Underwater echo ranging method based on mobile phone sound signals

Abstract

The invention discloses an underwater echo ranging method based on mobile phone sound signals. The method comprises the following steps: discontinuously transmitting customized signals by using a mobile phone loudspeaker, receiving return signals by using a mobile phone microphone, and dividing a plurality of key frame signals in the return signals; performing filtering, frequency mixing, separation, denoising and difference processing on each key frame signal and a customized signal in sequence to obtain a frequency difference; performing filtering, fast Fourier transform and difference processing on each key frame signal in sequence to obtain frequency deviation; adding the frequency difference and the frequency offset of each key frame signal to obtain a frequency comprehensive offset value of the key frame signal, further performing multi-frame joint judgment to filter out abnormal values, and averaging residual values to obtain a frequency comprehensive offset mean value; and the distance between the mobile phone and the water bottom is obtained through calculation processing by combining customized signals. According to the invention, high-precision acoustic signal echo distance measurement can be realized in an underwater environment with low cost, and the method can be applied to the fields of drowning detection, swimming rescue and the like.

Description

Technical Field

[0001] The invention belongs to the technical field of distance measurement, and in particular relates to an underwater echo distance measurement method based on mobile phone acoustic signals. Background Art

[0002] In recent years, with the popularity of swimming, the number of home and public swimming pools has increased significantly, resulting in a significant increase in the number of deaths from drowning each year. The widespread occurrence of drowning incidents has increased the responsibility of guardians or lifeguards, but long-term supervision not only requires a lot of manpower costs, but also lifeguards may be distracted, greatly increasing the risk of swimmers drowning. Therefore, how to effectively solve the detection of swimmer safety issues has become an urgent problem to be solved. Existing solutions have their own advantages and disadvantages:

[0003] Visual solution: The visual solution uses visual sensors to observe the situation in the venue in real time to detect drowning. Due to the moderate cost of visual sensors and the convenience of data acquisition, the visual solution has become the mainstream detection method. However, environmental factors such as light and occlusion will greatly affect the visual effect. At the same time, after the swimmer drowns and sinks into the water, the camera will find it difficult to provide timely warnings due to reasons such as hydrological reflections.

[0004] Wearable device solution: Wearable device solution detects human movement in real time through wearable sensors worn by the human body or detects drowning based on the underwater submersion time through water pressure sensors, and reminds swimmers when necessary. However, wearable device solution has poor portability and high customization cost. At the same time, wearable sensors require swimmers to actively seek help when drowning occurs, which will delay the swimmers' golden rescue time; Summary of the invention

[0005] In view of the above problems existing in the prior art, the present invention provides an underwater echo ranging method based on mobile phone acoustic signals, which can achieve high-precision echo ranging underwater and can be applied to scenes such as drowning detection and underwater rescue.

[0006] The present invention adopts the following technical solutions:

[0007] The underwater echo ranging method based on mobile phone acoustic signals of the present invention comprises:

[0008] Step (1): The speaker of the mobile phone is placed underwater and transmits a customized signal to the surrounding environment intermittently, and the customized signal is received as a return signal through the microphone of the mobile phone;

[0009] Step (2): select a part of the return signal and divide it into multiple signal segments, each of which is used as a key frame signal;

[0010] Step (3): each key frame signal in step (2) is combined with the customized signal and filtered, mixed, separated, denoised, and subjected to difference processing to obtain its own frequency difference Δf;

[0011] Step (4): After filtering, fast Fourier transform and difference processing of each key frame signal in step (2), the frequency offset Δf is obtained. t ;

[0012] Step (5): According to the frequency difference Δf and frequency offset Δf of each key frame signal t The frequency comprehensive offset values ​​of all key frame signals are jointly judged and calculated to obtain the distance between the mobile phone and the bottom of the water.

[0013] In the step (1), the custom signal c(t) is set according to the following formula:

[0014]

[0015] The customized signal is mainly composed of a linear frequency modulation signal and a single frequency signal, wherein f min represents the minimum frequency of the linear frequency modulation signal, t represents time, T represents the period of the linear frequency modulation signal, t∈[0,T], B represents the bandwidth of the linear frequency modulation signal, f c represents the frequency of a single-frequency signal, Indicates the phase of a single frequency signal.

