A multi-frequency multi-beam acoustic doppler flow velocity adaptive measurement method

Abstract

The present application relates to the technical field of acoustic Doppler current measurement, and discloses a multi-frequency multi-beam acoustic Doppler current adaptive measurement method, aiming at solving the problem that the existing fixed frequency and fixed mode current measurement can hardly consider both high resolution in shallow water and long distance measurement in deep water, and the continuity and reliability are insufficient in complex water bodies. The method constructs a multi-beam array containing a vertical beam and at least two groups of different frequency oblique beams; by establishing a propagation loss and echo signal-to-noise ratio prediction model, the effective measurement depth range of each frequency is determined; according to the real-time water depth, flow velocity range, signal-to-noise ratio and correlation coefficient, the transmission frequency, pulse form and Doppler processing mode are adaptively selected, and the quality is evaluated and optimally output in distance units to generate a continuous flow velocity profile. The present application can simultaneously meet the requirements of high-precision measurement in shallow water and long-distance measurement in deep water, and significantly improve the continuity and reliability of flow velocity measurement in complex water body environment.

Description

Technical Field

[0001] This invention relates to the field of acoustic Doppler flow velocity measurement technology, specifically to a multi-frequency multi-beam acoustic Doppler flow velocity adaptive measurement method. Background Technology

[0002] Acoustic Doppler current profiler technology transmits acoustic pulses into a water body and receives the scattered echoes from suspended particles, bubbles, or boundaries. It then uses the Doppler frequency shift principle to invert the water velocity profile and has been widely applied to flow field observation in rivers, lakes, channels, and nearshore sea areas. Existing typical acoustic Doppler current profilers usually employ a single operating frequency and a multi-beam Janus structure. They acquire radial velocity through multiple oblique beams and then combine the beam geometry to calculate the three-dimensional velocity.

[0003] In practical applications, the frequency of sound waves directly affects the measurement distance, resolution, and resistance to attenuation. High-frequency sound waves have shorter wavelengths, are sensitive to scattering bodies, and offer high distance resolution, making them suitable for fine measurements in shallow water or at close range. However, their propagation attenuation is significant, and the echo signal-to-noise ratio drops rapidly in slightly deeper water. Low-frequency sound waves have less attenuation and can detect deeper water layers, but their resolution is lower, their near-field blind zone is large, and their ability to characterize flow velocity details in near-bottom or shallow water areas is insufficient. Therefore, a single fixed-frequency flow measurement device cannot simultaneously meet the dual requirements of "high resolution in shallow water" and "long-distance detection in deep water."

[0004] Furthermore, acoustic Doppler measurements are significantly affected by aquatic environmental parameters and external noise. Quality indicators such as echo signal-to-noise ratio, correlation coefficient, and velocity stability fluctuate dramatically with changes in water depth, turbidity, and flow velocity. Fixed pulse formats (such as long-pulse incoherent processing and short-pulse coherent processing) and fixed Doppler processing methods (such as pulse coherent, broadband coding, and pulse incoherent) each have their advantages and disadvantages when dealing with different flow velocity ranges: pulse coherent processing offers high accuracy at low speeds but is prone to ambiguity; pulse incoherent processing has strong noise immunity but low resolution; broadband coding balances resolution and velocity range, but its pulse compression gain is significantly affected by echo correlation. Existing equipment typically employs only one processing mode; when the flow velocity exceeds the design range or the echo quality deteriorates, the velocity measurement results may deviate, jump, or even be completely lost.

[0005] Some existing technologies attempt to improve the above problems through dual-frequency or variable-frequency methods, but most rely on preset switching thresholds or manual frequency selection, failing to perform fully automatic, distance-layer-by-distance adaptive optimization based on real-time water depth, flow velocity range, and echo signal quality. Furthermore, they lack a frequency optimization mechanism based on propagation loss and signal-to-noise ratio prediction models, and cannot evaluate the quality of velocity measurement results from different frequencies within the same distance layer, nor can they select the best output. In summary, in water bodies with significant depth variations, complex flow velocity distributions, or spatially non-uniform suspended particle concentrations (such as estuaries, reservoir inlets and outlets, and mountain streams), traditional single-frequency or simple dual-frequency flow measurement methods are prone to problems such as insufficient shallow layer resolution, missing deep layer data, and abnormal velocity jumps, making it difficult to guarantee measurement continuity and reliability.

[0006] Therefore, it is necessary to propose an acoustic Doppler velocity measurement method that can adaptively select the operating frequency, pulse form, and Doppler processing mode based on real-time water depth, velocity range, and echo signal quality, so as to improve the continuity and reliability of velocity profile measurement in complex water environments. Summary of the Invention

[0007] In view of this, the present invention provides a multi-frequency multi-beam acoustic Doppler current velocity adaptive measurement method to solve the problems of existing acoustic Doppler current velocity measurement methods, which use fixed frequency and fixed measurement mode, making it difficult to simultaneously achieve high-resolution measurement in shallow water and long-distance measurement in deep water, and also have insufficient measurement continuity and reliability in complex water environments.

