A time-difference method for measuring river section flow velocity based on a linear frequency modulation signal

Abstract

The present application relates to the technical field of hydrological monitoring, and relates to a time-difference method for measuring river section flow velocity based on a linear frequency modulation signal, comprising: transmitting a preset linear frequency modulation broadband underwater acoustic signal as a detection signal, propagating the detection signal along a forward propagation path and a reverse propagation path of water flow; receiving the linear frequency modulation broadband underwater acoustic signal propagated along the forward propagation path and the reverse propagation path respectively to obtain a forward echo signal and a reverse echo signal; performing matching filter processing on the forward echo signal and the reverse echo signal respectively to compress the energy of the echo signal in the time domain, form a compressed signal with a sharp peak value, and determine the forward propagation time and the reverse propagation time of the detection signal according to the peak value position of the compressed signal; calculating the time difference according to the forward propagation time and the reverse propagation time, and combining preset acoustic path geometric parameters to obtain the water flow velocity of the river section.

Description

Technical Field

[0001] This invention relates to the field of hydrological monitoring technology, and in particular to a time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals. Background Technology

[0002] Real-time and accurate monitoring of river cross-sectional flow velocity is a crucial foundation for hydrological monitoring, water resource allocation, flood control early warning, and irrigation area metering. Time-of-flight ultrasonic current meters, due to their outstanding advantages such as non-contact operation, minimal flow field disturbance, and long-term online operation, have been widely used in this field. Their basic principle is as follows: underwater acoustic transducers are deployed in pairs on both banks of the river cross-section or upstream and downstream of the same cross-section, emitting and receiving sound wave signals in opposite directions. The difference between the downstream and upstream propagation times of the sound waves, combined with known acoustic path geometric parameters, is used to indirectly calculate the average or stratified flow velocity of the cross-section.

[0003] Currently, all commercially available time-of-flight (TOF) river current meters, both domestically and internationally, invariably use single-frequency narrowband pulse signals or fixed-frequency sinusoidal pulse signals as the underwater acoustic emission detection signal. These devices obtain the propagation delay by measuring the arrival time, envelope peak value, or phase change of the received signal. While this signal system is generally usable in ideal clear water and small-section river channels, it reveals fundamental flaws in actual natural river channels, specifically:

[0004] First, the time resolution is severely insufficient. The bandwidth of a single-frequency narrowband signal is usually only a small percentage of its center frequency. According to the time-bandwidth product principle, its time resolution is limited to 1 / B (B is the bandwidth), making it difficult to distinguish the minute hourly differences on the order of nanoseconds to microseconds caused by low flow velocities (<0.1m / s), resulting in large measurement errors and low sensitivity at low flow velocities.

[0005] Second, the anti-interference capability is weak. Natural river channels commonly exhibit strong scattering from suspended bubbles, sound attenuation and volumetric reverberation caused by high concentrations of sediment, and multipath reflections from the riverbed and banks. These interferences can lead to severe distortions in the amplitude, phase, and envelope of the received echo. Traditional time delay estimation algorithms based on threshold detection, zero-crossing comparison, or simple cross-correlation are extremely sensitive to waveform distortion, easily resulting in time delay misjudgments and spike jumps, causing significant fluctuations or even loss of flow velocity data.

[0006] Third, measurements are prone to failure under long-distance, low signal-to-noise ratio (SNR) conditions. In large-section, long-distance applications, the signal frequency needs to be reduced to ensure penetration capability, but the limited sound source level and propagation loss cause the received SNR to deteriorate sharply. Single-frequency signals do not have pulse compression processing gain, and the receiver can only rely on the original signal energy for detection, making it difficult to achieve reliable signal acquisition and accurate time delay locking in low SNR environments.

[0007] Fourth, there is an inherent contradiction between ranging accuracy and time difference resolution. Theoretically, improving time delay measurement accuracy requires increasing signal bandwidth, but increasing bandwidth in a single-frequency system will inevitably lead to a shortened pulse width or an increased center frequency, thereby weakening the signal propagation capability and system processing gain. It is difficult to achieve both simultaneously.

