Parameter measurement method and device based on dual-band mode, equipment and storage medium

Abstract

The invention relates to the technical field of meteorological observation, in particular to a parameter measurement method and device based on a dual-band mode, equipment and a storage medium. Generating a dual-band excitation signal according to the aligned sine wave signal; analyzing the echo signal according to a preset gain coefficient, a time difference method and a preset attitude compensation formula to obtain a reconstructed quasi-unipolar pulse, an actual wind speed, a horizontal wind direction angle, a pitch angle, a three-dimensional wind speed vector, a roll angle and a real wind direction; acquiring real-time air pressure, and correcting a preset standard state sound velocity according to a preset sound velocity correction formula and the real-time air pressure to obtain a corrected sound velocity; according to the scheme, a dual-band signal attached to a medium is generated, after efficient transmission analysis, high-resolution pulses and multi-dimensional wind field parameters are obtained by means of gain, a time difference method, attitude compensation and the like, the sound velocity is corrected in combination with air pressure, comprehensive, accurate and rapid updating of data are considered, and the measurement reliability is improved.

Description

Technical Field

[0001] This invention relates to the field of meteorological observation technology, and in particular to parameter measurement methods, devices, equipment and storage media based on dual-band mode. Background Technology

[0002] In fields such as meteorological observation, aerospace, ship navigation, and wind power generation, accurate measurement of three-dimensional wind speed (including wind speed magnitude, horizontal wind direction angle, and pitch angle) is the core foundation for environmental monitoring, equipment control, and safety early warning. The current mainstream measurement solution is a three-dimensional ultrasonic anemometer system. However, due to limitations in the performance of core components such as transducers and bottlenecks in signal processing technology, it faces significant technical barriers in high-precision, high-stability measurement scenarios. Existing systems generally use single-band ultrasonic transducers for measurement, which suffers from inherent drawbacks due to performance trade-offs: fixed operating frequencies (1-3MHz low frequency or 5-15MHz high frequency) and narrow bandwidth (30%-50%), making it impossible to balance transmission distance and measurement accuracy. Low-frequency transducers have large measurement errors at close range, while high-frequency transducers have a transmission distance of only within 0.5m. Multiple transducers covering multiple frequency bands are prone to signal crosstalk (crosstalk rejection ratio less than 20dB), leading to echo distortion. Furthermore, the transducer's impedance matching with air is rudimentary, making it prone to measurement failure in complex environments with an SNR (signal-to-noise ratio) of <8dB. Summary of the Invention

[0003] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a parameter measurement method, apparatus, device and storage medium based on dual-band mode.

[0004] The first aspect of this invention provides a parameter measurement method based on a dual-band mode, comprising: acquiring a first acoustic impedance and a second acoustic impedance; generating an aligned sinusoidal wave signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions; generating a dual-band excitation signal based on the aligned sinusoidal wave signal; generating a transmission compressed packet based on the dual-band excitation signal; performing transmission processing on the transmission compressed packet under a preset transmission signal mode; acquiring a return compressed packet based on the transmission compressed packet and parsing the return compressed packet to obtain an echo signal; analyzing the echo signal based on a preset gain coefficient, a time difference method, and a preset attitude compensation formula to obtain a reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction; acquiring real-time air pressure and correcting a preset standard state sound speed based on a preset sound speed correction formula and real-time air pressure to obtain a corrected sound speed; and generating measurement parameters based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed.

[0005] Further, the step of analyzing the echo signal according to a preset gain coefficient, time difference method, and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction includes: separating the echo signal according to a preset low-frequency channel, a preset high-frequency channel, and a gain coefficient to obtain high-frequency echo signal and low-frequency echo signal; analyzing the high-frequency echo signal and low-frequency echo signal according to a preset amplitude ratio to obtain the reconstructed quasi-monopolar pulse; obtaining the AB downwind time, BA headwind time, AC downwind time, CA headwind time, AD downwind time, and DA headwind time; and analyzing the AB downwind time, BA headwind time, AC downwind time, CA headwind time, AD downwind time, and DA headwind time according to the time difference method and attitude compensation formula to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction.

[0006] Furthermore, the step of analyzing the high-frequency echo signal and the low-frequency echo signal according to a preset amplitude ratio to obtain a reconstructed quasi-monopolar pulse includes: analyzing the high-frequency echo signal and the low-frequency echo signal to obtain a time delay compensation amount; performing wavelet decomposition on the high-frequency echo signal and the low-frequency echo signal to obtain a low-frequency wavelet dataset and a high-frequency wavelet dataset; and reconstructing the low-frequency wavelet dataset and the high-frequency wavelet dataset according to the amplitude ratio and the time delay compensation amount to obtain a reconstructed quasi-monopolar pulse.

[0007] Furthermore, the analysis of the AB tailwind time, BA headwind time, AC tailwind time, CA headwind time, AD tailwind time, and DA headwind time based on the time difference method and attitude compensation formula to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction includes: calculating the AB tailwind time, BA headwind time, AC tailwind time, CA headwind time, AD tailwind time, and DA headwind time based on the time difference method, a preset non-orthogonal array spatial projection relationship, and attitude compensation formula to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, and roll angle; The preset attitude calibration coefficients, horizontal wind direction angle, and pitch angle are calculated to obtain the magnetometer azimuth angle; the horizontal wind direction angle and the magnetometer azimuth angle are calculated to obtain the true wind direction.

[0008] Furthermore, the calculation of AB downwind time, BA headwind time, AC downwind time, CA headwind time, AD downwind time, and DA headwind time based on the time difference method, the preset non-orthogonal array spatial projection relationship, and the attitude compensation formula to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, and roll angle includes: calculating AB downwind time, BA headwind time, AC downwind time, CA headwind time, AD downwind time, and DA headwind time based on the time difference method and the preset tetrahedron edge length to obtain the first three-dimensional wind speed component; The first three-dimensional wind speed component is calculated based on the spatial projection relationship of the non-orthogonal array, preset sine and cosine values ​​to obtain the actual wind speed, horizontal wind direction angle, and pitch angle; the horizontal wind direction angle and pitch angle are solved to obtain the roll angle; the propagation time difference is obtained and converted according to preset geometric relationships, preset transducer spacing, and preset transducer axis angle to obtain the second three-dimensional wind speed component; the second three-dimensional wind speed component, horizontal wind direction angle, roll angle, and pitch angle are compensated according to the attitude compensation formula to obtain the three-dimensional wind speed vector.

