then combined to determine whether the signal-to-noise ratio (SNR) is degraded. If this exceeds the specified value, the first optimization step of interference superposition is triggered, adjusting the pulse repetition frequency (PRF). Consequently, when wind speed exceeds the specified value, the linear and nonlinear vibration frequencies of the bridge are calculated using parameters such as the Strouhal number and characteristic width. The bridge-vehicle coupling frequency is then calculated using parameters such as vehicle mass and stiffness. The frequency coupling between the bridge and vehicle, the bridge-vehicle coupling and the vehicle, or the entire frequency band is analyzed. Based on the overlap type, the multipath suppression filter cutoff frequency is adjusted in multiple stages using different functions. The PRF is then adjusted based on the SNR fluctuation loss coefficient. If the SNR is still insufficient, the false detection rate is too high, or the overlap exceeds the specified value after optimization, an audible and visual alarm is activated and data is recorded to ensure stable radar operation in complex environments.

[0021] 2. Focusing on signal attenuation in the complex environment of cross-sea bridges. By collecting real-time parameters such as humidity and rainfall, combined with pre-calibrated environmental factors, the system comprehensively assesses the degree of degradation in the radar's received signal's signal-to-noise ratio (SNR). When the SNR is determined to be below the stable detection threshold, the pulse repetition frequency (PRF) is dynamically adjusted: if the SNR loss is minor, the PRF remains at the baseline value to ensure signal stability; if the loss is significant, the PRF is gradually reduced to the minimum allowable value to avoid false detections due to signal overlap. This process effectively addresses signal attenuation in adverse weather conditions such as high salt fog and heavy rainfall, enhancing the radar's stable detection capabilities in complex environments and laying the foundation for subsequent interference suppression.

[0022] 3. When the ambient wind speed exceeds the set threshold, the coupling effect between the low-frequency nonlinear vibration of the bridge caused by strong wind and the vehicle vibration is analyzed, the bridge-vehicle coupling frequency is calculated, and combined with the main frequency of the vehicle vibration, the overlapping type of the three frequencies is determined. According to the overlapping type, the multipath suppression filter cutoff frequency, the height radar calibration detection threshold and the pulse repetition frequency are adjusted in a targeted manner; the bridge nonlinear pseudo-peaks, coupling pseudo-peaks and vehicle signals are effectively separated, which solves the signal aliasing problem caused by the strong coupling of multiple physical fields and significantly improves the detection accuracy of the radio height radar.

[0023] 4. This step ensures optimization effectiveness through closed-loop feedback. After optimization, if the radar's final signal-to-noise ratio remains below the effective threshold, the vehicle false detection rate falls short of the target, or the bridge-vehicle coupling overlap remains excessively high, the system triggers an audible and visual alarm and sends a warning message to maintenance personnel. The adjustment parameters, environmental parameters, and coupling parameters are also stored simultaneously. This step enables real-time tracking of optimization results and tracing of issues, facilitating timely troubleshooting of hardware degradation and ensuring long-term system reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1Flowchart of the artificial intelligence-based fully digital radio altimeter radar optimization method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The embodiments of the present application provide an artificial intelligence-based fully digital radio altimeter optimization method, which solves the problem in the prior art that the fully digital radio altimeter is insufficiently robust when dealing with nonlinear, strongly coupled multi-physical field interference, resulting in a decrease in the signal-to-noise ratio due to the combined influence coefficient analysis. If the signal-to-noise ratio exceeds the standard, the pulse repetition frequency is adjusted, and then the bridge vibration and coupling frequency are analyzed to determine the type of overlap with the vehicle frequency. The filter cutoff frequency and pulse repetition frequency are adjusted accordingly, thereby achieving the effect of improving the robustness when dealing with nonlinear, strongly coupled multi-physical field interference.

[0026] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] like Figure 1 As shown, it is a flow chart of the fully digital radio height-finding radar optimization method based on artificial intelligence provided in an embodiment of the present application, and the method includes the following steps: performing a first analysis of the natural environment interference effect of the cross-sea bridge height-finding radar, and performing a first optimization of the cross-sea bridge height-finding radar interference superposition; judging and performing a second analysis of the natural environment interference effect of the cross-sea bridge height-finding radar, and performing a second optimization of the cross-sea bridge height-finding radar interference superposition; performing feedback analysis of the optimization and making judgments and early warnings.

[0028] In this embodiment, a traditional radio height-finding radar transmits electromagnetic waves and receives reflected echoes from the target, calculating vertical distance based on time delay. However, in the context of vehicle load monitoring on cross-sea bridges, its simple signal processing algorithm and weak environmental adaptability are unable to meet the complex requirements. Specific issues include environmental corrosion: salt spray and humid and hot environments can easily cause oxidation of antenna feed lines and aging of the RF front end, reducing signal transmission / reception efficiency and the measurement signal-to-noise ratio. Multipath interference: Reflected signals from the bridge's steel box girders, cables, and metal vehicle bodies superimpose on the direct signal, forming multipath pseudo-peaks that are prone to misjudgment by traditional threshold detection, resulting in erratic measurement results. Dynamic signal aliasing: The vibration spectrum of the bridge caused by sea breezes and waves overlaps with the vibration spectrum of the vehicle traveling, making it impossible for traditional filtering algorithms to separate the deformation, and the deformation is masked by noise. Long-term drift: Electronic components drift over time, and the sensor mounting reference surface deforms due to vibration, leading to the gradual accumulation of measurement errors. Inadequate robustness to adverse weather conditions: Heavy rain and strong winds exacerbate signal attenuation and air turbulence, causing significant fluctuations in echo power, reducing the probability of effective ranging and making continuous and stable monitoring difficult.

[0029] Traditional hardware designs are not optimized for complex marine environments. Signal processing algorithms rely on simple thresholds and linear filtering, and are unable to cope with nonlinear, strongly coupled multi-physical field interference, resulting in insufficient measurement accuracy and reliability.