[0008] This invention provides a multi-frequency, multi-beam acoustic Doppler adaptive flow velocity measurement method, the method comprising: S1: Obtain the configuration parameters of the multi-beam combined array, wherein the multi-frequency multi-beam acoustic measurement array includes a vertical beam transducer and at least two sets of oblique beam transducers with different operating frequencies; the vertical beam transducer is used to obtain real-time water depth and identify the bottom interface, and the oblique beam transducer is used to obtain radial flow velocity information in different directions. S2: Determine the candidate frequency set based on the vertical beam transducer and the oblique beam transducer, and simultaneously determine the oblique beam tilt angle of the oblique beam transducer. Then, based on the candidate frequency set, the oblique beam tilt angle, the real-time water depth, the water absorption attenuation parameters, and the scattering characteristics of suspended particles, establish a propagation loss model. Then, calculate the echo signal-to-noise ratio of different candidate frequencies within the full measurement range of the target water body, and compare it with a preset signal-to-noise ratio threshold to determine the effective measurement depth range corresponding to each candidate frequency. S3: Based on the comparison between the real-time water depth and the preset water depth threshold, determine the transmission frequency of the vertical beam transducer and the oblique beam transducer according to the comparison result; S4: At the determined transmission frequency, based on the radial flow velocity information, determine the pulse form and Doppler processing method of the vertical beam transducer and the oblique beam transducer. When the absolute value of the radial flow velocity is lower than a preset low-velocity threshold, control the multi-beam array to use pulse coherent processing; when the absolute value of the radial flow velocity is between a preset low-velocity threshold and a preset high-velocity threshold, control the multi-beam array to use broadband coding processing; when the absolute value of the radial flow velocity is higher than a preset high-velocity threshold, or the echo correlation of the radial flow velocity is lower than a preset correlation coefficient threshold, control the multi-beam array to use pulse incoherent processing. Finally, based on the determined pulse form and Doppler processing method, perform quality evaluation and optimal output on the velocity measurement results of different distance layers within the effective measurement depth range to generate continuous velocity profiles and water depth information.

[0009] In one optional implementation, the echo signal-to-noise ratio is calculated as follows: In the formula, These are the source level parameters corresponding to the transmission power; For the transducer in the first candidate frequencies Equivalent send and receive responses; The volumetric backscattering intensity is formed by scattering from suspended particles. Indicates the radius of the suspended particles. Indicates the concentration of suspended sediments; Represents the propagation loss model; This is the equivalent noise level of the receiver.

[0010] In one optional implementation, the process of determining the effective measurement depth range in step S2 specifically involves: The echo signal-to-noise ratio of each measurement unit is calculated one by one along the acoustic wave propagation direction of the vertical beam transducer and the oblique beam transducer to obtain the signal-to-noise ratio distribution curve of different candidate frequencies in the full measurement range of the target water body. The signal-to-noise ratio (SNR) distribution curve is compared with a preset SNR threshold. When the echo SNR at a certain measurement unit is higher than or equal to the preset SNR threshold, the corresponding candidate frequency is determined to be usable for effective flow velocity measurement at the current water depth. When the echo SNR is lower than the preset SNR threshold, the corresponding candidate frequency is determined to not meet the effective flow measurement conditions at the current water depth, thereby determining the effective measurement depth range corresponding to each candidate frequency.

[0011] In one optional implementation, the formula for calculating the effective measurement depth range is: In the formula, Represents candidate frequency The corresponding effective measurement depth range; Indicates the first The vertical depth corresponding to each measurement unit; Represents candidate frequency The corresponding echo signal-to-noise ratio; This indicates the preset signal-to-noise ratio threshold.

[0012] In one optional implementation, the comparison process between the real-time water depth and the preset water depth threshold in step S3 specifically involves: A first water depth threshold and a second water depth threshold are set, with the first water depth threshold being less than the second water depth threshold. When the real-time water depth is less than or equal to the first water depth threshold, it is determined to be a shallow water measurement area, and the multi-beam array is controlled to adopt a high-frequency measurement scheme. When the real-time water depth is greater than or equal to the second water depth threshold, it is determined to be a deep water measurement area, and the multi-beam array is controlled to adopt a low-frequency measurement scheme.

[0013] In one optional implementation, the process of quality evaluation and optimal output in step S4 includes: A quality evaluation model is constructed. For the same distance layer, when both high-frequency and low-frequency speed measurement results are obtained, the quality evaluation values ​​corresponding to high-frequency and low-frequency speeds are compared, and the speed measurement result with the higher quality evaluation value of the quality evaluation model is selected and output. According to the quality evaluation model, when only one of the high-frequency and low-frequency frequencies meets the preset quality requirements, the corresponding frequency is output; when neither meets the preset quality requirements, the corresponding distance layer is marked as invalid.

[0014] In one optional implementation, the quality assessment model is: In the formula, Indicates the quality evaluation value. The weights representing the echo signal-to-noise ratio, The weights representing the correlation coefficients, Indicates the current echo signal-to-noise ratio. Represents the correlation coefficient. This indicates the preset correlation coefficient threshold.