[0008] In summary, existing signal systems based on "single-frequency narrowband pulse signals + traditional time delay estimation algorithms" consistently fail to simultaneously address the core contradiction of high time resolution and strong anti-interference capability in complex hydrological environments (high sediment, numerous air bubbles, large cross-sections, and low flow velocities). Although linear frequency modulation (LFM) signals have been successfully applied in radar, active sonar, and medical ultrasound imaging due to their large time-bandwidth product, extremely high peak time-domain gain after matched filtering, and excellent multipath and noise immunity, LFM signal systems and their corresponding matched filtering methods remain completely absent in the specific technical branch of river cross-section time-difference velocity measurement. Existing technologies lack specialized devices and methods for deeply integrating the physical characteristics of LFM signals with time-difference velocity measurement models. Summary of the Invention

[0009] The purpose of this invention is to design a time-difference method for measuring river cross-section velocity based on linear frequency modulated signals, which solves the technical defects of existing time-difference river current meters, which suffer from low time resolution, weak anti-interference ability, and easy failure when the signal-to-noise ratio deteriorates in complex hydrological environments due to the use of a single-frequency narrowband signal system.

[0010] This invention provides a time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals, comprising: S1: Transmit a preset linear frequency modulated broadband underwater acoustic signal as a detection signal, and propagate the detection signal along the forward propagation path and the reverse propagation path of the water flow; S2: Receive the linear frequency modulated broadband underwater acoustic signals after propagation through the forward propagation path and the reverse propagation path, respectively, to obtain forward echo signals and reverse echo signals; S3: Perform matched filtering on the forward echo signal and the reverse echo signal respectively to compress the energy of the echo signal in the time domain to form a compressed signal with sharp peaks, and determine the forward propagation time and reverse propagation time of the detection signal based on the peak position of the compressed signal. S4: Calculate the time difference based on the forward propagation time and the reverse propagation time, and combine it with the preset acoustic path geometry parameters to obtain the water flow velocity of the river cross section.

[0011] Preferably, in step S1, the linear frequency modulated broadband underwater acoustic signal has a preset time-bandwidth product, which is greater than 1, so as to simultaneously ensure that the detection signal has the long time-bandwidth energy required for long-distance propagation and the large bandwidth required for high time resolution.

[0012] Preferably, in step S1, before transmitting the preset linear frequency modulated broadband underwater acoustic signal, the method further includes: Based on the hydrological environmental characteristics of the river section to be measured, the center frequency, frequency modulation bandwidth, and pulse duration of the linear frequency modulated broadband underwater acoustic signal are configured.

[0013] Preferably, in step S3, the matched filtering process specifically includes: The forward echo signal and the reverse echo signal are respectively subjected to time-domain autocorrelation with the local reference linear frequency modulated signal.

[0014] Preferably, the matched filtering process compresses the energy of the echo signal to obtain processing gain, thereby suppressing background noise, volume reverberation, and multipath reflection interference in low signal-to-noise ratio environments.

[0015] Preferably, in step S3, determining the forward propagation time and reverse propagation time of the detection signal based on the peak position of the compressed signal includes: Identify the autocorrelation peak with the highest main lobe energy and sharpest peak in the compressed signal, and determine the time point corresponding to this peak as the arrival time of the propagation time.

[0016] Preferably, before performing matched filtering on the echo signal, the method further includes: The forward and reverse echo signals are preprocessed by filtering, amplification, and noise reduction.

[0017] Preferably, the propagation path of the detection signal is constructed by a pair of underwater acoustic transducers deployed on both banks of the river cross section or upstream and downstream of the same cross section.

[0018] Preferably, the method further includes: Based on multiple pairs of acoustic path geometric parameters arranged in layers along the water depth direction, steps S1, S2, S3 and S4 are repeatedly executed to obtain the layered velocity profile of the river cross section.

[0019] Preferably, the method further includes: Based on the calculated water flow velocity or stratified flow velocity, and combined with the cross-sectional area information of the river section, the instantaneous flow rate of the river section is obtained.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention discloses a time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals, which has the following advantages: (1) The bandwidth of broadband linear frequency modulation signals improves time resolution; By employing linear frequency modulation and obtaining a narrow main peak after compression, the minute time difference between forward and reverse propagation can be separated from the envelope noise, thereby improving the resolution of time delay measurements. This directly improves the measurable range and measurement accuracy of time delay at low flow rates.

