A method for detecting polar ice layer bending wave pulse signals

Abstract

The application discloses a polar ice layer bending wave pulse signal detection method, belongs to the polar ice layer signal detection field, and is based on the physical dispersion characteristics of the polar ice layer bending wave.The method comprises the following steps: S1, collecting an acoustic signal by using a sensor and preprocessing to obtain a preprocessed signal; S2, setting a frame length, a frame span, a frequency modulation order and a threshold; S3, performing transformation processing on the signal of each frame; S4, calculating the maximum value of the spectrum of each frame signal after transformation; and S5, judging whether the frame data has a signal or not by using a preset threshold.According to the frequency dispersion effect of the bending wave in the polar ice layer, a transformation method for signal detection is provided.The experimental results show that the method can realize the detection of the bending wave pulse signal in the polar ice layer, and the fast Fourier transformation is used to improve the calculation efficiency.

Description

Technical Field

[0001] This invention belongs to the field of polar ice layer signal detection, specifically relating to a method for detecting bending wave pulse signals in polar ice layers. Background Technology

[0002] Polar acoustics is one of the three major research directions in underwater acoustics. The Arctic is covered by thick ice sheets year-round, and the interaction between sound waves and the sea ice during propagation creates a unique polar underwater acoustic propagation environment. Researching underwater acoustic signal processing methods and equipment adapted to the polar environment is one of the important topics for Chinese Arctic underwater acoustics researchers.

[0003] Remote monitoring of Arctic sea ice vibrations using acoustic methods is of significant importance. For example, factors such as extreme weather, sea swells, and climate can cause ice in fixed ice zones to fracture instantaneously. Underwater vehicles needing satellite communication will generate pulsed sound when breaking through the Arctic ice. Researchers working on the ice also need to monitor the safety of personnel on the ice from a distance due to adverse weather conditions. Furthermore, explosions beneath the ice can also trigger vibrations within the ice layer.

[0004] Studies have shown that two Lamb wave modes exist in ice layers at low frequencies: flexural waves and longitudinal plate waves. Among them, the flexural waves excited by ice-based pulse sound sources have relatively high energy, and the sound absorption coefficient of ice is small at low frequencies, allowing flexural waves to propagate over long distances. However, due to the influence of Arctic environmental noise, the flexural wave pulse signals collected by ice surface sensors are still relatively weak.

[0005] To achieve remote monitoring of ice layer vibration, it is necessary to detect bending wave pulse signals in the ice layer under conditions of low signal-to-noise ratio. Based on the physical characteristics of low-frequency bending waves in polar environments, this invention proposes a method for detecting low-frequency bending wave pulse signals suitable for polar ice-covered sea areas. Summary of the Invention

[0006] In order to solve the technical problems existing in the background art, the present invention aims to provide a method for detecting bending wave pulse signals in polar ice layers.

[0007] To solve the technical problem, the technical solution of the present invention is as follows:

[0008] Bending waves are a type of elastic Lamb wave commonly found in ice layers, and their dispersion characteristic equation is:

[0009]

[0010] The ice layer thickness is 2h, and ω is the angular frequency of the acoustic signal. c L and c THere, denoted as P-wave velocity and S-wave velocity, respectively, and k is the characteristic value (horizontal wave number).

[0011] In the low-frequency range, the above formula is approximately expressed as:

[0012]

[0013] Because ω and k 2 It is a small quantity of the same order, with Substituting into the above equation, we get:

[0014]

[0015] According to the definition of group velocity, the group velocity of a curved wave is:

[0016]

[0017] in

[0018] The ice layer was set with a longitudinal wave velocity of 3800 m / s, a transverse wave velocity of 1900 m / s, and a density of 0.9 g / cm³. 3 The speed of sound in water is 1500 m / s, the water depth is 5 m, and the density is 1.0 g / cm³. 3 The sedimentary layer has a sound velocity of 2000 m / s, a depth of 2 m, and a density of 2.0 g / cm³. 3 The ice layer thickness ranges from 0.1 to 2.0 m. Based on the governing equations of the bending wave, the group velocity dispersion curve is obtained as follows: Figure 1 As shown, with the ice thickness remaining constant, the group velocity of the low-frequency bending wave increases with increasing frequency. Therefore, the instantaneous frequency of the received bending wave signal exhibits a modulation trend that decreases with increasing time.

[0019] This invention discloses a method for detecting bending wave pulse signals in polar ice layers, the method comprising:

[0020] S1: Acquire acoustic signals using sensors and preprocess them to obtain preprocessed signals;

[0021] S2: Set frame length, frame span, frequency modulation order, and threshold;

[0022] S3: Perform transformation processing on the above signals of each frame;

[0023] S4: Calculate the maximum value of the spectrum after the signal transformation of each frame;

[0024] S5: Use a preset threshold to determine whether there is a signal in the frame data.