[0009] Further, the step of generating an aligned sinusoidal signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions includes: calculating the first acoustic impedance and the second acoustic impedance to obtain the geometric mean of the characteristic impedance; analyzing the geometric mean of the characteristic impedance based on the boundary conditions to obtain an analysis result; generating a low-frequency sine wave and a high-frequency sine wave when the analysis result shows that the geometric mean of the characteristic impedance satisfies the boundary conditions; and aligning the low-frequency sine wave and the high-frequency sine wave to obtain an aligned sinusoidal signal.

[0010] Furthermore, the analysis of the high-frequency echo signal and the low-frequency echo signal to obtain the time delay compensation amount includes: performing a generalized quadratic correlation operation on the high-frequency echo signal and the low-frequency echo signal to obtain an integer multiple of the time difference; extracting features from the high-frequency echo signal and the low-frequency echo signal according to a preset Fourier transform algorithm to obtain spectral features; generating a fractional multiple of the time difference based on the spectral features; and calculating the integer multiple of the time difference and the fractional multiple of the time difference to obtain the time delay compensation amount.

[0011] A second aspect of the present invention provides a parameter measurement device based on a dual-band mode, comprising: an acoustic impedance acquisition module for acquiring a first acoustic impedance and a second acoustic impedance; a signal alignment module for generating an aligned sine wave signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions; an excitation signal generation module for generating a dual-band excitation signal based on the aligned sine wave signal; a compression module for generating a transmission compressed packet based on the dual-band excitation signal; a transmission module for performing transmission processing on the transmission compressed packet under a preset transmission signal mode; and a parsing module for acquiring a return compressed packet based on the transmission compressed packet and processing the return compressed packet. The system analyzes the echo signal to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction. A correction module acquires real-time air pressure and corrects the preset standard state sound speed according to a preset sound speed correction formula and real-time air pressure to obtain the corrected sound speed. A measurement parameter generation module generates measurement parameters based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed.

[0012] A third aspect of the present invention provides a parameter measurement device based on a dual-band mode, the parameter measurement device based on a dual-band mode comprising: a memory and at least one processor, the memory storing instructions; at least one of the processors calling the instructions in the memory to cause the computer device to execute the various steps of the parameter measurement method based on the dual-band mode described above.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the steps of the parameter measurement method based on dual-band mode as described in any of the preceding claims.

[0014] In this invention, a aligned sine wave signal is generated by combining boundary conditions to ensure that the signal propagation conforms to the characteristics of the medium from the source, reducing attenuation and distortion. Based on this, a dual-band excitation signal is generated, balancing the propagation stability of the low-frequency signal with the detail capture capability of the high-frequency signal, laying a high-quality signal foundation for subsequent measurements. In the signal transmission stage, the excitation signal is encapsulated into a compressed packet and transmitted efficiently in a preset mode. After parsing by a preset communication interface, the echo signal is accurately restored. Subsequently, weak echoes are amplified using a preset gain coefficient, wind speed core data is correlated using the time difference method, and attitude compensation formulas are used to correct equipment attitude errors. This solution not only generates high-resolution reconstructed quasi-monopolar pulses but also accurately calculates multi-dimensional wind field parameters such as actual wind speed and horizontal wind direction angle, avoiding problems such as insufficient accuracy in traditional measurement calculations. By introducing real-time air pressure combined with a sound speed correction formula, a corrected sound speed is obtained, ensuring that the wind speed calculation benchmark conforms to the real-time environment. Finally, multiple types of data are integrated to generate measurement parameters, balancing data comprehensiveness and accuracy, and enabling rapid parameter updates, effectively meeting the high requirements for wind field measurement in different scenarios and improving measurement reliability and practicality. Attached Figure Description

[0015] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 A first flowchart of a parameter measurement method based on dual-band mode provided in an embodiment of the present invention; Figure 2 A second flowchart of a parameter measurement method based on dual-band mode provided in an embodiment of the present invention; Figure 3 A third flowchart of a parameter measurement method based on dual-band mode provided in an embodiment of the present invention; Figure 4 The fourth flowchart of the parameter measurement method based on dual-band mode provided in the embodiments of the present invention; Figure 5 The fifth flowchart of the parameter measurement method based on dual-band mode provided in the embodiments of the present invention; Figure 6 The sixth flowchart of the parameter measurement method based on dual-band mode provided in the embodiments of the present invention; Figure 7 The seventh flowchart of the parameter measurement method based on dual-band mode provided in the embodiments of the present invention; Figure 8 A schematic diagram of the structure of a parameter measurement device based on dual-band mode provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a parameter measurement device based on dual-band mode provided in an embodiment of the present invention. Detailed Implementation

