Motion compensation method and device for passive sonar detection

Abstract

The invention provides a motion compensation method and device for passive sonar detection. The compensation method comprises the following steps: acquiring underwater acoustic signals acquired by a passive sonar in real time within a preset period; performing segmentation processing and Fourier transform on the underwater acoustic signal to obtain an underwater acoustic frequency domain signal segment; constructing a parameterized search matrix of each water audio frequency domain signal segment, and determining a motion compensation parameter of each water audio frequency domain signal segment through similar energy spectrum search; based on the motion compensation parameter, performing phase compensation on the water audio frequency domain signal segment to obtain a compensation frequency domain signal segment; and performing inverse discrete Fourier transform on the compensation frequency domain signal segment to obtain a compensation time domain signal segment so as to determine a long-time coherent integration result corresponding to the underwater acoustic signal. Through the method, the gain of passive sonar detection processing is improved under the condition of low signal-to-noise ratio, and the accuracy and stability of passive sonar detection are improved.

Description

Technical Field

[0001] This application relates to the field of underwater acoustic signal processing technology, and in particular to a motion compensation method and apparatus for passive sonar detection. Background Technology

[0002] Passive sonar detection technology achieves covert detection by receiving noise radiated by moving targets. The detection performance of passive sonar is limited by the signal accumulation time and the Doppler effect. In real-world scenarios, moving targets cause the generated signals to exhibit time delay spread and Doppler frequency shift, which destroys the signal phase coherence. Traditional long-time coherent integration methods (e.g., periodogram methods) significantly reduce the signal integration gain.

[0003] Currently, the autoregressive moving average frequency estimation method based on parameterized models can compensate for the Doppler effect by estimating the motion parameters of the target moving object. Although it can obtain good processing gain under high signal-to-noise ratio conditions, the parameter estimation error is large under low signal-to-noise ratio conditions, which reduces the accuracy and stability of passive sonar detection. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a motion compensation method and device for passive sonar detection. By segmenting and Fourier transforming the underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period, multiple underwater acoustic frequency domain signal segments are obtained. By constraining the search frequency and search speed of each underwater acoustic frequency domain signal segment, broadband spectral peak tracking is performed on each underwater acoustic frequency domain signal segment. Then, motion compensation parameters are determined by energy spectrum-like search. This method has the advantages of fast convergence speed and low computational complexity. While obtaining the motion-compensated underwater acoustic time domain signal, a long-time coherent integral result is also obtained, realizing the gain improvement of passive sonar detection processing under low signal-to-noise ratio conditions, and improving the accuracy and stability of passive sonar detection.

[0005] This application provides a motion compensation method for passive sonar detection, the motion compensation method comprising: Acquire underwater acoustic signals in real time from a passive sonar targeting moving objects in a target water area within a preset period; The underwater acoustic signal is segmented to obtain multiple underwater acoustic time-domain signal segments, and a Fourier transform is performed on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment. Construct a parameterized search matrix corresponding to each of the underwater acoustic frequency domain signal segments, and determine the motion compensation parameters corresponding to each of the underwater acoustic frequency domain signal segments based on the parameterized search matrix through a spectral energy search. Based on the motion compensation parameters, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment. The inverse discrete Fourier transform is performed on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

[0006] Furthermore, the underwater acoustic signal is segmented to obtain multiple underwater acoustic time-domain signal segments, including: The amplitude and length values ​​corresponding to the underwater acoustic signal are obtained, and based on the amplitude value, the length value and the preset phase signal coefficient, the polynomial underwater acoustic signal corresponding to each sampling moment within the preset period is determined; The polynomial underwater acoustic signal is segmented according to a preset segmented data volume to determine the time interval and non-overlapping data corresponding to each polynomial underwater acoustic signal. Based on the time interval and the non-overlapping data, a preset rectangular window function is used to determine the underwater acoustic time-domain signal segment corresponding to each polynomial underwater acoustic signal, so as to obtain multiple underwater acoustic time-domain signal segments.

[0007] Furthermore, the step of performing a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the corresponding underwater acoustic frequency-domain signal segment includes: Based on the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment, the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is determined. Perform a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segments corresponding to each underwater acoustic time-domain signal segment; wherein the frequency variation range corresponding to each underwater acoustic frequency-domain signal segment is greater than or equal to the calibrated frequency variation range.

[0008] Furthermore, the step of constructing a parameterized search matrix corresponding to each of the underwater acoustic frequency domain signal segments, and determining the motion compensation parameters corresponding to each of the underwater acoustic frequency domain signal segments based on the parameterized search matrix through a spectral energy search, includes: Based on the pre-constructed velocity relationship of the moving object relative to the passive sonar in the target water area, a parameterized search matrix is ​​constructed for each underwater acoustic frequency domain signal band; wherein, the parameterized search matrix includes a frequency search range parameter, a target velocity search range parameter, and an equivalent initial frequency; Based on the parameterized search matrix, a joint search of velocity and frequency is performed on each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking on each underwater acoustic frequency domain signal segment and determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment. Based on the target velocity search range, construct an energy spectrum-like search matrix; Based on the energy spectrum search matrix, an energy spectrum search is performed on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

[0009] Furthermore, the step of performing phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment includes: For each frequency point and the corresponding phase in each underwater acoustic frequency domain signal segment, a joint reconstruction is performed to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment; Based on the motion compensation parameters, the phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined by using the frequency domain data space matrix and the compensation operator matrix, respectively. Based on the phase compensation result, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0010] Furthermore, the step of jointly reconstructing each frequency point and the corresponding phase in each of the underwater acoustic frequency domain signal segments to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment includes: For each frequency point in each underwater acoustic frequency domain signal segment and the phase corresponding to each frequency point, a joint reconstruction is performed to construct a motion compensation model corresponding to the underwater acoustic frequency domain signal segment; Based on the motion compensation model, a discrete Fourier transform based on the frequency search range is performed on the parameterized search matrix to obtain the frequency search matrix; The frequency search matrix is ​​decomposed according to the frequency search range to obtain the velocity matching space matrix; Based on the velocity matching space matrix, the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment are determined.