[0030] The hardware functions of the fully digital radio height-finding radar must be determined during the design phase; otherwise, the protection level or core performance will be compromised. Example requirements are as follows: the antenna feed line is made of gold-plated copper alloy, the housing is made of polycarbonate + glass fiber composite material with a fluorocarbon coating on the surface; the sensor mounting bracket is made of stainless steel, and anti-corrosion gaskets are used at the fixing point to the bridge body. The corrosion resistance of the material directly determines the life of the hardware. The core sensor type and accuracy of the height-finding radar is selected from the inertial measurement unit with a high-precision fiber optic gyroscope, and the temperature and humidity sensor is an industrial-grade digital sensor that supports I 2 C / RS485 interface. Sensor accuracy determines the benchmark for subsequent signal processing. The altimeter radar's RF front-end uses a temperature-controlled crystal oscillator and a directional parabolic antenna. The RF module integrates a low-noise amplifier to ensure weak signal reception sensitivity. RF front-end performance directly affects the quality of the echo signal.

[0031] Furthermore, the first analysis of the natural environment interference effect of the cross-sea bridge height measurement radar is carried out, specifically including: collecting the height measurement radar environmental humidity through the temperature and humidity sensor; the humidity comes from the temperature and humidity sensor (SHT 31), with an accuracy of ±0.5% RH; directly obtaining the height measurement radar environmental rainfall intensity through the meteorological database; rainfall (Prain, unit: mm / h), comes from the meteorological station or the radar's own precipitation detection module (such as through microwave scattering measurement), with an accuracy of ±1mm / h; if the height measurement radar environmental humidity is greater than the height measurement radar environmental humidity threshold and the height measurement radar environmental rainfall intensity is greater than the height measurement radar environmental rainfall intensity threshold, then the cross-sea bridge height measurement radar is used to analyze the signal-to-noise ratio reduction value; SNRbase represents the baseline signal-to-noise ratio: the average SNR of the radar in a rain-free and interference-free environment, calibrated to 20dB through historical data; α represents the humidity influence coefficient, and for every 1% RH increase in humidity, the signal attenuation increases by 0.5dB, calibrated through historical data of experimental tests, such as when the humidity increases from 85% to 95%. , the signal attenuation increases by 5dB; β represents the rainfall influence coefficient, and the signal attenuation increases by 3dB for every 1mm / h increase in rainfall, which is calibrated through historical data of experimental tests; the signal-to-noise ratio failure represents the SNRthreshold threshold: when the SNR is lower than 10dB, the radar cannot stably detect the echo and optimization needs to be triggered; the SNR reduction value constraint formula is as follows: ΔSNR=α*(RH-YZ1)+β*(Prain / YZ2), where ΔSNR represents the signal-to-noise ratio degradation analysis value of the cross-sea bridge height measurement radar, YZ1 represents the height measurement radar environmental humidity threshold, and YZ2 represents the height measurement radar environmental rainfall intensity threshold; RH-YZ1: the part of the humidity that exceeds the height measurement radar environmental humidity threshold; Prain / YZ2: the multiple of the rainfall relative to the height measurement radar environmental rainfall intensity threshold.

[0032] In this embodiment, the environmental humidity threshold of the altimeter radar can be 85, which is measured based on historical humidity data at a specific location. This value is set because 85% RH is the critical value for salt spray corrosion at the corresponding location, and corrosion accelerates after exceeding it. The environmental rainfall intensity threshold of the altimeter radar can be 50, which is measured based on historical rainfall data at a specific location. This value is set because 50 mm / h is the threshold for heavy rain, and radar interference is significantly increased after exceeding it.

[0033] Furthermore, the first optimization of the interference superposition of the cross-sea bridge altimetry radar is carried out, specifically including: directly extracting the reference signal-to-noise ratio (SNR) of the altimetry radar from the historical database of the radio altimetry radar. If the reference SNR of the altimetry radar is compared and analyzed with the analysis value of the SNR decrease of the cross-sea bridge altimetry radar, the lower limit value of the SNR fluctuation of the cross-sea bridge altimetry radar can be obtained. If the lower limit value of the SNR fluctuation of the cross-sea bridge altimetry radar is greater than the SNR failure, the optimization is not triggered. If the lower limit value of the SNR fluctuation of the cross-sea bridge altimetry radar is equal to or less than the SNR failure, the optimization is triggered. SNRthreshold represents the SNR failure. The minimum pulse repetition frequency (PRF), the reference PRF of the altimetry radar, and the maximum SNR loss threshold are directly extracted from the comprehensive database of the radio altimetry radar. The constraint formula for optimizing the PRF of the altimetry radar is as follows: PRFnew = PRFmin + (PRFbase - PRFmin) * (1 - SNRloss / SNRmax_loss), where PRFnew represents the optimized value of the PRF of the altimetry radar, PRFmin represents the minimum PRF of the altimetry radar, which is the lowest PRF at which the radar can stably detect echoes and avoid false detection caused by signal overlap. PRFbase represents the reference PRF of the altimetry radar, which is the PRF of the radar in an interference-free and high-SNR environment. SNRloss represents the lower limit value of the SNR fluctuation of the cross-sea bridge altimetry radar, and SNRmax_loss represents the maximum SNR loss threshold, which is the critical value of the SNR loss that triggers the PRF to drop to the lowest value. After exceeding this value, the PRF no longer decreases.

[0034] In this embodiment, SNRthreshold is directly calibrated according to the experimental values of the corresponding altimetry radar. For example, when the SNR is lower than 10 dB, the radar cannot stably detect echoes and the optimization needs to be triggered.