[0016] In step (1), the method of using the mobile phone speaker to intermittently transmit the customized signal is specifically as follows:

[0017] S1, using the mobile phone speaker to transmit a cycle of customized signal and then stop transmitting for one cycle;

[0018] S2, and repeat the cycle.

[0019] The duration of the key frame signal in step (2) is twice the period T of the custom signal.

[0020] There is a certain interval between the frequencies of the single-frequency signals in the customized signals set for multiple mobile phones, which is used to distinguish different mobile phones.

[0021] The step (3) is specifically:

[0022] For each keyframe signal, perform the following operations:

[0023] Step (3.1): filtering the key frame signal, filtering the single frequency signal in the key frame signal, and obtaining the linear frequency modulation signal in the key frame signal;

[0024] Step (3.2): Mixing the linear frequency modulation signal in the key frame signal with the linear frequency modulation signal in the custom signal to obtain a mixed signal;

[0025] Step (3.3): performing signal separation on the mixed signal by using a multiple signal classification algorithm to obtain a linear frequency modulation signal in which a direct signal and an echo signal are separated from the mixed signal;

[0026] Step (3.4): Combine the constant false alarm rate algorithm to remove the noise signal from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixing signal, and obtain a spectrum diagram after the noise signal is removed;

[0027] Step (3.5): The frequency corresponding to the peak with the largest power on the spectrum after removing the noise signal is taken as the direct signal frequency f1, and the frequency corresponding to the peak with the largest power after removing the peak corresponding to the direct signal frequency is taken as the echo signal frequency f t , the direct signal frequency f1 and the echo signal frequency f t The frequency difference is obtained by subtracting the frequency from the key frame signal.

[0028] The step (3.2) is specifically as follows: extracting the linear frequency modulation signal in the customized signal in the same period and frequency band as the linear frequency modulation signal in the key frame signal, and then mixing it with the linear frequency modulation signal in the key frame signal to obtain a mixed signal.

[0029] The step (4) is specifically:

[0030] For each keyframe signal, perform the following operations:

[0031] Step (4.1): filtering the key frame signal, filtering the linear frequency modulation signal in the key frame signal, and obtaining the single frequency signal in the key frame signal;

[0032] Step (4.2): Perform fast Fourier transform on the single-frequency signal in step (4.1) to obtain a frequency spectrum of the single-frequency signal in the key frame signal;

[0033] Step (4.3): Compare the frequency corresponding to the maximum peak on the spectrum diagram of the single-frequency signal in the key frame signal with the frequency f of the single-frequency signal c Subtract and get the frequency offset Δf t .

[0034] The step (5) is specifically as follows: the frequency difference Δf and the frequency offset Δf of each key frame signal are t Add them together to get their own frequency integrated offset value; then perform multi-frame joint judgment on the frequency integrated offset values ​​of all key frame signals to filter out abnormal values, and take the average value of the remaining frequency integrated offset values ​​to get the frequency integrated offset mean Δf avg; Combine the custom signal and the frequency composite offset mean Δf avg Calculation is performed to obtain the distance between the mobile phone and the bottom of the water.

[0035] The distance between the mobile phone and the bottom of the water is specifically obtained by the following formula:

[0036]

[0037] Wherein, d represents the distance between the mobile phone and the bottom of the water, c represents the propagation speed of sound in water, B represents the bandwidth of the linear frequency modulation signal in the customized signal, and T represents the period of the linear frequency modulation signal in the customized signal.

[0038] The beneficial effects of the present invention are:

[0039] 1. The present invention adopts a customized signal in the range of 17kHz-19kHz as an excitation signal, which can reduce interference to humans on the one hand, and on the other hand, the frequency band can maintain a large working range in media such as water that severely suppress high-frequency signals.

[0040] 2. The present invention adopts a multiple signal classification algorithm and a constant false alarm rate algorithm to extract echo signals and process noise, adopts a frequency modulation continuous wave algorithm to calculate the frequency difference, and combines a multi-frame joint judgment and coding scheme to achieve optimization and multi-device multiplexing design. Then, a single-frequency signal in the customized signal is used to calculate the frequency offset, and the frequency difference is combined to calculate the distance between the mobile phone and the bottom of the swimming pool.

[0041] 3. The underwater echo ranging method based on mobile phone acoustic signals proposed in the present invention has the advantages of reasonable cost and portability, and is suitable for underwater scenarios that require real-time calculation and non-active excitation rescue. Therefore, the present invention has broad application prospects in multiple fields such as drowning detection and underwater rescue.

