Multi-mode aperture imaging sonar method and system

Abstract

The invention discloses a multi-mode aperture imaging sonar method and system, and the method and system achieve synthetic aperture imaging through the processes of orthogonal demodulation, pulse compression, intra-frame beam forming and inter-frame synthetic aperture, and expand the processes of single-beam real aperture imaging and multi-beam real aperture imaging in parallel on the basis of synthetic aperture imaging. Wherein the single-beam imaging data is acquired in a manner of performing channel superposition and resolution equalization on the pulse compression data, the multi-beam imaging data is acquired in a manner of performing azimuth matching on the intra-frame beam forming result data, and finally, the output of three acoustic diagrams is realized; according to the technical scheme of the invention, the single-beam imaging method, the multi-beam imaging method and the synthetic aperture imaging method are compatible in a manner of reasonably configuring the parallel data path and module cooperative relationship of each imaging process, the advantages of each imaging method are integrated, and the resource utilization rate is improved. And the adaptability of the sonar system to the imaging mode and the coverage of the sonar system to the application scene are expanded.

Description

Technical Field

[0001] The present application relates to the technical field of underwater acoustic imaging, and in particular to a multi-mode aperture imaging sonar method and system. Background Art

[0002] In the field of underwater acoustic imaging, traditional methods such as side-scan sonar and synthetic aperture sonar are relatively mature. Side-scan sonar utilizes real-aperture imaging, which offers advantages such as simple principle, low cost, ease of operation, and minimal impact from platform motion. However, it suffers from the disadvantage that azimuth resolution decreases with increasing target distance. When performing large-scale target identification or classification tasks, such as continuous inspection of submarine pipelines and sunken structures, the reduced resolution can hinder the identification of distant targets' outlines or details, reducing recognition accuracy. Synthetic aperture sonar, on the other hand, utilizes virtual-aperture imaging, a more advanced technology with the advantage of azimuth resolution being independent of target distance. However, it is significantly affected by platform motion and is prone to azimuth ambiguity at high speeds. During high-speed operations and dynamic monitoring, or in complex sea conditions (such as those with strong winds and waves or fluctuating currents), the platform's motion becomes unstable, leading to image distortion, impacting overall surveying and mapping efficiency and image quality, and in severe cases, even leading to imaging failure.

[0003] Therefore, in order to solve the above problems, it is urgent to design a method that can adapt to various complex monitoring situations and take into account the advantages of traditional imaging sonars such as side scan sonar and synthetic aperture sonar, so as to improve the imaging quality and wide adaptability of sonar. Summary of the Invention

[0004] The purpose of this application is to provide a multi-mode aperture imaging method to address the problems that the azimuth resolution of existing side-scan sonar technology varies with target distance during detection, and that the existing synthetic aperture sonar technology is greatly affected by the platform posture and speed during detection and is very prone to azimuth ambiguity. The method can simultaneously operate under three modes of aperture: single-beam real aperture, multi-beam real aperture and synthetic aperture, and output three types of mode sound images in real time, taking into account the advantages of traditional imaging sonars such as side-scan sonar and synthetic aperture sonar, thereby greatly improving imaging quality and adaptability.

[0005] The technical solution of the present application is to provide a multi-mode aperture imaging sonar method and system, the method comprising:

[0006] Step 1: construct a target echo model with the range time scale and the azimuth time scale as independent variables;

[0007] Step 2: Collect the original echo data, obtain the echo characteristic parameters from the original echo data, and bring the echo characteristic parameters into the target echo model to obtain a simplified multi-frame echo signal. The echo characteristic parameters include the range time scale, the azimuth time scale, and the initial distance from the target to the sonar;

[0008] Step 3: De-carrier each frame of echo signal by orthogonal demodulation to obtain multiple frames of baseband signals;

[0009] Step 4: pulse compress the multi-frame baseband signals respectively. Specifically, for a single-frame baseband signal, first perform a range Fourier transform, then perform an inverse range Fourier transform after passing through a matched filter to obtain multi-channel range pulse compressed data.

[0010] Step 5: Perform single-beam real aperture imaging using the single-frame pulse compressed data. Specifically, the multi-channel pulse compressed data of the single frame are superimposed channel by channel to form first two-dimensional image data. The resolution of the first two-dimensional image data in the azimuth and range directions is equalized by interpolation, and the processed first two-dimensional image data is converted into a single-beam real aperture acoustic image.

[0011] Step 6: Perform intra-frame beamforming on each frame of multi-channel range pulse compression data to obtain multi-frame beamforming result data;

[0012] Step 7: Perform multi-beam real aperture imaging using the single-frame beamforming result data. Specifically, extract several rows in the center range from the single-frame beamforming result data as second two-dimensional image data, and convert the second two-dimensional image data into a multi-beam real aperture acoustic image.

[0013] Step 8: Perform synthetic aperture imaging using the multi-frame beamforming result data. Specifically, coherently superimpose the multi-frame beamforming result data in the order of time frames, so that the overlapping parts between adjacent frames are superimposed and enhanced to form third two-dimensional image data, and convert the third two-dimensional image data into a synthetic aperture acoustic image.