[0035] When SNRbase - ΔSNR = SNRloss < SNRthreshold, that is, 20 - 3.1 = 16.9 dB > 10 dB, the optimization is not triggered. [[ID=⑦]] [[ID=⑧]]

[0036] [[ID=⑨]]If the rainfall increases to 80 mm / h and RH = 95%, then ΔSNR = 0.5 * 10 + 3 * (30 / 50) = 5 + 1.8 = 6.8 dB, and SNR = 20 - 6.8 = 13.2 dB, still higher than the threshold. [[ID=⑩]] [[ID=⑪]]

[0037] [[ID=⑫]]When the rainfall = 100 mm / h and RH = 100%, ΔSNR = 0.5 * 15 + 3 * (50 / 50) = 7.5 + 3 = 10.5 dB, and SNR = 20 - 10.5 = 9.5 dB < 10 dB, the optimization is triggered. [[ID=⑬]] [[ID=⑭]]

[0038] [[ID=⑮]]When SNRloss = 0, that is, there is no SNR loss, PRFnew = PRFbase, and the reference frequency is maintained.

[0039] When SNRloss=SNRmax_loss, the maximum allowed loss, PRFnew=PRFmin, which drops to the lowest frequency.

[0040] When SNRloss>SNRmax_loss, PRFnew remains at PRFmin to avoid signal overlap due to low frequencies.

[0041] Optimized logic for smooth transition: PRF decreases linearly with SNR loss to avoid unstable altimeter radar signal processing caused by sudden environmental changes; Minimum frequency protection: Prevents pulse overlap caused by excessively low PRF and triggering false detection; Strong adaptability: By optimizing PRFmin and SNRmax_loss, it can adapt to different radar models and environmental requirements.

[0042] Furthermore, a second analysis of the natural environment interference effect of the height measurement radar of the cross-sea bridge is determined, specifically including: if the height measurement radar environmental wind speed is less than or equal to the height measurement radar environmental wind speed threshold, the second analysis of the natural environment interference effect of the height measurement radar of the cross-sea bridge is not performed; if the height measurement radar environmental wind speed exceeds the height measurement radar environmental wind speed threshold, then under the action of strong wind, the bridge enters the nonlinear vibration zone due to large amplitude deformation, and its vibration frequency is no longer fixed, but decreases as the amplitude increases. The height measurement radar environmental wind speed threshold can be set to 15m / s, which can be set according to the expert's prior knowledge based on the specific bridge. The quantitative formula for the nonlinear vibration of the bridge under strong wind is as follows: Where fbridge_nonlinear represents the nonlinear vibration frequency of the bridge, fbridge_linear represents the linear vibration frequency of the bridge, and ∈ represents the nonlinear stiffness coefficient of the bridge. This dimensionless value characterizes the degree to which stiffness decreases with displacement. The nonlinear stiffness coefficient is obtained by applying a sinusoidal excitation to a simulated bridge model, measuring the displacement-force curve, and fitting the nonlinear stiffness coefficient. For example, an experimental calibration value of 0.1 is used. A represents the bridge vibration amplitude. The vibration displacement is measured in real time by an IMU sensor installed at the bottom of the bridge box girder, and the amplitude is extracted through fast Fourier transform analysis. fbridge_linear = S*v / d. S represents the Strouhal number, which is experimentally calibrated to 0.2 for cross-sea bridges. v represents the sea breeze speed, which is measured in real time by an anemometer at the top of the radar antenna mast. d represents the characteristic width of the bridge, which is obtained from the corresponding bridge design drawings.

[0043] In this example, under strong winds (v > 15 m / s), the bridge enters a nonlinear vibration regime due to large-amplitude deformation. Its vibration frequency is no longer fixed but decreases with increasing amplitude (a soft spring characteristic). A nonlinear stiffness model is used to describe this phenomenon. As the bridge amplitude A increases, the nonlinear term ∈*A increases, causing fbridge_nonlinear to decrease and frequency broadening. For example, when A = 0.1 m, fbridge_nonlinear = 0.9*fbridge_linear.

[0044] It is important to note that the phenomenon in which the frequency of a bridge's nonlinear vibration decreases as the amplitude A increases under strong winds is based on the "soft spring" characteristic of nonlinear stiffness. When a bridge vibrates in strong winds, if the amplitude A exceeds the linear vibration range, the structure will enter a nonlinear large deformation zone. At this point, the bridge's geometry causes changes in the stiffness of the material or structure: under large wind-induced displacements, the bridge's curvature changes, resulting in a decrease in bending stiffness; under high stress, steel may enter a plastic deformation zone, reducing its elastic modulus and further reducing stiffness. In this scenario, the bridge vibration also alters the vehicle's aerodynamic load, and the vehicle's vibration reacts on the bridge, creating a superimposed effect. This further impacts the robustness of the fully digital radio height-finding radar in dealing with nonlinear, strongly coupled multi-physics interference.

[0045] Furthermore, the second analysis of the natural environment interference effect of the height-finding radar on the cross-sea bridge also includes: directly extracting the bridge mass, bridge stiffness and fitted damping ratio through the radio height-finding radar comprehensive database; obtaining the total average mass of vehicles on the bridge in real time through the vehicle weighing system installed at the entrance and exit of the bridge; after identifying the specific vehicle model, directly obtaining the corresponding vehicle stiffness through the radio height-finding radar comprehensive database and then summing and averaging them to obtain the total average vehicle stiffness; coupling the fitted damping ratio with the bridge mass and the total average vehicle mass and then taking the square root analysis result to obtain the total coupling damping coefficient of the bridge vehicle ; After comparing and analyzing the bridge stiffness with the total average stiffness of the vehicle, the bridge stiffness is coupled with the total coupling damping coefficient of the bridge and vehicle and then squared, which is recorded as the total coupling attenuation coefficient of the bridge and vehicle; after coupling the bridge stiffness and the total average stiffness of the vehicle, the bridge stiffness is compared with the total coupling attenuation coefficient of the bridge and vehicle, and then the coupling result with the bridge mass and the total average mass of the vehicle is analyzed to obtain the basic value of the bridge-vehicle coupling frequency; after square root processing of the basic value of the bridge-vehicle coupling frequency, it is coupled with the predefined coefficient to obtain the bridge-vehicle coupling frequency, and the frequency coupling degree is analyzed according to the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency.

