Towed line array sonar active target depth estimation method based on time domain multipath matching

Abstract

The invention discloses a towed line array sonar active target depth estimation method based on time domain multipath matching, and the method comprises the steps: obtaining the azimuth and distance information of a reflector bright spot based on a small-aperture towed line array active sonar, and obtaining the multipath characteristics of the reflector bright spot based on the azimuth and distance information of the reflector bright spot, comprising multi-path amplitude and time delay information of an active transmitting signal propagating in an underwater acoustic channel; simulating echo signals when the reflector is located at different depths, and extracting a plurality of duplicate multipath features when the reflector is located at different depths through matched filtering; secondary matching processing is carried out on the multipath features of the reflector bright spots and the multiple duplicate multipath features of the reflectors at different depths, matching degree curves of the reflectors at different depths are obtained, and the reflector depth with the highest matching degree in the matching degree curves is used as the active detection echo depth. According to the towed line array sonar active target depth estimation method provided by the embodiment of the invention, the precision and reliability of depth estimation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonar detection, more particularly, to a towed line array sonar active target depth estimation method based on time domain multipath matching. BACKGROUND

[0002] With the development of ocean resources and the increasing demand for underwater security, the towed line array active sonar has become the core equipment for shallow water target detection. Limited by the platform size, the towed line array is usually small in aperture and easily distorted in array pattern, and a large amount of clutter such as water surface ships and seabed rocks is mixed in the received data. Accurate estimation of the depth of the echo corresponding to the reflector is a key link for identifying underwater vehicles, bottom targets or mines from the clutter, and is of great significance for improving the performance of sonar detection.

[0003] Existing depth estimation mainly relies on matched field processing or matched mode processing. The former uses a large-aperture array to calculate a copy field vector and matches it with the measured data, and the latter extracts normal mode components to invert the depth. Both methods require tens to hundreds of arrays, high signal-to-noise ratio and accurate environmental parameters. Under the conditions of small-aperture towed line array, low signal-to-noise ratio or channel mismatch, the sidelobe is raised and the modes are mixed, resulting in a sharp increase in depth estimation error or even failure, which is difficult to meet the engineering application requirements. SUMMARY

[0004] In view of at least one defect or improvement demand of the prior art, the present application provides a towed line array sonar active target depth estimation method based on time domain multipath matching, which can solve at least one of the problems in the background art.

[0005] To achieve the above-mentioned purpose, according to a first aspect of the present application, a towed line array sonar active target depth estimation method based on time domain multipath matching is provided, which comprises: A small-aperture towed line array active sonar acquires the azimuth and range information of a reflector highlight, and acquires the multipath characteristics of the reflector highlight based on the azimuth and range information of the reflector highlight, including the multipath amplitude and time delay information of the active transmitted signal propagating in the underwater acoustic channel; Based on the underwater acoustic channel model, the sonar position parameters and the azimuth and range information of the reflector highlight, the echo signals of the reflector located at different depths are simulated, and a plurality of copy multipath characteristics of the reflector located at different depths are extracted by matched filtering; The multipath characteristics of the reflector highlight and the plurality of copy multipath characteristics of the reflector located at different depths are respectively subjected to secondary matching processing; Based on the results of the secondary matching processing, a matching degree curve of the reflector located at different depths is obtained, and the reflector depth with the highest matching degree in the matching degree curve is taken as the active detection echo depth.

[0006] Further, the above-mentioned time-domain multipath matching-based towed line array sonar active target depth estimation method, the small-aperture-based towed line array active sonar obtains the azimuth and distance information of the reflector highlight, and the multipath characteristics of the reflector highlight are obtained based on the azimuth and distance information of the reflector highlight, specifically comprising: Based on the element spacing and the number of elements of the towed line array sonar, the received array data is subjected to conventional beamforming processing; Based on the signal parameters of the active emission of the towed line array sonar, the data after the conventional beamforming is subjected to matched filtering; The matched filtering data is subjected to constant false alarm detection; Based on the azimuth and distance information of the reflector highlight, the multipath characteristics of the reflector highlight after the array gain and the matching gain are obtained

[0007]

[0008] Among them, The autocorrelation function of the active emission signal is represented, And The time-domain impulse responses corresponding to the ocean channel and the target reflection are represented, respectively.

[0009] Further, the above-mentioned time-domain multipath matching-based towed line array sonar active target depth estimation method, based on the underwater acoustic channel model, the sonar position parameters and the azimuth and distance information of the reflector highlight, the echo signals of the reflector located at different depths are simulated, and multiple copy multipath characteristics of the reflector located at different depths are extracted by matched filtering, specifically comprising: Based on the distance information of the reflector highlight, the sonar position parameters and the underwater acoustic channel parameters, the underwater acoustic field calculation theory is used to simulate the two-way propagation multipath impulse response function of the reflector located at different depths ; Based on the signal parameters of the active emission of the towed line array sonar and the multipath impulse response function, the corresponding echo signals of different reflector depths are obtained by simulation, and multiple copy multipath characteristics are obtained by matched filtering processing

[0010] .