[0025] Furthermore, step S1 specifically includes:

[0026] Furthermore, sensors deployed in the polar ice layer are used to collect acoustic signals propagating in the environment. These sensors are vertical accelerometers or seismic detectors. The sampling frequency of the data acquisition device is 25.6 kHz, and the signal is initially low-pass filtered to eliminate high-frequency noise.

[0027] Furthermore, in step S2, a frame processing method is used to meet the real-time requirements of polar signal processing. The frame length refers to the time length of each frame of sampled data, which is set to 0.2s, i.e., 5120 consecutive sampling points; the frame step size refers to the time difference between two frames, which is set to 10 sampling points.

[0028] Based on the dispersion characteristics of curved waves, it can be known that curved waves have frequency modulation characteristics. The frequency modulation order ranges from 0 to 1, excluding 0 and 1. The frequency modulation order can be set to 0.5. The threshold is used to determine the presence or absence of a signal and needs to be determined according to the actual environment. When the output result is greater than the threshold, it is determined that there is an ice layer curved wave pulse signal in the current frame; otherwise, the data in the current frame is determined to be environmental noise. The threshold is set to the average value of the environmental noise output.

[0029] Furthermore, in step S3, a transformation operation is performed on each frame signal, specifically including:

[0030] Let a frame of data be in the form of p(t). First, the energy of this frame of signal is normalized, that is, each sample value needs to be divided by the vector 2 norm of the frame of data, i.e.:

[0031]

[0032] Then, by transforming x(t), we obtain:

[0033]

[0034] Where x(t) is the acquired signal, f is the frequency, and α is the frequency modulation order. Since it possesses the properties of a Fourier transform, using the Fast Fourier Transform can improve the computation speed. It can be expressed in Fourier transform form as follows:

[0035]

[0036] Where Γ[·] represents the Fast Fourier Transform operation, h(t) α ) = x(t);

[0037] Based on the calculated group velocity of the polar ice layer bending wave, it can be seen that the time-domain signal of the bending wave pulse has frequency modulation characteristics, and the instantaneous frequency decreases as time increases. When α∈(0,1), after transformation, the bending wave with weak signal and wide bandwidth will be converted into a single-frequency signal. The wide bandwidth energy is focused on the single frequency, thereby improving the signal-to-noise ratio, which is beneficial for the detection of polar ice layer signals. Therefore, α=0.5 is determined.

[0038] Furthermore, in step S4, calculating the maximum value of the spectrum after signal transformation for each frame specifically includes: assuming the result for a certain frame is y α (f), the maximum value of the spectral amplitude after the frame transformation is W(t) = max[|y α (f)|].

[0039] Furthermore, in step S5, the presence of a signal in each frame is determined based on a threshold. The determination method is as follows:

[0040]

[0041] Where D is the threshold.

[0042] Compared with the prior art, the advantages of the present invention are as follows:

[0043] This invention addresses the dispersion effect of bent waves in polar ice layers by proposing a signal detection method using a transformation approach. Experimental results show that this method can detect bent wave pulse signals in polar ice layers, and it utilizes Fast Fourier Transform (FFT) to improve computational efficiency. Attached Figure Description

[0044] Figure 1 , Polar ice layer bending wave dispersion;

[0045] Figure 2 Flowchart for polar ice layer pulse signal detection;

[0046] Figure 3 Signal waveforms collected at 50m;

[0047] Figure 4 Signal waveforms collected at 150m;

[0048] Figure 5 50m transformation results;

[0049] Figure 6 150m transformation results;

[0050] Figure 7 50m test results;

[0051] Figure 8 150m test results. Detailed Implementation

[0052] The specific implementation of the present invention is described below with reference to embodiments:

[0053] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the conditions under which the present invention can be implemented. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0054] Furthermore, the terms such as "upper," "lower," "left," "right," "middle," and "one" used in this specification are merely for clarity of description and are not intended to limit the scope of the invention. Any changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0055] Example 1:

[0056] like Figure 2 As shown, the flowchart for detecting polar ice pulse signals provided by this invention has been verified through field experiments. The specific steps are as follows:

[0057] Step 1 uses sensors deployed in polar ice to collect acoustic signals propagating in the environment. The sensor used in the experiment is a vertical accelerometer; besides accelerometers, seismic detectors and other equipment can also be used to collect data. The sampling frequency of the data acquisition device is 25.6kHz. The signal needs to undergo preliminary low-pass filtering to eliminate high-frequency noise. The filtered waveforms at sound source distances of 50m and 150m are shown below. Figure 3 and 4 As shown.

[0058] Step 2 sets the frame length, frame step size, frequency modulation order, and threshold. To meet the real-time requirements of polar signal processing, a frame processing method is used. The frame length refers to the duration of each frame of sampled data; in the experiment, the frame length is set to 0.2 seconds, which corresponds to 5120 consecutive sampling points. The frame step size refers to the time difference between two frames; in the experiment, the frame step size is 10 sampling points.

