Method and system for detecting coherent phase difference of near-seabed target based on multi-beam system

Abstract

The invention provides a near-seabed target coherent phase difference detection method and system based on a multi-beam system, and the method comprises the steps: S1, collecting target echoes, and solving a split beam initial phase difference sequence; s2, noise interference of the split beam initial phase difference sequence is filtered out, and a noise reduction result is obtained; and S3, obtaining seabed depth information according to the noise reduction result, and detecting a seabed task target according to the seabed depth information. Compared with a traditional target detection algorithm based on amplitude threshold detection, the coherent phase difference detection algorithm based on split beams can utilize two sub-arrays to receive beam phase information difference to extract a mutation section, and a near-seabed weak target covered by a seabed side lobe background can be better detected.

Description

Technical Field

[0001] The present invention belongs to the technical field of seabed detection, and in particular, relates to a coherent phase difference detection method and system for near-seabed targets based on a multi-beam system. Background Art

[0002] In addition to the function of seabed detection, the new generation of multi-beam systems also have the function of recording water body data. In recent years, researchers have begun to explore the important practical value of water body data. Through the analysis of water body data, the scattering characteristics of suspended sediment layers and zooplankton can be studied, natural gas leaks, internal ocean waves and other phenomena can be detected, and fine targets such as sunken ships and suspended sediment can be detected. When the multi-beam system detects targets in water body images, in addition to the information representing the target scatterer, there are also a lot of noise and seabed receiving sidelobe interference in the image, which will greatly affect the target clarity, reduce the signal-to-noise ratio, and hinder the progress of target identification and related investigation and research inside the water body. Sidelobe interference is also continuously stacked in the water body image to form a "false target". Only after analyzing and processing the noise and sidelobe interference can a clear water body image be obtained, and the subsequent development and research of water body images can be better carried out.

[0003] In recent years, researchers have continuously studied and improved the target detection methods under the interference of the seabed sidelobe background in response to the above-mentioned problems. At present, one of the commonly used methods is filtering or regional segmentation based on water image processing. The essence of this type of algorithm is to process the pixels of the image processing, which does not fundamentally solve the problem that the weak water target is annihilated by the large seabed background, so the effect is relatively limited; the other is to implement nearby constraint control or filtering on the sidelobe interference based on adaptive beamforming or other improved beamformers, but this method has high requirements for computing resources and mostly has delay and efficiency problems in real-time applications; Gao Jiawei of Harbin Engineering University proposed a method based on the joint processing of instantaneous frequency variance and echo amplitude in recent years, and the target echo detection capability has been significantly improved. Therefore, based on the above research results, it is necessary to further use phase information on the basis of echo amplitude in the target detection process to study target detection algorithms with stronger real-time performance and better performance.

[0004] The split beam phase difference detection algorithm was originally based on the phase method direction finding principle of the sonar system. The receiving array is divided into two sub-arrays of equal length, and beam forming processing is performed separately. The phase difference of the echo signal is used to detect the zero point from the phase difference sequence curve to obtain the delay value of each beam signal, thereby achieving the purpose of depth measurement. The abnormal mutation characteristics that may exist in the above initial phase difference sequence and the seabed depth information obtained by zero point detection make it possible to detect near-seabed targets using phase characteristics.

[0005] Patent document CN101718868A discloses a multi-beam bathymetry method based on multiple split-beam phase differences. This solution provides a high-resolution multi-beam seabed detection technology. By adopting a variety of split-beam division methods, multiple measurements of the phase difference curve in the wave arrival direction are formed. At the same time, the least squares processing is introduced to estimate the parameter error, which solves the problem of the difficulty in designing the automatic tracking gate of the traditional phase difference detection method. This solution enables it to still have high detection accuracy when performing seabed detection on edge beams with low echo signal-to-noise ratio. However, this solution cannot solve the problem of abnormal mutation characteristics that may exist in the initial phase difference sequence, and cannot solve the problem that the weak backscattering ability of near-bottom targets causes the echo amplitude to differ greatly from the seabed echo and cannot be effectively detected.

[0006] This problem needs to be solved urgently. Summary of the invention

[0007] In view of the defects in the prior art, the object of the present invention is to provide a method and system for coherent phase difference detection of near-seabed targets based on a multi-beam system.

[0008] According to the present invention, a near-seabed target coherent phase difference detection method based on a multi-beam system includes:

[0009] Step S1: Collect target echoes and solve the initial phase difference sequence of split beams;

[0010] Step S2: filtering out the noise interference of the split beam initial phase difference sequence to obtain a noise reduction result;

[0011] Step S3: Obtaining seabed depth information based on the noise reduction result, and detecting seabed mission targets based on the seabed depth information.