[0021] (2) Long time span × large bandwidth achieves both high power and high resolution; Compared to the trade-offs between short-pulse broadband and long-term narrow-band, linear frequency modulation (LFM) can achieve a narrow peak after compression while maintaining a large transmit energy. The system has both long-distance penetration capability and can obtain a highly recognizable delay peak at the receiver, thus eliminating the fundamental limitation of the "bandwidth-time width contradiction" in single-frequency systems.

[0022] (3) Improve the reliable detection rate under low signal-to-noise ratio conditions; In situations where high sand content, bubble scattering, or long-distance attenuation lead to low received SNR, matched filtering makes the main peak easier to detect and reduces the false detection rate, thereby reducing the probability of data jumps and failures and ensuring the stability of long-term online measurements in the field. Attached Figure Description

[0023] Figure 1 This is a schematic flowchart of a time-difference method for measuring river cross-section flow velocity based on linear frequency modulated signals, provided in an embodiment of the present invention. Figure 2 This is an internal schematic diagram of a time-difference method river cross-section velocity measurement device based on linear frequency modulation signal provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a time-difference method river cross-section velocity measurement device based on linear frequency modulation signal, installed either by wall contact or by piling, according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the slope-mounted installation of a time-difference method river cross-section flow velocity measurement device based on linear frequency modulation signals, provided in an embodiment of the present invention. Detailed Implementation

[0024] 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, and 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.

[0025] like Figure 1As shown, this application provides a time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals, including: A preset linear frequency modulated broadband underwater acoustic signal is transmitted as a detection signal, and the detection signal is propagated along the forward propagation path and the reverse propagation path of the water flow. The linear frequency modulated broadband underwater acoustic signals, after propagation through the forward propagation path and the reverse propagation path, are received respectively to obtain forward echo signals and reverse echo signals; The forward and reverse echo signals are subjected to matched filtering to compress the energy of the echo signals in the time domain, forming a compressed signal with sharp peaks. The forward propagation time and reverse propagation time of the detection signal are determined based on the peak position of the compressed signal. The time difference is calculated based on the forward propagation time and the reverse propagation time, and the water flow velocity at the river cross-section is obtained by combining the preset acoustic path geometry parameters.

[0026] like Figure 2 As shown in one embodiment of this application, a time-difference method river cross-section velocity measurement device based on linear frequency modulated (LFM) signal is provided, including a main control processing unit, an LFM signal modulation and transmission unit, a power drive module, a paired underwater acoustic transducer array, a signal receiving and conditioning unit, a synchronous acquisition unit, a storage and communication unit, and a power supply module.

[0027] Main control processing unit: Built-in LFM signal waveform parameter configuration program, time delay calculation algorithm, and flow rate calculation model; LFM signal modulation transmitting unit: generates a linear frequency modulated underwater acoustic baseband signal with preset bandwidth, frequency modulation duration, and center frequency; Power drive module: Amplifies the power of the LFM modulated signal to drive the underwater acoustic transducer to complete underwater sound wave transmission; Underwater acoustic transducers: Two sets are arranged facing each other, installed on both banks of the river cross section / upstream and downstream of the same cross section, to complete the transmission and reception of sound waves; Signal receiving and conditioning unit: performs filtering, amplification, and noise reduction preprocessing on the received signal; Synchronous acquisition unit: High-speed synchronous acquisition of bidirectional propagating linear frequency modulated echo signals; Storage and communication unit: Locally stores flow rate data and supports uploading to the hydrological monitoring platform via 4G / RS485.

[0028] When the device is in operation, follow these steps: Parameter presets: The main control unit sets the center frequency, frequency modulation bandwidth, pulse duration, cross-sectional acoustic path spacing, and layout tilt angle of the linear frequency modulation signal; Signal transmission: The modulation unit generates two linear frequency modulated underwater acoustic signals in both directions, which are then amplified and transmitted in opposite directions by the transducer; Echo reception: The upstream and downstream transducers receive the LFM echo signals propagating in the downstream and upstream directions, respectively, and perform filtering and noise reduction. Accurate delay extraction: The autocorrelation algorithm is used to perform matched filtering on the transmitted and received LFM signals to accurately solve the downstream propagation delay and the upstream propagation delay; Time difference calculation: Calculate the time difference between downstream and upstream sound wave propagation; Velocity calculation: Combining the cross-sectional acoustic path geometry distance and layout angle, the real-time water flow velocity of the river cross-section is calculated using the time-difference method velocity formula; Data output: Completes the calculation of layered flow velocity, cross-sectional average flow velocity, and instantaneous flow rate, stores it locally, and uploads it remotely.