[0042] 4. The present invention proposes an underwater echo ranging method based on mobile phone acoustic signals, which can be used in multiple scenarios such as drowning detection. The solution uses the mobile phone to send out acoustic signals in real time, which are reflected back to the device through the bottom of the water, and uses the time difference to perform echo ranging, and judges the swimmer's state by the change in the swimmer's distance from the bottom of the water. This technology integrates a portable mobile phone with an underwater echo ranging solution based on acoustic signals, avoiding the defect that wearable devices require swimmers to spontaneously ask for help, and provides a cost-effective and real-time underwater echo measurement solution that can be applied to drowning detection, underwater rescue and other scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a flow chart of the underwater echo ranging method based on mobile phone acoustic signal of the present invention;

[0045] Figure 2 It is a schematic diagram of underwater signal;

[0046] Figure 3 It is a schematic diagram of the signal design scheme;

[0047] Figure 4 is a schematic diagram of frequency compensation;

[0048] Figure 5 This is the echo ranging timing result diagram;

[0049] Figure 6 It is the cumulative distribution function diagram of echo ranging error. DETAILED DESCRIPTION

[0050] The following describes the embodiments of the present invention through specific embodiments, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0051] like Figure 1 As shown, the specific embodiment of the underwater echo ranging method of the present invention includes the following steps:

[0052] Step (1): The speaker of the smartphone is placed underwater and transmits a customized signal to the surrounding environment intermittently, and the transmitted customized signal is received by the smartphone microphone as a return signal, such as Figure 2 As shown, the return signal includes a direct signal, an echo signal and a noise signal. The echo signal is the signal received by the microphone of the smartphone after the transmitted custom signal is reflected by the bottom of the water;

[0053] The custom signal c(t) is set according to the following formula:

[0054]

[0055] The customized signal is mainly composed of linear frequency modulation signal and single frequency signal, where f min represents the minimum frequency of the linear frequency modulation signal, t represents time, T represents the period of the linear frequency modulation signal, t∈[0,T], B represents the bandwidth of the linear frequency modulation signal, f c represents the frequency of a single-frequency signal, Indicates the phase of a single frequency signal.

[0056] In this embodiment, the bandwidth B of the signal is set to 2kHz, the period T is set to 20ms, and the minimum frequency f is set to 2kHz. min is 17kHz, the starting frequency of the single frequency signal is f c Above 19kHz.

[0057] The linear frequency modulation signal has good correlation, its frequency changes linearly with time, and it is the signal frequency band that is least attenuated by the water medium among the inaudible sound frequency bands that can be selected by the mobile phone.

[0058] There is a certain interval between the frequencies of the single-frequency signals in the customized signals set by multiple smartphones, which is used to distinguish different smartphones. Figure 3 As shown, when multiple smartphones are used at the same time, the frequency band of the single-frequency signal in the customized signal is the identity information for different mobile phones to identify each other. In this embodiment, combined with the underwater Doppler effect information, a 500Hz protection interval is set between each single-frequency signal above 19kHz, and within the 3.5kHz available frequency band between 19.5kHz and 23kHz, 8 different single-frequency signals can be set at the same time, and the linear frequency modulation signal can be divided into a frequency modulation signal with increasing linear frequency and a frequency modulation signal with decreasing linear frequency, and a total of 16 devices can be set with identity information at the same time.

[0059] The customized signal transmitted intermittently by the smartphone speaker is as follows:

[0060] S1, using the smartphone speaker to transmit a custom signal for one cycle and then stop transmitting for one cycle;

[0061] S2, and repeat this cycle.

[0062] Step (2): select a continuous part from the return signal and divide it into multiple signal segments, each of which is used as a key frame signal;

[0063] The duration of the key frame signal is twice the custom signal period T. In this embodiment, the key frame signal is set to 40ms;

[0064] Step (3): each key frame signal is combined with the customized signal and filtered, mixed, separated, denoised, and subjected to difference processing to obtain its own frequency difference Δf;

[0065] The specific steps are as follows:

[0066] For each keyframe signal, perform the following operations:

[0067] Step (3.1): filtering the key frame signal with a filter to filter the single frequency signal in the key frame signal to obtain a linear frequency modulation signal in the key frame signal;

[0068] Step (3.2): Mixing the linear frequency modulation signal in the key frame signal with the linear frequency modulation signal in the custom signal to obtain a mixed signal, and using fast Fourier transform on the mixed signal to obtain a frequency spectrum of the mixed signal for input into a multiple signal classification algorithm;

[0069] Specifically, a linear frequency modulation signal in the same period and frequency band as the linear frequency modulation signal in the key frame signal is extracted from the linear frequency modulation signal in the custom signal, and then mixed with the linear frequency modulation signal in the key frame signal to obtain a mixed signal.