[0015] In one alternative implementation, it further includes: When the quality evaluation result of the preset candidate measurement scheme is better than that of the current measurement scheme, and the difference between the two reaches the preset hysteresis threshold and is valid for multiple consecutive measurement cycles, the system automatically switches from the current measurement scheme to the preset candidate measurement scheme. The switching content includes at least one of the following: transmission frequency, pulse form, signal bandwidth, or Doppler processing method of the multi-beam array.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention constructs a multi-beam array comprising a vertical beam and at least two sets of oblique beams of different frequencies. Combined with an echo signal-to-noise ratio prediction model based on water propagation loss and suspended particle scattering characteristics, it can adaptively determine the effective measurement depth range of each candidate frequency. Furthermore, it dynamically selects the transmission frequency, pulse form, and Doppler processing method (pulse coherence, broadband coding, pulse incoherence) based on real-time water depth, velocity range, signal-to-noise ratio, and correlation coefficient. Simultaneously, it performs quality evaluation and optimal output based on distance units. This addresses the contradiction between high resolution in shallow water and long-distance measurement in deep water using a single frequency. It also avoids measurement failures under conditions of low accuracy at low speeds and ambiguity or low correlation at high speeds through adaptive switching of multiple processing methods. Moreover, it ensures the continuity and reliability of the velocity profile through layered optimal output rather than simple fusion, thus achieving high-quality velocity profile measurement across the entire water depth and wide velocity range in complex water environments. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a multi-frequency, multi-beam acoustic Doppler adaptive flow velocity measurement method according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a multi-beam combined array according to an embodiment of the present invention; Figure 3 This is a flowchart of the operating frequency selection based on water propagation characteristics and echo signal quality according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the adaptive selection and switching of measurement schemes based on water depth, flow velocity range, and signal quality according to an embodiment of the present invention. Figure 5 This is a graph showing the relationship between candidate frequency and echo signal-to-noise ratio under shallow water conditions according to an embodiment of the present invention. Figure 6 This is a graph showing the relationship between candidate frequency and echo signal-to-noise ratio under deep-water conditions according to an embodiment of the present invention. Figure 7 This is a depth-SNR distribution curve at different operating frequencies according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Figure 1 This is a flowchart of a multi-frequency multi-beam acoustic Doppler adaptive flow velocity measurement method according to an embodiment of the present invention. The flowchart includes the following steps: S1: Obtain the configuration parameters of the multi-beam combined array, wherein the multi-frequency multi-beam acoustic measurement array includes a vertical beam transducer and at least two sets of oblique beam transducers with different operating frequencies; the vertical beam transducer is used to obtain real-time water depth and identify the bottom interface, and the oblique beam transducer is used to obtain radial flow velocity information in different directions.

[0021] In this embodiment, the structure of the multi-beam combined array is as follows: Figure 2 As shown, the device includes a vertical beam transducer and two sets of oblique beam transducers with different operating frequencies. The vertical beam transducer is positioned at the center of the bottom end face of the measuring device, with its acoustic axis coinciding with the vertical axis of the measuring device. It is used to measure the water depth of the target water body, identify the bottom interface of the target water body, and determine the effective flow profile range. The two sets of oblique beam transducers are arranged in a ring around the vertical beam transducer. Each set includes four oblique beams, symmetrically arranged according to a Janus structure. The azimuth angles of adjacent beams are spaced 90° apart, and the relative azimuth angles differ by 180°. The two sets of oblique beams use different operating frequencies and are staggered by a preset angle in the horizontal projection plane, preferably 45°, to reduce inter-beam crosstalk and improve the redundancy of flow velocity inversion.

[0022] The high-frequency oblique beam group in the oblique beam transducer is used for shallow water, short-range or high-resolution flow velocity measurement; the low-frequency oblique beam group of the oblique beam transducer is used for deep water, long-range or weak echo conditions for flow velocity profile measurement.

[0023] By combining a vertical beam transducer and two sets of oblique beam transducers with different operating frequencies, a multi-frequency, multi-beam acoustic measurement structure that combines vertical depth sounding, high-frequency velocity sounding, and low-frequency velocity sounding can be formed.

[0024] S2: Determine the candidate frequency set based on the vertical beam transducer and the oblique beam transducer, and simultaneously determine the oblique beam tilt angle of the oblique beam transducer. Then, based on the candidate frequency set, the oblique beam tilt angle, the real-time water depth, the water absorption attenuation parameters, and the scattering characteristics of suspended particles, establish a propagation loss model. Then, calculate the echo signal-to-noise ratio of different candidate frequencies within the full measurement range of the target water body, and compare it with a preset signal-to-noise ratio threshold to determine the effective measurement depth range corresponding to each candidate frequency.

[0025] In this embodiment, combined with Figure 3 The flowchart shown illustrates the operating frequency selection process based on water propagation characteristics and echo signal quality. First, a candidate frequency set is established based on the achievable operating frequency ranges of the vertical beam transducer and the oblique beam transducer. in, For the first A set of candidate operating frequencies, the candidate frequency set covering the high-frequency short-range flow measurement band and the low-frequency long-range flow measurement band.