[0011] Furthermore, the step of determining the phase compensation result corresponding to each underwater acoustic frequency domain signal segment based on the motion compensation parameters, using the frequency domain data space matrix and the compensation operator matrix respectively, includes: Determine the number of moving objects corresponding to each of the underwater acoustic frequency domain signal segments; For the single moving object, based on the motion compensation parameters, the first phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix respectively; For the multiple moving objects, based on the motion compensation parameters, the second phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix.

[0012] This application embodiment also provides a motion compensation device for passive sonar detection, the motion compensation device comprising: The signal acquisition module is used to acquire underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period. The segmented transformation module is used to segment the underwater acoustic signal to obtain multiple underwater acoustic time-domain signal segments, and to perform Fourier transform on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment. The motion compensation module is used to construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and based on the parameterized search matrix, determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment through a spectral energy search. The phase compensation module is used to perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters, so as to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment. The signal compensation module is used to perform inverse discrete Fourier transform on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

[0013] Furthermore, when the segmented transformation module is used to segment the underwater acoustic signal to obtain multiple underwater acoustic time-domain signal segments, the segmented transformation module is used to: The amplitude and length values ​​corresponding to the underwater acoustic signal are obtained, and based on the amplitude value, the length value and the preset phase signal coefficient, the polynomial underwater acoustic signal corresponding to each sampling moment within the preset period is determined; The polynomial underwater acoustic signal is segmented according to a preset segmented data volume to determine the time interval and non-overlapping data corresponding to each polynomial underwater acoustic signal. Based on the time interval and the non-overlapping data, a preset rectangular window function is used to determine the underwater acoustic time-domain signal segment corresponding to each polynomial underwater acoustic signal, so as to obtain multiple underwater acoustic time-domain signal segments.

[0014] Furthermore, when the segmented transformation module performs a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the corresponding underwater acoustic frequency-domain signal segments, the segmented transformation module is used to: Based on the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment, the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is determined. Perform a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segments corresponding to each underwater acoustic time-domain signal segment; wherein the frequency variation range corresponding to each underwater acoustic frequency-domain signal segment is greater than or equal to the calibrated frequency variation range.

[0015] Furthermore, when the motion compensation module constructs a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and determines the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment based on the parameterized search matrix through a spectral energy search, the motion compensation module is used to: Based on the pre-constructed velocity relationship of the moving object relative to the passive sonar in the target water area, a parameterized search matrix is ​​constructed for each underwater acoustic frequency domain signal band; wherein, the parameterized search matrix includes a frequency search range parameter, a target velocity search range parameter, and an equivalent initial frequency; Based on the parameterized search matrix, a joint search of velocity and frequency is performed on each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking on each underwater acoustic frequency domain signal segment and determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment. Based on the target velocity search range, construct an energy spectrum-like search matrix; Based on the energy spectrum search matrix, an energy spectrum search is performed on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

[0016] Furthermore, when the phase compensation module is used to perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment, the phase compensation module is used to: For each frequency point and the corresponding phase in each underwater acoustic frequency domain signal segment, a joint reconstruction is performed to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment; Based on the motion compensation parameters, the phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined by using the frequency domain data space matrix and the compensation operator matrix, respectively. Based on the phase compensation result, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0017] Furthermore, when the phase compensation module is used to jointly reconstruct each frequency point and the corresponding phase in each of the underwater acoustic frequency domain signal segments to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment, the phase compensation module is used to: For each frequency point in each underwater acoustic frequency domain signal segment and the phase corresponding to each frequency point, a joint reconstruction is performed to construct a motion compensation model corresponding to the underwater acoustic frequency domain signal segment; Based on the motion compensation model, a discrete Fourier transform based on the frequency search range is performed on the parameterized search matrix to obtain the frequency search matrix; The frequency search matrix is ​​decomposed according to the frequency search range to obtain the velocity matching space matrix; Based on the velocity matching space matrix, the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment are determined.

[0018] Furthermore, when the phase compensation module is used to determine the phase compensation result corresponding to each underwater acoustic frequency domain signal segment based on the motion compensation parameters and using the frequency domain data space matrix and the compensation operator matrix respectively, the phase compensation module is used to: Determine the number of moving objects corresponding to each of the underwater acoustic frequency domain signal segments; For the single moving object, based on the motion compensation parameters, the first phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix respectively; For the multiple moving objects, based on the motion compensation parameters, the second phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix.

[0019] This application embodiment also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the motion compensation method for passive sonar detection as described above are performed.