[0070] Step (3.3): Separate the mixed signal by a multiple signal classification algorithm to separate the direct signal and the echo signal, extract the real echo signal that is submerged by the direct signal due to the high speed of sound underwater, and obtain a linear frequency modulation signal in which the direct signal and the echo signal are separated in the mixed signal;

[0071] The multiple signal classification algorithm is as follows: first, the number of sampled signals M is customized, and then a customized Fourier frequency vector a with a length of M is used. z To estimate the spectrum of the main signal, set it according to the following formula:

[0072]

[0073] Where Q is the number of discrete points obtained after fast Fourier transform, and z is the index of the discrete frequency, ranging from 1 to Q-1. In this embodiment, M is set to 230 to adapt to the computing power of smartphones. The entire frequency space A is constructed by expanding the vectors of all Q frequencies, and is set to:

[0074] A=[a1,a2,…,a Q-1 ] T

[0075] In the time domain, the mixed signal is divided into sub-signals e of length M t,p , t is the time index of the sub-signal, p is the index of the sub-signal, ranging from 0 to LM-1, where L is the number of sampling points of the mixed signal, and calculates the covariance matrix of the sub-signal Then, the covariance matrix is ​​decomposed into eigenvalues, and the eigenvalues ​​are arranged in ascending order. The eigenvalues ​​with a custom number D are selected to form the noise subspace R n, the noise subspace R n and signal subspace A ′ z Orthogonal, signal subspace A ′ z It is a part of the frequency space A and is expressed as follows: R n ·A ′ z = 0. Therefore, a spectrum P composed of the main frequency components of the mixed signal can be obtained, which is set according to the following formula:

[0076]

[0077] The echo signal peak that is submerged by the direct peak can be extracted through the multiple signal classification algorithm.

[0078] Step (3.4): Combine the constant false alarm rate algorithm to remove the noise signal from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixing signal, and obtain a spectrum diagram after the noise signal is removed;

[0079] The specific constant false alarm rate algorithm is: based on the multiple signal classification algorithm, the constant false alarm rate algorithm is applied to the mixed signal. The core of the algorithm is to smooth the spectrum amplitude of the surrounding frequencies, i.e. the reference unit, so as to estimate the frequency of the background clutter and play a role in denoising. The smoothed frequency is set according to the following formula:

[0080]

[0081] Wherein, H is the number of reference units, which is set to 70 in this embodiment, and P z, is the spectrum obtained after the multiple signal classification algorithm. The underwater echo signal follows the Rayleigh distribution, while the noise follows the Gaussian distribution, but these two distributions will become exponential distributions after passing through the square law detector. Therefore, the probability density function P of the signal and noise fa , and then the false alarm rate is obtained. Since the false alarm rate is defined based on experience, the threshold factor can be obtained and expressed as follows:

[0082]

[0083] Then the threshold G of the constant false alarm rate can be obtained by the threshold factor β, which is set according to the following formula:

[0084]

[0085] The discrete spectrum part below the threshold is subjected to constant false alarm rate threshold noise filtering. The algorithm can automatically adjust the detection threshold according to the environmental noise and signal strength to filter out the reflected and refracted signals.

[0086] Step (3.5): The frequency corresponding to the peak with the largest power on the spectrum after removing the noise signal is taken as the direct signal frequency f1, and the frequency corresponding to the peak with the largest power after removing the peak corresponding to the direct signal frequency is taken as the echo signal frequency f t , the direct signal frequency f1 and the echo signal frequency f t The frequency difference is obtained by subtraction as the frequency difference Δf of the key frame signal. The horizontal axis of the spectrum is frequency, and the vertical axis is power.

[0087] Therefore, each key frame signal obtains its own frequency difference Δf.