[0026] For candidate frequency Depth measured according to the target and oblique beam tilt angle Determine the sound propagation distance of the corresponding measurement unit: in, For the first The vertical depth corresponding to each measurement unit This represents the propagation distance of the measuring unit along the oblique direction of the sound beam.

[0027] At each candidate frequency, a propagation loss model is established by comprehensively considering the absorption attenuation, geometric diffusion attenuation, scattering and viscous loss caused by suspended particles in the target water body of the sound waves emitted by the multi-beam array: in, For frequency The equivalent absorption attenuation coefficient is composed of the water absorption attenuation term and the suspended particle additional attenuation term: in, Indicates the absorption attenuation coefficient of the water medium. This represents the additional attenuation coefficient of suspended particles. Salinity Water temperature pH level The radius of the suspended particles, The concentration of suspended sediments. Particle density, This is the correction factor for particulate materials.

[0028] In this embodiment, the calculation process for the echo signal-to-noise ratio is as follows: In the formula, Echo signal-to-noise ratio; These are the source level parameters corresponding to the transmission power; For the transducer in the first candidate frequencies Equivalent send and receive responses; The volumetric backscattering intensity is formed by scattering from suspended particles. Indicates the radius of the suspended particles. Indicates the concentration of suspended sediments; Represents the propagation loss model; This is the equivalent noise level of the receiver.

[0029] In this embodiment, within the preset shallow water working depth range and deep-water working depth range Within the shallow water, candidate frequencies with the highest echo signal-to-noise ratio are searched to obtain the optimal operating frequency. and optimal operating frequency in deep water : in, For high-frequency candidate frequency subsets, This is a subset of low-frequency candidate frequencies. High-frequency operating frequencies. High-resolution current measurement for near-shore or shallow water areas, low-frequency operating frequency. Used for long-distance current measurement in remote or deep water areas.

[0030] Optionally, the echo signal-to-noise ratio (SNR) is calculated for each measurement unit along the acoustic wave propagation direction of the vertical beam transducer and the oblique beam transducer to obtain the SNR distribution curve of different candidate frequencies across the entire measurement range of the target water body. The SNR distribution curve is compared with a preset SNR threshold. When the echo SNR at a certain measurement unit is higher than or equal to the preset SNR threshold, the corresponding candidate frequency is determined to be usable for effective flow velocity measurement at the current water depth. When the echo SNR is lower than the preset SNR threshold, the corresponding candidate frequency is determined to not meet the effective flow measurement conditions at the current water depth, thereby determining the effective measurement depth range corresponding to each candidate frequency.

[0031] In this embodiment, the effective measurement depth range corresponding to each operating frequency is: in, Represents candidate frequency The corresponding effective measurement depth range; Indicates the first The vertical depth corresponding to each measurement unit; Represents candidate frequency The corresponding echo signal-to-noise ratio; This indicates the preset signal-to-noise ratio threshold.

[0032] When the echo signal-to-noise ratio at a certain measurement unit is lower than the preset signal-to-noise ratio threshold, it is determined that the frequency does not meet the effective flow measurement conditions at the current water depth; when the echo signal-to-noise ratio is higher than or equal to the preset signal-to-noise ratio threshold, the system determines that the frequency can be used for effective flow velocity measurement at the current water depth.

[0033] The above method enables the adaptive determination of shallow water and deep water operating frequencies based on the current water depth, suspended particle characteristics, and transducer structural parameters, while simultaneously outputting the effective measurement depth range corresponding to different frequencies. This allows for optimized frequency configuration of the multi-beam array in different water environments.

[0034] S3: Based on the comparison between the real-time water depth and the preset water depth threshold, determine the transmission frequency of the vertical beam transducer and the oblique beam transducer according to the comparison result.

[0035] Optionally, a first water depth threshold and a second water depth threshold are set, and the first water depth threshold is less than the second water depth threshold; when the real-time water depth is less than or equal to the first water depth threshold, it is determined to be a shallow water measurement area, and the multi-beam array is controlled to adopt a high-frequency measurement scheme; when the real-time water depth is greater than or equal to the second water depth threshold, it is determined to be a deep water measurement area, and the multi-beam array is controlled to adopt a low-frequency measurement scheme.

[0036] In this embodiment, real-time water depth is obtained through vertical beamforming. And according to the preset first water depth threshold Second water depth threshold (and Frequency scheme determination is performed. When the area is determined to be shallow water or a close-range measurement area, a high-frequency measurement scheme should be prioritized; when When the area is determined to be of medium water depth, both high-frequency and low-frequency schemes are considered as candidate schemes; when When the area is determined to be deep water or a long-distance measurement area, a low-frequency measurement scheme should be given priority.