[0020] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the motion compensation method for passive sonar detection as described above.

[0021] The passive sonar detection motion compensation method and apparatus provided in this application include: acquiring underwater acoustic signals collected in real time by a passive sonar targeting a moving object in a target water area within a preset period; segmenting the underwater acoustic signals to obtain multiple underwater acoustic time-domain signal segments, and performing a Fourier transform on each underwater acoustic time-domain signal segment to obtain an underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment; constructing a parameterized search matrix corresponding to each underwater acoustic frequency-domain signal segment, and determining motion compensation parameters corresponding to each underwater acoustic frequency-domain signal segment based on the parameterized search matrix through a spectral-like search; performing phase compensation on each frequency point in the underwater acoustic frequency-domain signal segment based on the motion compensation parameters to obtain a compensated frequency-domain signal segment corresponding to each underwater acoustic frequency-domain signal segment; and performing an inverse discrete Fourier transform on the compensated frequency-domain signal segment to obtain a compensated time-domain signal segment corresponding to each underwater acoustic time-domain signal segment, thereby determining the long-time coherent integral result corresponding to the underwater acoustic signal.

[0022] Compared with existing autoregressive moving average frequency estimation methods based on parameterized models, this method obtains multiple underwater acoustic signal segments by segmenting and performing Fourier transform on the underwater acoustic signals collected in real time by passive sonar for moving objects in the target water area within a preset period. By constraining the search frequency and search speed of each underwater acoustic signal segment, broadband spectral peak tracking is performed on each underwater acoustic signal segment. Then, motion compensation parameters are determined through energy spectrum-like search. This method has the advantages of faster convergence speed and lower computational complexity. It obtains long-time coherence integral results while obtaining the motion-compensated underwater acoustic time-domain signal, realizing gain improvement in passive sonar detection processing under low signal-to-noise ratio conditions, and improving the accuracy and stability of passive sonar detection.

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A flowchart illustrating a motion compensation method for passive sonar detection provided in an embodiment of this application; Figure 2 A comparative example diagram of low-frequency analysis and recording of underwater acoustic signals provided in an embodiment of this application; Figure 3 A comparative example diagram of an underwater acoustic signal line spectrum provided in an embodiment of this application; Figure 4 A schematic diagram of a motion compensation device for passive sonar detection provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0027] Research has found that passive sonar detection technology achieves covert detection by receiving noise radiated by moving targets. The detection performance of passive sonar is limited by the signal accumulation time and the Doppler effect. In real-world scenarios, moving targets cause time delay spread and Doppler frequency shift in the generated signal, which destroys the signal phase coherence. Traditional long-time coherent integration methods (e.g., periodogram methods) significantly reduce the signal integration gain.

[0028] Currently, the autoregressive moving average frequency estimation method based on parameterized models can compensate for the Doppler effect by estimating the motion parameters of the target moving object. Although it can obtain good processing gain under high signal-to-noise ratio conditions, the parameter estimation error is large under low signal-to-noise ratio conditions, which reduces the accuracy and stability of passive sonar detection.

[0029] Based on this, this application provides a motion compensation method for passive sonar detection. By segmenting and performing Fourier transform on the underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period, multiple underwater acoustic frequency domain signal segments are obtained. By constraining the search frequency and search speed of each underwater acoustic frequency domain signal segment, broadband spectral peak tracking is performed on each underwater acoustic frequency domain signal segment. Then, motion compensation parameters are determined through energy spectrum-like search. This method has the advantages of fast convergence speed and low computational complexity. While obtaining the motion-compensated underwater acoustic time domain signal, a long-time coherence integral result is also obtained, realizing the gain improvement of passive sonar detection processing under low signal-to-noise ratio conditions, and improving the accuracy and stability of passive sonar detection.

[0030] Please see Figure 1 , Figure 1 This is a flowchart illustrating a motion compensation method for passive sonar detection provided in an embodiment of this application. Figure 1 As shown in the figure, the motion compensation method for passive sonar detection provided in this application embodiment includes: S101. Acquire underwater acoustic signals collected in real time by a passive sonar for moving objects in the target water area within a preset period.

[0031] It should be noted that passive sonar is an important detection device in underwater acoustic engineering. It does not actively emit sound waves, but receives the noise radiated by the target itself in the water (such as mechanical noise, propeller noise and hydrodynamic noise), and extracts information such as the target's location, type, speed and distance from it, so as to achieve covert detection of the target.

[0032] In this embodiment of the application, a passive sonar is installed in the target water area. The passive sonar detects the moving object in the target water area by receiving the noise radiated by the moving object within a preset period, so as to obtain the underwater acoustic signal corresponding to the moving object within the preset period.

[0033] Here, there can be one or more moving objects in the target water area.

[0034] S102. The underwater acoustic signal is segmented to obtain multiple underwater acoustic time-domain signal segments, and Fourier transform is performed on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment.

[0035] In this embodiment of the application, in order to focus on underwater passive sonar detection, coherent gain is obtained through long-time integration in the frequency domain to achieve accurate target detection. Therefore, it is necessary to obtain the underwater acoustic frequency domain signal segment by segmenting the underwater acoustic time domain signal and performing Fourier transform.