[0046] In this embodiment, Where fcouple represents the bridge-vehicle coupling frequency; M bIndicates the bridge quality, which is obtained from the bridge structure design drawings of the radio height radar comprehensive database; M v Indicates the total average mass of the vehicle. The vehicle weighing system is installed at the entrance and exit of the bridge to measure the total average mass of the vehicle in real time; K b represents the bridge stiffness, which is obtained from the bridge structure design drawings in the radio height radar comprehensive database; K v represents the total average stiffness of the vehicle, which is obtained by measuring the displacement of the vehicle body under wheel excitation of the vehicle suspension system parameters through vehicle dynamics testing. After prior calibration, the corresponding vehicle stiffness is directly obtained for the specific vehicle model after identification and then summed and averaged; C represents the total coupling damping coefficient of the bridge vehicle, the damping characteristics of the bridge and vehicle, which are obtained through vibration attenuation testing. An acceleration sensor is installed on the bridge, the experimental vehicle travels at a constant speed, and the free attenuation curve is recorded. The damping ratio ζ is obtained by fitting. The fitted damping ratio is input into the radio height radar integrated database and then obtained by Calculated.

[0047] Furthermore, the frequency coupling degree is analyzed according to the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the vehicle coupling frequency of the bridge, specifically including: directly extracting the main frequency of vehicle vibration from the comprehensive database of radio height sounding radar; comparing and analyzing the frequency coupling degree by comparing the overlapping interval length of any two frequencies with the maximum coverage length of the main frequency of vehicle vibration, the nonlinear vibration frequency of the bridge and the vehicle coupling frequency, and obtaining the overlapping degree of the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration, the overlapping degree of the vehicle coupling frequency and the main frequency of vehicle vibration, and the overlapping degree of the nonlinear vibration frequency of the bridge and the vehicle coupling frequency; if the overlapping degree of the nonlinear vibration frequency of the bridge and the main frequency of vehicle vibration, the overlapping degree of the vehicle coupling frequency and the main frequency of vehicle vibration, the overlapping degree of the nonlinear vibration frequency of the bridge and the vehicle coupling frequency If the overlap of vehicle coupling frequencies is greater than the overlap judgment threshold, it is judged as full-band overlap; if the overlap of the bridge nonlinear vibration frequency and the vehicle vibration main frequency is greater than the overlap of the bridge-vehicle coupling frequency and the vehicle vibration main frequency, and the overlap of the bridge nonlinear vibration frequency and the vehicle vibration main frequency is greater than the overlap of the bridge nonlinear vibration frequency and the bridge-vehicle coupling frequency, it is judged as bridge-vehicle dominant overlap; if the overlap of the bridge-vehicle coupling frequency and the vehicle vibration main frequency is greater than the overlap of the bridge nonlinear vibration frequency and the vehicle vibration main frequency, and the overlap of the bridge-vehicle coupling frequency and the vehicle vibration main frequency is greater than the overlap of the bridge nonlinear vibration frequency and the bridge-vehicle coupling frequency, it is judged as bridge-vehicle coupling and vehicle dominant overlap; if none of the above situations occur, an early warning will be issued and relevant personnel will be notified.

[0048] In this embodiment, the main frequency of vehicle vibration can be directly obtained through acceleration sensor acquisition + fast Fourier transform spectrum analysis. The exemplary steps are as follows: a MEMS acceleration sensor is selected, which is characterized by low cost, small size, and wide bandwidth. The sensor is installed on the vehicle suspension system or chassis of various test vehicles to ensure that the sensor and the vehicle body vibration transmission path are consistent; the sampling frequency fs = 500 Hz is set to cover the main frequency range of 10-50 Hz, the sampling time length T = 10 s, a 5-point sliding average is performed on the filtered signal to eliminate random noise, the preprocessed time domain signal is converted into a frequency domain spectrum through fast Fourier transform, the main frequency is directly identified, and the frequency point with the largest amplitude is found in the spectrum diagram, which is the main frequency of vehicle vibration fvehicle (usually in the range of 10-50 Hz). The experimental data set of the main frequency of vehicle vibration is uploaded to the radio height radar comprehensive database.

[0049] In the cross-sea bridge scenario, three key frequencies are involved:

[0050] Bridge nonlinear vibration frequency (fbridge_nonlinear); bridge vehicle coupling frequency (fcou ple); vehicle vibration main frequency (fvehicle).

[0051] The overlapping scenarios of the three can be divided into three categories:

[0052] Low frequency overlap: fbridge_nonlinear partially overlaps with fvehicle;

[0053] Mid-high frequency overlap: fcouple and fvehicle partially overlap;

[0054] Full-band overlap: The frequency ranges of the three are highly overlapping.

[0055] Coverlap = the length of the overlapping interval of the three compared frequencies / the maximum coverage length of the three frequencies, where Coverlap represents the degree of overlap of the three frequencies. The overlapping interval length is the difference between the minimum upper limit and the maximum lower limit of the three compared frequencies. If the overlapping interval length is negative, there is no overlap, and the case of no overlap is not considered. The total frequency band coverage length is the difference between the maximum upper limit and the minimum lower limit of the above three frequencies.

[0056] The degree of overlap requires identifying the dominant overlapping frequency pair (i.e., the frequency pair that has the greatest impact on interference) and is determined by comparing the lengths of the overlapping intervals:

[0057] The following frequency overlap between the two frequencies is the length of the overlapping interval of the two frequencies being compared / the maximum coverage length of the two frequencies.