[0012] Preferably, in the step S1, the split beam initial phase difference is expressed as follows:

[0013] Step S1.1: collecting target echoes; the target echoes include a first subarray signal and a second subarray signal;

[0014] Step S1.2: multiply the conjugate of the second sub-array signal by the first sub-array signal to obtain a correlation sequence;

[0015] Step S1.3: performing windowed sliding average on the correlation sequence to obtain a complex conjugate sequence after sliding average;

[0016] Step S1.4: Calculate the phase of the complex conjugate sequence after the sliding average to obtain the initial phase difference sequence of the split beam after the sliding average processing;

[0017] In step S1.4, the mathematical expression of the split beam initial phase difference sequence is:

[0018]

[0019] Among them, arctan represents the inverse tangent operation; Im represents the imaginary part operation; Re represents the real part operation; represents the conjugate signal of the signal received by subarray 2; s1(n) represents the complex form of the signal at the receiving end of the first subarray; Based on s2(n), we get:

[0020] The mathematical expression of s1(n) is:

[0021]

[0022] Wherein, s1(n) represents the signal received by subarray 1; E1(n) represents the signal received by subarray 1, i.e., the amplitude sequence of the first subarray signal; represents the phase sequence of the signal received by subarray 1, where j represents an imaginary unit, and φ1(n) represents the phase value of the signal received by subarray 1;

[0023] The mathematical expression of s2(n) is:

[0024]

[0025] Wherein, s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, i.e., the amplitude sequence of the second subarray signal; represents the phase sequence of the signal received by subarray 2, where φ2(n) represents the phase value of the signal received by subarray 2;

[0026] In step S1.2, the mathematical expression of the correlation sequence is:

[0027]

[0028] Wherein, P(n) represents the correlation sequence of the received signals of the two sub-arrays;

[0029] In step S1.3, the mathematical expression for the complex conjugate sequence is:

[0030]

[0031] in, represents the complex conjugate sequence after sliding averaging; L is the sliding window length, W(l) is the sliding window weight coefficient sequence; P(n+l) represents the value of the (n+l)th point in the complex conjugate sequence; W(l) is the sliding window weight coefficient sequence, and L is the sliding window length.

[0032] Preferably, in the step S2, the method of filtering out the noise interference of the split beam initial phase difference sequence includes setting an amplitude threshold and setting a correlation coefficient threshold;

[0033] The setting of the amplitude threshold is to determine whether the maximum amplitude of the split beam initial phase difference sequence meets the set amplitude threshold. If the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated;

[0034] Setting the correlation coefficient threshold, i.e. judging whether the absolute value of the correlation coefficient is greater than or equal to 0.8; if the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated;

[0035] The absolute value of the correlation coefficient is expressed mathematically as follows:

[0036]

[0037] Here, SNR stands for signal-to-noise ratio.

[0038] Preferably, the step S3 includes:

[0039] Step S3.1: based on the split beam initial phase difference sequence, obtain the starting position of the phase difference oblique line interception; based on the noise reduction result, obtain the seabed line curve as the seabed depth information; the seabed line curve includes: a first seabed line phase difference curve and a second seabed line phase difference curve;

[0040] Step S3.2: intercepting the first seabed line phase difference curve and the second seabed line phase difference curve through the starting position of the phase difference oblique line interception to obtain two intercepted segment curves;

[0041] Step S3.3: Smoothing and fitting the two intercepted segment curves, detecting and judging whether the difference between the two intercepted segment curves is greater than a preset threshold; if the result is yes, it is prompted that the target is detected and step S3.4 is executed; if the result is no, no processing is performed;

[0042] Step S3.4: According to the intercepted segment curve detected in step S3.3, i.e., the mutation segment, the TOA value and the DOA value of the phase sequence of the intercepted segment curve are obtained; and the coordinate position of the seabed mission target is obtained according to the TOA value and the DOA value;

[0043] The DOA value is the angle corresponding to the main beam pointing of the current receiving beam.

[0044] According to the present invention, a near-seabed target coherent phase difference detection system based on a multi-beam system comprises:

[0045] Module M1: collect target echoes and solve the initial phase difference sequence of split beams;

[0046] Module M2: filtering out the noise interference of the initial phase difference sequence of the split beam to obtain a noise reduction result;

[0047] Module M3: Obtaining seabed depth information according to the noise reduction result, and detecting seabed mission targets according to the seabed depth information.