[0016] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] A three-dimensional ultrasonic anemometer system based on stacked dual-band transducers and quasi-monopolar pulses includes a tetrahedral transducer array and a signal transceiver circuit. Stacked dual-band ultrasonic transducers are arranged at the four vertices of the tetrahedral transducer array, and the spatial angle between the axes of any two transducers is 60°, forming three sets of opposing transceiver paths. The stacked dual-band ultrasonic transducer integrates a 1-3MHz low-frequency unit and a 5-15MHz high-frequency unit, and from bottom to top includes a backing layer, a low-frequency piezoelectric layer, an acoustic filter layer (AF layer), a high-frequency piezoelectric layer, and a double-layer matching layer. For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the parameter measurement method based on dual-band mode in this invention includes: 101. Obtain the first acoustic impedance and the second acoustic impedance; 102. Generate an aligned sine wave signal based on the first acoustic impedance, the second acoustic impedance, and the preset boundary conditions; 103. Generate a dual-band excitation signal based on the aligned sine wave signal; In this embodiment, a dual-band excitation signal is output at a sampling frequency of 100Hz. First, the first acoustic impedance (e.g., the acoustic impedance of a functional layer of the transducer) and the second acoustic impedance (e.g., the acoustic impedance of another matching layer) are acquired. These two are key medium parameters for sound wave propagation and directly affect signal transmission efficiency. If the impedances are mismatched, sound waves are easily reflected at the interface, leading to energy loss. Combined with preset boundary conditions (e.g., the impedance relationship of the matching layers), it can be ensured that the generated aligned sine wave signal conforms to the actual medium characteristics during propagation, reducing signal attenuation or distortion. The dual-band excitation signal is generated based on the aligned sine wave, which can retain the low-frequency signal. The signal transceiver circuitry combines stable propagation with the ability to capture details of high-frequency signals, laying the foundation for effective reception of subsequent echo signals. It includes a CD4052 analog switch, a transmitting circuit, and a receiving circuit. The CD4052 analog switch enables switching between transducer transmitting and receiving modes. The transmitting circuit outputs a low-frequency 5-cycle sine wave (peak value 1V) and a high-frequency 3-cycle sine wave (peak value 2-3V). The receiving circuitry is equipped with a 3MHz low-pass filter (low-frequency channel), a 5-10MHz band-pass filter (high-frequency channel), and a 40dB gain module to separate and amplify high- and low-frequency echo signals. 104. Generate transmission compressed packets based on the dual-band excitation signals; 105. Under the preset signal transmission mode, process the transmission compressed package for transmission; 106. Obtain the return compressed package based on the transmitted compressed package, and parse the return compressed package to obtain the echo signal; 107. Analyze the echo signal according to the preset gain coefficient, time difference method and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle and true wind direction; In this embodiment, the weak echo signal is amplified by gain coefficient and the error is corrected by attitude compensation, which effectively avoids the problem of inaccurate calculation caused by array layout and attitude deviation in traditional measurement. It can generate high-resolution reconstructed quasi-monopolar pulses and obtain multi-dimensional parameters such as actual wind speed and three-dimensional wind speed vector, providing data support for wind field measurement. 108. Obtain real-time air pressure, and correct the preset standard state sound speed according to the preset sound speed correction formula and real-time air pressure to obtain the corrected sound speed. In this embodiment, the expression for the sound speed correction formula is as follows: (11) ( The standard speed of sound. =331.4 m / s (under conditions of 0℃ and 101325 Pa)), the speed of sound can be accurately corrected by measuring P (real-time air pressure) in real time, and the propagation speed of ultrasound can be calibrated in real time. To correct for the speed of sound; 109. Generate measurement parameters based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed; In this embodiment, the measurement parameters are updated every 10 cycles (0.1s) to control the wind speed measurement error, and the time difference measurement accuracy is controlled within 0.1μs; In this embodiment, an aligned sine wave signal is generated by combining boundary conditions to ensure that the signal propagation conforms to the characteristics of the medium from the source, reducing attenuation and distortion. Based on this, a dual-band excitation signal is generated, which takes into account the propagation stability of the low-frequency signal and the detail capture capability of the high-frequency signal, laying a high-quality signal foundation for subsequent measurements. In the signal transmission stage, the excitation signal is encapsulated into a compressed packet and transmitted efficiently in a preset mode. After being parsed by a preset communication interface, the echo signal is accurately restored. Subsequently, the weak echo is amplified by a preset gain coefficient, the time difference method is used to correlate the core wind speed data, and the attitude compensation formula is used to correct the device attitude error. This solution not only generates a high-resolution reconstructed quasi-monopolar pulse, but also accurately calculates multi-dimensional wind field parameters such as actual wind speed and horizontal wind direction angle, avoiding the problem of insufficient accuracy in traditional measurement and calculation. By introducing real-time air pressure combined with the sound speed correction formula, the corrected sound speed is obtained, ensuring that the wind speed calculation benchmark conforms to the real-time environment. Finally, multiple types of data are integrated to generate measurement parameters, taking into account the comprehensiveness and accuracy of the data, and the parameters can be updated quickly, effectively meeting the high requirements for wind field measurement in different scenarios, and improving the reliability and practicality of measurement.