[0037] S4: At the determined transmission frequency, based on the radial flow velocity information, determine the pulse form and Doppler processing method of the vertical beam transducer and the oblique beam transducer. When the absolute value of the radial flow velocity is lower than a preset low-velocity threshold, control the multi-beam array to use pulse coherent processing; when the absolute value of the radial flow velocity is between a preset low-velocity threshold and a preset high-velocity threshold, control the multi-beam array to use broadband coding processing; when the absolute value of the radial flow velocity is higher than a preset high-velocity threshold, or the echo correlation of the radial flow velocity is lower than a preset correlation coefficient threshold, control the multi-beam array to use pulse incoherent processing. Finally, based on the determined pulse form and Doppler processing method, perform quality evaluation and optimal output on the velocity measurement results of different distance layers within the effective measurement depth range to generate continuous velocity profiles and water depth information.

[0038] Optionally, the process of quality evaluation and optimal output includes: constructing a quality evaluation model; for the same distance layer, when both high-frequency and low-frequency frequencies obtain valid velocity measurement results, comparing the quality evaluation values ​​corresponding to the high-frequency and low-frequency frequencies, and outputting the velocity measurement result with the higher quality evaluation value of the quality evaluation model; according to the quality evaluation model, when only one frequency among the high-frequency and low-frequency frequencies meets the preset quality requirements, outputting the corresponding frequency; when neither meets the preset quality requirements, marking the corresponding distance layer as invalid.

[0039] In this embodiment, after determining the candidate transmission frequency, the radial flow velocity is used as a basis. Select the pulse type and Doppler processing method. Set the preset low-speed threshold. and preset high-speed threshold .when When pulsed coherent processing is used, it is preferred; when When using wideband coding, priority should be given to wideband coding. When the echo correlation is low, pulse incoherent processing should be preferred.

[0040] After completing the candidate measurement schemes, the quality of the velocity measurement results at each distance level is evaluated. An effective echo signal-to-noise ratio threshold is then set. and preset correlation coefficient threshold For the first If the echo signal-to-noise ratio of a distance layer is... and correlation coefficient satisfy: , If the velocity measurement result of the distance layer is deemed valid, the current measurement scheme is maintained and the radial velocity result of that layer is output; if the following conditions are met: or If the measurement quality under the current scheme is deemed insufficient, a scheme or parameter update will be triggered. Update methods include switching the transmission frequency, adjusting the signal bandwidth, changing the pulse width, adjusting the pulse repetition interval, or switching the Doppler processing mode.

[0041] For the same distance layer, when both high-frequency and low-frequency velocities have obtained valid velocity measurement results, multi-frequency weighted fusion is not performed. Instead, the output is selected based on the output of the quality evaluation model.

[0042] The quality evaluation model can be expressed as: in, This is a quality evaluation value. The weights representing the echo signal-to-noise ratio, This represents the weight of the correlation coefficient, and .

[0043] When both high-frequency and low-frequency results meet the effective flow measurement conditions, their quality evaluation values ​​are calculated and output. The larger the velocity measurement result, the output will be the velocity measurement result corresponding to the frequency if only one frequency meets the valid flow measurement conditions; if neither frequency meets the valid flow measurement conditions, the distance layer will be marked as invalid.

[0044] Optionally, when the quality evaluation result of the preset candidate measurement scheme is better than that of the current measurement scheme, and the difference between the two reaches a preset hysteresis threshold and is valid for multiple consecutive measurement cycles, the current measurement scheme is automatically switched to the preset candidate measurement scheme; the switching content includes at least one of the transmission frequency, pulse form, signal bandwidth, or Doppler processing method of the multi-beam array.

[0045] In this embodiment, after determining each distance layer, the effective velocity results are output in the order of each distance layer to form a continuous velocity profile, and the water depth information obtained by the depth sounding module is output simultaneously. In the next measurement cycle, the above determination process is re-executed based on the latest water depth data, radial velocity information, echo signal-to-noise ratio, and correlation coefficient to achieve adaptive selection and switching of the measurement scheme.

[0046] The following is combined with Figure 4 The specific embodiments and simulation results of the adaptive selection of the measurement scheme shown further illustrate the working process of the present invention. It should be understood that the following embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Equivalent substitutions or adjustments made by those skilled in the art to the operating frequency, threshold parameters, number of beams, layer thickness, and signal processing methods without departing from the technical concept of the present invention should all fall within the scope of protection of the present invention.

[0047] Taking a river environment as the target water body for measurement as an example, the sound velocity was set to 1500 m / s, the water temperature to 20℃, the angle between the oblique beam and the vertical direction to 20°, the measurement layer thickness to 0.2 m, and the near-end blind zone to 0.2 m. The average radius of suspended particles was 23 μm, the suspended sediment concentration to 1 kg / m³, and the particle density to 2650 kg / m³. The candidate operating frequency range was set to 100 kHz to 5000 kHz, and the frequency search step to 100 kHz.

[0048] Based on water propagation characteristics and echo signal quality models, frequency optimization was performed using 3m and 20m as representative measurement depths for shallow and deep water, respectively. Figure 5 As shown, the optimal operating frequency under shallow water conditions is 2.8MHz. Figure 6 As shown, the optimal operating frequency under deep-water conditions is 1.1MHz. Further calculations were performed on the depth-SNR distribution curves for both frequencies, and the intersection of the two curves was used as the frequency switching reference point. Figure 7 It can be seen that the water depth corresponding to the intersection of the two curves is approximately 7m.