[0029] like Figure 3 and Figure 4 As shown, a time-difference method river cross-section velocity measurement device based on linear frequency modulated signals typically employs three installation methods, specifically: Wall mounting: This method involves directly fixing the bracket containing the equipment to the vertical surface of the target building. If the target vertical surface is uneven or not sturdy, steel bars or concrete are needed to reshape the target mounting surface.

[0030] Piling installation: Drive the corresponding piles into the riverbed at the designed location. The length of the pile into the riverbed is generally three times the distance of the pile above the riverbed. The installation method uses a clamp-type bracket to fix the pile to the pile.

[0031] Slope-mounted installation: This method involves fixing the bracket containing the equipment to a slope. If the target slope does not have a concrete foundation, a foundation suitable for the bracket needs to be constructed.

[0032] In one embodiment provided in this application, in step S1, the linear frequency modulated broadband underwater acoustic signal has a preset time-bandwidth product, which is greater than 1, so as to simultaneously ensure that the detection signal has the long time-bandwidth energy required for long-distance propagation and the large bandwidth required for high time resolution.

[0033] In the above scheme, during operation, the long time bandwidth (T) ensures that the transmitted acoustic signal carries sufficient total energy to penetrate complex water bodies with large cross-sections and high sediment content, overcoming propagation attenuation and ensuring that the long-distance receiver can still obtain a detectable signal. At the same time, the large bandwidth (B) is not directly manifested as a short pulse during transmission, but rather, after matched filtering at the receiver, the energy is compressed into an extremely narrow time window of 1 / B width, thereby releasing the potential for high time resolution.

[0034] The protection scope focuses on broadband signals with a large time-bandwidth product, such as LFM signals, forming a clear technical distinction from traditional single-frequency narrowband signals with a TB product of approximately 1. Due to the long time-bandwidth characteristic of the transmitted signal, its total energy is guaranteed, effectively overcoming attenuation during long-distance propagation and enhancing the signal's ability to penetrate water bodies, making it suitable for monitoring large-section, long-distance rivers. Furthermore, because the transmitted signal also possesses a large bandwidth, according to the time-bandwidth product principle, its theoretically achievable time resolution (1 / B) is extremely high. This provides the physical possibility for subsequently using matched filtering to accurately distinguish nanosecond to microsecond-level microsecond time differences generated by low flow velocities (<0.1 m / s), which is key to fundamentally improving the sensitivity and accuracy of low-flow-velocity measurements.

[0035] In one embodiment provided in this application, before transmitting the preset linear frequency modulated broadband underwater acoustic signal in step S1, the method further includes: Based on the hydrological environmental characteristics of the river section to be measured, the center frequency, frequency modulation bandwidth, and pulse duration of the linear frequency modulated broadband underwater acoustic signal are configured.

[0036] In the above scheme, through flexible parameter configuration, it can actively adapt to various hydrological environments, from clear streams to turbid rivers, significantly broadening the effective application range of the method and its survivability in harsh environments. For specific scenarios, such as pursuing low flow velocity accuracy or ensuring stability under strong interference, the core performance of the system can be adjusted to the optimal state under the current conditions by optimizing the LFM signal parameters, thereby obtaining better measurement results than fixed parameter signals.

[0037] In one embodiment provided in this application, the matched filtering process in step S3 specifically includes: The forward echo signal and the reverse echo signal are respectively subjected to time-domain autocorrelation with the local reference linear frequency modulated signal.

[0038] In the above scheme, when the received echo signal enters the processing unit, the algorithm performs point-by-point multiplication and accumulation with a local reference LFM signal template that slides in time. When the echo signal and the reference template are perfectly aligned in time, their waveforms are highly similar, and the result of the correlation operation produces a very large positive value, forming a very sharp peak. At any other misaligned moment, due to the pseudo-random nature of the LFM signal, its correlation with its misaligned version is very low, and the operation result is close to zero, forming very low sidelobes. In physical terms, this process compresses almost all the signal energy that was originally distributed over a long time span T into a single time point with a width of approximately 1 / B.