[0011] Further, the above-mentioned time-domain multipath matching-based towed line array sonar active target depth estimation method, the multipath characteristics of the reflector highlight and the multiple copy multipath characteristics of the reflector located at different depths are subjected to secondary matching processing, respectively, specifically comprising: Based on the multipath characteristics of the reflector highlight And multiple copy multipath characteristics​ , a secondary matching is performed; a result of the secondary matching processing is expressed as

[0012] the autocorrelation function of the is defined as , then is expressed as

[0013] wherein, the correlation processing of the multipath impulse response function of the channel corresponding to the echo of the bright spot of the reflector and the simulated multipath impulse response function at different reflector depths, when the reflector depth of one of the multiple copy multipath features is consistent with the target depth corresponding to the bright spot of the reflector, the reflector depth with the highest matching degree in the matching degree curve is taken as the matching peak value.

[0014] Further, the above-mentioned active target depth estimation method of the towed line array sonar based on time domain multipath matching, based on the result of the secondary matching processing, the matching degree curve of the reflector at different depths is obtained, and the reflector depth with the highest matching degree in the matching degree curve is taken as the active detection echo depth, specifically comprising: a result of the secondary matching processing the reflector depth with the highest matching degree in the matching degree curve at different reflector depths is expressed as

[0015] based on the matching peak value , a maximum value search is performed, and the depth corresponding to the matching peak value is taken as the reflector depth is expressed as .

[0016] Further, the above-mentioned active target depth estimation method of the towed line array sonar based on time domain multipath matching, after obtaining multiple copy multipath features, different signal-to-noise ratios of Gaussian white noise are added in the multiple copy multipath features respectively, and the signal-to-noise ratio of the beam domain is defined as

[0017] wherein, the signal-to-noise ratio of the target beam echo signal, indicates the beam domain echo power, indicates the power spectral density of the Gaussian white noise,​​ This indicates the bandwidth of the LFM signal.

[0018] According to a second aspect of the present invention, a depth estimation device for active targets of towed linear array sonar based on temporal multipath matching is also provided, comprising: The feature acquisition module is used to acquire the azimuth and distance information of the reflector bright spot based on the small aperture towed array active sonar, and to acquire the multipath features of the reflector bright spot based on the azimuth and distance information of the reflector bright spot, including the multipath amplitude and time delay information of the active transmitted signal propagating in the underwater acoustic channel. The matching module is used to simulate the echo signal of the reflector at different depths based on the underwater acoustic channel model, sonar position parameters and the azimuth and distance information of the reflector bright spot, and extract multiple replica multipath features of the reflector at different depths through matched filtering. The secondary matching module is used to perform secondary matching processing on the multipath features of the bright spot of the reflector and the multiple replica multipath features of the reflector when it is located at different depths. The echo depth acquisition module is used to acquire the matching degree curves of the reflector at different depths based on the results of the secondary matching process, and to take the reflector depth with the highest matching degree in the matching degree curve as the active echo depth.

[0019] According to a third aspect of the invention, a towed array sonar active target depth estimation device based on temporal multipath matching is also provided, which includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the steps of any of the methods described above.

[0020] According to a fourth aspect of the invention, a storage medium is also provided, which stores a computer program executable by a towed array sonar active target depth estimation device based on temporal multipath matching, wherein when the computer program is run on the towed array sonar active target depth estimation device based on temporal multipath matching, the towed array sonar active target depth estimation device performs the steps of any of the methods described above.

