A method for underwater echo ranging based on mobile phone acoustic signals

Abstract

The application discloses a kind of underwater echo ranging method based on mobile phone sound signal.This method will mobile phone loudspeaker intermittent emission custom signal and utilize mobile phone microphone to receive return signal, divide multiple key frame signals in return signal;Each key frame signal is combined with custom signal in turn after filtering, mixing, separation, denoising, difference processing and obtains frequency difference;Each key frame signal is sequentially filtered, fast fourier transform, difference processing and obtains frequency shift;The frequency difference and frequency shift of each key frame signal are added to obtain the frequency comprehensive shift value of itself, then multiple frames are combined to judge and filter out abnormal value, and the average value of the remaining value is obtained to obtain the frequency comprehensive shift mean value;Combined with custom signal to obtain the distance of mobile phone from water bottom.The application can realize high-precision acoustic signal echo ranging in underwater environment at low cost, and can be applied to drowning detection, swimming rescue and other fields.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of ranging, and particularly relates to an underwater echo ranging method based on a mobile phone sound signal. BACKGROUND

[0002] In recent years, with the popularity of swimming, the number of family and public swimming pools has increased significantly, resulting in a significant increase in the number of annual drowning deaths. The widespread occurrence of drowning incidents increases the responsibility of guardians or lifeguards, but long-term supervision not only requires a large amount of human cost, but also the lifeguards may be distracted, greatly increasing the risk of drowning for swimmers. Therefore, how to effectively solve the detection of the safety problem of swimmers has become a problem to be solved. The existing solutions have advantages and disadvantages:

[0003] Visual solution: The visual solution realizes the detection of the drowning state by observing the situation in the field in real time through a visual sensor. Since the visual sensor has moderate cost and convenient data acquisition, the visual solution has become the mainstream detection method at present. However, environmental factors such as light and shielding will greatly affect the visual effect, and at the same time, after the swimmer drowns, the swimmer sinks into the water, and the camera will be difficult to achieve timely warning due to water reflection and other reasons;

[0004] Wearable device solution: The wearable device solution detects the drowning of the swimmer in real time by wearing a wearable sensor on the human body or by a water pressure sensor according to the submerging time underwater, and reminds the swimmer when necessary. However, the wearable device solution has poor portability and high customization cost, and at the same time, the wearable sensor needs the swimmer to actively seek help when drowning occurs, which will delay the golden rescue time of the swimmer; SUMMARY

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

[0006] The application adopts the following technical solutions:

[0007] The underwater echo ranging method based on a mobile phone sound signal of the application comprises:

[0008] Step (1): The loudspeaker of the mobile phone is arranged underwater and intermittently emits a customized signal to the surrounding environment, and the customized signal is received by the microphone of the mobile phone as a return signal;

[0009] Step (2): A part of the return signal is selected and divided into multiple signal segments, and each signal segment is used as a key frame signal;

[0010] Step (3): the frequency difference Δf of each key frame signal in step (2) is obtained after the combination of the customized signal is sequentially filtered, mixed, separated, denoised and subtracted;

[0011] Step (4): the frequency offset Δf of each key frame signal in step (2) is obtained after the combination of the customized signal is sequentially filtered, fast Fourier transformed and subtracted t ;

[0012] Step (5): the frequency difference Δf and the frequency offset Δf of each key frame signal are used to calculate the frequency comprehensive offset value of all key frame signals. t The distance of the mobile phone from the water bottom is obtained by multi-frame joint judgment and calculation processing of the frequency comprehensive offset value of all key frame signals.

[0013] In the step (1), the customized 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 the single frequency signal, represents the phase of the single frequency signal.

[0016] In the step (1), the customized signal is intermittently emitted by the mobile phone speaker, which is specifically:

[0017] S1, emitting a period of customized signal by the mobile phone speaker and stopping emitting for a period;

[0018] S2, and reciprocating.

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

[0020] The frequencies of the single frequency signals in the customized signals of the plurality of mobile phones are spaced apart, which is used to distinguish different mobile phones.

[0021] The step (3) is specifically:

[0022] The following operations are performed on each key frame signal:

[0023] Step (3.1): filtering the key frame signal to filter the single frequency signal in the key frame signal to obtain 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 the direct signal and the echo signal are separated from the mixed signal;

[0026] Step (3.4): Using a constant false alarm rate algorithm, the noise signal is removed from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixed signal to 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 , direct signal frequency f1 and echo signal frequency f t The frequency difference is obtained by subtraction as the frequency difference Δf of the key frame signal.