[0059] Based on the dispersion characteristics of curved waves, it can be known that curved waves exhibit frequency modulation characteristics. The frequency modulation order ranges from 0 to 1, excluding 0 and 1, and can be set to 0.5. A threshold is used to determine the presence or absence of a signal and needs to be determined based on the actual environment. When the output result is greater than the threshold, it is considered that an ice layer curved wave pulse signal exists in the current frame; otherwise, the current frame data is considered to be environmental noise. The threshold is generally set to the average value of the environmental noise output; in experiments, it was set to 2000.

[0060] Step 3 performs a transformation operation on each frame of signal. Let the form of a frame of data be p(t). First, the energy of this frame of signal is normalized, that is, each sample value needs to be divided by the vector 2-norm of the frame of data, i.e.

[0061]

[0062] Then, x(t) is transformed to obtain...

[0063]

[0064] Where α = 0.5. The transformation results for sound source distances of 50m and 150m are as follows: Figure 5 and 6 As shown.

[0065] Step 4: Calculate the maximum value of the spectrum after signal transformation for each frame. Assume the result for a certain frame is y. α (f), the maximum value of the spectrum amplitude after the frame transformation is W(t) = max[y α (f)]. The detection results at sound source distances of 50m and 150m are as follows: Figure 7 and 8 As shown.

[0066] Step 5: Determine if there is a signal in each frame based on the threshold. The determination method is as follows:

[0067]

[0068] Where D is the threshold. According to Figure 7 and Figure 8 As shown, the output W(t) of the ambient noise in the field test is between 1000 and 2000. In the experiment, the threshold can be set to 2000, and the time when the detection result is greater than 2000 is considered to be the time when the signal appears. Figure 7 The signal timing of a 50m pulse sound source is approximately around 0.75e4. Figure 8 The value is around 0.5e4. The results demonstrate that the method proposed in this invention can effectively detect the bending wave pulse signal of polar ice layers.

[0069] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

[0070] Many other changes and modifications can be made without departing from the concept and scope of this invention. It should be understood that this invention is not limited to the specific embodiments, and the scope of this invention is defined by the appended claims.

Claims

1. A method for detecting bending wave pulse signals in polar ice layers, characterized in that, The method includes: S1: Acquire sound signals using sensors and preprocess them to obtain the preprocessed signal; S2: Set frame length, frame span, frequency modulation order, and threshold; S3: Perform transformation processing on the above signals of each frame, specifically including: Let the format of a frame of data be: First, the energy of the frame signal is normalized, that is, each sample value needs to be divided by the vector 2 norm of the data in that frame: ； Then to After transformation, we get: ； in In order to collect signals, For frequency, This represents the frequency modulation order; due to its Fourier transform properties, the Fast Fourier Transform is used to improve computational speed, and it is expressed in Fourier transform form: ； in Represents the Fast Fourier Transform operation. Based on the calculated group velocity of the bending wave in polar ice, it can be seen that the time-domain signal of the bending wave pulse has frequency modulation characteristics; the instantaneous frequency decreases as time increases. During this process, the weak and wide-bandwidth curved wave is converted into a single-frequency signal. The wide-bandwidth energy is focused onto a single frequency, improving the signal-to-noise ratio and facilitating the detection and determination of polar ice signals. ; S4: Calculate the maximum value of the spectrum after the signal transformation of each frame; S5: Use a preset threshold to determine whether there is a signal in the frame data.

2. The method for detecting bending wave pulse signals in polar ice layers according to claim 1, characterized in that, Step S1 specifically includes: Sensors deployed in polar ice are used to collect acoustic signals propagating in the environment. These sensors are either vertical accelerometers or seismic detectors. The sampling frequency of the data acquisition device is 25.6 kHz, and the signal is initially low-pass filtered to eliminate high-frequency noise.

3. The method for detecting bending wave pulse signals in polar ice layers according to claim 1, characterized in that, In step S2, a frame processing method is used to meet the real-time requirements of polar signal processing. The frame length refers to the time length of each frame of sampled data, which is set to 0.2s, i.e., 5120 consecutive sampling points. The frame step size refers to the time difference between two frames, which is set to 10 sampling points. Based on the dispersion characteristics of curved waves, it can be known that curved waves have frequency modulation characteristics. The frequency modulation order ranges from 0 to 1, excluding 0 and 1. The frequency modulation order can be set to 0.

5. The threshold is used to determine the presence or absence of a signal and needs to be determined according to the actual environment. When the output result is greater than the threshold, it is determined that there is an ice layer curved wave pulse signal in the current frame; otherwise, the data in the current frame is determined to be environmental noise. The threshold is set to the average value of the environmental noise output.

4. The method for detecting bending wave pulse signals in polar ice layers according to claim 1, characterized in that, Step S4, which calculates the maximum value of the spectrum after signal transformation for each frame, specifically includes: assuming the result for a certain frame is... The maximum value of the spectrum amplitude after the frame transformation is .

5. The method for detecting bending wave pulse signals in polar ice layers according to claim 1, characterized in that, In step S5, the presence of a signal in each frame is determined based on a threshold. The determination method is as follows: ； in The threshold value is used.

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