[0049] Therefore, in this embodiment, the first water depth threshold is set to 3m, and the second water depth threshold is set to 7m. When the real-time water depth is less than or equal to 3m, it is determined to be a shallow water measurement area, and a 2.8MHz high-frequency beam is preferentially used; when the real-time water depth is between 3m and 7m, it is determined to be a medium-depth water measurement area, and a high- or low-frequency beam can be selected according to the echo signal-to-noise ratio and resolution requirements; when the real-time water depth is greater than or equal to 7m, it is determined to be a deep water measurement area, and a 1.1MHz low-frequency beam is preferentially used.

[0050] Simultaneously, the effective echo signal-to-noise ratio threshold is set to 20dB. Figure 7 The depth-SNR distribution results show that the 1.1MHz low-frequency beam satisfies the echo signal-to-noise ratio greater than or equal to the effective echo signal-to-noise ratio threshold in the depth range of about 0 to 33m, and is suitable for flow measurement in deeper water layers; the 2.8MHz high-frequency beam satisfies the echo signal-to-noise ratio greater than or equal to the effective echo signal-to-noise ratio threshold in the depth range of about 0 to 14m, and is suitable for high-resolution flow measurement in shallow water layers.

[0051] Combination Figure 2 The multi-beam array shown in this embodiment has its optimal shallow water operating frequency set at 2.8MHz for the high-frequency Janus four-beam array and its optimal deep water operating frequency set at 1.1MHz for the low-frequency Janus four-beam array and the vertical sounding beam.

[0052] Based on the aforementioned frequency configuration, the current water depth is first obtained from the vertical beam within each measurement cycle. This is then combined with the results from the previous measurement cycle to estimate the current radial flow velocity range. Finally, the signal-to-noise ratio and correlation coefficient are used to determine whether a switch to a different measurement scheme is necessary. For example, if the real-time water depth in a given measurement cycle is 2.6m, and since this real-time water depth is less than the first water depth threshold, the current area is determined to be a shallow water measurement area, and the multi-beam array is prioritized for activation. Water tracking measurements are performed. If the echo signal-to-noise ratio of each distance layer within the cycle is greater than or equal to 20dB and the correlation coefficient is not lower than the preset correlation coefficient threshold, then the high-frequency measurement scheme is maintained, and the shallow flow velocity profile is output using high-frequency broadband coding or high-frequency pulse coherence.

[0053] When the real-time water depth is 5.5m, the current area is determined to be a medium-depth measurement area. At this point, both the 2.8MHz high-frequency scheme and the 1.1MHz low-frequency scheme are considered as candidate schemes. If the high-frequency beam satisfies an echo signal-to-noise ratio greater than or equal to 20dB and a stable correlation coefficient within the target measurement layer, the high-frequency measurement results are prioritized for output to obtain higher layer resolution. If the high-frequency beam exhibits an echo signal-to-noise ratio less than 20dB or a decreased correlation coefficient in some depth layers, the output frequency is switched to the optimal deep-water operating frequency for the current water depth layer to ensure the continuity of the velocity profile.

[0054] When the real-time water depth is 18m or 20m, the current area is determined to be a deep-water measurement area, and the multi-beam array is prioritized for activation. Water tracking measurements are performed. The high-frequency beam is primarily used for shallow or near-range auxiliary measurements, while deep flow velocity results are output from the low-frequency beam. When the low-frequency beam achieves an echo signal-to-noise ratio greater than or equal to 20 dB and the correlation coefficient meets the requirements, the system maintains the low-frequency measurement scheme. If the deep echo quality deteriorates, measurement stability is improved by increasing the pulse width, reducing the signal bandwidth, or switching to pulse incoherence processing.

[0055] In selecting the flow velocity processing method, the pulse form and Doppler processing method are selected based on the current radial flow velocity information. In this embodiment, the preset low-velocity threshold is 0.5 m / s, the preset high-velocity threshold is 2.0 m / s, and the absolute value of the radial flow velocity obtained in the current measurement cycle is used as the judgment criterion.

[0056] When the absolute value of the radial flow velocity is less than or equal to 0.5 m / s, it is considered a low-speed flow condition, and the pulse coherent processing method is preferred. This method estimates the flow velocity using the phase difference or complex autocorrelation result of adjacent pulse echoes, and is suitable for low-speed, high-precision velocity measurement scenarios. For example, in shallow water areas, if the current estimated flow velocity is 0.3 m / s, the pulse coherent processing method is preferred. A high-frequency pulse coherent measurement scheme is proposed to achieve high layering accuracy and low-speed measurement accuracy.