[0036] In one possible implementation of this application, in specific implementation, the step of segmenting the underwater acoustic signal in step S102 to obtain multiple underwater acoustic time-domain signal segments may include: S1021. Obtain the amplitude value and length value corresponding to the underwater acoustic signal, and determine the polynomial underwater acoustic signal corresponding to each sampling moment within a preset period based on the amplitude value, the length value and the preset phase signal coefficient.

[0037] In this embodiment of the application, the underwater acoustic signal can be approximated as a polynomial underwater acoustic signal, and the expression corresponding to the polynomial underwater acoustic signal is as follows.

[0038] .

[0039] in, This represents the polynomial underwater acoustic signal corresponding to each sampling time. This represents the amplitude value corresponding to the underwater acoustic signal; This represents the length value corresponding to the underwater acoustic signal; and This represents the preset phase signal coefficients. .

[0040] Here, due to the Doppler effect, based on the polynomial underwater acoustic signal corresponding to each sampling time, it can be determined that the received underwater acoustic signal is non-stationary and time-varying.

[0041] S1022. The polynomial underwater acoustic signal is segmented according to a preset segmented data volume to determine the time interval and non-overlapping data corresponding to each polynomial underwater acoustic signal.

[0042] Here, in order to reduce the sensitivity of the frequency resolution unit to Doppler frequency shift, the polynomial underwater acoustic signal is segmented.

[0043] In this step, before obtaining each underwater acoustic time-domain signal segment through segmentation, the polynomial underwater acoustic signal needs to be segmented according to the preset segmentation data volume, and the time interval and non-overlapping data between each polynomial underwater acoustic signal need to be determined during the segmentation process.

[0044] Among them, non-overlapping data means that each segment of underwater acoustic signal is connected end to end with no repeated sampling points; the time interval represents the product between the sampling interval and the number of sampling points.

[0045] S1023. Based on the time interval and the non-overlapping data, a preset rectangular window function is used to determine the underwater acoustic time domain signal segment corresponding to each of the polynomial underwater acoustic signals, so as to obtain multiple underwater acoustic time domain signal segments.

[0046] In this embodiment of the application, the expression for the underwater acoustic time-domain signal segment is as follows.

[0047] .

[0048] in, Indicates the first One underwater acoustic time-domain signal segment, Indicates the number of time-domain signal segments in underwater acoustics. This represents the length of each underwater acoustic time-domain signal segment, that is, the number of sampling points in the underwater acoustic time-domain signal segment; Represents a rectangular window function; Indicates non-overlapping data; Indicates the first The time interval of each underwater acoustic time-domain signal segment; and This represents the preset phase signal coefficient.

[0049] In one possible implementation of this application, in specific implementation, the step S102 of performing a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segment corresponding to each of the underwater acoustic time-domain signal segments may include: S1024. Based on the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment, determine the frequency variation range corresponding to each underwater acoustic frequency domain signal segment.

[0050] In the embodiments of this application, the expression for the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment is as follows.

[0051] .

[0052] in, Indicates the first The initial constant frequency corresponding to each underwater acoustic frequency domain signal segment; This represents the time interval for each underwater acoustic frequency domain signal segment; and This represents the preset phase signal coefficients; This indicates non-overlapping data.

[0053] In the embodiments of this application, the expression for the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is as follows.

[0054] .

[0055] in, This indicates the frequency variation range corresponding to each underwater acoustic frequency domain signal segment. Indicates a discrete frequency index; This indicates the length of each underwater acoustic frequency domain signal segment; This represents the time interval for each underwater acoustic frequency domain signal segment.

[0056] S1025. Perform a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segment corresponding to each of the underwater acoustic time-domain signal segments.

[0057] In this embodiment of the application, the first expression of the Fourier transform is as follows.

[0058] .

[0059] Furthermore, the second expression of the Fourier transform, derived from the first expression of the Fourier transform, is shown below.

[0060] .

[0061] in, Indicates the first One underwater acoustic frequency domain signal band; This indicates the length of each underwater acoustic frequency domain signal segment; This indicates the frequency variation range corresponding to each underwater acoustic frequency domain signal segment; This represents the amplitude value corresponding to the underwater acoustic signal; Indicates non-overlapping data; Indicates the first The time interval of each underwater acoustic frequency domain signal segment; and This represents the preset phase signal coefficients; Represents the first frequency band of underwater acoustic signal. One sampling point; express The sum of higher powers.

[0062] Wherein, the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is greater than or equal to the calibrated frequency variation range, and the corresponding expression is as follows.

[0063] .

[0064] in, This indicates frequency resolution, meaning that the frequency remains approximately constant within each underwater acoustic frequency domain signal segment; and This represents the preset phase signal coefficients; This indicates the length of each underwater acoustic frequency domain signal segment; This represents the time interval for each underwater acoustic frequency domain signal segment.

[0065] S103. Construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment based on the parameterized search matrix through energy spectrum-like search.

[0066] In the embodiments of this application, by constraining the search frequency and search speed, spectral peak tracking is performed in the underwater acoustic frequency domain signal band, and motion compensation parameters are obtained through energy spectrum-like search. This has a faster convergence speed and lower computational complexity, and enhances the effectiveness of compensation under dual search of frequency point and phase.

[0067] In one possible implementation of this application, step S103 may include: S1031. Based on the pre-constructed velocity relationship between the moving object and the passive sonar in the target water area, construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment.

[0068] The parameterized search matrix includes a frequency search range parameter, a target velocity search range parameter, and an equivalent initial frequency.