[0018] Please see Figure 2 The second embodiment of the parameter measurement method based on dual-band mode in this invention includes: 201. Separate the echo signal according to the preset low-frequency channel, preset high-frequency channel and gain coefficient to obtain high-frequency echo signal and low-frequency echo signal; In this embodiment, the gain coefficient is 40dB. The receiving circuit separates the high-frequency and low-frequency echo signals through a 3MHz low-pass filter (low-frequency channel) and a 5-10MHz band-pass filter (high-frequency channel) to obtain high-frequency and low-frequency echo signals. A gain of 40dB is set to improve signal processing performance. Echo signals of different frequencies carry different environmental information (low-frequency signals propagate stably, while high-frequency signals are rich in detail). Precise separation through filters can avoid frequency aliasing interference. The 40dB gain can amplify weak echo signals, improve the signal-to-noise ratio of subsequent signal analysis, and lay a high-quality data foundation for pulse reconstruction. 202. Analyze the high-frequency echo signal and the low-frequency echo signal according to the preset amplitude ratio to obtain the reconstructed quasi-monopolar pulse; In this embodiment, the low-frequency echo signal SL(t) and the high-frequency echo signal SH(t) are analyzed, and the expression for reconstructing the quasi-monopolar pulse is as follows: p(t)=SL(t)+2.1×SH(t-τ)), In the formula, the time domain width of the pulse is compressed to 0.1-0.2μs (only 1 / 5-1 / 10 of the traditional 3-cycle sine pulse), p(t) is a reconstructed quasi-monopolar pulse, and the amplitudes are generated by superimposing at a ratio of 2.1:1. By optimizing the energy distribution through the amplitude ratio of 2.1:1 and combining the time delay compensation of the high-frequency signal, the pulse time domain width is compressed to 0.1-0.2μs (only 1 / 5-1 / 10 of the traditional sine pulse). The advantage of the narrow pulse signal is that it has a higher time resolution, which can more accurately capture the subtle time difference of the round-trip propagation of ultrasonic waves, reduce the timing error caused by the excessive pulse width, and provide more accurate time data for subsequent wind speed calculation. 203. Obtain the tailwind time of AB, the headwind time of BA, the tailwind time of AC, the headwind time of CA, the tailwind time of AD, and the headwind time of DA; In this embodiment, for the three groups of opposing ultrasonic transducers AB, AC, and AD, the time difference method is used to quantitatively calculate the wind speed component in the corresponding direction by measuring the time difference of the ultrasonic wave's round-trip propagation between the two opposing transducers. 204. Based on the time difference method and attitude compensation formula, analyze the downwind time of AB, the upwind time of BA, the downwind time of AC, the upwind time of CA, the downwind time of AD, and the upwind time of DA to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction; In this embodiment, a 3MHz low-pass filter and a 5-10MHz band-pass filter are first used to separate high- and low-frequency echo signals. A 40dB gain is then used to amplify the weak signal, avoiding frequency aliasing and improving the signal-to-noise ratio, laying a high-quality data foundation for subsequent processing. Next, a quasi-monopolar pulse is reconstructed using a 2.1:1 amplitude ratio and time delay compensation, compressing the time domain width to 1 / 5-1 / 10 of traditional signals, improving time resolution to accurately capture the ultrasonic round-trip time difference and reduce timing errors. Finally, the round-trip time is obtained through three sets of opposing transducers. Combining the time difference method and attitude compensation formula, multi-dimensional parameters such as actual wind speed and three-dimensional wind speed vector are calculated, breaking through the limitations of traditional single detection. The overall solution considers signal quality, detection accuracy, and dimensionality, adapting to multiple scenario requirements and improving data reliability and practicality.

[0019] Please see Figure 3 The third embodiment of the parameter measurement method based on dual-band mode in this invention includes: 301. Analyze the high-frequency echo signal and the low-frequency echo signal to obtain the time delay compensation amount; In this embodiment, by analyzing the characteristics of the high-frequency echo signal (SH(t)) and the low-frequency echo signal (SL(t)), the difference in their propagation time is extracted, and the time delay compensation amount τ is determined. The core objective of this step is to reduce the timing deviation caused by the difference in propagation speed and path between the high and low frequency signals, lay the foundation for "time synchronization" for subsequent signal fusion, and avoid signal distortion after fusion due to timing misalignment. 302. Perform wavelet decomposition on the high-frequency echo signal and the low-frequency echo signal to obtain the low-frequency wavelet dataset and the high-frequency wavelet dataset. In this embodiment, wavelet decomposition is performed on the low-frequency echo signal SL(t) and the high-frequency echo signal SH(t) to obtain low-frequency wavelet datasets and high-frequency wavelet datasets. The wavelet decomposition is implemented using the Mallat algorithm, which includes multi-resolution decomposition and reconstruction of the signal: decomposing the signal into approximate coefficients. With detail coefficient During reconstruction, the original signal features are restored in the following way: the Mallat algorithm achieves the decomposition and reconstruction of the signal at different scales through iterative calculation of the low-pass filter coefficients and high-pass filter coefficients. It can not only preserve the stable propagation characteristics of low-frequency signals, but also capture the subtle fluctuation information of high-frequency signals, providing a complete data source for subsequent fusion. In the formula, Let r be the integer index and n be the discrete-time index (dimensionless). Low-pass filter coefficients The coefficients of the high-pass filter and ; 303. The low-frequency wavelet dataset and the high-frequency wavelet dataset are reconstructed according to the amplitude ratio and the time delay compensation to obtain the reconstructed quasi-monopolar pulse; In this embodiment, signal sharpness can be improved by fusion (τ is the delay compensation amount): ; In the formula, To reconstruct the quasi-monopolar pulse, this fusion process ensures the alignment of high and low frequency signal peaks through time delay compensation, and optimizes the signal energy distribution through amplitude ratio, ultimately improving signal sharpness. In this embodiment, high-frequency and low-frequency echo signals are first analyzed to extract the propagation time difference and determine the time delay compensation amount. This reduces the timing deviation caused by different propagation speeds and paths, laying a foundation for time synchronization in fusion and avoiding signal distortion caused by timing misalignment. Then, the Mallat algorithm wavelet decomposition is used to split the two types of signals into low-frequency and high-frequency wavelet datasets. This preserves the stable propagation characteristics of low-frequency signals while capturing subtle fluctuations in high-frequency signals, ensuring the integrity of the data source features. Finally, the signal is reconstructed by combining the amplitude ratio and the time delay compensation amount, achieving peak alignment and energy distribution optimization of high and low frequency signals, effectively improving the sharpness of the reconstructed quasi-monopolar pulse. The overall process takes into account timing synchronization, feature integrity, and signal sharpness, providing high-quality data support for subsequent accurate signal-based detection (such as target recognition and parameter measurement), and improving detection accuracy and reliability.