[0028] The step (3.2) is specifically as follows: extracting the linear frequency modulation signal in the custom 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 as follows:

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

[0031] Step (4.1): filtering the key frame signal to filter the linear frequency modulation signal in the key frame signal to obtain a 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 the 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 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 up to get its 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 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] Where d represents the distance between the mobile phone and the bottom of the water, c represents the speed of sound propagation in water, B represents the bandwidth of the linear frequency modulation signal in the custom signal, and T represents the period of the linear frequency modulation signal in the custom 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 the excitation signal. On the one hand, it can reduce interference to humans. On the other hand, this frequency band can maintain a large working range in media such as water that severely suppress high-frequency signals.

[0040] 2. The present invention uses a multiple signal classification algorithm and a constant false alarm rate algorithm to extract echo signals and process noise, a frequency-modulated 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, the 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. It 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. This invention proposes an underwater echo ranging method based on mobile phone acoustic signals, which can be used in various scenarios, including drowning detection. This solution uses the mobile phone to emit real-time acoustic signals, which are reflected from the bottom of the water and returned to the device. The time difference is used for echo ranging, and the swimmer's status is determined by the change in the swimmer's distance from the bottom. By integrating a portable mobile phone with an underwater echo ranging solution based on acoustic signals, this technology avoids the drawback of wearable devices that requires the swimmer to spontaneously call for help. It provides a cost-effective and real-time underwater echo measurement solution that can be applied to scenarios such as drowning detection and underwater rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative effort based on these drawings.

[0044] Figure 1 is a flow chart of the underwater echo ranging method based on the mobile phone sound signal according to the present application;

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

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

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

[0048] Figure 5 is a timing result diagram of echo ranging;

[0049] Figure 6 is an error accumulation distribution function diagram of echo ranging. DETAILED DESCRIPTION

[0050] The embodiments of the present application will be described below through specific, concrete embodiments, and those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in the present description. The present application can also be implemented or applied through other different specific embodiments, and each detail in the present description can be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0051] As shown in Figure 1 , the specific embodiment of the underwater echo ranging method according to the present application includes the following steps:

[0052] Step (1): The loudspeaker of the smart phone is arranged underwater and intermittently emits a customized signal to the surrounding environment, and the emitted customized signal is received by the smart phone microphone as a return signal, as shown in Figure 2 , the return signal includes a direct signal, an echo signal and a noise signal, and the echo signal is the signal received by the smart phone microphone after the emitted customized signal is reflected by the water bottom;

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

[0054]

[0055] The customized signal mainly consists 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, and its frequency changes linearly with time. Moreover, among the inaudible sound frequency bands that can be selected by mobile phones, it is the signal frequency band that is least attenuated by the water medium.

[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 simultaneously, the frequency band of the single-frequency signal in the customized signal serves as identification information for different smartphones. In this embodiment, a 500Hz guard interval is set between each single-frequency signal above 19kHz, taking into account the underwater Doppler effect. Within the 3.5kHz available frequency band between 19.5kHz and 23kHz, eight different single-frequency signals can be set simultaneously. Furthermore, the linear frequency modulation signal can be divided into an increasing linear frequency modulation signal and a decreasing linear frequency modulation signal. This allows for simultaneous identification of up to 16 devices.

[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 of 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 the 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 performing fast Fourier transform on the mixed signal to obtain a spectrum of the mixed signal for input into the multiple signal classification algorithm;

[0069] Specifically, a linear frequency modulation signal with the same time 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 using a multiple signal classification algorithm to separate the direct signal from the echo signal. Extract the true echo signal that is submerged by the direct signal due to the high speed of sound underwater, and obtain a linear frequency modulation signal that separates the direct signal from the echo signal in the mixed signal.

[0071] The specific algorithm of multiple signal classification is as follows: first, customize the number of sampled signals M, and then use the customized Fourier frequency vector a of length M 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 the 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 accommodate the computing power of smartphones. The entire frequency space A is constructed by expanding the vectors of all Q frequencies and is set according to the following formula:

[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 calculate 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, 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 consisting 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): Using a constant false alarm rate algorithm, the noise signal is removed from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixed signal to obtain a spectrum diagram after the noise signal is removed;

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

[0080]

[0081] Where H is the number of reference units, which is set to 70 in this embodiment, and P z, This is the spectrum obtained after the multiple signal classification algorithm. The underwater echo signal obeys the Rayleigh distribution, while the noise obeys 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 is 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 constant false alarm rate threshold G 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 , direct signal frequency f1 and 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] Thus, each key frame signal obtains its own frequency difference Δf.

