Sound wave signal arrival time delay detection method and device and electronic equipment

Abstract

The present disclosure relates to the technical field of acoustic wave indoor positioning, and discloses an acoustic wave signal time delay detection method, device and electronic equipment. The method comprises: extracting an effective received acoustic wave signal containing useful components within a target bandwidth from an original received acoustic wave signal; constructing a reference acoustic wave signal matched with the characteristics of the acoustic wave signal emitted by a target sound source based on the target bandwidth and a set signal duration; obtaining a generated reference signal CAF image and a received signal CAF image through a complex cross-correlation operation, and determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image; generating a Radon projection curve based on the received signal CAF image and the optimal Radon projection angle, and determining the earliest arrival time delay of the acoustic wave signal emitted by the target sound source according to the curve. The above method can accurately obtain the earliest arrival time delay, which helps to improve the stability and ranging accuracy of the TDOA positioning system.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of acoustic indoor positioning, for example to an acoustic signal time of arrival detection method, device and electronic equipment. BACKGROUND

[0002] With the continuous development of application scenarios such as smart city, intelligent security, indoor navigation and emergency rescue, the demand for technical means to achieve high-precision positioning under the condition of no GPS signal coverage is increasing. Acoustic indoor positioning has become one of the hot research and application directions in recent years due to its low cost, flexible deployment and strong environmental adaptability. Compared with electromagnetic waves and other signals, acoustic waves have lower propagation speed and higher time resolution in near-distance propagation environment, and can achieve centimeter-level ranging accuracy, so they are particularly suitable for solving the problem of target positioning in complex indoor environment. In scenarios such as smart home control, robot navigation, intelligent manufacturing line monitoring, barrier-free auxiliary positioning, and precise guidance in places with dense flow of people such as shopping malls and museums, acoustic positioning shows good application prospects.

[0003] Among many acoustic positioning methods, the positioning method based on time difference of arrival (TDOA) is widely used due to its simple structure and high estimation accuracy. The TDOA method measures the time difference of arrival of the same sound source signal at different receivers by arranging multiple receivers at known positions, and calculates the sound source position combined with the sound speed information. This method only relies on the relative time synchronization between sound sources, without absolute synchronization between receivers and sound sources, which reduces the complexity of system design and is suitable for resource-limited or dynamically deployed application scenarios.

[0004] In the TDOA positioning framework, the audio arrival time (AAT) of the acoustic signal is the specific time point at which the acoustic signal propagates from the sound source to the receiver and is detected. Based on the arrival time, the earliest time delay can be further defined as: the time interval between the time when the sound source transmits the signal and the time when it first arrives at the receiver along the shortest path. This time delay reflects the time required for the acoustic signal to travel the shortest path from the sound source to the receiver. The above shortest path usually corresponds to the direct wave path, i.e. the path along which the signal propagates directly from the sound source to the receiver without reflection, refraction or other interference. In an ideal environment, the direct wave is the first signal to arrive at the receiver, and its corresponding earliest arrival time delay can accurately reflect the geometric distance between the sound source and the receiver. However, in actual indoor environments, due to complex spatial structure, strong reflection of walls and floors, dense personnel obstacles, etc., acoustic signal propagation is often accompanied by multiple high-energy reflection paths, and early strong echoes generated by near-distance obstacles often appear in time and even before the direct wave, forming the phenomenon of "near-far effect".

[0005] The prior art proposes to identify the initial arrival time of the acoustic signal by detecting the signal short-time energy mutation point, which mainly relies on the energy mutation point, peak amplitude or integral energy change as the basis for judgment, but the early reflection path may have higher energy and arrive earlier than the direct wave, thus being misjudged as the earliest arrival path. The prior art proposes to use a sliding window energy accumulation strategy to improve the detection sensitivity in a low signal-to-noise ratio environment, but in the case of multiple path energy concentration and small time interval, the cumulative curve cannot clearly separate the path energy, which easily leads to the earliest path being covered. The prior art proposes to use peak trajectory tracking to realize dynamic detection of the direct wave path to cope with dynamic sources or multi-path interference. Although this method is suitable for changing environments, it still lacks the ability to identify the true path because its core is still based on amplitude peak judgment, and it is also easy to identify errors when strong secondary waves dominate.

[0006] In summary, the prior art still has obvious deficiencies in the ability to obtain the earliest arrival time delay of the acoustic wave signal in a complex indoor acoustic environment, which directly affects the accuracy and stability of the TDOA positioning system. How to accurately identify the direct wave or its equivalent path under multi-path interference conditions and extract reliable earliest arrival time delay from it has become a key problem to improve the TDOA positioning accuracy. SUMMARY

[0007] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not a general review, nor is it intended to determine the key / important components or delineate the scope of protection of these embodiments, but as a prelude to the detailed description below.

[0008] The embodiments of the present disclosure provide a sound wave signal arrival time delay detection method, device and electronic equipment, which can accurately obtain the earliest arrival time delay in a complex multi-path environment, and help to improve the stability and ranging accuracy of the TDOA positioning system.

[0009] According to a first aspect of the present disclosure, a sound wave signal arrival time delay detection method is provided, comprising:

[0010] extracting an effective received sound wave signal containing useful components within a target bandwidth from the original received sound wave signal of the target receiver, the target bandwidth being the frequency range of the sound wave signal emitted by the target sound source;

[0011] constructing a reference sound wave signal matched with the characteristics of the sound wave signal emitted by the target sound source based on the target bandwidth and the set signal duration;

[0012] performing complex cross-correlation operation on the reference sound wave signal and itself to generate a reference signal CAF image, and determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image;

[0013] performing complex cross-correlation operation on the effective received acoustic signal and the reference acoustic signal to generate a received signal CAF image;

[0014] performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining the earliest arrival time delay of the acoustic signal emitted by the target sound source according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve.

[0015] In some embodiments, the effective received acoustic signal containing useful components within the target bandwidth is extracted from the original received acoustic signal of the target receiver, including:

[0016] setting the start frequency and the end frequency of the target bandwidth as the passband boundary frequencies of the bandpass filter;

[0017] filtering the original received acoustic signal of the target receiver by using a bidirectional zero-phase filtering method based on the bandpass filter to obtain an intermediate received acoustic signal containing useful components within the target bandwidth;

[0018] performing Hilbert transform on the intermediate received acoustic signal to obtain the effective received acoustic signal in complex analytic form.