[0021] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: The active target depth estimation method based on time-domain multipath matching for towed linear array sonar provided in this application obtains the azimuth and distance information of the reflector bright spot using a small-aperture towed linear array sonar, and further extracts multipath features, including the multipath amplitude and time delay information of the actively transmitted signal in the underwater acoustic channel. Using an underwater acoustic channel model, sonar position parameters, and distance information of the reflector bright spot, the echo signal of the reflector at different depths is simulated, and multiple replica multipath features are extracted. The multipath features of the reflector bright spot are then matched with these replica multipath features in a secondary process to find the most similar feature combination. Based on the secondary matching result, a matching degree curve is obtained, and the depth of the reflector with the highest matching degree is determined as the active detection echo depth. Through these technical means, the requirement for array aperture in conventional underwater acoustic depth estimation techniques is reduced, robustness to unknown target reflection characteristics is improved, and the accuracy of depth estimation for low signal-to-noise ratio echo signals is enhanced by utilizing spatial array gain and active signal matching gain. This significantly improves the accuracy and reliability of depth estimation, enhancing its practicality and effectiveness in actual marine exploration missions. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating the active target depth estimation method for towed linear sonar based on temporal multipath matching provided in this application embodiment; Figure 2 A schematic diagram of a shallow sea channel model for simulation provided in this application embodiment; Figure 3 This is a schematic diagram of a target reflection multi-bright spot model provided in an embodiment of this application; Figure 4 A schematic diagram comparing the matching degree curves of the depth estimation method provided in the embodiments of this application with those of conventional broadband matching field processing techniques; Figure 5 A schematic diagram comparing the depth estimation results of the depth estimation method provided in the embodiments of this application with those of the broadband matched field processing technique; Figure 6 A schematic diagram comparing the RMSE of the depth estimation method provided in the embodiments of this application with that of broadband matched field processing technology for echo depth estimation under different beam domain signal-to-noise ratios. Detailed Implementation

[0024] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application. In addition, the technical features involved in the various embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0025] The terms "first", "second", "third" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish different objects, and are not used to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[0026] Figure 1 A flowchart of the method for estimating the depth of an active target of a towed line array sonar based on time domain multipath matching provided by the embodiments of the present application is shown in FIG. 1, and the method for estimating the depth of an active target of a towed line array sonar based on time domain multipath matching provided by the embodiments of the present application includes the following steps. Figure 1 The method for estimating the depth of an active target of a towed line array sonar based on time domain multipath matching provided by the embodiments of the present application includes the following steps: The towed line array active sonar based on a small aperture acquires the azimuth and distance information of a reflector highlight, and acquires the multipath characteristics of the reflector highlight based on the azimuth and distance information of the reflector highlight, including the multipath amplitude and time delay information of the active transmitted signal propagating in the underwater acoustic channel; Based on the underwater acoustic channel model, the sonar position parameters and the azimuth and distance information of the reflector highlight, the echo signals of the reflector located at different depths are simulated, and a plurality of copy multipath characteristics of the reflector located at different depths are extracted through matched filtering; The multipath characteristics of the reflector highlight and the plurality of copy multipath characteristics of the reflector located at different depths are respectively subjected to secondary matching processing; Based on the results of the secondary matching processing, a matching degree curve of the reflector located at different depths is acquired, and the reflector depth with the highest matching degree in the matching degree curve is taken as the active detection echo depth.

[0027] Specifically, the method for estimating the depth of an active target of a towed line array sonar based on time domain multipath matching provided by the embodiments of the present application mainly includes the following steps: The azimuth and range information of the reflector's bright spot, as well as the multipath characteristics, are obtained. The towed line array active sonar with a small aperture emits acoustic signals and receives the echo signals reflected by the reflector. By processing the received signals, the azimuth and range information of the reflector's bright spot can be obtained. Based on this information, the multipath characteristics are further extracted, including the multipath amplitude and time delay information generated when the actively emitted signals propagate in the underwater acoustic channel. The multipath amplitude information reflects the energy size of the echo signals on different paths, and the time delay information embodies the time difference of signal propagation on different paths.

[0028] The echo signals of the simulated reflector at different depths are simulated, and multiple copy multipath characteristics are extracted. First, according to the underwater acoustic channel model, sonar position parameters, and the azimuth and range information of the reflector's bright spot, each depth where the reflector may be located is simulated. The underwater acoustic channel model is used to simulate the propagation characteristics of sound waves in water, including the effects of sound speed profile, seawater density, seabed parameters, etc. on sound wave propagation. The sonar position parameters provide the specific position and attitude information of the sonar in water. Through these parameters, the echo signals generated by the reflector at different depths can be accurately simulated. Then, the simulated echo signals are processed by matched filtering to extract multiple copy multipath characteristics, which also contain multipath amplitude and time delay information, corresponding to the case where the reflector is located at different depths.

[0029] Second matching processing is performed. The multipath characteristics of the reflector's bright spot obtained in the first step are compared with the multiple copy multipath characteristics obtained in the second step, and the copy multipath characteristics most similar to the actual echo signal's multipath characteristics are found, thereby determining the actual depth of the reflector. In the matching process, correlation algorithms and other methods can be used to measure the similarity between the actual multipath characteristics and the copy multipath characteristics, and a matching degree curve is generated, which reflects the matching degree corresponding to different reflector depths.

[0030] The active detection echo depth is determined. According to the matching degree curve obtained in the third step, the peak point in the curve is found, and the reflector depth corresponding to the peak point is the active detection echo depth. Because when the actual depth of the reflector is consistent with the simulated depth, the multipath characteristics of the two are most similar, resulting in the maximum matching degree. Through this method, the depth of the reflector in water can be accurately estimated, even in the case of low signal-to-noise ratio, the depth information can be effectively extracted, providing key basis for subsequent target recognition and positioning.