[0020] Please see Figure 4 The fourth embodiment of the parameter measurement method based on dual-band mode in this invention includes: 401. Based on the time difference method, the preset non-orthogonal array spatial projection relationship, and the attitude compensation formula, calculate the downwind time of AB, the upwind time of BA, the downwind time of AC, the upwind time of CA, the downwind time of AD, and the upwind time of DA to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, and roll angle; 402. Calculate the preset attitude calibration coefficients, horizontal wind direction angle, and pitch angle to obtain the magnetometer azimuth angle; In this embodiment, the formula for calculating the azimuth angle of the magnetometer is as follows: , In the formula Where is the roll angle, and k is the attitude calibration coefficient (ranging from 0.8 to 1.2). β is the horizontal wind direction angle, and β is the pitch angle; 403. The true wind direction is obtained by calculating the horizontal wind direction angle and the magnetometer azimuth angle; In this embodiment, the magnetometer azimuth angle is combined with... Calculate the true wind direction θ using the following formula, assuming the azimuth angle measured by the magnetometer is Φ (0°≤Φ≤360°), and the true wind direction is θ (0°<θ<360°), considering the following two cases: The system calculates the true wind direction based on different scenarios. By dividing the scenario, it can address measurement deviations in different azimuth angle ranges, ensuring that the true wind direction output is consistent with the actual environment, and providing accurate directional reference for subsequent environmental monitoring and safety early warning. In this embodiment, based on the six time parameters of the transducer array, combined with the time difference method, non-orthogonal array projection, and attitude compensation, the core parameters such as actual wind speed and horizontal wind direction angle are accurately calculated. Then, an attitude calibration coefficient is introduced, and the magnetometer azimuth angle is calculated through a dedicated formula to reduce pitch angle interference. Finally, the actual wind direction is calculated according to different scenarios to avoid cross-interval errors in the azimuth angle. The entire process not only reduces system errors through multi-layer correction and ensures data reliability in complex environments, but also adapts to the needs of multiple scenarios such as meteorology and aerospace through dynamic coefficients and scenario-based design, providing high-precision and highly stable wind speed and direction data support for environmental monitoring and safety early warning.

[0021] Please see Figure 5 The fifth embodiment of the parameter measurement method based on dual-band mode in this invention includes: 501. Calculate the downwind time of AB, the upwind time of BA, the downwind time of AC, the upwind time of CA, the downwind time of AD, and the upwind time of DA based on the time difference method and the preset edge length of the regular tetrahedron to obtain the first three-dimensional wind speed component. In this embodiment, the three opposing transmit / receive paths of the tetrahedral transducer array are AB, AC, and AD, respectively, and the corresponding wind speed components are calculated using the time-difference method. , In the formula, ( , ) represents the first three-dimensional wind speed component. Let be the wind speed component in the AB direction. Let AC be the wind speed component in the AC direction. Let L1 be the wind speed component along the AD direction, and L1 be the edge length of the tetrahedron. For the tailwind time of AB, For BA's headwind time, This refers to AC's tailwind time. For CA headwind time, For AD's tailwind time, For DA headwind time; 502. Based on the spatial projection relationship of the non-orthogonal array, the preset sine value and the preset cosine value, the first three-dimensional wind speed components are calculated to obtain the actual wind speed, horizontal wind direction angle and pitch angle. In this embodiment, the spatial projection relationship of a non-orthogonal array (the relationship between spatial projection and trigonometric functions, and the sine value of the side angle) is utilized. cosine value The actual wind speed v, horizontal wind direction angle α, and pitch angle β are calculated from the second three-dimensional wind speed components, realizing the conversion from component data to intuitive meteorological parameters; the calculation formulas for actual wind speed v, horizontal wind direction angle α, and pitch angle β are as follows: (2) (3) (4) , 503. Solve for the horizontal wind direction angle and pitch angle to obtain the roll angle; In this embodiment, the roll angle is calculated using the following formula: In the formula, For roll angle; 504. Obtain the propagation time difference; convert the propagation time difference according to the preset geometric relationship, preset transducer spacing and preset transducer axis angle to obtain the second three-dimensional wind speed component. In this embodiment, the geometric relationship refers to the geometric relationship of three sets of transducers. The second three-dimensional wind speed component conversion process is as follows, and the geometric relationship equations can be solved using the least squares method. , In the formula, c is the speed of ultrasonic wave propagation in air (approximately 340 m / s under standard conditions, but actual speed needs to be corrected according to temperature, humidity, etc.), the transducer spacing is L2, the angle between the transducer axes is θ{ij}, and the propagation time difference between the i-th and j-th transducers is Δt{ij}; the second three-dimensional wind speed component is ( , ); 505. Based on the attitude compensation formula, the second three-dimensional wind speed component, horizontal wind direction angle, roll angle and pitch angle are compensated and calculated to obtain the three-dimensional wind speed vector; In this embodiment, the expression for the attitude compensation formula is as follows: ; In the formula, The compensated three-dimensional wind speed vector; In this embodiment, the first three-dimensional wind speed component is calculated by combining the time difference method and the edge length; then, based on the transducer spacing, the axial angle, and the propagation time difference, the second three-dimensional wind speed component is converted using the least squares method. The actual wind speed, horizontal wind direction angle, and pitch angle are derived by using the non-orthogonal array projection relationship. After calculating the roll angle, the accurate three-dimensional wind speed vector is obtained through the attitude compensation formula. The entire process makes full use of the geometric characteristics of the transducer array and mathematical algorithms. It ensures the reliability of the data foundation through multiple sets of path measurements and corrects errors with attitude compensation. It effectively avoids the problem of inaccurate calculation caused by array layout and attitude deviation in traditional measurements, providing high-precision three-dimensional wind speed data for meteorology, aerospace and other fields, and adapting to the measurement needs of complex scenarios.