[0039] Matched filtering is concretized into time-domain autocorrelation operations. Through these operations, the long duration T and wide bandwidth B of the LFM echo signal are successfully compressed into a sharp pulse with a duration of approximately 1 / B in the time domain, achieving energy focusing. The compressed signal has an extremely narrow main lobe width, and its peak position can indicate the signal's arrival time with extremely high precision. Compared to the flat envelope peaks of traditional single-frequency signals, this sharp peak allows even minute time differences on the nanosecond scale to be clearly distinguished, thus providing a prerequisite for high-precision propagation time determination.

[0040] In one embodiment provided in this application, the matched filtering process obtains processing gain by compressing the energy of the echo signal in order to suppress background noise, volume reverberation and multipath reflection interference in a low signal-to-noise ratio environment.

[0041] In the above scheme, in natural river channels, the received echo signal is always submerged in various interferences, resulting in a very low signal-to-noise ratio. When this mixed signal passes through a matched filter: For the LFM signal component, since its waveform perfectly matches the filter template, its energy is coherently accumulated, forming a sharp peak at the output that is amplified by TB times.

[0042] The background noise and volumetric reverberation are caused by random scattered echoes generated by a large amount of suspended sediment and bubbles. Their waveforms are random and uncorrelated. After passing through the filter, the energy cannot be coherently accumulated, and the output is still a low-amplitude random fluctuation.

[0043] For multipath reflection interference, due to their different arrival times, they are misaligned when performing correlation operations with the main path signal. Therefore, their output also exhibits side lobes with lower amplitude, which are much lower than the main peak.

[0044] Ultimately, even if the peak signal at the input is much lower than the noise level (signal-to-noise ratio < 0 dB), after matched filtering, the peak signal at the output can be much higher than the noise floor, thus allowing it to be reliably detected.

[0045] A processing gain of approximately TB is achieved through matched filtering, significantly improving the signal-to-noise ratio (SNR) of the output signal. This allows weak signals that were previously submerged in noise to be extracted and highlighted. The processing gain effectively suppresses background noise and volume reverberation unrelated to the LFM signal. Simultaneously, the excellent autocorrelation characteristics of the LFM signal effectively suppress interference from multipath reflection signals, ensuring accurate identification of the main path signal. Because it can stably extract signals in low SNR and strong interference environments, it significantly reduces the probability of data jumps, misjudgments, and loss due to harsh environments, greatly improving the stability and all-weather reliability of flow velocity measurement. It is particularly suitable for turbulent rivers with high sediment content and numerous bubbles, or industrial environments with electromagnetic interference.

[0046] In one embodiment provided in this application, step S3, determining the forward propagation time and backward propagation time of the detection signal based on the peak position of the compressed signal, includes: Identify the autocorrelation peak with the highest main lobe energy and sharpest peak in the compressed signal, and determine the time point corresponding to this peak as the arrival time of the propagation time.

[0047] In the above scheme, within the processing unit, after an echo signal undergoes matched filtering, a time series data is generated, depicting the waveform of the autocorrelation function. A peak detection algorithm iterates through this sequence, searching for its maximum value. Since the autocorrelation peak generated by the direct wave after matched filtering of the LFM signal is theoretically much higher than any sidelobes or spurious peaks generated by multipath reflections or noise, finding the global maximum value allows for a high-probability determination that this peak is the main lobe peak. The position of this peak on the time axis, minus the signal's transmission time, yields the precise propagation time.

[0048] Using the sharp autocorrelation peak as a time marker provides a much higher degree of certainty in its location compared to traditional methods that rely on smooth envelopes or zero-crossings. This allows for timestamp extraction accuracy to reach one-tenth of the sampling period, directly improving the final accuracy of time delay measurements. This criterion naturally leverages the characteristic that the main lobe energy is much higher than the side lobes. Even with multiple multipath echoes, their correlation peaks are much lower than the main peak, automatically filtering out most multipath interference and ensuring the identification of the shortest direct sound path, thus improving measurement accuracy. This peak-detection-based algorithm is well-suited for automated computer processing; the criterion is objective and stable, avoiding uncertainties caused by human interpretation or complex threshold settings, and guaranteeing the objectivity and repeatability of the measurement results.