[0031] The method for active target depth estimation of the towed line array sonar based on time domain multipath matching provided in the embodiments of the present application acquires the azimuth and distance information of the reflector highlight based on a small-aperture towed line array sonar, further extracts multipath characteristics, including the multipath amplitude and time delay information of the active transmitted signal in the underwater acoustic channel, simulates the echo signal when the reflector is located at different depths by using the underwater acoustic channel model, the sonar position parameters and the distance information of the reflector highlight, extracts multiple copy multipath characteristics, performs secondary matching processing on the multipath characteristics of the reflector highlight and the multiple copy multipath characteristics, finds the most similar characteristic combination, acquires a matching degree curve based on the secondary matching result, and determines the reflector depth with the highest matching degree as the active detection echo depth. Through the above technical means, the requirement of the conventional underwater depth estimation technology for the array aperture is reduced, the robustness to unknown target reflection characteristics is improved, the spatial array gain and the active signal matching gain are used to improve the depth estimation accuracy of the low signal-to-noise ratio echo signal, the precision and reliability of the depth estimation are significantly improved, and the practicability and effectiveness in actual marine detection tasks are enhanced.

[0032] Optionally, the method for active target depth estimation of the towed line array sonar based on time domain multipath matching provided in the embodiments of the present application acquires the azimuth and distance information of the reflector highlight based on a small-aperture towed line array sonar, acquires the multipath characteristics of the reflector highlight based on the azimuth and distance information of the reflector highlight, and specifically includes: Based on the element spacing and the number of elements of the towed line array sonar, the received array data is subjected to conventional beamforming processing; Based on the signal parameters of the active transmission of the towed line array sonar, the data after the conventional beamforming is subjected to matched filtering; The matched filtering data is subjected to constant false alarm detection; Based on the azimuth and distance information of the reflector highlight, the multipath characteristics of the reflector highlight after the array gain and the matching gain are acquired

[0033]

[0034] wherein, represents the autocorrelation function of the active transmitted signal, and respectively represent the time domain impulse responses corresponding to the ocean channel and the target reflection.

[0035] Specifically, the inter-element spacing and the number of elements of the towed line array sonar are used to perform conventional beamforming on the received array data. The towed line array sonar is composed of multiple elements, and the inter-element spacing and the number of elements are key parameters that affect the performance of the sonar. The array data refers to the signal data received by each element. Conventional beamforming is a common signal processing technique, and its purpose is to perform phase correction and coherent synthesis on the signals received by multiple elements to improve the directional resolution and signal-to-noise ratio of the signals. In this way, the azimuth information of the reflector bright spot, i.e., the direction of the reflector relative to the sonar, can be determined.

[0036] Based on the signal parameters of the active transmission of the towed line array sonar, the data after conventional beamforming is matched filtered. According to the known characteristics of the transmitted signal, the received signal is filtered to maximize the output signal-to-noise ratio. In this embodiment, by performing matched filtering on the data after beamforming, the detection capability of the reflector bright spot can be further improved, and more accurate distance information can be obtained. Matched filtering can effectively compress the pulse width of the transmitted signal, improve the distance resolution, and make the reflector bright spot more clear in the distance dimension.

[0037] The data after matched filtering is subjected to constant false alarm detection. Constant false alarm detection is an algorithm for automatically detecting target signals, which automatically adjusts the detection threshold to adapt to different environmental noise changes while keeping the false alarm rate constant. In the underwater acoustic environment, noise has randomness and instability, and the use of constant false alarm detection can effectively detect reflector bright spots from background noise while reducing false alarms. By setting a reasonable false alarm rate, the system can automatically determine the detection threshold and judge signals exceeding the threshold as reflector bright spots, thereby extracting effective azimuth and distance information.

[0038] Based on the azimuth and distance information of the reflector bright spot, the multipath characteristics of the reflector bright spot after array gain and matched gain are obtained. Array gain refers to the gain effect of the towed line array sonar due to factors such as array aperture and the number of elements, which can improve the receiving sensitivity and directional resolution of the signal. Matched gain is the gain brought by matched filtering, mainly reflected in improving the signal-to-noise ratio and distance resolution. When obtaining the multipath characteristics, the influence of these two gains is fully considered, making the extracted multipath characteristics more accurate and reliable. These multipath characteristics contain the multipath amplitude and time delay information of the actively transmitted signal in the underwater acoustic channel, providing important basic data for subsequent depth estimation.