[0069] In practical applications, when an underwater moving object is moving in the far field, the velocity relationship of the moving object relative to the passive sonar in the target water area is pre-constructed, and the expression of the velocity relationship is as follows.

[0070] 。

[0071] in, This represents the velocity value of a moving object. This represents the initial distance between the moving object and the passive sonar. Indicates the target azimuth angle between the moving object and the passive sonar; Indicates the signal sampling time.

[0072] Furthermore, based on the above velocity relationship, it can be determined that the change in instantaneous Doppler frequency shift can be approximated as a linear change.

[0073] In this embodiment of the application, the expression of the parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment is as follows.

[0074] .

[0075] in, Represents the parameterized search matrix. Indicates the frequency search range parameter. This parameter represents the target velocity search range. Indicates the equivalent initial frequency; This represents a joint search of frequency and velocity in the underwater acoustic frequency domain signal band. This indicates linear phase compensation for underwater acoustic signal bands.

[0076] S1032. Based on the parameterized search matrix, perform a joint search of velocity and frequency for each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking for each underwater acoustic frequency domain signal segment and determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment.

[0077] In the embodiments of this application, a joint search of velocity and frequency is performed on each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking on each underwater acoustic frequency domain signal segment, determine the setting form of frequency search range parameters, target velocity search range parameters and equivalent initial frequency in the parameterized search matrix, and then determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment.

[0078] Here, the search parameters in the parameterized search matrix are set in the following form.

[0079] .

[0080] in, This indicates the number of parameters for the frequency search range. This indicates the number of parameters representing the target velocity search range. Indicates the number of equivalent initial frequencies; Indicates the frequency search range; Indicates the target speed search range. Indicates the equivalent initial frequency range; It is the search range of the target velocity search range parameter. It is the search interval of the equivalent initial frequency.

[0081] S1033. Based on the target velocity search range, construct an energy spectrum-like search matrix.

[0082] In this step, after jointly searching for velocity and frequency, i.e., through cross-frequency point frequency shift correction and linear phase difference compensation, an energy spectrum-like search matrix can be constructed based on the target velocity search range.

[0083] Here, cross-frequency shift correction is the matching between the frequency search range and the target velocity search range, and linear phase difference compensation is the matching between the target velocity search range and the initial frequency range.

[0084] In this embodiment of the application, the expression for the energy spectrum search matrix is ​​as follows.

[0085] .

[0086] in, Represents the energy spectrum search matrix; This represents the motion compensation parameters.

[0087] Here, the motion compensation parameter represents the velocity search parameter when matching the Doppler frequency shift of the moving object.

[0088] S1034. Based on the energy spectrum search matrix, perform an energy spectrum search on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

[0089] In this step, a similar energy spectrum search matrix is ​​used to perform a similar energy spectrum search on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

[0090] Furthermore, based on the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment, a linear compensation vector corresponding to each underwater acoustic frequency domain signal segment is determined, so as to realize the coherent accumulation of the energy of the passive sonar received signal in the parameterized search matrix.

[0091] S104. Based on the motion compensation parameters, perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0092] In one possible implementation of this application, step S104 may include: S1041. Jointly reconstruct each frequency point and the phase corresponding to each frequency point in each underwater acoustic frequency domain signal segment to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment.

[0093] In one possible implementation of this application, step S1041 may include: S10411. Jointly reconstruct each frequency point and the phase corresponding to each frequency point in each underwater acoustic frequency domain signal segment to construct the motion compensation model corresponding to the underwater acoustic frequency domain signal segment.

[0094] In this embodiment of the application, the expression of the motion compensation model is as follows.

[0095] .

[0096] in, Represents the parameterized search matrix. Indicates the frequency search range parameter. This parameter represents the target velocity search range. Indicates the equivalent initial frequency; Represents the frequency search matrix; Indicates the total number of parameters; This represents the angular frequency value of the passive sonar.

[0097] S10412. Based on the motion compensation model, perform a discrete Fourier transform on the parameterized search matrix based on the frequency search range to obtain the frequency search matrix.

[0098] In this application, a discrete Fourier transform based on the frequency search range is performed on the parameterized search matrix, and the expression for the frequency search range is as follows.

[0099] .

[0100] in, Indicates the frequency search range; Indicates the number of parameters for the frequency search range; This indicates the length of each underwater acoustic frequency domain signal segment; This represents the time interval for each underwater acoustic frequency domain signal segment.

[0101] Furthermore, the expression for the frequency search matrix is ​​shown below.

[0102] .

[0103] in, Represents the frequency search matrix; Indicates the frequency search term; This indicates the number of parameters for the frequency search range.

[0104] S10413. Decompose the frequency search matrix according to the frequency search range to obtain the velocity matching space matrix.

[0105] In this application, the expression for the velocity matching space matrix obtained by decomposing the frequency search matrix according to the frequency search range is shown below.

[0106] .

[0107] in, Represents the velocity matching space matrix; Represents the frequency domain data space matrix; Represents the compensation operator matrix; This indicates the number of parameters for the target velocity search range.

[0108] S10414. Based on the velocity matching space matrix, determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment.

[0109] In this application, the expression for the frequency domain data space matrix corresponding to each underwater acoustic frequency domain signal segment is as follows.

[0110] .