[0022] The high-frequency echo signal and the low-frequency echo signal are analyzed to obtain low-frequency time difference data and high-frequency time difference data; In this embodiment, the GQCC-STFT algorithm (which combines the time-frequency localization characteristics of Short-Time Fourier Transform (STFT) with the high-resolution characteristics of the generalized quadratic correlation algorithm) is used to analyze the high-frequency and low-frequency echo signals to obtain the low-frequency time difference. With high frequency time difference STFT can accurately pinpoint local features of a signal across different time and frequency dimensions, avoiding information ambiguity during overall signal analysis; the generalized quadratic correlation algorithm can improve the resolution of time difference measurements, reduce the omission of subtle time differences, and extract low-frequency time differences. With high frequency time difference This provides high-quality foundational data for subsequent integration; The preset low-frequency time difference weight and preset high-frequency time difference weight are adjusted according to the echo signal-to-noise ratio to obtain the low-frequency adjustment time difference weight and the high-frequency adjustment time difference weight. The low-frequency time difference data and the high-frequency time difference data are calculated based on the low-frequency adjustment time difference weight and the high-frequency adjustment time difference weight to obtain the fused time difference data; In this embodiment, the low-frequency time difference is adjusted according to the echo signal-to-noise ratio (SNR). With high frequency time difference Weighting: When SNR ≥ 12dB (low environmental interference), the weight of the low-frequency adjustment time difference is ω1 = 0.3, and the resolution advantage of the high-frequency signal is more prominent, so the weight of the high-frequency adjustment time difference is set to ω2 = 0.7; when SNR < 5dB (high environmental interference), the low-frequency signal has stronger anti-interference ability, so the weights are adjusted to ω1 = 0.7 and ω2 = 0.3; the fusion time difference is... = ×ω1+ ×ω2; Please see Figure 6 The sixth embodiment of the parameter measurement method based on dual-band mode in this invention includes: 601. Calculate the first acoustic impedance and the second acoustic impedance to obtain the geometric mean of the characteristic impedance; In this embodiment, when sound waves propagate from the transducer to the air medium, due to the significant difference in acoustic impedance between the transducer's internal piezoelectric layer and the air, without a matching layer, the sound wave energy will be significantly reflected at the transducer-air interface, resulting in extremely low transmission efficiency. In this embodiment, the double-layer matching layer, by rationally setting the acoustic impedance value, constructs a gradual transition of acoustic impedance from the transducer's internal materials to the air medium. Based on the theory of sound wave propagation in multi-layered media, this effectively reduces sound wave reflection at the interface and increases transmission, thereby optimizing the energy transmission efficiency to the air medium. This ensures that the transducer can efficiently transmit ultrasonic signals to the surrounding air and accurately receive the reflected signals for wind speed calculation in actual wind speed measurement scenarios. In this matching scenario, the first acoustic impedance Za and the second acoustic impedance Zb are the acoustic impedances of different functional layers within the transducer (which can be calculated from ρ (medium density) and c (sound wave velocity in the medium)), and the geometric mean of the characteristic impedance is... ; 602. Analyze the geometric mean of the characteristic impedance based on the boundary conditions to obtain the analysis results; In this embodiment, the boundary conditions are: < < ; 603. When the analysis result shows that the geometric mean of the characteristic impedance satisfies the boundary conditions, low-frequency sine waves and high-frequency sine waves are generated. In this embodiment, under this matching scenario, the following conditions must be met: < < Boundary conditions, , These are the acoustic impedances of the two layers in the matching layer, respectively. 604. Align the low-frequency sine wave and the high-frequency sine wave to obtain an aligned sine wave signal; In this embodiment, the dual-layer matching layer design and precise signal generation effectively overcome the energy transmission bottleneck of traditional transducers, laying a crucial foundation for dual-band wind speed measurement. By calculating the first and second acoustic impedances of different functional layers inside the transducer, the geometric mean of the characteristic impedance is obtained. Then, based on boundary conditions, high and low frequency sine waves are generated and aligned after the conditions are met. This scheme constructs a gradual transition of acoustic impedance from the transducer's internal material to the air, reducing sound wave reflection at the interface, improving energy transmission efficiency, avoiding the problem of extremely low transmission efficiency without a matching layer, and ensuring efficient transmission and accurate reception of ultrasonic signals. At the same time, the generated aligned dual-band signals provide a high-quality signal source for subsequent wind speed calculation that balances measurement distance and accuracy, enhancing the system's applicability in real-world scenarios.

[0023] Please see Figure 7 The seventh embodiment of the parameter measurement method based on dual-band mode in this invention includes: 701. Perform a generalized quadratic correlation operation on the high-frequency echo signal and the low-frequency echo signal to obtain an integer multiple of the time difference; In this embodiment, performing a secondary correlation operation on the echo signal can improve the signal-to-noise ratio of the echo signal; 702. Based on the preset Fourier transform algorithm, feature extraction is performed on the high-frequency echo signal and the low-frequency echo signal to obtain the spectral features; In this embodiment, the Fourier transform algorithm is the short-time Fourier transform algorithm, and the mathematical expression of the discrete short-time Fourier transform algorithm is: In the formula, The time-frequency domain output (i.e., spectral characteristics) of the discrete short-time Fourier transform represents the time-frequency energy distribution of the signal at the center index m and discrete frequency index k of the time window. n is the index of the discrete time-domain sampling point, traversing the entire signal sequence. m is the center index of the time window, used to control the time localization position of the time-frequency analysis. x[n] is the non-stationary waveform signal, and φ[nm] is the window function centered at m. It is a complex exponential basis function in the discrete frequency domain, where j is the imaginary unit (defined as j²=-1), used to uniformly describe the amplitude and phase of the signal in complex exponential form; k is the frequency domain index (values ​​0, 1, ..., N-1), used to correspond to different frequency components, with larger k indicating higher frequencies, and traversing k allows extraction of all frequency information; n is the time domain index (values ​​0, 1, ..., N-1), used to correspond to discrete time points and to calculate the projection of the time-domain signal onto each frequency point; N is the transform length (total number of time-domain samples or length after zero-padding), used to determine the frequency domain resolution (larger N indicates higher precision) and constrain the periodicity of the basis function. All four are connected through the complex exponential basis function. Achieving time-frequency conversion of a signal is a core parameter in Fourier analysis, used together for time-frequency analysis or Fourier decomposition of the signal. By comparing spectral characteristics, matching / offset information in the frequency domain can be obtained, such as the phase difference of the spectrum, the fit of the amplitude distribution, and the corresponding deviation of frequency components. These differences reflect the fine offset of the signal in the frequency domain, providing a basis for subsequent calculation of fractional time differences. 703. Generate fractional time differences based on spectral characteristics; In this embodiment, by combining the time-frequency analysis characteristics of STFT, the non-integer multiple of the time delay (i.e., fractional time difference) can be fitted or derived from the frequency domain differences obtained by "spectral feature comparison" (such as the fine pattern of phase change, the residual of spectrum matching, etc.). ); 704. Calculate the time difference in integer multiples and fractional multiples to obtain the time delay compensation amount; In this embodiment, the integer multiples of time difference are obtained through "generalized quadratic correlation". The final total delay (delay compensation, ranging from 0.05 to 0.1 μs) ensures peak alignment when high and low frequency signals are spatially superimposed, thus improving the amplitude ratio η of the quasi-monopolar pulse. ; In this embodiment, a generalized quadratic correlation operation is used to accurately capture integer multiples of the time difference, ensuring the basic accuracy of the time delay measurement. Then, the STFT algorithm is used to extract the spectral features of high and low frequency echo signals, and the fractional multiples of the time difference are derived from frequency domain differences such as phase difference and amplitude matching, so as to achieve fine correction of the time delay. Finally, a high-precision time delay compensation amount is obtained by calculation. This processing method not only leverages the reliability of generalized quadratic correlation in integer-level time delay identification, but also utilizes the time-frequency localization characteristics of STFT to capture subtle frequency domain offsets, improving the accuracy of time difference measurement. This provides accurate data support for subsequent high and low frequency signal reconstruction and three-dimensional wind speed parameter calculation, effectively improving the anti-interference capability and stability of signal processing in complex environments (such as low SNR scenarios), and helping the dual-band measurement scheme to balance transmission distance and measurement accuracy.