[0039] Optionally, the method for estimating the depth of an active target using a towed linear array sonar based on time-domain multipath matching provided in this application embodiment, which simulates the echo signal of the reflector at different depths based on the underwater acoustic channel model, sonar position parameters, and the azimuth and distance information of the reflector bright spot, and extracts multiple replica multipath features of the reflector at different depths through matched filtering, specifically includes: Based on the distance information of the reflector's bright spot, sonar location parameters, and underwater acoustic channel parameters, underwater acoustic field calculation theory is used to simulate the reflector at different depths. Two-way propagation multipath impact response function ; Based on the signal parameters actively emitted by the towed linear array sonar and the multipath impact response function, simulations were used to obtain data for different reflector depths. The corresponding echo signals are processed by matched filtering to obtain multiple replica multipath features.

[0040] .

[0041] Specifically, based on the distance information of the reflector's bright spot, sonar position parameters, and underwater acoustic channel parameters, underwater acoustic field calculation theory is used to simulate the reflector at different depths. d The two-way propagation multipath impact response function is given. The distance information of the reflector's bright spot reflects the straight-line distance between the reflector and the sonar. The sonar position parameters provide the specific position and attitude information of the sonar in the water. The underwater acoustic channel parameters include environmental parameters that affect sound wave propagation, such as sound velocity profile, seawater density, and seabed parameters. Underwater acoustic field calculation theory is a theoretical model used to simulate the propagation characteristics of sound waves underwater. Common models include ray acoustic models and normal mode models. Through these theoretical models, the propagation characteristics of the reflector at different depths can be calculated. d The multipath impact response function describes the time delay, amplitude, and phase characteristics of a sound wave along different propagation paths. Two-way propagation refers to the entire propagation process of a sound wave from its emission from the sonar to the reflector and back to the sonar.

[0042] Based on the signal parameters actively emitted by the towed array sonar and the aforementioned multipath impact response function, simulations were used to obtain data for different reflector depths. d The corresponding echo signal is processed using matched filtering to obtain multiple replica multipath features. The parameters of the actively transmitted signal include waveform, frequency, pulse width, and other characteristics. During the simulation, the actively transmitted signal is convolved with the multipath impact response function to obtain the results for different reflector depths. dThe corresponding echo signals. These echo signals incorporate the effects of multipath propagation, simulating the echo signals generated by the reflector at different depths in real-world conditions. Then, matched filtering is applied to these simulated echo signals to extract multiple replica multipath features. Matched filtering is used to improve the signal-to-noise ratio and detection performance. The replica multipath features also contain multipath amplitude and time delay information, corresponding to the reflector's location at different depths. d The situation at that time.

[0043] Optionally, the depth estimation method for active targets of towed linear sonar based on temporal multipath matching provided in this application embodiment includes, in particular, performing secondary matching processing on the multipath features of the bright spot of the reflector and the multiple replica multipath features of the reflector at different depths, as well as: Based on the multipath characteristics of the reflector's bright spot and multiple replica multipath features Perform a second matching; The result of the secondary matching process Represented as

[0044] The definition The autocorrelation function is ,but Represented as

[0045] in, The multipath impulse response function of the channel corresponding to the echo of the bright spot of the reflector and different reflector depths The relevant processing of the simulated multipath impact response function, when the reflector depth of one of the replicas in the multipath feature is... When the target depth corresponds to the bright spot of the reflector, the reflector depth with the highest matching degree in the matching degree curve is obtained as the matching peak value.

[0046] Specifically, the multipath characteristics of the reflector's bright spot and its multiple replica multipath characteristics are subjected to secondary matching processing. The multipath characteristics of the reflector's bright spot are extracted from the actual received echo signal and include multipath amplitude and time delay information generated when the actively transmitted signal propagates in the underwater acoustic channel. The multiple replica multipath characteristics are obtained through simulation and correspond to the reflector being located at different depths. d The purpose of secondary matching is to find the replica feature that best matches the actual feature by comparing the similarity between the actual multipath feature and each replica multipath feature, thereby determining the actual depth of the reflector.

[0047] In the secondary matching process, a correlation algorithm or other method can be used to measure the similarity between the actual multipath feature and the copy multipath feature. Specifically, the correlation algorithm calculates the correlation coefficient of two signals in the time domain or frequency domain to evaluate their similarity. The correlation coefficient usually ranges from 0 to 1, and the closer the value is to 1, the more similar the two signals are. By correlating the actual multipath feature with each copy multipath feature, a series of correlation coefficients are obtained, and a matching degree curve is formed. This curve reflects the corresponding matching degree, i.e., the similarity, of different reflector depths d .