[0049] In one embodiment provided in this application, before performing matched filtering on the echo signal, the method further includes: The forward and reverse echo signals are preprocessed by filtering, amplification, and noise reduction.

[0050] In the above scheme, the weak electrical signal received from the underwater acoustic transducer first enters the signal receiving and conditioning unit, where a bandpass filter filters out signals irrelevant to the LFM signal frequency range. Next, the filtered signal is amplified by a variable gain amplifier or a fixed gain LNA. The adjusted signal is then sent to a high-speed synchronous acquisition unit for digitization and finally delivered to a processor for matched filtering. Although matched filtering itself has strong noise immunity, proper preprocessing can allow it to operate under even better conditions, further improving overall performance.

[0051] By using bandpass filtering, out-of-band noise is effectively removed, reducing the dynamic range requirements of the subsequent ADC and the computational load on the DSP, and preventing amplifier saturation or nonlinear distortion that may be caused by strong out-of-band interference. Amplification ensures that weak echo signals can be quantized by the ADC with sufficient resolution, preserving signal details and providing high-quality digital input for subsequent high-precision matched filtering. Although the main processing gain comes from matched filtering, the filtering and low-noise amplification operations in the preprocessing stage themselves constitute the first line of defense for improving the signal-to-noise ratio, making a beneficial contribution to obtaining excellent measurement results and forming multiple safeguards.

[0052] In one embodiment provided in this application, the propagation path of the detection signal is constructed by a pair of underwater acoustic transducers deployed on both banks of a river cross section or upstream and downstream of the same cross section.

[0053] In the above scheme, during measurement, upstream transducer A transmits an LFM signal, which is received by downstream transducer B. This process measures the downstream propagation time t1. Immediately afterwards or simultaneously, transducer B transmits the same LFM signal, which is received by transducer A. This process measures the upstream propagation time t2. This pair of opposing transmit and receive operations completely constructs the two core time quantities required to calculate the time difference Δt = t2 - t1.

[0054] The pairing of transducers facing each other makes the technical solution physically feasible, forming a complete velocity measurement system. This arrangement is the physical prerequisite for generating the time difference between upstream and downstream propagation. The presence of water flow causes a slight difference in the propagation speed of sound waves along the two paths. It is this difference that is captured by a high-precision time delay extraction method and ultimately used to calculate the flow velocity.

[0055] In one embodiment provided in this application, the method further includes: Based on multiple pairs of acoustic path geometric parameters arranged in layers along the water depth direction, steps S1, S2, S3 and S4 are repeatedly executed to obtain the layered velocity profile of the river cross section.

[0056] In the above scheme, it is assumed that N pairs of transducers are installed vertically on both sides of the river cross-section, with each pair defining an acoustic path at a specific water depth. The system will activate each pair of transducers sequentially or in parallel. For example, the first pair of transducers executes steps S1-S4, using the LFM signal and matched filtering to accurately calculate the flow velocity v1 of the first water layer. Subsequently, the second pair of transducers repeats this process to obtain the flow velocity v2 of the second layer, and so on, until the Nth pair of transducers measures the flow velocity v of the Nth layer. n Ultimately, the system obtains a set of variables [v1, v2, ..., v...]. nA discrete dataset describing the variation of water flow with depth, consisting of [a series of data points], is called a stratified velocity profile.

[0057] Upgrading single-point / single-line average velocity measurement to a fine characterization of the vertical velocity distribution across the entire cross-section reveals the vertical non-uniformity of flow, providing richer and more accurate fundamental data for hydrological analysis and hydraulic models. Based on stratified velocity profiles, the total cross-sectional discharge can be calculated using more precise integration methods, improving the accuracy of discharge measurement, especially in rivers with highly non-uniform velocity distribution.

[0058] In one embodiment provided in this application, the method further includes: Based on the calculated water flow velocity or stratified flow velocity, and combined with the cross-sectional area information of the river section, the instantaneous flow rate of the river section is obtained.