[0019] In some embodiments, the reference acoustic signal matching the characteristics of the acoustic signal emitted by the target sound source is constructed based on the target bandwidth and the set signal duration, including:

[0020] constructing a linear frequency sweep signal in complex analytic form based on the start frequency and the end frequency of the target bandwidth and the set signal duration, wherein the expression of the linear frequency sweep signal is: , represents the linear frequency sweep signal, represents the imaginary unit, represents the start frequency of the target bandwidth, represents the end frequency of the target bandwidth, represents the signal duration, and t represents the time variable;

[0021] applying a window function to the linear frequency sweep signal for time domain weighting to obtain the reference acoustic signal matching the characteristics of the acoustic signal emitted by the target sound source, wherein the expression of the reference acoustic signal is: , represents the reference acoustic signal, represents the window function, and t represents the time variable.

[0022] In some embodiments, the reference signal CAF image is obtained by the following formula:

[0023] ,

[0024] denotes a reference signal CAF image, denotes a time delay variable, denotes a frequency shift variable, denotes a complex conjugate of a delayed reference sound signal, denotes a discrete reference sound signal, denotes a total number of sampling points of a signal, denotes a time index variable, denotes a sampling time interval, denotes a Doppler shift kernel function.

[0025] In some embodiments, determining an optimal Radon projection angle with the most concentrated energy based on a reference signal CAF image comprises:

[0026] performing a Radon transform on the reference signal CAF image in a preset angle range to obtain a one-dimensional projection curve of the reference signal CAF image, wherein the Radon transform is a line integral of energy distribution in the reference signal CAF image along a set direction, and an expression of the one-dimensional projection curve of the reference signal CAF image is: , is the one-dimensional projection curve of the reference signal CAF image, denotes a projection angle, denotes a Radon projection position coordinate, denotes a reference signal CAF image, denotes a Dirac delta function;

[0027] discretely sampling in a preset variation interval of the projection angle by a set step size, calculating a total projection energy corresponding to each projection angle, and an expression of the total projection energy is: , denotes a total projection energy corresponding to a projection angle;

[0028] selecting a projection angle that makes the total projection energy reach a maximum value as an optimal Radon projection angle, and an expression of the optimal Radon projection angle is: , denotes an optimal Radon projection angle.

[0029] In some embodiments, a received signal CAF image is obtained by the following formula:

[0030] ,

[0031] denotes a received signal CAF image, denotes a time delay variable, denotes a frequency shift variable, denotes a complex conjugate of the delayed reference acoustic signal, denotes a discrete valid received acoustic signal, denotes a total number of signal samples, denotes a time index variable, denotes a sampling time interval, denotes a Doppler shift kernel function.

[0032] In some embodiments, a one-dimensional integral projection is performed on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and according to a Radon projection amplitude and a Radon projection position of a local peak in the Radon projection curve, an earliest arrival time delay of the acoustic signal emitted by the target acoustic source is determined, including:

[0033] performing a one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve representing a change of the Radon projection value with the Radon projection position;

[0034] identifying all local peaks in the Radon projection curve through a local maximum search, and regarding a local peak greater than a set threshold as a candidate peak;

[0035] regarding a time delay corresponding to the candidate peak with the largest Radon projection amplitude and the Radon projection position greater than 0 as the earliest arrival time delay of the acoustic signal emitted by the target acoustic source.

[0036] In some embodiments, the set threshold is 10% of the largest Radon projection value in the Radon projection curve.

[0037] According to a second aspect of the present disclosure, there is provided an acoustic signal arrival time delay detection device, including:

[0038] The received signal processing module is configured to extract a valid received acoustic signal containing useful components within a target bandwidth from the original received acoustic signal of the target receiver, the target bandwidth being a frequency range of the acoustic signal emitted by the target acoustic source;

[0039] The reference signal generation module is configured to construct a reference acoustic signal matching the characteristics of the acoustic signal emitted by the target acoustic source based on the target bandwidth and a set signal duration;

[0040] The first CAF image module is configured to perform a complex cross-correlation operation on the reference acoustic signal and itself to generate a reference signal CAF image, and determine an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image;

[0041] a second CAF image module configured to perform a complex cross-correlation operation on the effective received acoustic wave signal and the reference acoustic wave signal to generate a received signal CAF image;

[0042] a time delay detection module configured to perform one-dimensional integral projection on the received signal CAF image along an optimal Radon projection angle to generate a Radon projection curve, and determine an earliest time delay of the acoustic wave signal emitted by the target sound source according to a Radon projection amplitude and a Radon projection position of a local peak in the Radon projection curve.

[0043] According to a third aspect of the present disclosure, an electronic device is provided, which includes a processor and a memory storing program instructions, the processor being configured to execute the acoustic wave signal time delay detection method provided in the first aspect of the present disclosure when running the program instructions.

[0044] The acoustic wave signal time delay detection method, device and electronic device provided by the embodiments of the present disclosure can achieve the following technical effects:

[0045] The acoustic wave signal time delay detection method provided by the embodiments of the present disclosure extracts the effective received acoustic wave signal containing useful components in the target bandwidth from the original received acoustic wave signal of the target receiver, where the target bandwidth is the frequency range of the acoustic wave signal emitted by the target sound source. Subsequently, based on the target bandwidth and the set signal duration, a reference acoustic wave signal matching the characteristics of the acoustic wave signal emitted by the target sound source is constructed.

[0046] Further, the reference acoustic wave signal is subjected to a complex cross-correlation operation with itself to generate a reference signal CAF image, and an optimal Radon projection angle with the most concentrated energy is determined based on the image. Then, the effective received acoustic wave signal is subjected to a complex cross-correlation operation with the reference acoustic wave signal to generate a received signal CAF image.

[0047] Since the cross ambiguity function is essentially a measure of the similarity of two signals in the time delay-frequency shift domain, the received signal CAF image can strengthen the response characteristics of the real direct wave in this domain. Even if some early reflection paths are dominant in energy, due to the difference in signal structure between them and the reference acoustic wave signal, the matching degree is low in the complex cross-correlation operation, resulting in a weak correlation response in the received signal CAF image, and thus being effectively suppressed.

[0048] On this basis, one-dimensional integral projection is performed on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve. According to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve, the earliest time delay of the acoustic wave signal emitted by the target sound source is determined, thereby realizing stable identification of the earliest arrival path.

[0049] To sum up, the embodiments of the present disclosure significantly improve the recognition ability of the real direct wave path from the perspective of signal structure consistency by introducing a reference sound wave signal matched with the characteristics of the target sound source and combining CAF analysis and Radon transform mechanism. Meanwhile, the system robustness in a complex multipath environment is effectively enhanced by using Radon projection to extract the linear energy concentration trend, thereby avoiding the misjudgment problem caused by the prominent energy of early strong reflection path. Therefore, the method provided by the present disclosure can more accurately obtain the earliest arrival time delay of the sound wave signal in a complex indoor environment, which helps to improve the stability and ranging accuracy of the TDOA positioning system.