[0111] in, Indicates the first The frequency domain data space matrix corresponding to each underwater acoustic frequency domain signal segment; Indicates the frequency search range.

[0112] In this application, the expression for the compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment is shown below.

[0113] .

[0114] in, Indicates the first The compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment; Indicates the target speed search range. Indicates the equivalent initial frequency range; Indicates the frequency search range.

[0115] S1042. Based on the motion compensation parameters, the phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined by using the frequency domain data space matrix and the compensation operator matrix respectively.

[0116] In one possible implementation of this application, step S1042 may include: S10421. Determine the number of moving objects corresponding to each underwater acoustic frequency domain signal segment.

[0117] In this embodiment of the application, the corresponding phase compensation result is determined based on the number of moving objects corresponding to each underwater acoustic frequency domain signal segment being one or more.

[0118] S10422. For the single moving object, based on the motion compensation parameters, the first phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix.

[0119] In this application, the expression for the first phase compensation result is as follows.

[0120] .

[0121] in, This indicates the result of the first phase compensation; Indicates motion compensation parameters; Indicates the number of frequency domain signal segments in the underwater acoustic domain; Indicates the frequency search range parameter. This represents the equivalent initial frequency.

[0122] S10423. For the multiple moving objects, based on the motion compensation parameters, the second phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix respectively.

[0123] In this application, the expression for the second phase compensation result is as follows.

[0124] .

[0125] in, This indicates the result of the second phase compensation; Indicates motion compensation parameters; Indicates the number of frequency domain signal segments in the underwater acoustic domain; Indicates the frequency search range parameter. This represents the equivalent initial frequency.

[0126] S1043. Based on the phase compensation result, perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0127] Here, based on the phase compensation results, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment, so that all parameter information in the parameterized search matrix is ​​considered and the characteristics of each parameter can be preserved, thus obtaining the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0128] S105. Perform inverse discrete Fourier transform on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

[0129] In this embodiment, based on known motion compensation parameters, phase compensation is performed on all frequency points in each underwater acoustic frequency domain signal segment. Conjugate symmetry is used to perform inverse discrete Fourier transform on each frame signal, which not only obtains the motion-compensated time domain signal segment, but also outputs the long-time coherent integral result, thereby achieving gain improvement in passive sonar detection processing under low signal-to-noise ratio conditions.

[0130] For example, a simulation test was conducted on the compensation effect of the embodiments of this application. The signal-to-noise ratio was set to -27dB, the sampling frequency to 5000Hz, and the speed of the moving object to 3m / s. A signal model was established for a single passive sonar receiving a linear target moving at a constant speed from a passive system. It was assumed that a moving target object moves along a straight line at a constant speed, the initial distance between the moving target object and the receiver of the passive sonar is 1500m, the angle between the moving target object and the receiver of the passive sonar relative to the direction of motion of the passive sonar is 85°, and the speed of sound in water is 1500m / s. Comparative tests were conducted under these simulation conditions.

[0131] Please see Figure 2 , Figure 3 , Figure 2 This is a comparative example diagram showing the low-frequency analysis and recording of underwater acoustic signals provided in an embodiment of this application. Figure 3 This is a comparative example diagram of an underwater acoustic signal line spectrum provided in an embodiment of this application.

[0132] like Figure 2 As shown in the figure, the low-frequency analysis and recording of the underwater acoustic time-domain signal before and after compensation can be compared. It can be seen that the embodiment of this application not only obtains the underwater acoustic time-domain signal after motion compensation, but also outputs the long-time coherent integration result, thereby realizing the gain improvement of passive sonar detection processing under low signal-to-noise ratio conditions.

[0133] like Figure 3 As shown in the figure, a comparison of the signal line spectra of the underwater acoustic time domain signals before and after compensation shows that the underwater acoustic signals compensated in this embodiment of the application improve the accuracy and stability of passive sonar detection.

[0134] The motion compensation method for passive sonar detection provided in this application involves segmenting and performing Fourier transform on the underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period to obtain multiple underwater acoustic frequency domain signal segments. By constraining the search frequency and search speed of each underwater acoustic frequency domain signal segment, broadband spectral peak tracking is performed on each underwater acoustic frequency domain signal segment. Then, motion compensation parameters are determined through energy spectrum-like search. This method has the advantages of fast convergence speed and low computational complexity. It obtains long-time coherence integral results while obtaining the motion-compensated underwater acoustic time domain signal, thereby achieving gain improvement in passive sonar detection processing under low signal-to-noise ratio conditions and improving the accuracy and stability of passive sonar detection.

[0135] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a motion compensation device for passive sonar detection provided in an embodiment of this application. Figure 4 As shown, the motion compensation device 400 includes: The signal acquisition module 410 is used to acquire underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period. The segmented transformation module 420 is used to segment the underwater acoustic signal to obtain multiple underwater acoustic time-domain signal segments, and to perform Fourier transform on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment. The motion compensation module 430 is used to construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment based on the parameterized search matrix through a spectral energy search. The phase compensation module 440 is used to perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters, so as to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment. The signal compensation module 450 is used to perform inverse discrete Fourier transform on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

[0136] Furthermore, when the segmentation transformation module 420 is used to segment the underwater acoustic signal to obtain multiple underwater acoustic time-domain signal segments, the segmentation transformation module 420 is used to: The amplitude and length values ​​corresponding to the underwater acoustic signal are obtained, and based on the amplitude value, the length value and the preset phase signal coefficient, the polynomial underwater acoustic signal corresponding to each sampling moment within the preset period is determined; The polynomial underwater acoustic signal is segmented according to a preset segmented data volume to determine the time interval and non-overlapping data corresponding to each polynomial underwater acoustic signal. Based on the time interval and the non-overlapping data, a preset rectangular window function is used to determine the underwater acoustic time-domain signal segment corresponding to each polynomial underwater acoustic signal, so as to obtain multiple underwater acoustic time-domain signal segments.