[0088] Step (4): For each key frame signal in step (2), the frequency shift Δf is obtained by filtering, fast Fourier transforming, and performing difference processing in sequence through the frequency modulation continuous wave method. t ;

[0089] The specific steps are as follows:

[0090] For each keyframe signal, perform the following operations:

[0091] Step (4.1): filtering the key frame signal with a filter to filter the linear frequency modulation signal in the key frame signal to obtain a single frequency signal in the key frame signal;

[0092] Step (4.2): Perform fast Fourier transform on the single-frequency signal in step (4.1) to obtain a frequency spectrum of the single-frequency signal in the key frame signal;

[0093] Step (4.3): Compare the frequency corresponding to the maximum peak on the spectrum diagram of the single-frequency signal in the key frame signal with the frequency f of the single-frequency signal c Subtract and get the frequency offset Δf t ;

[0094] Thus, each key frame signal obtains its own frequency offset Δf t .

[0095] Step (5): According to the frequency difference Δf and frequency offset Δf of each key frame signal t The frequency comprehensive offset values ​​of all key frame signals are jointly judged and calculated to obtain the distance between the smartphone and the bottom of the water.

[0096] Specifically: Figure 4 As shown, the frequency difference Δf and frequency offset Δf of each key frame signal are t Add them together to get their own frequency integrated offset value; then perform multi-frame joint judgment on the frequency integrated offset values ​​of all key frame signals to filter out abnormal values, and take the average value of the remaining frequency integrated offset values ​​to get the frequency integrated offset mean Δf avg; Combine the custom signal and the frequency composite offset mean Δf avg Calculation is performed to obtain the distance between the smartphone and the bottom of the water.

[0097] The frequency comprehensive offset values ​​of all key frame signals are judged by multi-frame joint judgment through the quartile method to filter out abnormal values, and the remaining values ​​are averaged to obtain the frequency comprehensive offset mean Δf avg ;

[0098] The multi-frame joint judgment is to determine the upper limit of the outlier value E by the quartile method. max and the lower bound E min , and the abnormal value is the value that is not in the range. It is used to filter out multipath signals from other mobile devices or reflected by the underwater environment.

[0099] The specific multi-frame joint judgment is as follows: Figure 2 As shown in the figure, when the strength of the signal received by the smartphone from other underwater devices is similar to that of the reflected signal, the quartile method is used to perform multi-frame joint judgment, and the quartiles Q1, Q2, and Q3 of the frequency difference in the 10-frame signal are calculated and set according to the following formula:

[0100] E min =Q1-k(Q3-Q1),E max =k(Q3-Q1)

[0101] In the formula, E min and E max are the upper and lower bounds of the abnormal value, and k is the ratio, which is set to 1.5. Data beyond the upper and lower bounds of the abnormal value is abnormal data, which may come from signals from other devices or underwater noise. In this embodiment, each key frame signal is 40ms. After multi-frame joint judgment of 10 frames of signals, the remaining signal frequency difference is averaged, and a frequency comprehensive offset mean Δf is output every 0.4s. avg .

[0102] The distance between the smartphone and the bottom of the water is obtained by the following formula:

[0103]

[0104] Wherein, d represents the distance between the smartphone and the bottom of the water, c represents the propagation speed of sound in water, B represents the bandwidth of the linear frequency modulation signal in the customized signal, and T represents the period of the linear frequency modulation signal in the customized signal.

[0105] like Figure 5 and Figure 6As shown in the figure, the echo ranging error results in underwater scenes are: the median error of the echo ranging at 1.5m from the bottom of the water is 0.03m; the median error of the echo ranging at 2m from the bottom of the water is 0.05m; the median error of the echo ranging at 2.5m from the bottom of the water is 0.07m. It can be seen that the underwater echo ranging method based on the acoustic signal of the smartphone achieves centimeter-level precision measurement in underwater scenes, and can provide real-time monitoring solutions in combination with actual scene requirements such as drowning.

[0106] The embodiments described above are merely descriptions of preferred implementation modes of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope of the present invention.

Claims

1. An underwater echo ranging method based on mobile phone acoustic signals, characterized in that: The method comprises the following steps: Step (1): The speaker of the mobile phone is placed underwater and transmits a customized signal to the surrounding environment intermittently, and the customized signal is received as a return signal through the microphone of the mobile phone; Step (2): select a part of the return signal and divide it into multiple signal segments, each of which is used as a key frame signal; Step (3): each key frame signal in step (2) is combined with the customized signal and filtered, mixed, separated, denoised, and subjected to difference processing to obtain its own frequency difference Δf; Step (4): After filtering, fast Fourier transform and difference processing of each key frame signal in step (2), the frequency offset Δf is obtained. t ; Step (5): According to the frequency difference Δf and frequency offset Δf of each key frame signal t The frequency comprehensive offset values ​​of all key frame signals are jointly judged and calculated to obtain the distance between the mobile phone and the bottom of the water.

2. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1 is characterized in that: In the step (1), the custom signal c(t) is set according to the following formula: The customized signal is mainly composed of a linear frequency modulation signal and a single frequency signal, wherein f min represents the minimum frequency of the linear frequency modulation signal, t represents time, T represents the period of the linear frequency modulation signal, t∈[0,T], B represents the bandwidth of the linear frequency modulation signal, f c represents the frequency of a single-frequency signal, Indicates the phase of a single frequency signal.

3. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1 is characterized in that: In step (1), the method of using the mobile phone speaker to intermittently transmit the customized signal is specifically as follows: S1, using the mobile phone speaker to transmit a cycle of customized signal and then stop transmitting for one cycle; S2, and repeat the cycle.

4. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The duration of the key frame signal in step (2) is twice the period T of the custom signal.

5. The underwater echo ranging method based on mobile phone acoustic signals according to claim 2 is characterized in that: There is a certain interval between the frequencies of the single-frequency signals in the customized signals set for multiple mobile phones, which is used to distinguish different mobile phones.

6. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The step (3) is specifically: For each keyframe signal, perform the following operations: Step (3.1): filtering the key frame signal, filtering the single frequency signal in the key frame signal, and obtaining the linear frequency modulation signal in the key frame signal; Step (3.2): Mixing the linear frequency modulation signal in the key frame signal with the linear frequency modulation signal in the custom signal to obtain a mixed signal; Step (3.3): performing signal separation on the mixed signal by using a multiple signal classification algorithm to obtain a linear frequency modulation signal in which a direct signal and an echo signal are separated from the mixed signal; Step (3.4): Combine the constant false alarm rate algorithm to remove the noise signal from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixing signal, and obtain a spectrum diagram after the noise signal is removed; Step (3.5): The frequency corresponding to the peak with the largest power on the spectrum after removing the noise signal is taken as the direct signal frequency f1, and the frequency corresponding to the peak with the largest power after removing the peak corresponding to the direct signal frequency is taken as the echo signal frequency f t , the direct signal frequency f1 and the echo signal frequency f t The frequency difference is obtained by subtracting the frequency from the key frame signal.

7. The underwater echo ranging method based on mobile phone acoustic signals according to claim 6, characterized in that: The step (3.2) is specifically as follows: extracting the linear frequency modulation signal in the customized signal in the same period and frequency band as the linear frequency modulation signal in the key frame signal, and then mixing it with the linear frequency modulation signal in the key frame signal to obtain a mixed signal.

8. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The step (4) is specifically: For each keyframe signal, perform the following operations: Step (4.1): filtering the key frame signal, filtering the linear frequency modulation signal in the key frame signal, and obtaining the single frequency signal in the key frame signal; Step (4.2): Perform fast Fourier transform on the single-frequency signal in step (4.1) to obtain a frequency spectrum of the single-frequency signal in the key frame signal; Step (4.3): Compare the frequency corresponding to the maximum peak on the spectrum diagram of the single-frequency signal in the key frame signal with the frequency f of the single-frequency signal c Subtract and get the frequency offset Δf t .

9. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The step (5) is specifically as follows: the frequency difference Δf and the frequency offset Δf of each key frame signal are t Add them together to get their own frequency integrated offset value; then perform multi-frame joint judgment on the frequency integrated offset values ​​of all key frame signals to filter out abnormal values, and take the average value of the remaining frequency integrated offset values ​​to get the frequency integrated offset mean Δf avg ; Combine the custom signal and the frequency composite offset mean Δf avg Calculation is performed to obtain the distance between the mobile phone and the bottom of the water.

10. The underwater echo ranging method based on mobile phone acoustic signals according to claim 9, characterized in that: The distance between the mobile phone and the bottom of the water is specifically obtained by the following formula: Wherein, d represents the distance between the mobile phone and the bottom of the water, c represents the propagation speed of sound in water, B represents the bandwidth of the linear frequency modulation signal in the customized signal, and T represents the period of the linear frequency modulation signal in the customized signal.

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