[0050] The foregoing general description and the following description are merely exemplary and explanatory and are not intended to limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0051] One or more embodiments are exemplarily illustrated by corresponding drawings, which do not constitute a limitation on the embodiments, elements with the same reference numerals in the drawings are shown as similar elements, the drawings do not constitute a proportional limitation, and wherein:

[0052] Figure 1 is a flowchart of a sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure;

[0053] Figure 2 is a flowchart of another sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure;

[0054] Figure 3 is a time-frequency graph of a raw received sound wave signal provided by the embodiments of the present disclosure;

[0055] Figure 4 is a time-frequency graph of an intermediate received sound wave signal obtained by filtering the raw received sound wave signal provided by the embodiments of the present disclosure;

[0056] Figure 5 is a flowchart of another sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure;

[0057] Figure 6 is a flowchart of another sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure;

[0058] Figure 7 is a reference signal CAF image of a reference sound wave signal provided by the embodiments of the present disclosure;

[0059] Figure 8 is a received signal CAF image of an effective received sound wave signal provided by the embodiments of the present disclosure;

[0060] Figure 9 This is a schematic flowchart of another acoustic signal arrival delay detection method provided in this embodiment of the present disclosure;

[0061] Figure 10 This is a schematic diagram of the Radon projection curve provided in an embodiment of this disclosure;

[0062] Figure 11 This is a schematic diagram showing the relationship between Radon projection amplitude and time delay corresponding to the Radon projection curve provided in this embodiment of the disclosure;

[0063] Figure 12 This is a schematic diagram of the structure of an acoustic signal arrival delay detection device provided in an embodiment of this disclosure;

[0064] Figure 13 This is a schematic diagram of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0065] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0066] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0067] Unless otherwise stated, the term "multiple" means two or more.

[0068] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0069] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0070] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0071] The embodiment of the present disclosure provides a sound wave signal arrival time delay detection method, which comprises the following steps. Figure 1 As shown in the figure, the sound wave signal arrival time delay detection method comprises the following steps.

[0072] S101, extracting an effective received sound wave signal containing useful components within a target bandwidth from an original received sound wave signal of a target receiver.

[0073] In the embodiment of the present disclosure, the original received sound wave signal includes sound wave signals emitted by at least one sound source received by the target receiver, and the target bandwidth is the frequency range of the sound wave signals emitted by the target sound source. Taking an example of the original received sound wave signal including sound wave signals emitted by four sound sources received by the target receiver, the frequency ranges of the sound wave signals emitted by the four sound sources are 16khz-19khz, 19khz-16khz, 20khz-23khz and 23khz-20khz respectively, and taking an example of the sound source emitting the sound wave signal with the frequency range of 16khz-19khz as the target sound source, the target bandwidth is 16khz-19khz. In this case, an effective received sound wave signal containing useful components within 16khz-19khz is extracted from the original received sound wave signal of the target receiver for a specified time length, which can be determined according to actual design needs, for example, the specified time length can be 20ms.

[0074] S102, constructing a reference sound wave signal matched with the characteristics of the sound wave signals emitted by the target sound source based on the target bandwidth and the set signal duration.

[0075] As described above, the target bandwidth is the frequency range of the sound wave signals emitted by the target sound source, for example, the target bandwidth is 16khz-19khz. The signal duration can be determined according to actual design needs, for example, the signal duration can be 50ms. Based on the frequency range of 16kHz to 19kHz and the signal duration of 50ms, a reference sound wave signal matched with the characteristics of the sound source in this frequency range is constructed. The reference sound wave signal constructed in this way can accurately reflect the characteristics of the sound wave signals emitted by the target sound source, providing an accurate basis for further signal processing.

[0076] S103, performing complex cross-correlation operation on the reference sound wave signal and itself to generate a reference signal CAF image, and determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image.

[0077] In the embodiments of the present disclosure, the reference sound wave signal can be analyzed by using a cross-ambiguity function (CAF) to generate a reference signal CAF image, and the optimal Radon projection angle with the most concentrated energy can be determined based on the CAF image. Here, the CAF image obtained by analyzing the reference sound wave signal by using the cross-ambiguity function is defined as the reference signal CAF image.

[0078] S104, performing complex cross-correlation operation on the effective received sound wave signal and the reference sound wave signal to generate a received signal CAF image.

[0079] In the embodiments of the present disclosure, the effective received sound wave signal and the reference sound wave signal can be analyzed by using a cross-ambiguity function to generate a received signal CAF image. Here, the CAF image obtained by analyzing the effective received sound wave signal and the reference sound wave signal by using the cross-ambiguity function is defined as the received signal CAF image.

[0080] S105, performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining the earliest arrival time delay of the sound wave signal emitted by the target sound source according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve.

[0081] The sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure extracts the effective received sound wave signal containing the useful components in the target bandwidth from the original received sound wave signal of the target receiver, where the target bandwidth is the frequency range of the sound wave signal emitted by the target sound source. Then, based on the target bandwidth and the set signal duration, a reference sound wave signal matching the characteristics of the sound wave signal emitted by the target sound source is constructed.

[0082] Further, the reference sound wave signal is cross-correlated with itself to generate a reference signal CAF (Cross-Ambiguity Function) image, and the optimal Radon projection angle with the most concentrated energy is determined based on the image. Then, the effective received sound wave signal and the reference sound wave signal are cross-correlated to generate a received signal CAF image.

[0083] Since the cross-ambiguity function is essentially a measure of the similarity of two signals in the time delay-frequency shift domain, the received signal CAF image can enhance the response characteristics of the real direct wave in this domain. Even if some early reflection paths are dominant in energy, due to the difference in signal structure from the reference sound wave signal, the matching degree is low in the complex cross-correlation operation, resulting in a weak correlation response in the received signal CAF image, and thus being effectively suppressed.

[0084] On this basis, one-dimensional integral projection is performed on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve. According to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve, the earliest arrival time delay of the sound wave signal emitted by the target sound source is determined, thereby realizing stable identification of the earliest arrival path.

[0085] To sum up, the embodiments of the present disclosure significantly improve the identification ability of the real direct wave path by introducing a reference sound wave signal matched with the characteristics of the target sound source and combining CAF analysis and Radon transform mechanism from the perspective of signal structure consistency. Meanwhile, the system robustness in a complex multipath environment is effectively enhanced by using Radon projection to extract the energy concentration trend, thereby avoiding misjudgment caused by the prominent energy of early strong reflection paths. Therefore, the sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure can more accurately obtain the earliest arrival time delay of the sound wave signal in a complex indoor environment, which helps to improve the stability and ranging accuracy of the TDOA positioning system.