[0088] Step (4): Each key frame signal in step (2) is filtered, fast Fourier transformed, and processed by frequency modulation continuous wave method to obtain the frequency offset Δf 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 the 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 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 up to get its 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 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 integrated 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 average of the remaining values ​​is taken to obtain the frequency integrated offset mean Δf avg ;

[0098] The multi-frame joint judgment is to determine the upper bound of the outlier value E by the quartile method. max and the lower bound E min , abnormal values ​​are values ​​outside the range. Used to filter out multipath signals from other mobile devices or reflected by underwater environments.

[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 frames of signal are calculated and set according to the following formula:

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

[0101] Where, E min and E max are the upper and lower bounds of the outlier value, and k is the ratio, which is set to 1.5. Data that exceeds the upper and lower bounds of the outlier value is considered outlier 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 signal, the remaining signal frequency difference is averaged, and a frequency integrated offset mean Δf is output every 0.4s. avg .

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

[0103]

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

[0105] like Figure 5 and Figure 6As shown in the figure, the echo ranging error results in underwater scenarios are: the median error of echo ranging at 1.5 meters from the bottom is 0.03 meters; the median error of echo ranging at 2 meters from the bottom is 0.05 meters; and the median error of echo ranging at 2.5 meters from the bottom is 0.07 meters. This shows that the underwater echo ranging method based on smartphone acoustic signals achieves centimeter-level accuracy in underwater scenarios and can provide real-time monitoring solutions based on the needs of actual scenarios such as drowning.

[0106] The embodiments described above are merely descriptions of preferred implementations 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 fall within the scope of protection of the present invention.

Claims

1. A method for underwater echo ranging 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 portion of the return signal and divide it into multiple signal segments, each of which is used as a key frame signal; Step (3): Combine each key frame signal in step (2) with the customized signal and perform filtering, mixing, separation, denoising, and difference processing in sequence 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 Perform multi-frame joint judgment and calculation on the frequency comprehensive offset values ​​of all key frame signals to obtain the distance between the mobile phone and the bottom of the water; In step (1), the custom signal c(t) is set according to the following formula: The customized signal mainly consists 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; The step (5) is specifically as follows: the frequency difference Δf and the frequency offset Δf of each key frame signal are t Add up to get its 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 of the remaining frequency integrated offset values ​​to get the frequency integrated offset mean Δf avg ; Combine the custom signal and the frequency integrated offset mean Δf avg Perform calculations to obtain the distance between the mobile phone and the bottom of the water; The distance between the mobile phone and the bottom of the water is specifically obtained by the following formula: Where d represents the distance between the mobile phone and the bottom of the water, c represents the speed of sound propagation in water, B represents the bandwidth of the linear frequency modulation signal in the custom signal, and T represents the period of the linear frequency modulation signal in the custom signal.

2. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, 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. Use the mobile phone speaker to transmit a customized signal for one cycle and then stop transmitting for one cycle; S2, and repeat the process.

3. 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.

4. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, 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.

5. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The step (3) is specifically as follows: For each keyframe signal, perform the following operations: Step (3.1): filtering the key frame signal to filter the single frequency signal in the key frame signal to obtain 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 the direct signal and the echo signal are separated from the mixed signal; Step (3.4): Using a constant false alarm rate algorithm, the noise signal is removed from the linear frequency modulation signal separated from the direct signal and the echo signal in the mixed signal to 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 , direct signal frequency f1 and echo signal frequency f t The frequency difference is obtained by subtraction as the frequency difference Δf of the key frame signal.

6. The underwater echo ranging method based on mobile phone acoustic signals according to claim 5, characterized in that: The step (3.2) is specifically as follows: extracting the linear frequency modulation signal in the custom 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.

7. The underwater echo ranging method based on mobile phone acoustic signals according to claim 1, characterized in that: The step (4) is specifically as follows: For each keyframe signal, perform the following operations: Step (4.1): filtering the key frame signal to filter the linear frequency modulation signal in the key frame signal to obtain a 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 the 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 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 .

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