[0024] The parameter measurement method based on dual-band mode in the embodiments of the present invention has been described above. The parameter measurement device based on dual-band mode in the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 8 One embodiment of the parameter measurement device based on dual-band mode in this invention includes: Acoustic impedance acquisition module 1 is used to acquire the first acoustic impedance and the second acoustic impedance. Signal alignment module 2 is used to generate an aligned sine wave signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions. Excitation signal generation module 3 is used to generate a dual-band excitation signal based on the aligned sine wave signal; Compression module 4 is used to generate transmission compression packets based on the dual-band excitation signal; The transmission module 5 is used to process the transmission compressed package under a preset transmission signal mode; The parsing module 6 is used to obtain the return compressed package based on the transmission compressed package, and to parse the return compressed package to obtain the echo signal; The signal analysis module 7 is used to analyze the echo signal according to the preset gain coefficient, time difference method and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle and true wind direction; Correction module 8 is used to obtain real-time air pressure and correct the preset standard state sound speed according to the preset sound speed correction formula and real-time air pressure to obtain the corrected sound speed. The measurement parameter generation module 9 is used to generate measurement parameters based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed. In this embodiment, an aligned sine wave signal is generated by combining boundary conditions to ensure that the signal propagation conforms to the characteristics of the medium from the source, reducing attenuation and distortion. Based on this, a dual-band excitation signal is generated, which takes into account the propagation stability of the low-frequency signal and the detail capture capability of the high-frequency signal, laying a high-quality signal foundation for subsequent measurements. In the signal transmission stage, the excitation signal is encapsulated into a compressed packet and transmitted efficiently in a preset mode. After being parsed by a preset communication interface, the echo signal is accurately restored. Subsequently, the weak echo is amplified by a preset gain coefficient, the time difference method is used to correlate the core wind speed data, and the attitude compensation formula is used to correct the device attitude error. This solution not only generates a high-resolution reconstructed quasi-monopolar pulse, but also accurately calculates multi-dimensional wind field parameters such as actual wind speed and horizontal wind direction angle, avoiding the problem of insufficient accuracy in traditional measurement and calculation. By introducing real-time air pressure combined with the sound speed correction formula, the corrected sound speed is obtained, ensuring that the wind speed calculation benchmark conforms to the real-time environment. Finally, multiple types of data are integrated to generate measurement parameters, taking into account the comprehensiveness and accuracy of the data, and the parameters can be updated quickly, effectively meeting the high requirements for wind field measurement in different scenarios, and improving the reliability and practicality of measurement.

[0025] Figure 9 This is a schematic diagram of the structure of a parameter measurement device based on dual-band mode provided in an embodiment of the present invention. The dual-band mode parameter measurement device 900 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 910 (e.g., one or more processors) and a memory 920, and one or more storage media 930 (e.g., one or more mass storage devices) storing application programs 933 or data 932. The memory 920 and storage media 930 can be temporary or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the diagram), each module may include a series of instruction operations on the dual-band mode parameter measurement device 900. Furthermore, the processor 910 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on the dual-band mode parameter measurement device 900 to implement the steps of the dual-band mode parameter measurement method provided in the above-described method embodiments.

[0026] The parameter measurement device 900 based on dual-band mode may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Server, MacOSX, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 9 The illustrated dual-band mode-based parameter measurement device structure does not constitute a limitation on dual-band mode-based parameter measurement devices, which may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0027] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of a parameter measurement method based on a dual-band mode.

[0028] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0029] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0030] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A parameter measurement method based on dual-band mode, characterized in that, include: Obtain the first acoustic impedance and the second acoustic impedance; An aligned sine wave signal is generated based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions. A dual-band excitation signal is generated based on the aligned sine wave signal; Generate transmission compression packets based on dual-band excitation signals; The compressed data packet is transmitted under the preset signal transmission mode. The return compressed package is obtained from the transmitted compressed package, and the return compressed package is parsed to obtain the echo signal; The echo signal is analyzed based on the preset gain coefficient, time difference method and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle and true wind direction; The system obtains real-time air pressure and corrects the preset standard state sound speed according to the preset sound speed correction formula and real-time air pressure to obtain the corrected sound speed. Measurement parameters are generated based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed.