[0086] In some embodiments, the effective received sound wave signal containing useful components within the target bandwidth is extracted from the original received sound wave signal of the target receiver, including: setting the starting frequency and the ending frequency of the target bandwidth as the passband boundary frequencies of a band-pass filter; filtering the original received sound wave signal of the target receiver based on the band-pass filter to obtain an intermediate received sound wave signal containing useful components within the target bandwidth by using a bidirectional zero-phase filtering method; and performing Hilbert transformation on the intermediate received sound wave signal to obtain a complex analytical form of the effective received sound wave signal.

[0087] In the embodiments of the present disclosure, taking the target bandwidth of 16 kHz to 19 kHz as an example, the starting frequency 16 kHz and the ending frequency 19 kHz of the frequency band can be set as the passband boundaries of the band-pass filter. The band-pass filter used can be a 6th order Butterworth filter, and other types of band-pass filters can also be selected. By processing the original received sound wave signal through the filter, the interference components and background noise in the non-target frequency band can be effectively suppressed, thereby extracting the intermediate received sound wave signal containing useful information within the target bandwidth. Further, the bidirectional zero-phase filtering method is used in the filtering process, which avoids the phase distortion that may be introduced by the traditional filtering method, thereby obtaining a smoother and more stable output signal. The intermediate received sound wave signal is still a real signal, and the complex analytical form of the signal is generated after the Hilbert transformation of the intermediate received sound wave signal. The signal is used as the effective received sound wave signal, and the effective received sound wave signal retains the instantaneous amplitude and phase information of the original waveform.

[0088] The embodiments of the present disclosure provide another sound wave signal arrival time delay detection method, as shown inFigure 2 As shown in the figure, the sound wave signal arrival time delay detection method includes:

[0089] S201, set the start frequency and end frequency of the target bandwidth as the passband boundary frequency of the bandpass filter.

[0090] In the embodiments of the present disclosure, the target bandwidth is the frequency range of the sound wave signal emitted by the target sound source.

[0091] S202, filter the original received sound wave signal of the target receiver in a bidirectional zero-phase filtering manner based on the bandpass filter to obtain an intermediate received sound wave signal containing useful components within the target bandwidth.

[0092] Figure is a time-frequency diagram of the original received sound wave signal, and the original received sound wave signal is filtered in a bidirectional zero-phase filtering manner using a 6th order Butterworth filter to obtain an intermediate received sound wave signal containing useful components within the target bandwidth, Figure 4 is a time-frequency diagram of the intermediate received sound wave signal obtained after filtering the original received sound wave signal.

[0093] S203, perform Hilbert transform on the intermediate received sound wave signal to obtain an effective received sound wave signal in complex analytic form.

[0094] S204, based on the target bandwidth and the set signal duration, construct a reference sound wave signal matched with the characteristics of the sound wave signal emitted by the target sound source.

[0095] S205, perform complex cross-correlation operation on the reference sound wave signal and itself to generate a reference signal CAF image, and determine the optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image.

[0096] S206, perform complex cross-correlation operation on the effective received sound wave signal and the reference sound wave signal to generate a received signal CAF image.

[0097] S207, perform one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determine the earliest arrival time delay of the sound wave signal emitted by the target sound source according to the Radon projection amplitude and Radon projection position of the local peak in the Radon projection curve.

[0098] In some embodiments, based on the target bandwidth and the set signal duration, the reference acoustic wave signal matched with the characteristic of the acoustic wave signal emitted by the target sound source is constructed, comprising: based on the start frequency and the end frequency of the target bandwidth and the set signal duration, a linear sweep signal in complex analytic form is constructed; and the linear sweep signal is time domain weighted by applying a window function to obtain the reference acoustic wave signal matched with the characteristic of the acoustic wave signal emitted by the target sound source.

[0099] The expression of the linear sweep signal is: , wherein the linear sweep signal is represented by f(t), the imaginary unit is represented by j, the start frequency of the target bandwidth is represented by f0, the end frequency of the target bandwidth is represented by f1, the signal duration is represented by T, and t represents the time variable.

[0100] The expression of the reference acoustic wave signal is: , wherein the reference acoustic wave signal is represented by s(t), the window function is represented by w(t), and t represents the time variable.

[0101] Considering that the linear sweep signal in complex analytic form is hard-truncated in time, unnecessary sidelobe interference is introduced in the frequency spectrum, leading to dispersed energy distribution and affecting the accuracy of subsequent analysis. Therefore, a window function processing link is introduced after obtaining the linear sweep signal, for smoothing the transition at the start and end of the signal, thereby effectively suppressing the spectrum leakage and regulating the sidelobe level. The linear sweep signal processed by the window function exhibits higher main lobe clarity and signal-to-noise ratio in the cross ambiguity function (CAF) analysis, significantly enhancing the recognizability and processing accuracy of the signal. The optimized spectral characteristics are also helpful for more accurately capturing the signal characteristics in subsequent Radon projection and other processing links, reducing the influence of noise and interference, thereby improving the stability and reliability of the entire system. Moreover, the instantaneous amplitude and phase information of the original waveform are preserved.

[0102] In the embodiments of the present disclosure, the Tukey window or the Hamming window can be selected as the window function, both of which can better meet the above performance requirements. In order to reduce the spectrum leakage phenomenon, the linear sweep signal is weighted by the Tukey window function, and the window function parameter is set to 0.2. The Tukey window maintains full amplitude at the center and gradually decays to zero at the edge, taking into account the main lobe width and sidelobe suppression effect of the window function.

[0103] The embodiments of the present disclosure provide another acoustic wave signal arrival time delay detection method, as shown in Figure 5 The acoustic wave signal arrival time delay detection method comprises:

[0104] S501, extract an effective received acoustic wave signal containing useful components within a target bandwidth from an original received acoustic wave signal of a target receiver.

[0105] In the embodiments of the present disclosure, the target bandwidth is a frequency range of the acoustic wave signal emitted by the target sound source.

[0106] S502, construct a linear sweep signal in complex analytic form based on the start frequency and the end frequency of the target bandwidth and the set signal duration.

[0107] The expression of the linear sweep signal is: represents the linear sweep signal, represents the imaginary unit, represents the start frequency of the target bandwidth, represents the end frequency of the target bandwidth, represents the signal duration, and t represents the time variable.

[0108] S503, apply a window function to the linear sweep signal for time domain weighting to obtain a reference acoustic wave signal matching the characteristics of the acoustic wave signal emitted by the target sound source.

[0109] The expression of the reference acoustic wave signal is: represents the reference acoustic wave signal, represents the window function, and t represents the time variable.

[0110] S504, perform complex cross-correlation operation on the reference acoustic wave signal and itself to generate a reference signal CAF image, and determine an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image.

[0111] Optionally, when performing the complex cross-correlation operation on the reference acoustic wave signal and itself, a two-dimensional cross ambiguity function can be calculated within the frequency shift range of (step size ), the horizontal axis is the time delay ( ), and the vertical axis is the frequency shift. Under each frequency shift step, the frequency-shifted reference acoustic wave signal is complexly correlated with the original reference acoustic wave signal to obtain the reference signal CAF image.