[0014] Furthermore, step 1 specifically includes the following steps:

[0015] Step 11: Establish the initial target echo model:

[0016]

[0017] Where t is the time scale in range, η is the time scale in azimuth, x is the spatial scale in range, y is the spatial scale in azimuth, ff(x,y) is the target scattering characteristic, a(t,x,y-vη) is the joint directivity function of sonar transmission and reception, v represents the uniform velocity of the carrier in azimuth, and p is m(·) is the sonar transmission signal, c is the speed of sound, R is the distance from the target to the sonar, * t represents the convolution operation on the distance to time scale t;

[0018] Step 12, taking a point target with a constant reflection coefficient and a known initial position as the detection target, simplifies the initial target echo model, specifically including:

[0019] Since the one-way directivity function is approximately a sinc(·) function, the expression of a(t,x,y-vη) is written as:

[0020]

[0021] Where λ is the wavelength of the sound wave corresponding to the sonar emission signal at the center frequency, D T and D R are respectively the transmitting array aperture and the receiving array aperture of the sonar system. When D T With D R When they are equal, they are uniformly written as the array aperture D, and we get:

[0022]

[0023] Taking a point target with a constant reflection coefficient A0 and an initial position (R0, 0) relative to the sonar system as the detection target, the joint directivity function is simplified to obtain:

[0024]

[0025] The simplified joint directivity function is introduced into the target echo model, and the sonar emission signal p m (·) is expressed as a linear frequency modulation signal, and the simplified target echo model is obtained, which is expressed as:

[0026]

[0027] Where rect(·) is the rectangular window function, T is the pulse width, f0 is the center frequency of the sonar emission signal, K is the modulation frequency of the sonar emission signal,

[0028] Furthermore, step 3 specifically includes:

[0029] For a single-frame high-frequency echo signal, multiply and mix it with two local oscillator signals cos(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the in-phase component. Then, multiply and mix the single-frame high-frequency echo signal with two local oscillator signals sin(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the orthogonal component. The in-phase component is used as the real part and the orthogonal component is used as the imaginary part for superposition and combination to obtain the baseband signal ee after carrier removal. b (t,η):

[0030]

[0031] Where, frequency Since vη<<R0, the distance R(η) from the target to the sonar is simplified to:

[0032]

[0033] Substitute the simplified R(η) term into the baseband signal ee after removing the carrier b (t,η).

[0034] Furthermore, in step 4, the data after pulse compression is expressed as:

[0035]

[0036] In the formula, Ee b (f,η) is the baseband signal after the range Fourier transform, f is the frequency of the baseband signal, H(f) is the matched filter, expressed as H(f) = S * (f), S * (f) is the frequency domain conjugate of the sonar transmission signal s(t).

[0037] Furthermore, step 5 specifically includes the following steps:

[0038] Step 51: For a single frame of multi-channel pulse compression data, the pulse compression data of all channels are superimposed in the range direction to form first two-dimensional image data. The first two-dimensional image data is represented as:

[0039]

[0040] Where M is the number of channels, m is the index of the channel, the first two-dimensional image data has azimuth distances as rows and distance sampling points as columns, where the value corresponding to each coordinate is the intensity value;

[0041] Step 52, according to the preset azimuth resolution and range resolution, a set of points uniformly spaced in the row and column direction is reset, the intensity value corresponding to each new point in the original first two-dimensional image data is calculated by using the bilinear interpolation method, and new first two-dimensional image data is generated, so as to complete the equalization processing of image resolution.

[0042] Further, step 52 specifically comprises:

[0043] Traverse each new point, for the current new point (x, y), find out the coordinates of the nearest points in the upper left, upper right, lower left and lower right of the original first two-dimensional image data, which are (x1, y1), (x2, y2), (x3, y3) and (x4, y4) in turn, and the intensity value of the current new point (x, y) is calculated by using the intensity values of the four points, which is represented as:

[0044]

[0045] In the formula, f(·) represents the intensity value of a single point.

[0046] Further, step 6 specifically comprises:

[0047] For single-frame multi-channel range pulse compression data, the target point coordinates (x, y) corresponding to each pixel point of the two-dimensional image are set, for each target point, the corresponding sampling time in each channel echo is determined according to its geometric position, the intensity value at the corresponding sampling time in each channel pulse compression data is extracted, and the beam forming result of each target point is obtained by superimposing these intensity values. The phase compensation term is introduced into the beam forming result of each target point, and the final single-frame beam forming result data is obtained. The beam forming result of the target point (x, y) is represented as:

[0048]

[0049] In the formula, y0 is the azimuth distance of the center of the frame, is the phase compensation term.

[0050] Further, step 7 specifically comprises:

[0051] The range of the single-frame beam forming result data in the azimuth direction is For each frame of beam forming result data, the data with a range of is extracted from the center as the second two-dimensional image data, which is represented as:

[0052]

[0053] In the formula, prt is the pulse transmission interval of the sonar sound wave, r max is the maximum detection distance of the sonar, and θ is the beam opening angle of a single array element in the sonar.

[0054] Furthermore, step 8 specifically includes:

[0055] The beamforming result of the target point (x, y) in the single frame beamforming result data is ee bf (x, y), in order to distinguish the beamforming result data corresponding to different frames, a frame sequence p is introduced. For the same target point, the corresponding beamforming result data are extracted from several consecutive frames and coherently superimposed to form the third two-dimensional image data. After superposition, the beamforming result of the target point is expressed as:

[0056]

[0057] Where p1 and p2 are the starting and ending serial numbers of the frame where the target point is located, respectively.

[0058] The technical solution of the present application also provides a multi-mode aperture imaging sonar system, which is used to perform the above-mentioned multi-mode aperture imaging sonar method. The multi-mode aperture imaging sonar system includes a transmitting transducer array, a multi-channel receiving transducer array, a transmitter, a multi-channel receiver, an underwater control center, a signal processor, a display and control computer, and a power supply. The transmitting transducer array is connected to the transmitter via a cable, the multi-channel receiving transducer array is connected to the multi-channel receiver via a cable, the transmitter, the multi-channel receiver, the signal processor, and the display and control computer are respectively connected to the underwater control center for communication, and the power supply is electrically connected to other modules.