[0137] Furthermore, when the segmented transformation module 420 performs a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment, the segmented transformation module 420 is used to: Based on the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment, the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is determined. Perform a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segments corresponding to each underwater acoustic time-domain signal segment; wherein the frequency variation range corresponding to each underwater acoustic frequency-domain signal segment is greater than or equal to the calibrated frequency variation range.

[0138] Furthermore, when the motion compensation module 430 constructs a parameterized search matrix corresponding to each of the underwater acoustic frequency domain signal segments, and determines the motion compensation parameters corresponding to each of the underwater acoustic frequency domain signal segments based on the parameterized search matrix through a spectral energy search, the motion compensation module 430 is used to: Based on the pre-constructed velocity relationship of the moving object relative to the passive sonar in the target water area, a parameterized search matrix is ​​constructed for each underwater acoustic frequency domain signal band; wherein, the parameterized search matrix includes a frequency search range parameter, a target velocity search range parameter, and an equivalent initial frequency; Based on the parameterized search matrix, a joint search of velocity and frequency is performed on each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking on each underwater acoustic frequency domain signal segment and determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment. Based on the target velocity search range, construct an energy spectrum-like search matrix; Based on the energy spectrum search matrix, an energy spectrum search is performed on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

[0139] Furthermore, when the phase compensation module 440 performs phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment, the phase compensation module 440 is used to: For each frequency point and the corresponding phase in each underwater acoustic frequency domain signal segment, a joint reconstruction is performed to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment; Based on the motion compensation parameters, the phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined by using the frequency domain data space matrix and the compensation operator matrix, respectively. Based on the phase compensation result, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

[0140] Furthermore, when the phase compensation module 440 is used to jointly reconstruct each frequency point and the corresponding phase in each of the underwater acoustic frequency domain signal segments to determine the frequency domain data space matrix and compensation operator matrix corresponding to each of the underwater acoustic frequency domain signal segments, the phase compensation module 440 is used to: For each frequency point in each underwater acoustic frequency domain signal segment and the phase corresponding to each frequency point, a joint reconstruction is performed to construct a motion compensation model corresponding to the underwater acoustic frequency domain signal segment; Based on the motion compensation model, a discrete Fourier transform based on the frequency search range is performed on the parameterized search matrix to obtain the frequency search matrix; The frequency search matrix is ​​decomposed according to the frequency search range to obtain the velocity matching space matrix; Based on the velocity matching space matrix, the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment are determined.

[0141] Furthermore, when the phase compensation module 440 is used to determine the phase compensation result corresponding to each underwater acoustic frequency domain signal segment based on the motion compensation parameters and using the frequency domain data space matrix and the compensation operator matrix respectively, the phase compensation module 440 is used to: Determine the number of moving objects corresponding to each of the underwater acoustic frequency domain signal segments; For the single moving object, based on the motion compensation parameters, the first phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix respectively; For the multiple moving objects, based on the motion compensation parameters, the second phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix.

[0142] The motion compensation device for passive sonar detection provided in this application embodiment segments and performs Fourier transform on the underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period to obtain multiple underwater acoustic frequency domain signal segments. By constraining the search frequency and search speed of each underwater acoustic frequency domain signal segment, broadband spectral peak tracking is performed on each underwater acoustic frequency domain signal segment. Then, motion compensation parameters are determined through energy spectrum-like search. It has the effect of fast convergence speed and low computational complexity. While obtaining the motion-compensated underwater acoustic time domain signal, it also obtains long-time coherence integral results, realizing gain improvement of passive sonar detection processing under low signal-to-noise ratio conditions, and improving the accuracy and stability of passive sonar detection.

[0143] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 500 includes a processor 510, a memory 520, and a bus 530.

[0144] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 and the memory 520 communicate via the bus 530. When the machine-readable instructions are executed by the processor 510, they can perform the operations described above. Figure 1 The steps of the motion compensation method for passive sonar detection in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0145] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 The steps of the motion compensation method for passive sonar detection in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0146] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0148] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0149] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0150] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0151] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A motion compensation method for passive sonar detection, characterized in that, The motion compensation method includes: Acquire underwater acoustic signals in real time from a passive sonar targeting moving objects in a target water area within a preset period; The underwater acoustic signal is segmented to obtain multiple underwater acoustic time-domain signal segments, and a Fourier transform is performed on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment. Construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment based on the parameterized search matrix through a spectral energy search. Based on the motion compensation parameters, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment. The inverse discrete Fourier transform is performed on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

2. The method according to claim 1, characterized in that, The underwater acoustic signal is segmented to obtain multiple underwater acoustic time-domain signal segments, including: The amplitude and length values ​​corresponding to the underwater acoustic signal are obtained, and based on the amplitude value, the length value and the preset phase signal coefficient, the polynomial underwater acoustic signal corresponding to each sampling moment within the preset period is determined; The polynomial underwater acoustic signal is segmented according to a preset segmented data volume to determine the time interval and non-overlapping data corresponding to each polynomial underwater acoustic signal. Based on the time interval and the non-overlapping data, a preset rectangular window function is used to determine the underwater acoustic time domain signal segment corresponding to each polynomial underwater acoustic signal, so as to obtain multiple underwater acoustic time domain signal segments.