[0112] S505, perform complex cross-correlation operation on the effective received acoustic wave signal and the reference acoustic wave signal to generate a received signal CAF image.

[0113] Optionally, when performing the complex cross-correlation operation on the effective received acoustic wave signal and the reference acoustic wave signal, a two-dimensional cross ambiguity function can be calculated within the frequency shift range of (step size ), the horizontal axis is the time delay ( ​​), and the vertical axis is frequency shift. Under each frequency shift step, the effective received acoustic signal is complexly correlated with the reference acoustic signal to obtain a received signal CAF image.

[0114] In the embodiments of the present disclosure, the brightness in the received signal CAF image represents the signal similarity under different combinations of frequency shift and time delay, and has obvious path energy focusing characteristics. The received signal CAF image has the same structure as the reference signal CAF image, and contains the actual propagation path delay, frequency shift and multipath information, which is the key basis for subsequent positioning estimation.

[0115] S506, one-dimensional integral projection is performed on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and the earliest arrival time delay of the acoustic signal emitted by the target sound source is determined according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve.

[0116] In some embodiments, determining the optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image includes: performing Radon transformation on the reference signal CAF image in a preset angle range to obtain a one-dimensional projection curve of the reference signal CAF image; discretely sampling in a preset variation interval of the projection angle according to a set step size, and calculating the total projection energy corresponding to each projection angle; and selecting the projection angle that makes the total projection energy maximum as the optimal Radon projection angle.

[0117] In the embodiments of the present disclosure, the Radon transformation is a line integral of the energy distribution in the reference signal CAF image along a set direction, and the expression of the one-dimensional projection curve of the reference signal CAF image is: , is the one-dimensional projection curve of the reference signal CAF image, denotes the projection angle, denotes the Radon projection position coordinate, denotes the reference signal CAF image, denotes the Dirac delta function.

[0118] The expression of the total projection energy is: , denotes the total projection energy corresponding to a projection angle.

[0119] The expression of the optimal Radon projection angle is: , denotes the optimal Radon projection angle.

[0120] The embodiments of the present disclosure can adaptively select the optimal Radon projection angle, effectively highlight the linear features of the earliest arriving path, and suppress the interference of multipath echoes and stray noise on peak detection, thereby providing a projection result with a higher signal-to-noise ratio for subsequent peak positioning and time delay extraction.

[0121] In practical applications, the variation range of the projection angle and the sampling step can be dynamically adjusted according to specific scenarios to balance the calculation efficiency on the premise of ensuring the projection accuracy. Preferably, the preset angle range can be to , and the set step can be .

[0122] The embodiments of the present disclosure provide another method for detecting the time delay of an acoustic signal, as shown in Figure 6 , the method for detecting the time delay of an acoustic signal comprises:

[0123] S601, extracting an effective received acoustic signal containing useful components within a target bandwidth from an original received acoustic signal of a target receiver.

[0124] In the embodiments of the present disclosure, the target bandwidth is the frequency range of the acoustic signal emitted by the target sound source.

[0125] S602, based on the target bandwidth and the set signal duration, constructing a reference acoustic signal matched with the characteristics of the acoustic signal emitted by the target sound source.

[0126] S603, performing a complex cross-correlation operation on the reference acoustic signal and itself to generate a reference signal CAF image.

[0127] Figure 7 is the reference signal CAF image of the reference acoustic signal, and the reference signal CAF image is obtained by the following formula:

[0128] ,

[0129] represents the reference signal CAF image, represents a time delay variable, represents a frequency shift variable, represents the complex conjugate of the delayed reference acoustic signal, represents the discrete reference acoustic signal, represents the total number of signal sampling points, represents a time index variable, represents a sampling time interval, represents a Doppler shift kernel function.

[0130] S604, performing Radon transform on the reference signal CAF image in a preset angle range to obtain a one-dimensional projection curve of the reference signal CAF image.

[0131] The Radon transform is a line integral of the energy distribution in the reference signal CAF image along a set direction, and the expression of the one-dimensional projection curve of the reference signal CAF image is: , is the one-dimensional projection curve of the reference signal CAF image, denotes a projection angle, denotes a Radon projection position coordinate, denotes the reference signal CAF image, denotes a Dirac delta function;

[0132] S605, discretely sampling the projection angle in a preset variation interval at a set step size, and calculating the total projection energy corresponding to each projection angle.

[0133] The expression of the total projection energy is: , denotes the total projection energy corresponding to a projection angle;

[0134] S606, selecting the projection angle that makes the total projection energy reach a maximum value as an optimal Radon projection angle.

[0135] The expression of the optimal Radon projection angle is: , denotes the optimal Radon projection angle.

[0136] S607, performing complex cross-correlation operation on the effective received acoustic wave signal and the reference acoustic wave signal to generate a received signal CAF image.

[0137] In the embodiments of the present disclosure, Figure 8 is a received signal CAF image of the effective received acoustic wave signal, and the received signal CAF image is obtained by the following formula:

[0138] ,

[0139] denotes the received signal CAF image, denotes a time delay variable, denotes a frequency shift variable, denotes a complex conjugate of the delayed reference acoustic wave signal, denotes a discrete effective received acoustic wave signal, denotes a total number of signal sampling points, denotes a time index variable, denotes a sampling time interval, represents a Doppler shift kernel function.

[0140] S608, performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining the earliest arrival time delay of the sound wave signal emitted by the target sound source according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve.

[0141] In some embodiments, performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining the earliest arrival time delay of the sound wave signal emitted by the target sound source according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve, includes: performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve representing the change of the Radon projection value with the Radon projection position; identifying all local peaks in the Radon projection curve through local maximum value search, and taking the local peak greater than a set threshold as a candidate peak; and taking the time delay corresponding to the candidate peak with the largest Radon projection amplitude and the Radon projection position greater than 0 as the earliest arrival time delay of the sound wave signal emitted by the target sound source.

[0142] Another sound wave signal arrival time delay detection method is provided in the embodiments of the present disclosure, as shown in the following Figure 9 The sound wave signal arrival time delay detection method includes:

[0143] S901, extracting an effective received sound wave signal containing useful components within a target bandwidth from the original received sound wave signal of the target receiver.

[0144] In the embodiments of the present disclosure, the target bandwidth is the frequency range of the sound wave signal emitted by the target sound source.

[0145] S902, constructing a reference sound wave signal matched with the characteristics of the sound wave signal emitted by the target sound source based on the target bandwidth and a set signal duration.

[0146] S903, performing complex cross-correlation operation on the reference sound wave signal and itself to generate a reference signal CAF image, and determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image.