[0059] The transmitting transducer array is used for transmitting detection acoustic wave signals;

[0060] The multi-channel receiving transducer array is used to receive target echo signals;

[0061] The transmitter is used to generate a high-voltage signal of a predetermined waveform and drive the transmitting array to emit a detection sound wave;

[0062] The multi-channel receiver is used to perform pre-processing operations such as amplification, filtering, and analog-to-digital conversion on the original echo signals collected by the multi-channel receiving transducer array;

[0063] The underwater control center is used to coordinate and manage all modules in the sonar system;

[0064] The signal processor is used to perform pulse compression, intra-frame beamforming, and single-beam, multi-beam, and synthetic aperture imaging processing on the received multi-channel echo data to generate two-dimensional image data;

[0065] The display and control computer is used to display two-dimensional image data.

[0066] The beneficial effects of this application are:

[0067] Firstly, the technical scheme in the application realizes synthetic aperture imaging through the processes of orthogonal demodulation, pulse compression, intra-frame beam forming and inter-frame synthetic aperture, and parallelly expands a single-beam real aperture imaging process and a multi-beam real aperture imaging process on the basis of the synthetic aperture imaging process. In the single-beam real aperture imaging process, imaging data is obtained by channel superposition and resolution equalization of pulse compression data. In the multi-beam real aperture imaging process, imaging data is obtained by azimuth matching of intra-frame beam forming result data. The processes of the two kinds of imaging are simplified. For single-beam real aperture imaging, the imaging mode only depends on the superposition and interpolation of single intra-frame channel data, and there is no data or process conflict with the processing based on beam direction in multi-beam imaging and the processing based on inter-frame coherent superposition in synthetic aperture imaging. Like multi-beam imaging and synthetic aperture imaging, the single-beam real aperture imaging also needs to be processed based on pulse compression channel data, and therefore can be executed in parallel with multi-beam imaging and synthetic aperture imaging. For multi-beam real aperture imaging, imaging can be performed by extracting data of several rows at the center from each frame of beam forming result data as effective data. There is no data or process conflict with the processing based on inter-frame coherent superposition in synthetic aperture imaging, and like synthetic aperture imaging, the multi-beam real aperture imaging also needs to be processed based on beam forming result data, and therefore can be executed in parallel with synthetic aperture imaging.

[0068] In the traditional method, each imaging mode is an independent mode and is not expanded. For example, the traditional single-beam side scan sonar and multi-beam side scan sonar cannot realize synthetic aperture imaging because of the small number of channels. The CS algorithm, RD algorithm and ωK algorithm used in the traditional synthetic aperture algorithm do not support data extraction and shunt processing in the processing process, and cannot perform single-beam real aperture imaging and multi-beam real aperture imaging. The technical scheme in the application can be compatible with single-beam real aperture imaging, multi-beam real aperture imaging and synthetic aperture imaging by reasonably configuring the parallel data channel and module coordination relationship of each imaging process. Compared with the traditional method, the technical scheme in the application combines the advantages of each imaging method. When the carrier attitude is stable, the synthetic aperture sonogram with better imaging is used. When the carrier attitude is unstable, the single-beam real aperture sonogram and the multi-beam real aperture sonogram with better imaging are used as compensation. The imaging continuity is ensured while the imaging robustness is improved. Each imaging method enhances each other in the functional level, improves the processing efficiency and resource utilization of the sonar system, expands the adaptability and application scene coverage of the sonar system to the imaging mode, and can form a complete and hierarchical imaging output system.

[0069] Secondly, the technical scheme in the application generates single-beam imaging data by channel superposition and interpolation processing of pulse compression data, simplifies the process of single-beam imaging, improves the angle resolution, reduces the processing delay, and is suitable for real-time imaging and fast preview; traditional single-beam imaging usually scans the vertical track direction of the sonar through one receiving channel, and multiple scan lines are formed as the sonar moves, and then spliced into a two-dimensional image. The traditional single-beam array is usually short and high in frequency, so the detection distance is short and the detection efficiency is low. The technical scheme in the application utilizes the advantage of forming a long array by the multi-channel receiving transducer of the synthetic aperture sonar, and the channel superposition is equivalent to utilizing the aperture of a whole long array, so the angle resolution is high, and the detection distance and detection efficiency can be effectively improved. Moreover, the single-beam imaging in the application can be performed simultaneously with the other two imaging methods, saving the operation time.

[0070] The channel superposition is equivalent to fusing the information of multiple channels on the basis of the real aperture, and the distance characteristics of the target are preserved as much as possible without involving complex inter-frame processing, has a spatial filtering effect, can suppress random noise, can improve the overall image quality, and enhance the information richness of the single-beam real aperture sonar image; in addition, the technical scheme in the application further adds an interpolation processing step after channel superposition, which can balance the image resolution, improve the imaging accuracy and quality, and the single-beam imaging method only processes single-frame data when performing channel superposition, does not depend on the accuracy of continuous motion of the platform, and has the advantage of strong anti-attitude error capability.

[0071] Thirdly, the technical scheme in the application generates multi-beam imaging data by extracting data of several rows at the center from the intra-frame beam forming result data, which simplifies the steps of multi-beam imaging while realizing parallel execution with the synthetic aperture imaging process, and improves the resolution and image clarity in the azimuth direction; traditional multi-beam imaging needs to perform complex processes such as overall time delay correction, phase adjustment, and weighted superposition on echo signals in multiple directions and multiple scales, while the technical scheme in the application introduces a phase compensation term when performing intra-frame beam forming, and directly extracts data of several rows at the center from the beam forming result data of each frame as effective data for imaging when performing subsequent multi-beam real aperture imaging, thereby reducing the amount of data to be processed, reducing the complexity of calculation and processing time, and the intra-frame beam forming can accurately extract echo information in each direction, and by matching and selecting data corresponding to multiple directions at the center, the resolution and image clarity in the azimuth direction can be effectively improved; in addition, the multi-beam imaging method only depends on intra-frame data processing, does not need to accurately register or compensate the phase between multiple frames, has low requirements for the attitude of the carrier, and can be applied to dynamic environments and resource-limited carrier platforms. BRIEF DESCRIPTION OF DRAWINGS