[0048] The result of the secondary matching process is represented as a matching degree function, which describes the relationship between the reflector depth d and the matching degree. The autocorrelation function is defined as , which reflects the correlation characteristics of the signal itself. The correlation result of the channel impulse response function corresponding to the echo of the reflector highlight and the simulated channel impulse response function under different reflector depths is represented as . When the reflector depth of one of the copy multipath features matches the target depth corresponding to the reflector highlight, it will reach a maximum value, forming a peak on the matching degree curve. The reflector depth corresponding to this peak is the matching peak, represented as .

[0049] Optionally, the active target depth estimation method for a towed line array sonar based on time domain multipath matching provided by the embodiments of the present application includes: obtaining a matching degree curve of the reflector under different depths based on the result of the secondary matching process, and taking the reflector depth with the highest matching degree in the matching degree curve as the active detection echo depth. Specifically, the method includes the following steps: obtaining the result of the secondary matching process taking the reflector depth with the highest matching degree in the matching degree curve under different reflector depths as the matching peak , represented as

[0050] performing maximum value search based on the matching peak , and taking the depth corresponding to the matching peak as the reflector depth , represented as .

[0051] ​Specifically, through the secondary matching processing, a matching degree curve of the reflector at different depths can be obtained. The curve intuitively shows the matching degree change of the reflector at each possible depth. The horizontal axis of the matching degree curve represents the possible depth of the reflector, and the vertical axis represents the corresponding matching degree value.

[0052] In the matching degree curve, the point corresponding to the depth of the reflector with the highest matching degree is the matching peak value. In order to accurately find the matching peak value, various numerical search methods can be used. After determining the matching peak value, the corresponding reflector depth can be used as the active probe echo depth. In practical applications, this process can be realized by computer program to realize automatic processing.

[0053] Optionally, the active target depth estimation method of the towed line array sonar based on time domain multipath matching provided in the embodiment of the present application adds Gaussian white noise with different signal-to-noise ratios in the plurality of copy multipath features respectively, and the signal-to-noise ratio in the beam domain is defined as

[0054] wherein, is the signal-to-noise ratio of the target beam echo signal, represents the beam domain echo power, represents the power spectral density of the Gaussian white noise, represents the bandwidth of the LFM signal.

[0055] Specifically, in the actual underwater acoustic environment, noise is one of the important factors affecting the performance of the sonar system. In order to better simulate the echo signal in the actual environment and verify the performance stability of the depth estimation method under different signal-to-noise ratios, after obtaining the plurality of copy multipath features, Gaussian white noise with different signal-to-noise ratios is added in the plurality of copy multipath features respectively.

[0056] Gaussian white noise is a commonly used noise model, and its probability density function obeys Gaussian distribution and has a flat power spectral density in the frequency domain. In this embodiment, by adding Gaussian white noise with different signal-to-noise ratios to each copy multipath feature, the echo signal situation under different noise interference degrees can be simulated. The signal-to-noise ratio in the beam domain is defined as

[0057] wherein, is the signal-to-noise ratio of the target beam echo signal, represents the beam domain echo power, represents the power spectral density of the Gaussian white noise, represents the bandwidth of the LFM signal.

[0058] In this way, the depth estimation method can be tested and verified under different signal-to-noise ratio conditions. Specifically, based on the copy multipath features after adding noise, the subsequent secondary matching processing and depth estimation steps are repeated, and the accuracy and stability of the depth estimation results under different signal-to-noise ratio conditions can be observed and analyzed. This helps to evaluate the anti-interference ability and adaptability of the proposed method in practical applications, ensuring its reliability and effectiveness in complex and variable marine environments.

[0059] To verify the active target depth estimation method of the towed line array sonar based on time domain multipath matching provided by the embodiments of the present application, the Bellhop algorithm of the ray theory is used to simulate the echo signals at different target distances in the underwater acoustic channel, Figure 2 The shallow sea channel model used in the simulation is given, the water depth is 100 m, the seawater sound speed is 1500 m / s, the seawater density is 1000 kg / m 3 , the seabed sound speed is 1850 m / s, the seabed density is 1850 kg / m 3 , the seabed sound absorption is 0.3 dB / λ, the source depth is 65 m, the receiving array depth is 72 m, the target distance is 5-20 km, 150 equidistant echo samples are taken in this distance range, and the target depth is assumed to be 5 m, 52 m and 95 m, respectively, to study the depth estimation effect of the present invention for sea surface targets, underwater targets and seabed targets. Table 1 gives the array parameters used in the simulation, wherein the number of towed line array elements is 60, the element spacing is 1.5 m, the active signal form is linear frequency modulation signal (LFM), the frequency range of the active signal is 200-500 Hz, and the pulse width is 1 s. Since the existing matching mode technology under this array parameter cannot separate different modes in the sound field, the conventional broadband matching field processing technology is selected as the comparison method.