[0147] S904, performing complex cross-correlation operation on the effective received sound wave signal and the reference sound wave signal to generate a received signal CAF image.

[0148] S905, performing one-dimensional integral projection along the optimal Radon projection angle of the received signal CAF image to generate a Radon projection curve representing the variation of Radon projection value with Radon projection position.

[0149] Figure 10 is a schematic diagram of the Radon projection curve. After generating the Radon projection curve, the Radon projection curve can be smoothed and normalized to reduce the interference of noise spikes on subsequent peak detection. The smoothing process can be implemented by using a moving average or Gaussian filtering method.

[0150] S906, identifying all local peaks in the Radon projection curve through local maximum value search, and taking the local peaks greater than a set threshold as candidate peaks.

[0151] Optionally, the set threshold is 10% of the maximum Radon projection value in the Radon projection curve.

[0152] S907, taking the time delay corresponding to the candidate peak with the largest Radon projection amplitude and the Radon projection position greater than 0 as the earliest arrival time delay of the sound wave signal emitted by the target sound source.

[0153] In the embodiments of the present disclosure, Figure 11 is a schematic diagram of the relationship between the Radon projection amplitude and the time delay corresponding to the Radon projection curve. After determining the candidate peaks with the Radon projection position greater than 0, the candidate peak with the largest Radon projection amplitude can be further determined from these candidate peaks. This candidate peak is defined as the target peak, and the time delay corresponding to the target peak is taken as the earliest arrival time delay of the sound wave signal emitted by the target sound source.

[0154] In the embodiments of the present disclosure, the expression of the earliest arrival time delay is as follows:

[0155] ,

[0156] represents the earliest arrival time delay; represents the coordinates of the Radon projection position, representing the position along a certain angle during the integral projection in the Radon transformation process, and different correspond to different time delay possibilities; represents the Radon projection value in the Radon projection curve at a specific projection position , which reflects the energy concentration degree of the signal at this position; represents a set threshold, which is usually set as a certain percentage (such as 10%) of the maximum Radon projection value in the Radon projection curve, to distinguish significant peaks from background noise or irrelevant smaller peaks.

[0157] The determination rule set in the embodiments of the present disclosure, that is, selecting the candidate peak value with the largest projection amplitude and greater than 0, can not only effectively exclude the low-time-delay high-amplitude interference caused by the main lobe of the near-field strong reflection, but also can preferentially identify and retain the main peak corresponding to the direct wave in the case of multiple peaks being relatively concentrated, thereby improving the accuracy and reliability of the earliest arrival time delay determination.

[0158] The sound wave signal arrival time delay detection method provided by the embodiments of the present disclosure measures the matching degree of each path from the perspective of signal structure similarity in the time delay-frequency shift two-dimensional domain by constructing a reference chirp signal consistent with the target sound source emission signal characteristics and performing cross ambiguity function calculation with the received sound wave signal. Since the direct wave and the reference signal are highly consistent in time-frequency structure, they form a clear and energy-concentrated main peak response in the CAF image. Although the near-distance reflection path may have a higher amplitude, it is relatively discrete and has a lower amplitude due to the mismatch of its time-frequency characteristics, and is effectively suppressed. This method breaks through the limitations of traditional methods that only rely on signal energy judgment, and can accurately identify the real direct path from the signal structure consistency, even in the case where the main and secondary paths have similar time delays, and has higher resolution and anti-misjudgment performance.

[0159] To further improve the detection accuracy in a multipath environment, Radon transform is introduced to perform directional energy accumulation analysis on the CAF image. By scanning and integrating the energy distribution under different projection angles, the linear structure is effectively extracted. When the projection direction of the Radon transform is consistent with the time-frequency track of the real direct path, the energy of the path will be concentrated in a group of high-amplitude and directionally clear peak values in the projection curve, thereby significantly improving the identification accuracy of the earliest arrival time delay. Compared with the traditional fixed-angle projection or maximum value determination method, the present application combines an adaptive angle selection mechanism to dynamically optimize the projection direction, ensuring the stability and distinguishability of the main path response in different application scenarios.

[0160] In summary, by combining cross ambiguity function with time-frequency structure matching analysis and introducing Radon transform for directional energy enhancement, a structure-driven arrival time delay detection method is constructed. This method not only improves the identification ability of the earliest arrival path in a complex multipath environment, but also enhances the stability and robustness of the system under low signal-to-noise ratio conditions. It is suitable for various indoor acoustic positioning, sound wave positioning, underwater acoustic detection and other practical applications that require high time delay estimation accuracy.

[0161] In combination with Figure 12As shown, the acoustic signal arrival time delay detection device 1000 provided by the embodiment of the present disclosure comprises a received signal processing module 1001, a reference signal generation module 1002, a first CAF image module 1003, a second CAF image module 1004 and an arrival time delay detection module 1005.

[0162] The received signal processing module 1001 is configured to extract an effective received acoustic signal containing useful components within a target bandwidth from the original received acoustic signal of the target receiver, the target bandwidth being the frequency range of the acoustic signal emitted by the target sound source.

[0163] The reference signal generation module 1002 is configured to construct a reference acoustic signal matching the characteristics of the acoustic signal emitted by the target sound source based on the target bandwidth and the set signal duration.

[0164] The first CAF image module 1003 is configured to perform complex cross-correlation operation on the reference acoustic signal and itself to generate a reference signal CAF image, and determine the optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image.

[0165] The second CAF image module 1004 is configured to perform complex cross-correlation operation on the effective received acoustic signal and the reference acoustic signal to generate a received signal CAF image.

[0166] The arrival time delay detection module 1005 is configured to perform one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determine the earliest arrival time delay of the acoustic signal emitted by the target sound source according to the Radon projection amplitude and Radon projection position of the local peak in the Radon projection curve.

[0167] The acoustic signal arrival time delay detection device provided by the embodiment of the present disclosure extracts an effective received acoustic signal containing useful components within a target bandwidth from the original received acoustic signal of the target receiver, wherein the target bandwidth is the frequency range of the acoustic signal emitted by the target sound source. Then, a reference acoustic signal matching the characteristics of the acoustic signal emitted by the target sound source is constructed based on the target bandwidth and the set signal duration.

[0168] Further, complex cross-correlation operation is performed on the reference acoustic signal and itself to generate a reference signal CAF (Cross Ambiguity Function) image, and the optimal Radon projection angle with the most concentrated energy is determined based on the image. Then, complex cross-correlation operation is performed on the effective received acoustic signal and the reference acoustic signal to generate a received signal CAF image.

[0169] Since the cross ambiguity function is essentially a measure of the similarity of two signals in the time-delay-frequency shift domain, the received signal CAF image can enhance the response characteristics of the real direct wave in this domain. Even if some early reflection paths are dominant in energy, due to the difference in signal structure from the reference acoustic signal, the matching degree is low in the complex cross-correlation operation, resulting in a weak correlation response in the received signal CAF image, and thus being effectively suppressed.