[0072] The advantages of the above and / or additional aspects of the present application will become apparent and readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0073] Figure 1 is a schematic flow chart of a multi-mode aperture imaging sonar method and system according to an embodiment of the present application;

[0074] Figure 2 This is a structural block diagram of a sonar system for implementing a multi-mode aperture imaging method according to an embodiment of the present application;

[0075] Figure 3 is a schematic diagram of resolution equalization according to an embodiment of the present application;

[0076] Figure 4 is a schematic diagram of bilinear interpolation according to an embodiment of the present application;

[0077] Figure 5 This is a diagram of the composition of the sonar system used in the example;

[0078] Figure 6 is a single-beam real aperture acoustic image generated by the method of the present application in the example;

[0079] Figure 7 is a multi-beam real aperture acoustic image generated by the method of the present application in the example;

[0080] Figure 8 It is a synthetic aperture acoustic image generated by the method of the present application in the example. DETAILED DESCRIPTION

[0081] In order to more clearly understand the above-mentioned objectives, features and advantages of the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features therein can be combined with each other in the absence of conflict.

[0082] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0083] like Figure 1 As shown, this embodiment provides a multi-mode aperture imaging sonar method, including:

[0084] Step 1: Construct a target echo model with the range time scale and the azimuth time scale as independent variables. The target echo model is used to describe the mapping relationship between the time domain and the target spatial distribution during the echo signal generation process, providing basic data for subsequent echo data processing and imaging. The specific steps include the following:

[0085] Step 11: Establish an initial target echo model, expressed as:

[0086]

[0087] Where t is the time scale in range, η is the time scale in azimuth, (t,η) is the dimension of the echo data, x is the spatial scale in range, y is the spatial scale in azimuth, (x,y) is the dimension of the imaging result, ff(x,y) is the target scattering characteristic, a(t,x,y-vη) is the joint directivity function of sonar transmission and reception, v represents the speed of the carrier (the carrier refers to the platform carrying the sonar system and performing the imaging task) in uniform motion in azimuth, and p is the target scattering characteristic. m (·) is the sonar transmission signal, c is the speed of sound, R is the distance from the target to the sonar, is the echo delay, * t Represents the convolution operation on the distance to time scale t.

[0088] In this embodiment, the range direction describes the change in the straight-line distance between the target and the sonar system, and the azimuth direction describes the direction of movement of the sonar platform, sometimes also called the "along-track direction."

[0089] Step 12, taking a point target with a constant reflection coefficient and a known initial position as the detection target, simplifies the initial target echo model, specifically including:

[0090] a(t,x,y-vη) is the joint directivity function. Since the directivity function of a single path is approximately the sinc(·) function, the expression of a(t,x,y-vη) is written as:

[0091]

[0092] Where λ is the wavelength of the sound wave corresponding to the sonar emission signal at the center frequency, D T and D R are respectively the transmitting array aperture and the receiving array aperture of the sonar system. When D T With D R When they are equal, they are uniformly written as the array aperture D, and we get:

[0093]

[0094] Taking a point target with a constant reflection coefficient A0 and an initial position (R0, 0) relative to the sonar system as the detection target, the joint directivity function is simplified to obtain:

[0095]

[0096] The simplified joint directivity function is introduced into the target echo model, and the sonar emission signal p m (·) is expressed as a linear frequency modulation signal, and the simplified target echo model is obtained, which is expressed as:

[0097]

[0098] Where rect(·) is the rectangular window function, T is the pulse width, f0 is the center frequency of the sonar transmission signal, K is the modulation frequency of the sonar transmission signal, exp(·) represents the exponential function, and j in jπK is the imaginary unit.

[0099] Step 2: Collect the original echo data, obtain the echo characteristic parameters from the original echo data, bring the echo characteristic parameters into the target echo model, and obtain a simplified multi-frame echo signal, where the echo characteristic parameters include the range time scale t, the azimuth time scale η, and the initial distance R0 from the target to the sonar.

[0100] Step 3: De-carrier each frame of echo signal by orthogonal demodulation to obtain multiple frames of baseband signals. Specifically, the following steps are performed:

[0101] For a single-frame high-frequency echo signal, multiply and mix it with two local oscillator signals cos(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the in-phase component. Then, multiply and mix the single-frame high-frequency echo signal with two local oscillator signals sin(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the orthogonal component. The in-phase component is used as the real part and the orthogonal component is used as the imaginary part for superposition and combination to obtain the baseband signal ee after carrier removal. b (t,η), expressed as:

[0102]

[0103] The initial distance from the target to the sonar is R0. Since vη<<R0, the distance from the target to the sonar R(η) is simplified to:

[0104]

[0105] Will The baseband signal ee after removing the carrier frequency is brought into b (t,η), we get:

[0106]

[0107] In the formula, the relationship between wavelength λ and frequency f0 is

[0108] Step 4, pulse compression is performed on the multi-frame baseband signals respectively, specifically, for a single-frame baseband signal, first, distance-direction Fourier transform is performed, then, after passing through a matched filter, inverse distance-direction Fourier transform is performed, to obtain multi-channel distance-direction pulse compressed data, the pulse compressed data is expressed as:

[0109]

[0110] In the formula, Ee b (f,η) is the baseband signal after distance-direction Fourier transform, f is the frequency of the baseband signal, IFFT{·} is inverse discrete Fourier transform, H(f) is a matched filter, and is expressed as:

[0111] H(f)=S * (f)

[0112] In the formula, S * (f) is the frequency domain conjugate of the sonar transmission signal s(t).