[0057] When the absolute value of the radial flow velocity falls between a preset low-velocity threshold and a preset high-velocity threshold, it is determined to be a medium-velocity condition, and the system preferentially employs a wideband coded Doppler processing method. This method improves processing gain by encoding the signal while also considering distance resolution and velocity measurement range. For example, when the real-time water depth is 5.5m and the flow velocity is approximately 1.2m / s, it falls within the medium-depth region. High-frequency broadband solutions and The low-frequency broadband scheme is selected as a candidate, and the optimal output is selected based on the echo signal-to-noise ratio and correlation coefficient.

[0058] When the absolute value of the radial velocity is greater than or equal to 2.0 m / s, it is considered a high-speed flow or a condition with large velocity variations, and the pulse incoherent processing method is preferred. This method has a lower dependence on the phase continuity of adjacent echoes and is suitable for high-speed flow, strong turbulence, or conditions with poor echo correlation. For example, when the current estimated velocity reaches 2.3 m / s, or the correlation coefficient obtained from pulse coherent processing decreases significantly, the pulse incoherent processing method is switched to reduce the impact of phase ambiguity and decreased correlation on the velocity measurement results.

[0059] After the candidate measurement scheme is executed, the system evaluates the quality of the measurement results at each distance layer. In this embodiment, the effective echo signal-to-noise ratio threshold is set to... The preset correlation coefficient threshold is When a certain distance layer satisfies: , ,Right now: When the measurement result of the distance layer is deemed valid, the system maintains the current frequency and processing method, and outputs the flow velocity result of that distance layer. If the following conditions are met: Right now: If the current measurement quality is deemed insufficient, the measurement scheme will be updated. Specifically, when high-frequency measurement is performed using the optimal shallow water operating frequency and the echo signal-to-noise ratio of the deep distance cell is below 20dB, the system will automatically switch to outputting the low-frequency beam of the optimal deep water operating frequency. When the correlation coefficient under pulse coherent processing is below 0.6, the system will switch to broadband coding or pulse incoherent processing mode to improve measurement stability.

[0060] For the same distance layer, when both high-frequency and low-frequency measurements yield valid velocity results, the system does not perform multi-frequency weighted fusion, but instead selects the best output based on measurement quality. This embodiment uses a quality evaluation value. The calculation formula for evaluating speed measurement results at different frequencies is as follows: in, Indicates the echo signal-to-noise ratio at the current distance layer; This represents the echo correlation coefficient at the current distance layer.

[0061] In this embodiment, the weights for both the echo signal-to-noise ratio and the correlation coefficient are set to 0.5. If the high-frequency measurement results meet the following conditions... , And its quality evaluation value If the result is higher than the low-frequency measurement result, then the high-frequency speed measurement result will be output; if the quality evaluation value of the low-frequency measurement result is higher... If the value is too high, the low-frequency velocity measurement result will be output. If only one frequency meets the quality threshold, the velocity measurement result corresponding to that frequency will be output; if neither frequency meets the quality requirements, the distance layer will be marked as invalid, and a new measurement scheme will be selected in the next measurement cycle.

[0062] For example, when the real-time water depth When the area is determined to be shallow water, priority should be given to using... The optimal operating frequency for shallow water; when the real-time water depth is... At that time, it was determined to be a medium water depth area, and the optimal operating frequency for shallow water and deep water was compared. , The optimal operating frequency value for deep water is selected and output based on the real-time water depth. When the area is identified as deep water, the low-frequency beam with the optimal operating frequency for deep water is used first. When the quality of the deep echo deteriorates, the measurement stability is improved by increasing the pulse width, reducing the signal bandwidth, or switching to pulse incoherent processing mode.

[0063] After selecting the appropriate distance-layer scheme, the system outputs the effective velocity results in sequence according to the distance cells, forming a continuous velocity profile, and simultaneously outputs the water depth information obtained by the vertical beam. At the start of the next measurement cycle, the system re-evaluates the measurement scheme based on the latest water depth, velocity range, signal-to-noise ratio, and correlation coefficient, achieving adaptive continuous flow measurement under different water depths, velocities, and echo quality conditions.

[0064] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A multi-frequency, multi-beam acoustic Doppler adaptive flow velocity measurement method, characterized in that, The method includes: S1: Obtain the configuration parameters of the multi-beam combined array, wherein the multi-frequency multi-beam acoustic measurement array includes a vertical beam transducer and at least two sets of oblique beam transducers with different operating frequencies; the vertical beam transducer is used to obtain real-time water depth and identify the bottom interface, and the oblique beam transducer is used to obtain radial flow velocity information in different directions. S2: Determine the candidate frequency set based on the vertical beam transducer and the oblique beam transducer, and simultaneously determine the oblique beam tilt angle of the oblique beam transducer. Then, based on the candidate frequency set, the oblique beam tilt angle, the real-time water depth, the water absorption attenuation parameters, and the scattering characteristics of suspended particles, establish a propagation loss model. Then, calculate the echo signal-to-noise ratio of different candidate frequencies within the full measurement range of the target water body, and compare it with a preset signal-to-noise ratio threshold to determine the effective measurement depth range corresponding to each candidate frequency. S3: Based on the comparison between the real-time water depth and the preset water depth threshold, determine the transmission frequency of the vertical beam transducer and the oblique beam transducer according to the comparison result; S4: At the determined transmission frequency, based on the radial flow velocity information, determine the pulse form and Doppler processing method of the vertical beam transducer and the oblique beam transducer. When the absolute value of the radial flow velocity is lower than a preset low-velocity threshold, control the multi-beam array to use pulse coherent processing; when the absolute value of the radial flow velocity is between a preset low-velocity threshold and a preset high-velocity threshold, control the multi-beam array to use broadband coding processing; when the absolute value of the radial flow velocity is higher than a preset high-velocity threshold, or the echo correlation of the radial flow velocity is lower than a preset correlation coefficient threshold, control the multi-beam array to use pulse incoherent processing. Finally, based on the determined pulse form and Doppler processing method, perform quality evaluation and optimal output on the velocity measurement results of different distance layers within the effective measurement depth range to generate continuous velocity profiles and water depth information.