[0170] On this basis, one-dimensional integral projection is performed on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve. According to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve, the earliest arrival time delay of the acoustic wave signal emitted by the target sound source is determined, thereby realizing stable identification of the earliest arrival path.

[0171] In summary, the embodiments of the present disclosure significantly improve the recognition ability of the real direct wave path by introducing a reference acoustic signal matched with the characteristics of the target sound source, and combining CAF analysis and Radon transform mechanism, from the perspective of signal structure consistency; at the same time, the system robustness in complex multipath environment is effectively enhanced by using Radon projection to extract the energy concentration trend, avoiding the misjudgment problem caused by the energy of early strong reflection path. Therefore, the acoustic wave signal arrival time delay detection device provided by the embodiments of the present disclosure can more accurately obtain the earliest arrival time delay of the acoustic wave signal in a complex indoor environment, which helps to improve the stability and ranging accuracy of the TDOA positioning system.

[0172] In some embodiments, the received signal processing module 1001 is configured to: set the starting frequency and the ending frequency of the target bandwidth as the passband boundary frequencies of the band-pass filter; filter the original received acoustic wave signal of the target receiver by using a bidirectional zero-phase filtering manner based on the band-pass filter, to obtain an intermediate received acoustic wave signal containing useful components within the target bandwidth; and perform Hilbert transform on the intermediate received acoustic wave signal to obtain an effective received acoustic wave signal in complex analytic form.

[0173] In some embodiments, the reference signal generation module 1002 is configured to: based on the starting frequency and the ending frequency of the target bandwidth, and the set signal duration, construct a linear frequency sweep signal in complex analytic form, and the expression of the linear frequency sweep signal is: , wherein f(t) represents the linear frequency sweep signal, j represents an imaginary unit, f0 represents the starting frequency of the target bandwidth, f1 represents the ending frequency of the target bandwidth, T represents the signal duration, and t represents a time variable;

[0174] The linear sweep signal is weighted in time domain by applying a window function to obtain a reference sound wave signal matching the characteristics of the sound wave signal emitted by the target sound source, where the expression of the reference sound wave signal is: , represents the reference sound wave signal, represents the window function, and t represents the time variable.

[0175] In some embodiments, the reference signal CAF image is obtained by the following formula:

[0176] ,

[0177] represents the reference signal CAF image, represents the time delay variable, represents the frequency shift variable, represents the complex conjugate of the delayed reference sound wave signal, represents the discrete reference sound wave signal, represents the total number of signal sampling points, represents the time index variable, represents the sampling time interval, represents the Doppler shift kernel function.

[0178] In some embodiments, the first CAF image module 1003 is configured to perform Radon transform on the reference signal CAF image within a preset angle range to obtain a one-dimensional projection curve of the reference signal CAF image, where the Radon transform is a line integral of the energy distribution in the reference signal CAF image along a set direction, and the expression of the one-dimensional projection curve of the reference signal CAF image is: , is the one-dimensional projection curve of the reference signal CAF image, represents the projection angle, represents the Radon projection position coordinate, represents the reference signal CAF image, represents the Dirac delta function; along the preset variation interval of the projection angle, the preset variation interval is discretely sampled at a set step, the total projection energy corresponding to each projection angle is calculated, and the expression of the total projection energy is: , represents the total projection energy corresponding to a projection angle; the projection angle making the total projection energy reach the maximum value is selected as the optimal Radon projection angle, and the expression of the optimal Radon projection angle is: , represents the optimal Radon projection angle.

[0179] In some embodiments, the received signal CAF image is obtained by the following formula:

[0180] ,

[0181] represents a received signal CAF image, represents a time delay variable, represents a frequency shift variable, represents a complex conjugate of a delayed reference sound wave signal, represents a discrete valid received sound wave signal, represents a total number of signal sampling points, represents a time index variable, represents a sampling time interval, represents a Doppler shift kernel function.

[0182] In some embodiments, the arrival time delay detection module 1005 is configured to perform one-dimensional integral projection on the received signal CAF image along an optimal Radon projection angle, to generate a Radon projection curve representing Radon projection values varying with Radon projection positions; identify all local peaks in the Radon projection curve through local maximum value search, and take local peaks greater than a set threshold as candidate peaks; and take a time delay corresponding to a candidate peak with the largest Radon projection amplitude and a Radon projection position greater than 0 as an earliest arrival time delay of a sound wave signal emitted by a target sound source.

[0183] In some embodiments, the set threshold is 10% of the largest Radon projection value in the Radon projection curve.

[0184] In combination with Figure 13 As shown in FIG. 8, the embodiments of the present disclosure provide an electronic device 2000, which includes a processor 2001 and a memory 2002. Optionally, the device 2000 can further include a communication interface 2003 and a bus 2004. The processor 2001, the communication interface 2003, and the memory 2002 can complete communication with each other through the bus 2004. The communication interface 2003 can be used for information transmission. The processor 2001 can invoke logical instructions in the memory 2002 to execute the sound wave signal arrival time delay detection method of the above-described embodiments. In addition, the logical instructions in the memory 2002 described above can be implemented in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer readable storage medium.

[0185] The memory 2002 can be configured to store software programs, computer executable programs, such as program instructions / modules corresponding to the method in the embodiments of the present disclosure. The processor 2001 can execute the function application and data processing by running the program instructions / modules stored in the memory 2002, that is, implement the method for detecting the time delay of the sound wave signal in the above embodiments.

[0186] The memory 2002 can include a program storage area and a data storage area. The program storage area can store an operating system and at least one application required by a function. The data storage area can store data created according to the use of the terminal device, and the like. In addition, the memory 2002 can include a high-speed random access memory, and can also include a nonvolatile memory.

[0187] The above description and drawings sufficiently illustrate the embodiments of the present disclosure to enable one skilled in the art to practice them. Other embodiments can include structural, logical, electrical, process, and other changes. The embodiments represent only a few of the possible variations. Individual components and functions are optional unless explicitly required, and the order of operations can be varied. Parts and features of some embodiments can be included in or substituted for parts and features of other embodiments. Also, the words used in this application are used for description only and not for limitation. As used in the description of the embodiments and the claims that follow, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more of the associated listed items. In addition, the term "comprise" and variations of the term, such as "comprises" and / or "comprising", and the like, as used in this application, are intended to be inclusive, in that they mean that the stated features, integers, steps, operations, elements, and / or components are present, but not excluding the presence of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Unless otherwise expressly stated, the use of the term "or" in the claims should not be understood as having an exclusive meaning that the significant conjunction limits the claims to only the features that are expressly listed. Rather, the term "or" as used in the claims is intended to be an open-ended transition term that is used to connect a transitional phrase to at least one transitional phrase, but not to exclude the presence of one or more other transitional phrases that are not expressly listed. In this document, each embodiment can focus on the differences from other embodiments, and the same or similar parts between embodiments can be referred to each other. For the method, product, and the like disclosed in the embodiments, if it corresponds to the method part of the embodiments, the relevant part can be referred to the description of the method part.