[0113] It should be noted that the transmission signal s(t) of the sonar system is a known signal, which is designed and controlled to be generated before the sonar is used. In practice, a sine wave, a linear frequency modulation signal or a phase coded pulse can be used.

[0114] Step 5, single-beam real aperture imaging is performed using the single-frame pulse compressed data, specifically, the multi-channel pulse compressed data of a single frame is stacked according to the channel to form a first two-dimensional image data, the azimuth direction and the distance direction of the first two-dimensional image data are balanced by interpolation, and the processed first two-dimensional image data is converted into a single-beam real aperture acoustic image.

[0115] Step 51, the multi-channel pulse compressed data of a single frame is stacked in the distance direction, to form a first two-dimensional image data, wherein in the first two-dimensional image data, the value corresponding to each distance sampling point in the distance direction is the superposition of the pulse compressed data of multiple channels at the distance sampling point, and the first two-dimensional image data is expressed as:

[0116]

[0117] In the formula, M is the number of channels (each channel corresponds to an array element in the receiving array), and m is the index of the channel. The first two-dimensional image data has the azimuth direction and the distance direction as rows and the distance direction sampling points as columns, and each coordinate corresponds to an intensity value.

[0118] Step 52: Based on the preset azimuth resolution and range resolution, a group of points with consistent spacing in the row and column directions are reset, and the intensity value corresponding to each new point in the original first two-dimensional image data is calculated using a bilinear interpolation method to generate new first two-dimensional image data, thereby completing the equalization processing of the image resolution. Preferably, the preset azimuth resolution and range resolution are the same.

[0119] like Figure 4 Specifically, the intensity value corresponding to each new point in the original first two-dimensional image data is calculated using a bilinear interpolation method, including the following steps:

[0120] Traverse each new point. For the current new point (x, y), find the coordinates of the points closest to it in the upper left, upper right, lower left, and lower right of the original first two-dimensional image data, which are (x1, y1), (x2, y2), (x3, y3), and (x4, y4) respectively. Use the intensity values ​​of these four points to calculate the intensity value of the current new point (x, y), expressed as:

[0121]

[0122] Where f(·) represents the intensity value of a single point.

[0123] After completing the resolution equalization, the new two-dimensional intensity matrix can be converted into a single-beam real aperture acoustic image by grayscale rendering or acoustic image drawing in the display and control computer.

[0124] It should be noted that for the original two-dimensional intensity matrix, its resolution in the range direction is determined by the echo signal bandwidth B, which is relatively high. The resolution in the azimuth direction is determined by the carrier speed v and the pulse transmission interval prt of the sound wave, which is relatively low. The resolutions in these two directions usually differ by 1 to 2 orders of magnitude, so resolution equalization processing is required. Among them, the relationship between the time t for the sound wave transmission in the range direction and the range sampling point sequence n and the distance x in the range direction is:

[0125]

[0126] Where, d x1 To balance the resolution in the forward range direction. In azimuth, the time is related to the pulse transmission interval prt. The time of the kth frame is η = k·prt, and the resolution of the equalization front direction is d y1 =v·prt, after completing the resolution equalization by interpolation, the distance resolution d after equalization is obtained x1 and the resolution d of the equalized front direction y1 , d x1 =d y1 ,like Figure 3 shown.

[0127] In this embodiment, a bilinear interpolation method is used to perform resolution equalization processing. In addition, methods such as nearest neighbor interpolation and bicubic interpolation can also be used.

[0128] Step 6: Perform intra-frame beamforming on each frame of multi-channel range pulse compression data to obtain multi-frame beamforming result data, specifically including:

[0129] For single-frame multi-channel range pulse compression data, set the target point coordinates (x, y) corresponding to each pixel point of the two-dimensional image. For each target point, determine its corresponding sampling time in each channel echo according to its geometric position (that is, calculate the time when the echo of the target point arrives at each channel). Extract the intensity value at the corresponding sampling time from the pulse compression data of each channel (interpolation is possible). These intensity values ​​are superimposed to obtain the beamforming result of each target point. A phase compensation term is introduced into the beamforming result of each target point to obtain the final single-frame beamforming result data. The single-frame beamforming result data is a two-dimensional image data; the beamforming result of the target point (x, y) is expressed as:

[0130]

[0131] Where y0 is the azimuth distance of the center of the current frame (i.e., the position of the carrier when acquiring the data of this frame), is the phase compensation term, where e is the base of the natural logarithm.

[0132] In this embodiment, the maximum detection distance of the sonar is set to r max , the beam opening angle of a single element in the sonar is θ, then the illumination range of the sonar single frame beam is r in the range direction max , in the azimuth direction r max θ, which is the range of the beamforming process.

[0133] Step 7: Perform multi-beam real aperture imaging using the single-frame beamforming result data. Specifically, extract several rows in the center range from the single-frame beamforming result data as second two-dimensional image data, and convert the second two-dimensional image data into a multi-beam real aperture acoustic image.

[0134] It should be noted that after intra-frame beamforming, for the single-frame beamforming result data, its azimuth range is to The range required for multi-beam real aperture imaging is to It is much larger than prt·v, so it is necessary to extract several middle rows from the beamforming results as effective imaging data for multi-beam real aperture imaging.

[0135] The single-frame beamforming result data ranges in the azimuth direction For each frame of beamforming result data, data ranging from the center of the frame to is extracted as valid imaging data to form a second two-dimensional image data (i.e., directional bit matching is performed on the beamforming result data), which ranges in the azimuth direction and in the distance direction, wherein each coordinate pair corresponds to an intensity value, which can represent the two-dimensional reflection intensity distribution in the target scene; the valid imaging data corresponding to a single frame is represented as:

[0136]

[0137] In the formula, prt is the pulse transmission interval of the sonar sound wave, r max is the maximum detection distance of the sonar, and θ is the beam opening angle of a single array element in the sonar.