[0059] In the above scheme, based on the average flow velocity calculation, if the measured cross-sectional average flow velocity V_avg (e.g., measured through a single-layer acoustic path), and the current cross-sectional area A is obtained through the water level gauge and the cross-sectional database, then the instantaneous flow rate Q = V_avg A. Based on stratified velocity calculations, if the measured velocity profile is a stratified velocity profile [v1, v2, ..., v] n ], and the cross-sectional area of ​​each layer is known [a1, a2, ..., a n The instantaneous flow rate is obtained by summing the flow rates of each layer: Q = Σ(v i a i (i) where i ranges from 1 to n. This method, based on cross-sectional integration, is generally more accurate than the previous one. Finally, the system outputs a value representing how many cubic meters of water have flowed through the cross-section at that moment.

[0060] This ensures high precision and stability in flow velocity measurement from the source, and this precision advantage is directly transferred to flow calculation. It enables more accurate and reliable instantaneous flow monitoring than traditional technologies. Accurate real-time flow data is the core basis for all water management work, including water resource allocation, flood warning, irrigation area metering, and ecological flow control. By providing high-quality flow data, it provides solid data support for these decisions, resulting in significant social and economic benefits. Including the flow calculation step forms a complete technical chain from signal transmission, echo processing, flow velocity calculation to final flow output.

[0061] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals, characterized in that, include: S1: Transmit a preset linear frequency modulated broadband underwater acoustic signal as a detection signal, and propagate the detection signal along the forward propagation path and the reverse propagation path of the water flow; S2: Receive the linear frequency modulated broadband underwater acoustic signals after propagation through the forward propagation path and the reverse propagation path, respectively, to obtain forward echo signals and reverse echo signals; S3: Perform matched filtering on the forward echo signal and the reverse echo signal respectively to compress the energy of the echo signal in the time domain to form a compressed signal with sharp peaks, and determine the forward propagation time and reverse propagation time of the detection signal based on the peak position of the compressed signal. S4: Calculate the time difference based on the forward propagation time and the reverse propagation time, and combine it with the preset acoustic path geometry parameters to obtain the water flow velocity of the river cross section.

2. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, In step S1, the linear frequency modulated broadband underwater acoustic signal has a preset time-bandwidth product, which is greater than 1, so as to simultaneously ensure that the detection signal has the long time-bandwidth energy required for long-distance propagation and the large bandwidth required for high time resolution.

3. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, In step S1, before transmitting the preset linear frequency modulated broadband underwater acoustic signal, the following steps are also included: Based on the hydrological environmental characteristics of the river section to be measured, the center frequency, frequency modulation bandwidth, and pulse duration of the linear frequency modulated broadband underwater acoustic signal are configured.

4. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, In step S3, the matched filtering process specifically includes: The forward echo signal and the reverse echo signal are respectively subjected to time-domain autocorrelation with the local reference linear frequency modulated signal.

5. The time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 4, characterized in that, The matched filtering process compresses the energy of the echo signal to obtain processing gain, thereby suppressing background noise, volume reverberation, and multipath reflection interference in low signal-to-noise ratio environments.

6. The time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, In step S3, determining the forward propagation time and backward propagation time of the detection signal based on the peak position of the compressed signal includes: Identify the autocorrelation peak with the highest main lobe energy and sharpest peak in the compressed signal, and determine the time point corresponding to this peak as the arrival time of the propagation time.

7. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, Before performing matched filtering on the echo signal, the process further includes: The forward and reverse echo signals are preprocessed by filtering, amplification, and noise reduction.

8. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, The propagation path of the detection signal is constructed by pairing underwater acoustic transducers deployed on both banks of the river cross section or upstream and downstream of the same cross section.

9. The time-difference method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 1, characterized in that, The method further includes: Based on multiple pairs of acoustic path geometric parameters arranged in layers along the water depth direction, steps S1, S2, S3 and S4 are repeatedly executed to obtain the layered velocity profile of the river cross section.

10. The method for measuring river cross-sectional flow velocity based on linear frequency modulated signals according to claim 9, characterized in that, The method further includes: Based on the calculated water flow velocity or stratified flow velocity, and combined with the cross-sectional area information of the river section, the instantaneous flow rate of the river section is obtained.

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