[0188] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

Claims

1. A method of detecting the time of arrival of an acoustic wave signal, characterized by, The method comprises the following steps: extracting an effective received acoustic wave signal containing useful components within a target bandwidth from an original received acoustic wave signal of a target receiver, the target bandwidth being a frequency range of acoustic wave signals emitted by a target sound source; constructing a reference acoustic wave signal matching characteristics of the acoustic wave signals emitted by the target sound source based on the target bandwidth and a set signal duration; performing a complex cross-correlation operation on the reference acoustic wave signal and itself to generate a reference signal CAF image, and determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image; performing a complex cross-correlation operation on the effective received acoustic wave signal and the reference acoustic wave signal to generate a received signal CAF image; performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining an earliest arrival time delay of the acoustic wave signals emitted by the target sound source according to a Radon projection amplitude and a Radon projection position of a local peak in the Radon projection curve.

2. The acoustic wave signal time of arrival detection method of claim 1, wherein, The method for extracting an effective received acoustic wave signal containing useful components within a target bandwidth from an original received acoustic wave signal of a target receiver comprises the following steps: setting a start frequency and an end frequency of the target bandwidth as passband boundary frequencies of a band-pass filter; filtering the original received acoustic wave signal of the target receiver by using a bidirectional zero-phase filtering mode based on the band-pass filter to obtain an intermediate received acoustic wave signal containing useful components within the target bandwidth; performing Hilbert transform on the intermediate received acoustic wave signal to obtain the effective received acoustic wave signal in a complex analytic form.

3. The acoustic wave signal time of arrival detection method of claim 1, wherein, The method for constructing a reference acoustic wave signal matching characteristics of the acoustic wave signals emitted by the target sound source based on the target bandwidth and a set signal duration comprises the following steps: Based on the start frequency and the end frequency of the target bandwidth and the set signal duration, a linear sweep signal in complex analytic form is constructed, wherein an expression of the linear sweep signal is: , represents the linear sweep signal, represents an imaginary unit, represents the start frequency of the target bandwidth, represents the end frequency of the target bandwidth, represents the signal duration, and t represents a time variable; The linear sweep signal is weighted in time domain by applying a window function to obtain a reference sound wave signal matching the characteristics of the sound wave signal emitted by the target sound source, wherein the expression of the reference sound wave signal is: , represents the reference sound wave signal, represents the window function, and t represents the time variable.

4. The acoustic wave signal time of arrival detection method of claim 1, wherein, The reference signal CAF image is obtained by the following formula: ； represents a reference signal CAF image, represents a time delay variable, represents a frequency shift variable, represents a complex conjugate of a delayed reference sound signal, represents a discrete reference sound signal, represents a total number of signal samples, represents a time index variable, represents a sampling time interval, represents a Doppler shift kernel function.

5. The acoustic wave signal time of arrival detection method of claim 4, wherein, The method for determining an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image comprises the following steps: performing Radon transform on the reference signal CAF image in a preset angle range to obtain a one-dimensional projection curve of the reference signal CAF image, wherein the Radon transform is a line integral of energy distribution in the reference signal CAF image along a set direction, and an expression of the one-dimensional projection curve of the reference signal CAF image is: , is the one-dimensional projection curve of the reference signal CAF image, denotes a projection angle, denotes a Radon projection position coordinate, denotes the reference signal CAF image, denotes a Dirac delta function; The preset variation range of the projection angle is discretely sampled according to a set step, and the total projection energy corresponding to each projection angle is calculated, and the total projection energy expression is: , denotes the total projection energy corresponding to one projection angle. The projection angle that maximizes the total projected energy is selected as the optimal Radon projection angle. The expression for the optimal Radon projection angle is: , This represents the optimal Radon projection angle.

6. The acoustic wave signal time of arrival detection method of claim 1, wherein, The received signal CAF image is obtained by the following formula: ； represents a received signal CAF image, represents a time delay variable, represents a frequency shift variable, represents a complex conjugate of a delayed reference acoustic signal, represents a discrete valid received acoustic signal, represents a total number of signal samples, represents a time index variable, represents a sampling time interval, represents a Doppler shift kernel function.

7. The acoustic wave signal time of arrival detection method of claim 1, wherein, The method for performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determining an earliest arrival time delay of the acoustic wave signals emitted by the target sound source according to a Radon projection amplitude and a Radon projection position of a local peak in the Radon projection curve comprises the following steps: performing one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve representing changes of Radon projection values with Radon projection positions; identifying all local peaks in the Radon projection curve by local maximum value search, and taking a local peak greater than a set threshold value as a candidate peak; taking a time delay corresponding to a candidate peak with the largest Radon projection amplitude and a Radon projection position greater than 0 as the earliest arrival time delay of the acoustic wave signals emitted by the target sound source.

8. The acoustic wave signal time of arrival detection method of claim 7, wherein, The set threshold value is 10% of the largest Radon projection value in the Radon projection curve.

9. An apparatus for detecting time of arrival of an acoustic wave signal, characterized by The method comprises the following steps: a received signal processing module configured to extract an effective received acoustic wave signal containing useful components within a target bandwidth from an original received acoustic wave signal of a target receiver, the target bandwidth being a frequency range of acoustic wave signals emitted by a target sound source; The reference signal generation module is configured to construct a reference sound wave signal matching the characteristics of the sound wave signal emitted by the target sound source based on the target bandwidth and the set signal duration; The first CAF image module is configured to perform a complex cross-correlation operation on the reference sound wave signal and itself to generate a reference signal CAF image, and determine an optimal Radon projection angle with the most concentrated energy based on the reference signal CAF image; The second CAF image module is configured to perform a complex cross-correlation operation on the effective received sound wave signal and the reference sound wave signal to generate a received signal CAF image; The arrival time delay detection module is configured to perform one-dimensional integral projection on the received signal CAF image along the optimal Radon projection angle to generate a Radon projection curve, and determine the earliest arrival time delay of the sound wave signal emitted by the target sound source according to the Radon projection amplitude and the Radon projection position of the local peak in the Radon projection curve.

10. An electronic device comprising a processor and a memory having stored program instructions, wherein the program instructions, when executed by the processor, cause the electronic device to perform the method of any one of claims 1-9. The processor is configured to execute the sound wave signal arrival time delay detection method as claimed in any one of claims 1 to 8 when running the program instructions.

Images