[0138] After the valid imaging data is extracted, the two-dimensional intensity matrix can be converted into a multi-beam real-aperture sonar image in the display control computer through gray-scale image rendering or sound image plotting.

[0139] In this embodiment, since the single-frame beamforming ranges in a relatively large azimuth direction, and the speed of the sonar platform is generally several knots, the distance traveled by the platform in a frame of time is much smaller than the distance in the azimuth direction of the beamforming, and thus only a part of the image in the beamforming result corresponding to the actual distance traveled needs to be extracted. The image in the center range of the beamforming has a higher azimuth resolution and concentrated energy, and thus a better imaging result can be obtained by taking a subset of the beams symmetric to the center beam.

[0140] Step 8: Synthetic aperture imaging is performed using the multi-frame beamforming result data. Specifically, the multi-frame beamforming result data is coherently superimposed in the order of time frames, the overlapping part between adjacent frames is superimposed and enhanced, a third two-dimensional image data is formed, and the third two-dimensional image data is converted into a synthetic aperture sonar image.

[0141] It should be noted that, since the carrier of the sonar is in motion, the same target point will be continuously irradiated by multiple transmission pulses and leave echo data in different frames, and thus for a certain target point, the corresponding data thereof needs to be extracted from several continuous frames, phase-aligned, and superimposed to enhance the signal, suppress the noise, and improve the azimuth resolution; in the process of step 6, the phase compensation term has been introduced in the beamforming result, the echo data of each frame is phase-compensated, and the coherence of the signal phase can be ensured when the data across frames is coherently superimposed, thereby effectively enhancing the target echo and suppressing the random noise, and improving the imaging quality and the azimuth resolution.

[0142] The beamforming result of the target point (x, y) in the single-frame beamforming result data is eebf (x,y), in order to distinguish the forming result data corresponding to different frames, a frame sequence p is introduced, and for the same target point, the corresponding beamforming result data is extracted from several continuous frames for coherent superposition to form a third two-dimensional image data, where the value corresponding to each coordinate is an intensity value; after superposition, the beamforming result of the target point is represented as:

[0143]

[0144] where p1 and p2 are the starting sequence number and the ending sequence number of the frame where the target point is located, respectively. After completing the coherent superposition of the beamforming result data of each frame, the two-dimensional intensity matrix can be converted into a synthetic aperture sonar image in the display and control computer through the way of gray scale rendering or acoustic image plotting.

[0145] In the embodiment, before the coherent superposition of the multi-frame beamforming result data in the order of time frames, geometric registration is needed to align each target point in adjacent multi-frames. The geometric registration can use existing registration methods based on track information (using the inertial navigation or GPS positioning information of the carrier to calculate the attitude and position changes during imaging, and inversely calculate the geometric position difference of the target point in the image for geometric transformation alignment), image cross-correlation registration (sliding window cross-correlation is performed on adjacent frame images to find the maximum correlation position offset Δx, Δy as the registration parameter, including two-dimensional cross-correlation algorithm and phase correlation algorithm), feature point matching registration (extracting feature points in the two-dimensional data matrix for matching, such as corner points, edges, etc., to estimate the affine transformation matrix), and the like.

[0146] As shown in Figure 2 The embodiment also provides a sonar system for implementing the above-mentioned multi-mode aperture imaging sonar method, which comprises a transmitting transducer array, a multi-channel receiving transducer array, a transmitter, a multi-channel receiver, an underwater control center, a signal processor, a display and control computer, and a power supply. The transmitting transducer array is connected with the transmitter through a cable, the multi-channel receiving transducer array is connected with the multi-channel receiver through a cable, the transmitter, the multi-channel receiver, the signal processor, and the display and control computer are respectively in communication connection with the underwater control center, and the power supply is electrically connected with each module.

[0147] The transmitting transducer array is used for transmitting a detection acoustic wave signal, which covers a predetermined underwater detection area to provide a sound source signal for subsequent echo reception and imaging.

[0148] The multi-channel receiving transducer array is used for receiving a target echo signal, which contains a plurality of spatially distributed receiving elements, each element corresponding to a channel, and can realize high-resolution spatial sampling.

[0149] The transmitter is used to generate a high-voltage signal of a predetermined waveform and drive the transmitting array to emit detection sound waves.

[0150] The multi-channel receiver is used to perform pre-processing operations such as amplification, filtering, and analog-to-digital conversion on the original echo signals collected by the multi-channel receiving transducer array, providing raw data for subsequent digital echo signal processing.

[0151] The underwater control center is used to uniformly dispatch and manage each module in the system.

[0152] The signal processor is used to run the above-mentioned multi-mode aperture imaging sonar method, perform pulse compression, intra-frame beamforming, single-beam / multi-beam / synthetic aperture imaging processing on the received multi-channel echo data, generate two-dimensional image data, and realize target imaging and information extraction.

[0153] The display and control computer is used to display two-dimensional image data.

[0154] The power supply is used to provide stable power to each module in the system.

[0155] Examples:

[0156] The common synthetic aperture sonar in practice is selected as the hardware structure of the technical solution of this application, such as Figure 5 As shown in the figure, the hardware structure includes a transducer array, a sonar electronic cabin host computer and a power supply. The transducer array is connected to the sonar electronic cabin through a cable, and the sonar electronic cabin is connected to the power supply and the host computer through cables respectively. The transducer array integrates a transmitting transducer array and a multi-channel receiving transducer array, the electronic cabin integrates a transmitter, a receiver, and an underwater control center, and the host computer integrates a signal processing function module and a display control function module.