2. The parameter measurement method based on dual-band mode as described in claim 1, characterized in that, The process of analyzing the echo signal based on a preset gain coefficient, time difference method, and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction includes: The echo signal is separated according to the preset low-frequency channel, the preset high-frequency channel and the gain coefficient to obtain the high-frequency echo signal and the low-frequency echo signal; The high-frequency echo signal and the low-frequency echo signal are analyzed according to the preset amplitude ratio to obtain the reconstructed quasi-monopolar pulse; Obtain the tailwind time for AB, the headwind time for BA, the tailwind time for AC, the headwind time for CA, the tailwind time for AD, and the headwind time for DA; The tailwind time of AB, the headwind time of BA, the tailwind time of AC, the headwind time of CA, the tailwind time of AD, and the headwind time of DA are analyzed based on the time difference method and attitude compensation formula to obtain the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction.

3. The parameter measurement method based on dual-band mode as described in claim 2, characterized in that, The step of analyzing the high-frequency echo signal and the low-frequency echo signal according to a preset amplitude ratio to obtain a reconstructed quasi-monopolar pulse includes: The high-frequency echo signal and the low-frequency echo signal are analyzed to obtain the time delay compensation amount; Wavelet decomposition is performed on the high-frequency echo signal and the low-frequency echo signal to obtain the low-frequency wavelet dataset and the high-frequency wavelet dataset. The low-frequency wavelet dataset and the high-frequency wavelet dataset are reconstructed based on the amplitude ratio and the time delay compensation to obtain the reconstructed quasi-monopolar pulse.

4. The parameter measurement method based on dual-band mode as described in claim 2, characterized in that, The analysis of AB tailwind time, BA headwind time, AC tailwind time, CA headwind time, AD tailwind time, and DA headwind time using the time difference method and attitude compensation formula yields the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, and true wind direction, including: The actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector and roll angle are calculated based on the time difference method, the preset non-orthogonal array spatial projection relationship and attitude compensation formula. The preset attitude calibration coefficients, horizontal wind direction angle, and pitch angle are calculated to obtain the magnetometer azimuth angle; The true wind direction is obtained by calculating the horizontal wind direction angle and the magnetometer azimuth angle.

5. The parameter measurement method based on dual-band mode as described in claim 4, characterized in that, The calculation of AB downwind time, BA headwind time, AC downwind time, CA headwind time, AD downwind time, and DA headwind time, based on the time difference method, a preset non-orthogonal array spatial projection relationship, and attitude compensation formula, yields the actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, and roll angle, including: The first three-dimensional wind speed component is obtained by calculating the downwind time of AB, the upwind time of BA, the downwind time of AC, the upwind time of CA, the downwind time of AD, and the upwind time of DA based on the time difference method and the preset edge length of the tetrahedron. The first three-dimensional wind speed components are calculated based on the non-orthogonal array spatial projection relationship, preset sine values, and preset cosine values ​​to obtain the actual wind speed, horizontal wind direction angle, and pitch angle. The horizontal wind direction angle and pitch angle are calculated to obtain the roll angle; The propagation time difference is obtained, and the propagation time difference is converted according to the preset geometric relationship, the preset transducer spacing and the preset transducer axis angle to obtain the second three-dimensional wind speed component. The second three-dimensional wind speed component, horizontal wind direction angle, roll angle and pitch angle are compensated according to the attitude compensation formula to obtain the three-dimensional wind speed vector.

6. The parameter measurement method based on dual-band mode as described in claim 1, characterized in that, The step of generating an aligned sine wave signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions includes: The first and second acoustic impedances are calculated to obtain the geometric mean of the characteristic impedance; The geometric mean of the characteristic impedance is analyzed based on the boundary conditions to obtain the analysis results; When the analysis results show that the geometric mean of the characteristic impedance satisfies the boundary conditions, low-frequency sine waves and high-frequency sine waves are generated. The low-frequency sine wave and the high-frequency sine wave are aligned to obtain an aligned sine wave signal.

7. The parameter measurement method based on dual-band mode as described in claim 3, characterized in that, The analysis of high-frequency and low-frequency echo signals to obtain the time delay compensation includes: A generalized quadratic correlation operation is performed on the high-frequency echo signal and the low-frequency echo signal to obtain an integer multiple of the time difference; Based on the preset Fourier transform algorithm, feature extraction is performed on the high-frequency echo signal and the low-frequency echo signal to obtain the spectral features; Generate fractional time differences based on spectral characteristics; Calculate the time difference in integer multiples and fractional multiples to obtain the time delay compensation amount.

8. A parameter measurement device based on dual-band mode, characterized in that, include: Acoustic impedance acquisition module, used to acquire the first acoustic impedance and the second acoustic impedance; The signal alignment module is used to generate an aligned sine wave signal based on the first acoustic impedance, the second acoustic impedance, and preset boundary conditions. The excitation signal generation module is used to generate a dual-band excitation signal based on the aligned sine wave signal; The compression module is used to generate transmission compressed packets based on the dual-band excitation signal; The transmission module is used to process the transmission of compressed packets under a preset transmission signal mode; The parsing module is used to obtain the return compressed package based on the transmission compressed package, and to parse the return compressed package to obtain the echo signal; The signal analysis module is used to analyze the echo signal according to the preset gain coefficient, time difference method and preset attitude compensation formula to obtain the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle and true wind direction; The correction module is used to obtain real-time air pressure and correct the preset standard state sound speed according to the preset sound speed correction formula and real-time air pressure to obtain the corrected sound speed. The measurement parameter generation module is used to generate measurement parameters based on the reconstructed quasi-monopolar pulse, actual wind speed, horizontal wind direction angle, pitch angle, three-dimensional wind speed vector, roll angle, true wind direction, and corrected sound speed.

9. A parameter measurement device based on dual-band mode, characterized in that, The parameter measurement device based on dual-band mode includes: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the dual-band mode-based parameter measurement device to perform the steps of the dual-band mode-based parameter measurement method as described in any one of claims 1-7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the parameter measurement method based on dual-band mode as described in any one of claims 1-7.

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