3. The method according to claim 1, characterized in that, The step of performing a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the corresponding underwater acoustic frequency-domain signal segments includes: Based on the initial constant frequency corresponding to each underwater acoustic frequency domain signal segment, the frequency variation range corresponding to each underwater acoustic frequency domain signal segment is determined. Perform a Fourier transform on each of the underwater acoustic time-domain signal segments to obtain the underwater acoustic frequency-domain signal segments corresponding to each underwater acoustic time-domain signal segment; wherein the frequency variation range corresponding to each underwater acoustic frequency-domain signal segment is greater than or equal to the calibrated frequency variation range.

4. The method according to claim 1, characterized in that, The step of constructing a parameterized search matrix corresponding to each of the underwater acoustic frequency domain signal segments, and determining the motion compensation parameters corresponding to each of the underwater acoustic frequency domain signal segments based on the parameterized search matrix through a spectral energy search, includes: Based on the pre-constructed velocity relationship of the moving object relative to the passive sonar in the target water area, a parameterized search matrix is ​​constructed for each underwater acoustic frequency domain signal band; wherein, the parameterized search matrix includes a frequency search range parameter, a target velocity search range parameter, and an equivalent initial frequency; Based on the parameterized search matrix, a joint search for velocity and frequency is performed on each underwater acoustic frequency domain signal segment to perform broadband spectral peak tracking on each underwater acoustic frequency domain signal segment and determine the target velocity search range corresponding to each underwater acoustic frequency domain signal segment. Based on the target velocity search range, construct an energy spectrum-like search matrix; Based on the energy spectrum search matrix, an energy spectrum search is performed on each underwater acoustic frequency domain signal segment to determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment.

5. The method according to claim 1, characterized in that, The step of performing phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment includes: For each frequency point and the corresponding phase in each underwater acoustic frequency domain signal segment, a joint reconstruction is performed to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment; Based on the motion compensation parameters, the phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined by using the frequency domain data space matrix and the compensation operator matrix, respectively. Based on the phase compensation result, phase compensation is performed on each frequency point in the underwater acoustic frequency domain signal segment to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment.

6. The method according to claim 5, characterized in that, The step of jointly reconstructing each frequency point and the corresponding phase in each of the underwater acoustic frequency domain signal segments to determine the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment includes: For each frequency point in each underwater acoustic frequency domain signal segment and the phase corresponding to each frequency point, a joint reconstruction is performed to construct a motion compensation model corresponding to the underwater acoustic frequency domain signal segment; Based on the motion compensation model, a discrete Fourier transform based on the frequency search range is performed on the parameterized search matrix to obtain the frequency search matrix; The frequency search matrix is ​​decomposed according to the frequency search range to obtain the velocity matching space matrix; Based on the velocity matching space matrix, the frequency domain data space matrix and compensation operator matrix corresponding to each underwater acoustic frequency domain signal segment are determined.

7. The method according to claim 5, characterized in that, The step of determining the phase compensation result for each underwater acoustic frequency domain signal segment based on the motion compensation parameters, using the frequency domain data space matrix and the compensation operator matrix respectively, includes: Determine the number of moving objects corresponding to each of the underwater acoustic frequency domain signal segments; For the single moving object, based on the motion compensation parameters, the first phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix respectively; For the multiple moving objects, based on the motion compensation parameters, the second phase compensation result corresponding to each underwater acoustic frequency domain signal segment is determined using the frequency domain data space matrix and the compensation operator matrix.

8. A motion compensation device for passive sonar detection, characterized in that, The motion compensation device includes: The signal acquisition module is used to acquire underwater acoustic signals collected in real time by the passive sonar for moving objects in the target water area within a preset period. The segmented transformation module is used to segment the underwater acoustic signal to obtain multiple underwater acoustic time-domain signal segments, and to perform Fourier transform on each underwater acoustic time-domain signal segment to obtain the underwater acoustic frequency-domain signal segment corresponding to each underwater acoustic time-domain signal segment. The motion compensation module is used to construct a parameterized search matrix corresponding to each underwater acoustic frequency domain signal segment, and based on the parameterized search matrix, determine the motion compensation parameters corresponding to each underwater acoustic frequency domain signal segment through a spectral energy search. The phase compensation module is used to perform phase compensation on each frequency point in the underwater acoustic frequency domain signal segment based on the motion compensation parameters, so as to obtain the compensated frequency domain signal segment corresponding to each underwater acoustic frequency domain signal segment. The signal compensation module is used to perform inverse discrete Fourier transform on the compensated frequency domain signal segment to obtain the compensated time domain signal segment corresponding to each underwater acoustic time domain signal segment, so as to determine the long-time coherent integration result corresponding to the underwater acoustic signal.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the motion compensation method for passive sonar detection as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the motion compensation method for passive sonar detection as described in any one of claims 1 to 7.

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