[0157] The sonar is deployed on a pre-prepared carrier using a side-mounted or unmanned platform installation method. The carrier is used to carry the sonar for lake testing. The carrier is driven to move in a straight line. An echo is collected every time it moves a predetermined distance. The integrated echo is transmitted to the signal processing function module and imaging is performed according to the above steps 2 to 7. Finally, a single-beam real aperture acoustic image, a multi-beam real aperture acoustic image, and a synthetic aperture acoustic image are obtained, as shown in FIG. Figure 6 、 Figure 7 and Figure 8As shown in the figure, due to the instability of the carrier, jitter occurs during operation, so that the output synthetic aperture sonar image is distorted, and part of the area in the figure is blurred, while the single-beam real aperture sonar image and the multi-beam real aperture sonar image are not affected, and the texture in the figure is clear. When the technical scheme of the application is used for detection and underwater acoustic imaging, the single-beam real aperture sonar image, the multi-beam real aperture sonar image and the synthetic aperture sonar image can be generated at the same time, effectively overcoming the problem of imaging failure in the prior art when the attitude is unstable or the environment is complex, improving the robustness, adaptability and application breadth of system imaging, and meeting the target detection and image analysis requirements in multiple scenarios.

[0158] It should be noted that when the traditional side-scan sonar is used for imaging, the azimuth resolution will increase with the distance of the target, that is, the farther the target is, the worse the sonar is in distinguishing two targets in the azimuth direction, and the more blurred the image is. The synthetic aperture sonar has very high requirements for the position, speed and attitude accuracy of the carrier platform, and once the platform is unstable, the synthesis will fail or the accuracy will be greatly reduced. When the technical scheme of the application is used, single-beam real aperture sonar image, multi-beam real aperture sonar image and synthetic aperture sonar image can be output at the same time, so when the attitude is poor, the output quality of the synthetic aperture sonar image is reduced, and the single-beam real aperture sonar image and the multi-beam real aperture sonar image can be used as compensation, which can avoid the defects of the two kinds of sonar, combine the advantages of each other, improve the robustness of imaging while ensuring the continuity of imaging, and the technical scheme of the application can be directly applied to the traditional synthetic aperture sonar, and different imaging modes can be used to flexibly obtain sonar images under different sea conditions and platform stability conditions, and the application range is wider.

[0159] The steps in the application can be adjusted, combined and reduced in sequence according to actual needs.

[0160] The units in the device of the application can be combined, divided and reduced according to actual needs.

[0161] Although the application is disclosed in detail with reference to the accompanying drawings, it should be understood that the description is only exemplary and is not intended to limit the application. The scope of protection of the application is defined by the appended claims, and can include various modifications, improvements and equivalent schemes made to the application without departing from the scope and spirit of the application.

Claims

1. A multi-mode aperture imaging sonar method, characterized in that: The method includes: Step 1: construct a target echo model with the range time scale and the azimuth time scale as independent variables; Step 2: Collecting raw echo data, obtaining echo characteristic parameters from the raw echo data, and introducing the echo characteristic parameters into the target echo model to obtain a simplified multi-frame echo signal. The echo characteristic parameters include the range time scale, the azimuth time scale, and the initial distance from the target to the sonar; Step 3: De-carrier each frame of echo signal by orthogonal demodulation to obtain multiple frames of baseband signals; Step 4: pulse compress the multi-frame baseband signals respectively. Specifically, for a single-frame baseband signal, first perform a range Fourier transform, then perform an inverse range Fourier transform after passing through a matched filter to obtain multi-channel range pulse compressed data. Step 5: Perform single-beam real aperture imaging using the single-frame pulse compressed data. Specifically, the multi-channel pulse compressed data of the single frame are superimposed channel by channel to form first two-dimensional image data. The resolution of the first two-dimensional image data in the azimuth and range directions is equalized by interpolation, and the processed first two-dimensional image data is converted into a single-beam real aperture acoustic image. Step 6: Perform intra-frame beamforming on each frame of multi-channel range pulse compression data to obtain multi-frame beamforming result data; Step 7: Perform multi-beam real aperture imaging using the single-frame beamforming result data. Specifically, extract several rows in the center range from the single-frame beamforming result data as second two-dimensional image data, and convert the second two-dimensional image data into a multi-beam real aperture acoustic image. Step 8: Perform synthetic aperture imaging using the multi-frame beamforming result data. Specifically, coherently superimpose the multi-frame beamforming result data in the order of time frames, so that the overlapping parts between adjacent frames are superimposed and enhanced to form third two-dimensional image data, and convert the third two-dimensional image data into a synthetic aperture acoustic image.

2. The multi-mode aperture imaging sonar method according to claim 1, wherein: The step 1 specifically includes the following steps: Step 11: Establish the initial target echo model: Where t is the time scale in range, η is the time scale in azimuth, x is the spatial scale in range, y is the spatial scale in azimuth, ff(x,y) is the target scattering characteristic, a(t,x,y-vη) is the joint directivity function of sonar transmission and reception, v represents the uniform velocity of the carrier in azimuth, and p is m (·) is the sonar transmission signal, c is the speed of sound, R is the distance from the target to the sonar, * t represents the convolution operation on the distance to time scale t; Step 12, taking a point target with a constant reflection coefficient and a known initial position as the detection target, simplifies the initial target echo model, specifically including: Since the one-way directivity function is approximately a sinc(·) function, the expression of a(t,x,y-vη) is written as: Where λ is the wavelength of the sound wave corresponding to the sonar emission signal at the center frequency, D T and D R are respectively the transmitting array aperture and the receiving array aperture of the sonar system. When D T With D R When they are equal, they are uniformly written as the array aperture D, and we get: Taking a point target with a constant reflection coefficient A0 and an initial position (R0, 0) relative to the sonar system as the detection target, the joint directivity function is simplified to obtain: The simplified joint directivity function is introduced into the target echo model, and the sonar emission signal p m (·) is expressed as a linear frequency modulation signal, and the simplified target echo model is obtained, which is expressed as: Where rect(·) is the rectangular window function, T is the pulse width, f0 is the center frequency of the sonar emission signal, K is the modulation frequency of the sonar emission signal, 3. The multi-mode aperture imaging sonar method according to claim 2, wherein: The step 3 specifically includes: For a single-frame high-frequency echo signal, multiply and mix it with two local oscillator signals cos(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the in-phase component. Then, multiply and mix the single-frame high-frequency echo signal with two local oscillator signals sin(2πf0t) of the same frequency and a phase difference of 90°, and then remove the high-frequency component in the mixed signal by low-pass filtering to obtain the orthogonal component. The in-phase component is used as the real part and the orthogonal component is used as the imaginary part for superposition and combination to obtain the baseband signal ee after carrier removal. b (t,η): Where, frequency Since vη<<R0, the distance R(η) from the target to the sonar is simplified to: Substitute the simplified R(η) term into the baseband signal ee after removing the carrier b (t,η).