[0058] Cbridge-vehicle represents the overlap between the nonlinear vibration frequency of the bridge and the main vibration frequency of the vehicle, Ccouple-vehicle represents the overlap between the bridge-vehicle coupling frequency and the main vibration frequency of the vehicle, and Cbridge-couple represents the overlap between the nonlinear vibration frequency of the bridge and the bridge-vehicle coupling frequency;

[0059] If Cbridge-vehicle>Ccouple-vehicle and Cbridge-vehicle>Cbridge-couple, then the dominant overlap is the bridge and the vehicle (fbridge_nonlinear and fvehicle);

[0060] If Ccouple-vehicle>Cbridge-vehicle and Ccouple-vehicle>Cbridge-co uple, then the dominant overlap is the coupling and the vehicle (fcouple and fvehicle);

[0061] If the three overlaps are similar, it is full-band overlap.

[0062] It should be noted that there are other comparison situations, but there are almost no corresponding actual situations, and low-probability events are not considered here.

[0063] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is carried out, specifically including: if it is determined that the bridge and the vehicle are dominantly overlapping, the results of the comparative analysis of the vehicle vibration main frequency and the first frequency of the safety interval and the results of the coupling analysis of the bridge nonlinear vibration pseudo-peak frequency and the first frequency of the safety interval are processed by the maximum function to obtain the multipath suppression filter cutoff adjustment frequency; the multipath suppression filter cutoff frequency of the height measurement radar is determined according to the multipath suppression filter cutoff adjustment frequency; the multipath suppression filter cutoff frequency: lower the cutoff frequency to filter out the low-frequency pseudo-peak of the bridge, and the first formula for adjusting the multipath suppression filter cutoff frequency is: fcutoff_new1=max(fvehicle-2Δf, fbridge_nonlinear+Δf1), where fcutoff_new1 represents the multipath suppression filter cutoff adjustment first frequency, and Δf1 is the first frequency of the safety interval, ensuring that the cutoff frequency is between the bridge pseudo-peak and the vehicle signal. For example, the bridge pseudo-peak frequency can be taken as the difference between the vehicle vibration main frequency and the bridge pseudo-peak frequency. The first frequency of the safety interval is set as one-quarter of the obtained frequency interval, which is determined based on prior expert knowledge. The calibration coefficient, the overlap between the bridge-vehicle coupling frequency and the vehicle vibration main frequency, and the unit-one coupling result are processed using a logarithmic function to obtain the test calibration value. The radar's original detection threshold is compared with the calibration value to obtain the radar calibration detection threshold. The height-finding radar calibration detection threshold is determined based on the radar calibration detection threshold. Lowering the threshold enhances the vehicle's low-frequency signal. The radar calibration detection threshold formula is: Pthreshold_new = Pthreshold_base - 10*lg(1+TX*Cbridge-vehicle), where Pthreshold_new represents the radar calibration detection threshold and Pthreshold_base represents the radar's original detection threshold, i.e., the signal power exceeding this value indicates a target presence. Lowering the threshold increases the probability of detecting weak signals. TX represents the first calibration coefficient of the threshold, which is determined based on prior expert knowledge. The lower adjustment limit of the radar calibration detection threshold is directly derived from the operating parameters in the height-finding radar's factory log. The radar calibration detection threshold cannot fall below the lower adjustment limit.

[0064] In this embodiment, if the bridge and vehicle signals are dominantly overlapped, this means that the bridge's nonlinear vibration artifacts overlap with the vehicle's vibration signal, masking the vehicle's signal. In this case, the bridge's low-frequency vibration artifacts are suppressed while preserving the vehicle's low-frequency characteristics.

[0065] By filtering out low-frequency pseudo-peaks from bridges and lowering the detection threshold, the problem of vehicle signals being masked by low-frequency nonlinear interference in fully digital radio height-finding radars is solved, significantly improving detection accuracy in low-frequency scenarios.

[0066] In this case, the PRF of the altimeter radar with low-frequency overlap does not need to be adjusted, and the time resolution requirement of the low-frequency signal is relatively low.

[0067] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is performed, which also includes: if it is determined that the bridge-vehicle coupling and the vehicle-dominant overlap, the results of the coupling analysis of the vehicle vibration main frequency and the first frequency of the safety interval and the results of the comparative analysis of the bridge-vehicle coupling frequency and the second frequency of the safety interval are processed by the minimum function to obtain the second frequency of the multipath suppression filter cutoff adjustment, and the height measurement radar multipath suppression filter cutoff frequency is determined according to the second frequency of the multipath suppression filter cutoff adjustment; the height measurement radar pulse repetition frequency adjustment first frequency is obtained through the height measurement radar pulse repetition frequency reference value, the pulse repetition frequency adjustment coefficient, the overlap degree of the bridge-vehicle coupling frequency and the vehicle vibration main frequency and the unit-one coupling analysis, and the height measurement radar pulse repetition frequency adjustment first frequency is adjusted according to the height measurement radar pulse repetition frequency adjustment first frequency.

[0068] In this embodiment, the coupling and vehicle dominant frequencies overlap at mid- and high-frequency levels. The coupling frequency overlaps with the vehicle's dominant vibration frequency, masking the vehicle signal with the coupling pseudo-peak. This adjustment is used to separate the coupling pseudo-peak from the vehicle signal, preserving the vehicle's dominant frequency characteristics.

[0069] Multipath suppression filter cutoff frequency: Increase the cutoff frequency to filter out coupling pseudo-peaks. The formula for adjusting the second frequency of the multipath suppression filter cutoff is as follows: fcutoff_new1 = min(fvehicle + 2Δf2, fcouple - Δf2), where fcutoff_new2 represents the second frequency of the multipath suppression filter cutoff adjustment, and Δf2 is the second frequency of the safety interval. This frequency is set by expert prior knowledge to ensure that the cutoff frequency is between the bridge-vehicle coupling frequency and the main frequency of vehicle vibration.