[0060] Table 1 Simulation towed line array sonar parameters

[0061] To study the depth estimation performance of the present invention under channel parameter mismatch, the above channel parameters are used when simulating the copy multipath features, but when simulating the echo signal multipath features, some channel parameters are modified as shown in Table 2. At the same time, in order to study the depth estimation technology of the present invention under unknown target reflection characteristics, a 5 bright spot reflection model as shown in Figure 3 is further added in the echo signal simulation.

[0062] Table 2 Mismatched channel parameters

[0063] To further increase the authenticity, Gaussian white noise with different signal-to-noise ratios is added to the simulated target beam echo signal, and the signal-to-noise ratio in the beam domain is defined as:

[0064] wherein, denotes the signal-to-noise ratio of the target beam echo signal, denotes the echo power in the beam domain, denotes the power spectral density of the Gaussian white noise, denotes the bandwidth of the LFM signal. Figure 4 The matching results of the matching multipath processing technology of the application and the conventional wideband matched field processing technology under the condition of a beam domain signal-to-noise ratio of 10 dB are given for 150 frames of echo signals at different distances of 52 m, 5 m and 95 m depths, Figure 5 The estimated depth obtained by using maximum value search is given. Figure 6 The depth estimation RMSE results of the matching multipath processing technology of the application and the conventional wideband matched field processing technology for 150 frames of echo signals under different signal-to-noise ratios are given. From the above results, it can be seen that under the conditions of channel parameter mismatch, unknown reflection characteristics and ocean environmental noise, the depth estimation performance of the matching multipath processing technology proposed in the application is obviously better than that of the conventional wideband matched field processing technology.

[0065] Optionally, the embodiment of the application further provides a time domain multipath matching-based towed line array sonar active target depth estimation device, which comprises: a feature acquisition module configured to acquire the azimuth and distance information of a reflector highlight based on a small-aperture towed line array active sonar, and acquire the multipath features of the reflector highlight based on the azimuth and distance information of the reflector highlight, including the multipath amplitude and time delay information of the active transmission signal propagating in the underwater acoustic channel; a matching module configured to simulate the echo signal of the reflector at different depths based on the underwater acoustic channel model, the sonar position parameters and the azimuth and distance information of the reflector highlight, and extract multiple copy multipath features of the reflector at different depths through matched filtering; a secondary matching module configured to perform secondary matching processing on the multipath features of the reflector highlight and the multiple copy multipath features of the reflector at different depths, respectively; a detection echo depth acquisition module configured to acquire a matching degree curve of the reflector at different depths based on the results of the secondary matching processing, and take the reflector depth with the highest matching degree in the matching degree curve as the active detection echo depth.

[0066] The application further provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps of the method. The computer readable storage medium can include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0067] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all described as a series of action combinations, but those skilled in the art should know that the application is not limited to the order of the actions described, because according to the application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the application.

[0068] In the above embodiments, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0069] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic. The division of the units is only a logical function division. There can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some services interfaces, devices or units, and can be electrical or other forms.

[0070] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0071] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0072] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present application. The aforementioned memory includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0073] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer readable memory, which can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0074] The above is only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Those skilled in the art will easily think of embodiments of the present disclosure after considering the specification and practicing the disclosure herein. The present application is intended to cover any variations, uses or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and examples are only considered as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

[0075] The technical features of the above embodiments can be combined in any way. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, however, as long as the combinations of the technical features do not contradict, they should be considered as within the scope of the present disclosure.

[0076] Those skilled in the art readily understand that the above only describes preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A depth estimation method for active targets in towed linear array sonar based on temporal multipath matching, characterized in that, Includes the following steps: The active sonar based on small aperture towed array acquires the azimuth and distance information of the reflector bright spot, and acquires the multipath characteristics of the reflector bright spot based on the azimuth and distance information of the reflector bright spot, including the multipath amplitude and time delay information of the active transmitted signal propagating in the underwater acoustic channel. Based on the underwater acoustic channel model, sonar position parameters, and the azimuth and distance information of the reflector bright spot, the echo signal of the reflector at different depths is simulated, and multiple replica multipath features of the reflector at different depths are extracted by matched filtering. The multipath features of the bright spot of the reflector and the multiple replica multipath features of the reflector at different depths are respectively subjected to secondary matching processing; Based on the results of the secondary matching process, matching degree curves of the reflector at different depths are obtained, and the depth of the reflector with the highest matching degree in the matching degree curve is taken as the active detection echo depth.