4. The multi-mode aperture imaging sonar method according to claim 3, wherein: In step 4, the data after pulse compression is expressed as: In the formula, Ee b (f,η) is the baseband signal after the range Fourier transform, f is the frequency of the baseband signal, H(f) is the matched filter, expressed as H(f) = S * (f), S * (f) is the frequency domain conjugate of the sonar transmission signal S(t).

5. The multi-mode aperture imaging sonar method according to claim 4, wherein: The step 5 specifically includes the following steps: Step 51: For a single frame of multi-channel pulse compression data, the pulse compression data of all channels are superimposed in the range direction to form first two-dimensional image data. The first two-dimensional image data is represented as: Wherein, M is the number of channels, m is the index of the channel, the first two-dimensional image data has azimuth distances as rows and distance sampling points as columns, where the value corresponding to each coordinate is an intensity value; In step 52, based on the preset azimuth resolution and range resolution, a set of points with uniform spacing in the row and column directions is reset, and the intensity value corresponding to each new point in the original first two-dimensional image data is calculated using the bilinear interpolation method to generate new first two-dimensional image data, thereby completing the image resolution equalization processing.

6. The multi-mode aperture imaging sonar method according to claim 5, wherein: The step 52 specifically includes: Traverse each new point. For the current new point (x, y), find the coordinates of the points closest to it in the upper left, upper right, lower left, and lower right of the original first two-dimensional image data, which are (x1, y1), (x2, y2), (x3, y3), and (x4, y4) respectively. Use the intensity values ​​of these four points to calculate the intensity value of the current new point (x, y), expressed as: Where f(·) represents the intensity value of a single point.

7. The multi-mode aperture imaging sonar method according to claim 4, wherein: The step 6 specifically includes: For single-frame multi-channel range pulse compression data, set the target point coordinates (x, y) corresponding to each pixel of the two-dimensional image. For each target point, determine its corresponding sampling time in each channel echo based on its geometric position. Extract the intensity value at the corresponding sampling time from the pulse compression data of each channel. Superimpose these intensity values ​​to obtain the beamforming result of each target point. Introduce a phase compensation term into the beamforming result of each target point to obtain the final single-frame beamforming result data. The beamforming result of the target point (x, y) is expressed as: Where y0 is the azimuth distance of the center of this frame, is the phase compensation term.

8. The multi-mode aperture imaging sonar method according to claim 7, wherein: The step 7 specifically includes: The range of single-frame beamforming result data in azimuth direction is For each frame of beamforming result data, extract the range of The data is used as the second two-dimensional image data, expressed as: Where prt is the pulse emission interval of sonar sound waves, r max is the maximum detection range of the sonar, and θ is the beam angle of a single array element in the sonar.

9. The multi-mode aperture imaging sonar method according to claim 7, wherein: The step 8 specifically includes: The beamforming result of the target point (x, y) in the single frame beamforming result data is ee bf (x, y), in order to distinguish the beamforming result data corresponding to different frames, a frame sequence p is introduced. For the same target point, the corresponding beamforming result data are extracted from several consecutive frames and coherently superimposed to form the third two-dimensional image data. After superposition, the beamforming result of the target point is expressed as: Where p1 and p2 are the starting and ending serial numbers of the frame where the target point is located, respectively.

10. A multi-mode aperture imaging sonar system, characterized in that: The system is used to execute the multi-mode aperture imaging sonar method of any one of claims 1 to 9, wherein the multi-mode aperture imaging sonar system includes a transmitting transducer array, a multi-channel receiving transducer array, a transmitter, a multi-channel receiver, an underwater control center, a signal processor, a display and control computer, and a power supply. The transmitting transducer array is connected to the transmitter via a cable, the multi-channel receiving transducer array is connected to the multi-channel receiver via a cable, the transmitter, the multi-channel receiver, the signal processor, and the display and control computer are respectively communicatively connected to the underwater control center, and the power supply is electrically connected to other modules. The transmitting transducer array is used for transmitting detection acoustic wave signals; The multi-channel receiving transducer array is used to receive target echo signals; The transmitter is used to generate a high-voltage signal of a predetermined waveform and drive the transmitting array to emit a detection sound wave; The multi-channel receiver is used to perform pre-processing operations such as amplification, filtering, and analog-to-digital conversion on the original echo signals collected by the multi-channel receiving transducer array; The underwater control center is used to coordinate and manage all modules in the sonar system; The signal processor is used to perform pulse compression, intra-frame beamforming, and single-beam, multi-beam, and synthetic aperture imaging processing on the received multi-channel echo data to generate two-dimensional image data; The display and control computer is used to display two-dimensional image data.

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