2. The adaptive measurement method for multi-frequency multi-beam acoustic Doppler current velocity according to claim 1, characterized in that, The calculation process for the echo signal-to-noise ratio is as follows: In the formula, These are the source level parameters corresponding to the transmission power; For the transducer in the first candidate frequencies Equivalent send and receive responses; The volumetric backscattering intensity is formed by scattering from suspended particles. Indicates the radius of the suspended particles. Indicates the concentration of suspended sediments; Represents the propagation loss model; This represents the equivalent noise level of the receiver.

3. The adaptive measurement method for multi-frequency multi-beam acoustic Doppler flow velocity according to claim 2, characterized in that, The process of determining the effective measurement depth range in step S2 is as follows: The echo signal-to-noise ratio of each measurement unit is calculated one by one along the acoustic wave propagation direction of the vertical beam transducer and the oblique beam transducer to obtain the signal-to-noise ratio distribution curve of different candidate frequencies in the full measurement range of the target water body. The signal-to-noise ratio (SNR) distribution curve is compared with a preset SNR threshold. When the echo SNR at a certain measurement unit is higher than or equal to the preset SNR threshold, the corresponding candidate frequency is determined to be usable for effective flow velocity measurement at the current water depth. When the echo SNR is lower than the preset SNR threshold, the corresponding candidate frequency is determined to not meet the effective flow measurement conditions at the current water depth, thereby determining the effective measurement depth range corresponding to each candidate frequency.

4. The multi-frequency multi-beam acoustic Doppler adaptive flow velocity measurement method according to claim 3, characterized in that, The formula for calculating the effective measurement depth range is as follows: In the formula, Represents candidate frequency The corresponding effective measurement depth range; Indicates the first The vertical depth corresponding to each measurement unit; Represents candidate frequency The corresponding echo signal-to-noise ratio; This indicates the preset signal-to-noise ratio threshold.

5. The adaptive measurement method for multi-frequency multi-beam acoustic Doppler current velocity according to claim 1, characterized in that, The comparison process between the real-time water depth and the preset water depth threshold in step S3 is as follows: A first water depth threshold and a second water depth threshold are set, with the first water depth threshold being less than the second water depth threshold. When the real-time water depth is less than or equal to the first water depth threshold, it is determined to be a shallow water measurement area, and the multi-beam array is controlled to adopt a high-frequency measurement scheme. When the real-time water depth is greater than or equal to the second water depth threshold, it is determined to be a deep water measurement area, and the multi-beam array is controlled to adopt a low-frequency measurement scheme.

6. The multi-frequency multi-beam acoustic Doppler adaptive flow velocity measurement method according to claim 1, characterized in that, The process of quality evaluation and optimal output in step S4 includes: A quality evaluation model is constructed. For the same distance layer, when both high-frequency and low-frequency speed measurement results are obtained, the quality evaluation values ​​corresponding to high-frequency and low-frequency speeds are compared, and the speed measurement result with the higher quality evaluation value of the quality evaluation model is selected and output. According to the quality evaluation model, when only one of the high-frequency and low-frequency frequencies meets the preset quality requirements, the corresponding frequency is output; when neither meets the preset quality requirements, the corresponding distance layer is marked as invalid.

7. The adaptive measurement method for multi-frequency multi-beam acoustic Doppler current velocity according to claim 6, characterized in that, The quality evaluation model is as follows: In the formula, Indicates the quality evaluation value. The weights representing the echo signal-to-noise ratio, The weights representing the correlation coefficients, Indicates the current echo signal-to-noise ratio. Represents the correlation coefficient. This indicates the preset correlation coefficient threshold.

8. The multi-frequency multi-beam acoustic Doppler adaptive flow velocity measurement method according to claim 1, characterized in that, Also includes: When the quality evaluation result of the preset candidate measurement scheme is better than that of the current measurement scheme, and the difference between the two reaches the preset hysteresis threshold and is valid for multiple consecutive measurement cycles, the system automatically switches from the current measurement scheme to the preset candidate measurement scheme. The switching content includes at least one of the following: transmission frequency, pulse form, signal bandwidth, or Doppler processing method of the multi-beam array.

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