[0070] Increasing the PRF improves temporal resolution and separates coupled pseudo-peaks from rapid changes in vehicle signals. The first formula for adjusting the pulse repetition frequency of the altimeter radar is: PRFnew1 = PRFbase*(1+TX1*Ccouple-vehicle), where PRFnew1 represents the first frequency for adjusting the pulse repetition frequency of the altimeter radar, PRFbase represents the reference value of the pulse repetition frequency of the altimeter radar, and Ccouple-vehicle represents the overlap between the bridge-vehicle coupling frequency and the main frequency of vehicle vibration. The original detection threshold of the radar remains unchanged, and TX1 represents the pulse repetition frequency adjustment coefficient, which is set by expert prior knowledge.

[0071] Furthermore, a second optimization of the interference superposition of the cross-sea bridge height measurement radar is performed, which also includes: if it is determined that the full frequency band overlaps, the nonlinear vibration frequency of the bridge, the bridge vehicle coupling frequency and the main frequency of the vehicle vibration are processed by the median function to obtain the third frequency of the multipath suppression filter cutoff adjustment; the band-stop filter frequency of the height measurement radar multipath suppression filter is determined according to the second frequency of the multipath suppression filter cutoff adjustment; the second adjustment coefficient of the threshold, the frequency overlap of the three and the coupling result of unit one are processed by the logarithmic function, recorded as the three frequency coupling adjustment coefficient, to obtain the first test adjustment detection value, the original detection threshold of the radar is compared and analyzed with the first test adjustment detection value to obtain the first threshold of the radar adjustment detection, and the height measurement radar adjustment detection threshold is determined according to the first threshold of the radar adjustment detection; the first frequency of the height measurement radar pulse repetition frequency adjustment is obtained by analyzing the reference value of the height measurement radar pulse repetition frequency, the first coefficient of the pulse repetition frequency adjustment, the frequency overlap of the three and the coupling of unit one, and the height measurement radar pulse repetition frequency is adjusted according to the first frequency of the pulse repetition frequency adjustment.

[0072] In this embodiment, full-band overlap refers to a high degree of overlap in the three frequency ranges. Bridge and coupling pseudo-peaks are intertwined with vehicle signals, making them difficult to distinguish. Therefore, it is necessary to comprehensively suppress low-frequency bridge pseudo-peaks and mid- and high-frequency coupling pseudo-peaks while preserving the vehicle's dominant frequency characteristics. The multipath suppression filter simultaneously suppresses the low-frequency bridge signal (bridge_nonlinear) and the mid- and high-frequency coupling signal (fcouple). The formula for adjusting the third frequency cutoff of the multipath suppression filter is as follows: fcutoff_new3 = median(fbridge_nonlinear, fcouple, fvehicle); fcutoff_new3 represents the third frequency cutoff of the multipath suppression filter, which is the filter frequency set after the multipath suppression filter is adjusted to a band-stop filter.

[0073] The threshold is significantly lowered to enhance vehicle signals. The constraint formula for the first threshold of radar calibration detection is: Pthreshold_new1 = Pthreshold_base - 10*lg(1 + TX3*Coverlap), where Pthreshold_new1 represents the first threshold of radar calibration detection, Coverlap represents the frequency overlap between the three, and TX3 represents the second threshold calibration coefficient, which is set based on expert prior knowledge. TX3 > TX. The lower limit of the radar calibration detection threshold is directly derived from the operating parameters in the altimeter radar's factory log. The radar calibration detection threshold cannot fall below the lower limit.

[0074] Significantly increase the PRF to improve temporal resolution and separate overlapping signals. The formula is: PRFnew2 = PRFBase * (1 + TX2 * Coverlap). TX2 represents the first coefficient of pulse repetition frequency adjustment, set by expert prior knowledge. TX2 > TX1. PRFnew2 represents the second frequency of the pulse repetition frequency adjustment for the altimeter radar.

[0075] Furthermore, we conduct optimized feedback analysis and make judgments and early warnings, including:

[0076] After optimization and adjustment, if the final signal-to-noise ratio of the cross-sea bridge height measurement radar is less than the preset signal-to-noise ratio effective threshold, or the final false detection rate of vehicle detection is still greater than the preset false detection rate target value, or the overlap of the bridge-vehicle coupling frequency is still greater than the preset safety overlap threshold, the radar system's sound and light alarm device will be activated and an email will be simultaneously pushed to the maintenance personnel terminal, containing key parameters such as the current signal-to-noise ratio, false detection rate, and overlap. The execution results of all current adjustment steps (such as the filter cutoff frequency adjustment value, PRF adjustment value, and threshold adjustment value), environmental parameters (humidity, rainfall, wind speed), and bridge-vehicle coupling parameters (vibration frequency, overlap) will be stored in non-volatile memory to facilitate subsequent troubleshooting.

[0077] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0079] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0081] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0082] Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations fall within the scope of the claims and their equivalents, the present invention is intended to include such modifications and variations.

Claims

1. A fully digital radio altimeter radar optimization method based on artificial intelligence, characterized in that: The following steps are involved: Conduct the first analysis of the natural environment interference effect of the cross-sea bridge height measurement radar, and conduct the first optimization of the interference superposition of the cross-sea bridge height measurement radar; Conduct a second analysis of the natural environment interference effect of the cross-sea bridge height measurement radar, and conduct a second optimization of the interference superposition of the cross-sea bridge height measurement radar; Conduct optimized feedback analysis and make judgments and early warnings.

2. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 1, characterized in that: The first analysis of the natural environment interference effect of the sea-crossing bridge height measurement radar specifically includes: The ambient humidity of the altimeter radar is collected through temperature and humidity sensors; Directly obtain the rainfall intensity of the altimeter radar environment through the meteorological database; The humidity influence coefficient and rainfall influence coefficient are directly extracted from the radio altimeter radar comprehensive database; If the ambient humidity of the altimeter radar is greater than the ambient humidity threshold of the altimeter radar and the ambient rainfall intensity of the altimeter radar is greater than the ambient rainfall intensity threshold of the altimeter radar, the signal-to-noise ratio degradation analysis value of the sea-crossing bridge altimeter radar is obtained through a comprehensive analysis of the ambient humidity of the altimeter radar, the ambient rainfall intensity of the altimeter radar, the humidity influence coefficient and the rainfall influence coefficient.

3. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 1, characterized in that: The first optimization of the cross-sea bridge height measurement radar interference superposition specifically includes: The base signal-to-noise ratio of the radio height-finding radar is directly extracted from the historical database of the radio height-finding radar. By comparing the base signal-to-noise ratio of the height-finding radar with the signal-to-noise ratio drop analysis value of the cross-sea bridge height-finding radar, the lower limit of the signal-to-noise ratio fluctuation of the cross-sea bridge height-finding radar is obtained. If the lower limit of the signal-to-noise ratio fluctuation of the sea-crossing bridge height measurement radar is greater than the signal-to-noise ratio failure, the optimization will not be triggered. If the lower limit of the signal-to-noise ratio fluctuation of the sea-crossing bridge height measurement radar is equal to or less than the signal-to-noise ratio failure, the optimization will be triggered. The minimum value of the pulse repetition frequency of the radio altimeter radar, the reference value of the pulse repetition frequency of the radio altimeter radar and the maximum signal-to-noise ratio loss threshold are directly extracted from the radio altimeter radar comprehensive database. After comparing and analyzing the pulse repetition frequency baseline value of the height-finding radar with the minimum value of the pulse repetition frequency of the height-finding radar, the result is recorded as the pulse repetition frequency adjustment range value of the height-finding radar. The result of the ratio analysis of the unit 1 and the lower limit of the signal-to-noise ratio fluctuation of the sea-crossing bridge height-finding radar and the maximum signal-to-noise ratio loss threshold is compared and analyzed to obtain the signal-to-noise ratio fluctuation loss coefficient of the height-finding radar. The minimum value of the pulse repetition frequency of the altitude radar, the adjustment range of the pulse repetition frequency of the altitude radar and the signal-to-noise ratio fluctuation loss coefficient of the altitude radar are coupled and analyzed to obtain the optimized value of the pulse repetition frequency of the altitude radar. The trigger optimization is used to determine the pulse repetition frequency output by the altimeter radar according to the optimized value of the pulse repetition frequency of the altimeter radar.

4. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 1, wherein: The second analysis of the natural environment interference effect of the sea-crossing bridge height measurement radar is specifically performed as follows: If the ambient wind speed of the height-measuring radar is less than or equal to the ambient wind speed threshold of the height-measuring radar, the second analysis of the natural environment interference effect of the height-measuring radar of the cross-sea bridge will not be performed; If the ambient wind speed of the height measuring radar exceeds the threshold value of the ambient wind speed of the height measuring radar, the second analysis of the natural environment interference effect of the height measuring radar of the cross-sea bridge is carried out; The second analysis of the natural environment interference effect of the sea-crossing bridge height measurement radar includes: The Strouhal number, characteristic width and nonlinear stiffness coefficient of the sea-crossing bridge are directly extracted from the radio height radar comprehensive database. The wind speed of the cross-sea bridge is collected by the wind speed and direction meter at the top of the radar antenna mast; The inertial measurement sensor installed at the bottom of the bridge box girder measures the vibration displacement in real time, and the amplitude is extracted through fast Fourier transform analysis to obtain the maximum amplitude of the bridge vibration; The linear vibration frequency of the bridge is obtained by coupling the Strouhal number of the sea-crossing bridge with the sea breeze speed and then comparing it with the characteristic width of the bridge. Compare and analyze the coupling results of the unity and the bridge nonlinear stiffness coefficient with the maximum amplitude of the bridge vibration, and then perform square root analysis to obtain the bridge nonlinear vibration frequency adjustment coefficient; The linear vibration frequency of the bridge is coupled with the tuning coefficient of the nonlinear vibration frequency of the bridge to obtain the nonlinear vibration frequency of the bridge.

5. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 4, characterized in that: The second analysis of the natural environment interference effect of the sea-crossing bridge height measurement radar also includes: The bridge mass, bridge stiffness and fitted damping ratio are directly extracted from the radio height radar comprehensive database; The total average mass of vehicles on the bridge is measured in real time by the vehicle weighing system installed at the entrance and exit of the bridge; After identifying the specific vehicle model, the corresponding vehicle stiffness is directly obtained through the radio height radar integrated database, and then summed and averaged to obtain the total average stiffness of the vehicle; The total bridge-vehicle coupling damping coefficient is obtained by fitting the damping ratio and then coupling it with the bridge mass and the total average mass of the vehicle and then performing square root analysis. After comparing the bridge stiffness with the total average stiffness of the vehicle, the total coupling damping coefficient of the bridge and vehicle is coupled and square rooted to obtain the total coupling attenuation coefficient of the bridge and vehicle. After coupling analysis of bridge stiffness and total average vehicle stiffness, the results are compared with the total bridge-vehicle coupling attenuation coefficient. Furthermore, a proportional analysis is performed with the coupling results of bridge mass and total average vehicle mass to obtain the basic value of the bridge-vehicle coupling frequency. The bridge-vehicle coupling frequency base value is squared and then coupled with a predefined coefficient to obtain the bridge-vehicle coupling frequency; The frequency coupling degree is analyzed based on the vehicle vibration main frequency, bridge nonlinear vibration frequency and bridge-vehicle coupling frequency.

6. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 5, characterized in that: The analysis of the frequency coupling degree according to the vehicle vibration main frequency, the bridge nonlinear vibration frequency and the bridge-vehicle coupling frequency specifically includes: The main vibration frequency of the vehicle is directly extracted from the comprehensive database of radio height-finding radar; By comparing the overlapping interval length of any two frequencies with the maximum coverage length of the vehicle vibration main frequency, the bridge nonlinear vibration frequency and the bridge-vehicle coupling frequency analysis frequency coupling degree, the overlapping degree of the bridge nonlinear vibration frequency and the vehicle vibration main frequency, the overlapping degree of the bridge-vehicle coupling frequency and the vehicle vibration main frequency, and the overlapping degree of the bridge nonlinear vibration frequency and the bridge-vehicle coupling frequency are obtained; If the overlap between the bridge nonlinear vibration frequency and the vehicle vibration main frequency is greater than the overlap between the bridge vehicle coupling frequency and the vehicle vibration main frequency, and the overlap between the bridge nonlinear vibration frequency and the vehicle vibration main frequency is greater than the overlap between the bridge nonlinear vibration frequency and the bridge vehicle coupling frequency, then it is judged that the bridge and vehicle are dominantly overlapping; If the degree of overlap between the bridge-vehicle coupling frequency and the vehicle's dominant vibration frequency is greater than the degree of overlap between the bridge's nonlinear vibration frequency and the vehicle's dominant vibration frequency, and the degree of overlap between the bridge-vehicle coupling frequency and the vehicle's dominant vibration frequency is greater than the degree of overlap between the bridge's nonlinear vibration frequency and the bridge-vehicle coupling frequency, then it is determined that the bridge-vehicle coupling and the vehicle's dominant frequency overlap; If the overlap between the bridge nonlinear vibration frequency and the vehicle vibration main frequency, the overlap between the bridge vehicle coupling frequency and the vehicle vibration main frequency, and the overlap between the bridge nonlinear vibration frequency and the bridge vehicle coupling frequency are all greater than the overlap judgment threshold, it is judged as full-band overlap.

7. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 6, characterized in that: The second optimization of the cross-sea bridge height measurement radar interference superposition specifically includes: If it is determined that the bridge and the vehicle are dominantly overlapping, the results of the comparative analysis between the vehicle vibration main frequency and the first frequency of the safety interval and the results of the coupling analysis between the pseudo-peak frequency of the bridge nonlinear vibration and the first frequency of the safety interval are processed using a maximum function to obtain the first frequency of the multipath suppression filter cutoff adjustment. The cutoff frequency of the multipath suppression filter of the height measurement radar is determined based on the first frequency of the multipath suppression filter cutoff adjustment. The first threshold adjustment coefficient, the overlap between the bridge vehicle coupling frequency and the vehicle vibration main frequency, and the coupling result of unit one are processed through a logarithmic function to obtain the inspection and adjustment detection value. The radar original detection threshold is compared with the inspection and adjustment detection value to obtain the radar adjustment detection threshold. The height measurement radar adjustment detection threshold is determined based on the radar adjustment detection threshold.

8. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 6, characterized in that: The performing of the second optimization of the cross-sea bridge height measurement radar interference superposition also includes: If it is determined that the bridge-vehicle coupling overlaps with the vehicle dominant frequency, the results of the coupling analysis between the vehicle vibration dominant frequency and the first frequency of the safety interval and the results of the comparative analysis between the bridge-vehicle coupling frequency and the second frequency of the safety interval are processed using a minimum function to obtain the second frequency of the multipath suppression filter cutoff adjustment. The cutoff frequency of the multipath suppression filter of the height measurement radar is determined based on the second frequency of the multipath suppression filter cutoff adjustment. The first frequency of the pulse repetition frequency adjustment of the altimeter radar is obtained through the pulse repetition frequency reference value of the altimeter radar, the pulse repetition frequency calibration coefficient, the overlap degree of the bridge vehicle coupling frequency and the vehicle vibration main frequency, and the unit-coupling analysis. The pulse repetition frequency of the altimeter radar is adjusted according to the first frequency of the pulse repetition frequency adjustment of the altimeter radar.

9. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 6, characterized in that: The performing of the second optimization of the cross-sea bridge height measurement radar interference superposition also includes: If it is determined that the full frequency band overlaps, the bridge nonlinear vibration frequency, the bridge vehicle coupling frequency and the vehicle vibration main frequency are processed by the median function to obtain the multipath suppression filter cutoff adjustment third frequency; Adjusting the second frequency according to the multipath suppression filter cutoff to determine the band-stop filter frequency of the height-finding radar multipath suppression filter; The second threshold adjustment coefficient, the frequency overlap of the three, and the coupling result of unit 1 are processed by a logarithmic function and recorded as the three-frequency coupling adjustment coefficient to obtain the first test adjustment detection value. The original radar detection threshold is compared with the first test adjustment detection value to obtain the first radar adjustment detection threshold. The height measurement radar adjustment detection threshold is determined based on the first radar adjustment detection threshold. The altimeter radar pulse repetition frequency adjustment first frequency is obtained by analyzing the altimeter radar pulse repetition frequency reference value, the pulse repetition frequency adjustment first coefficient, the frequency overlap of the three and the unit-one coupling. The altimeter radar pulse repetition frequency is adjusted according to the altimeter radar pulse repetition frequency adjustment first frequency.

10. The artificial intelligence-based fully digital radio altimeter optimization method according to claim 1, characterized in that: The optimized feedback analysis and judgment and early warning specifically include: After optimization and adjustment, if the final signal-to-noise ratio of the cross-sea bridge height measurement radar is less than the preset signal-to-noise ratio effective threshold, or the final false detection rate of vehicle detection is still greater than the preset false detection rate target value, or the overlap of the bridge-vehicle coupling frequency is still greater than the preset safety overlap threshold, the radar system's sound and light alarm device will be activated, an email will be sent to the maintenance personnel terminal at the same time, and the execution results of all current adjustment steps, environmental parameters, and bridge-vehicle coupling parameters will be stored in non-volatile memory.

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