2. The method for estimating the depth of active targets in towed linear array sonar based on temporal multipath matching as described in claim 1, characterized in that, The active sonar based on a small-aperture towed array acquires the azimuth and distance information of the reflector bright spot, and acquires the multipath characteristics of the reflector bright spot based on the azimuth and distance information of the reflector bright spot, specifically including: Based on the element spacing and number of elements of the towed linear array sonar, conventional beamforming processing is performed on the received array data. Based on the signal parameters actively transmitted by the towed array sonar, the data after conventional beamforming is subjected to matched filtering; Perform constant false alarm rate (CFAR) detection on the matched filter data; Based on the orientation and distance information of the bright spot of the reflector, the multipath characteristics of the bright spot of the reflector after array gain and matching gain are obtained. in, The autocorrelation function representing an actively transmitted signal. and These represent the time-domain impulse responses corresponding to the ocean channel and target reflection, respectively.

3. The method for estimating the depth of active targets in towed linear array sonar based on temporal multipath matching as described in claim 2, characterized in that, Based on the underwater acoustic channel model, sonar position parameters, and the azimuth and distance information of the reflector's bright spot, the echo signal of the reflector at different depths is simulated. Multiple replica multipath features of the reflector at different depths are extracted using matched filtering, specifically including: Based on the distance information of the reflector's bright spot, sonar location parameters, and underwater acoustic channel parameters, underwater acoustic field calculation theory is used to simulate the reflector at different depths. Two-way propagation multipath impact response function ; Based on the signal parameters actively emitted by the towed linear array sonar and the multipath impact response function, simulations were used to obtain data for different reflector depths. The corresponding echo signals are processed by matched filtering to obtain multiple replica multipath features. 。 4. The method for estimating the depth of active targets in towed linear array sonar based on temporal multipath matching as described in claim 3, characterized in that, The multipath features of the bright spot of the reflector and the multiple replica multipath features of the reflector at different depths are subjected to secondary matching processing, specifically including: Based on the multipath characteristics of the reflector's bright spot and multiple replica multipath features Perform a second matching; The result of the secondary matching process Represented as Where * denotes the conjugate operation; The definition The autocorrelation function is ,but Represented as in, The multipath impulse response function of the channel corresponding to the echo of the bright spot of the reflector and different reflector depths The relevant processing of the simulated multipath impact response function, when the reflector depth of one of the replicas in the multipath feature is... When the target depth corresponds to the bright spot of the reflector, the reflector depth with the highest matching degree in the matching degree curve is obtained as the matching peak value.

5. The method for estimating the depth of active targets in towed linear array sonar based on temporal multipath matching as described in claim 4, characterized in that, Based on the result of the secondary matching process, matching degree curves of the reflector at different depths are obtained. The depth of the reflector with the highest matching degree in the matching degree curve is taken as the active detection echo depth. Specifically, this includes: The result of the secondary matching process At different reflector depths The depth of the reflector with the highest matching degree in the matching degree curve is taken as the matching peak. , represented as Based on the matching peak value Perform a maximum value search to obtain the depth corresponding to the matching peak value as the depth of the reflector. , represented as 。 6. The method for estimating the depth of active targets in towed linear array sonar based on temporal multipath matching as described in claim 3, characterized in that, After obtaining multiple replica multipath features, Gaussian white noise with different signal-to-noise ratios is added to each of the multiple replica multipath features. The signal-to-noise ratio in the beam domain is defined as... in, The signal-to-noise ratio of the target beam echo signal. Indicates the beam domain echo power. This represents the power spectral density of Gaussian white noise. This indicates the bandwidth of the LFM signal.

7. A towed linear array sonar active target depth estimation device based on temporal multipath matching, characterized in that, include: The feature acquisition module is used to acquire the azimuth and distance information of the reflector bright spot based on the small aperture towed array active sonar, and to acquire the multipath features of the reflector bright spot based on the azimuth and distance information of the reflector bright spot, including the multipath amplitude and time delay information of the active transmitted signal propagating in the underwater acoustic channel. The matching module is used to simulate the echo signal of the reflector at different depths based on the underwater acoustic channel model, sonar position parameters and the azimuth and distance information of the reflector bright spot, and extract multiple replica multipath features of the reflector at different depths through matched filtering. The secondary matching module is used to perform secondary matching processing on the multipath features of the bright spot of the reflector and the multiple replica multipath features of the reflector when it is located at different depths. The echo depth acquisition module is used to acquire the matching degree curves of the reflector at different depths based on the results of the secondary matching process, and to take the reflector depth with the highest matching degree in the matching degree curve as the active echo depth.

8. A towed linear array sonar active target depth estimation device based on temporal multipath matching, characterized in that, It includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the steps of the method according to any one of claims 1 to 6.

9. A storage medium, characterized in that, It stores a computer program executable by a towed array sonar active target depth estimation device based on temporal multipath matching. When the computer program is run on the towed array sonar active target depth estimation device based on temporal multipath matching, the towed array sonar active target depth estimation device based on temporal multipath matching performs the steps of the method described in any one of claims 1 to 6.

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