[0048] Preferably, in the module M1, the split beam initial phase difference is expressed as follows:

[0049] Module M1.1: collecting target echo; the target echo includes a first subarray signal and a second subarray signal;

[0050] Module M1.2: multiply the conjugate of the second sub-array signal by the first sub-array signal to obtain a correlation sequence;

[0051] Module M1.3: performing windowed sliding average on the correlation sequence to obtain a complex conjugate sequence after sliding average;

[0052] Module M1.4: Calculate the phase of the complex conjugate sequence after the sliding average to obtain the initial phase difference sequence of the split beam after the sliding average processing;

[0053] In the module M1.4, the mathematical expression of the split beam initial phase difference sequence is:

[0054]

[0055] Among them, arctan represents the inverse tangent operation; Im represents the imaginary part operation; Re represents the real part operation; represents the conjugate signal of the signal received by subarray 2; s1(n) represents the complex form of the signal at the receiving end of the first subarray; Based on s2(n), we get:

[0056] The mathematical expression of s1(n) is:

[0057]

[0058] Wherein, s1(n) represents the signal received by subarray 1; E1(n) represents the signal received by subarray 1, i.e., the amplitude sequence of the first subarray signal; represents the phase sequence of the signal received by subarray 1, where j represents an imaginary unit, and φ1(n) represents the phase value of the signal received by subarray 1;

[0059] The mathematical expression of s2(n) is:

[0060]

[0061] Wherein, s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, i.e., the amplitude sequence of the second subarray signal; represents the phase sequence of the signal received by subarray 2, where φ2(n) represents the phase value of the signal received by subarray 2;

[0062] In the module M1.2, the mathematical expression of the correlation sequence is:

[0063]

[0064] Wherein, P(n) represents the correlation sequence of the received signals of the two sub-arrays;

[0065] In the module M1.3, the mathematical expression for the complex conjugate sequence is:

[0066]

[0067] in, represents the complex conjugate sequence after sliding averaging; L is the sliding window length, W(l) is the sliding window weight coefficient sequence; P(n+l) represents the value of the (n+l)th point in the complex conjugate sequence; W(l) is the sliding window weight coefficient sequence, and L is the sliding window length.

[0068] Preferably, in the module M2, the method of filtering out the noise interference of the split beam initial phase difference sequence includes setting an amplitude threshold and setting a correlation coefficient threshold;

[0069] The setting of the amplitude threshold is to determine whether the maximum amplitude of the split beam initial phase difference sequence meets the set amplitude threshold. If the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated;

[0070] Setting the correlation coefficient threshold, i.e. judging whether the absolute value of the correlation coefficient is greater than or equal to 0.8; if the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated;

[0071] The absolute value of the correlation coefficient is expressed mathematically as follows:

[0072]

[0073] Here, SNR stands for signal-to-noise ratio.

[0074] Preferably, the module M3 includes:

[0075] Module M3.1: based on the split beam initial phase difference sequence, obtain the starting position of the phase difference oblique line interception; based on the noise reduction result, obtain the seabed line curve as the seabed depth information; the seabed line curve includes: a first seabed line phase difference curve and a second seabed line phase difference curve;

[0076] Module M3.2: intercepting the first seabed line phase difference curve and the second seabed line phase difference curve through the starting position of the phase difference oblique line interception to obtain two intercepted segment curves;

[0077] Module M3.3: Smoothing and fitting the two intercepted segment curves, detecting and judging whether the difference between the two intercepted segment curves is greater than a preset threshold; if the result is yes, it prompts that the target is detected and executes step S3.4; if the result is no, no processing;

[0078] Module M3.4: according to the intercepted segment curve detected by module M3.3, the TOA value and the DOA value of the phase sequence of the intercepted segment curve, i.e., the mutation segment, are obtained; and the coordinate position of the seabed mission target is obtained according to the TOA value and the DOA value;

[0079] The DOA value is the angle corresponding to the main beam pointing of the current receiving beam.

[0080] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the near-seabed target coherent phase difference detection method based on a multi-beam system are implemented.

[0081] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the near-seabed target coherent phase difference detection method based on a multi-beam system are implemented.

[0082] Compared with the prior art, the present invention has the following beneficial effects:

[0083] 1. Compared with the traditional target detection algorithm based on amplitude threshold detection, the coherent phase difference detection algorithm based on split beam can extract the mutation segment by using the difference in phase information of the two sub-array receiving beams, so as to better detect the weak near-seabed targets covered by the seabed sidelobe background.

[0084] 2. The present invention further improves the accuracy of the suspected target position through a series of screening, fitting and averaging methods, thereby effectively improving the detection and positioning capabilities of the multi-beam system for near-seabed targets, and is better suited to actual application scenarios.

[0085] 3. In order to solve the problem that under the background interference of the seabed receiving side lobes, the backscattering ability of near-bottom targets is weak, resulting in a huge difference in echo amplitude from the seabed echo, which makes it impossible to be effectively detected. Based on utilizing the receiving array to split the beam to process the phase information difference, a new method for coherent phase difference detection of near-bottom targets in a multi-beam system is provided to improve the detection performance of the multi-beam system for water targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0087] Figure 1 The algorithm processing flow chart provided by the present invention;

[0088] Figure 2 A full-sector multi-beam water body image obtained by conventional processing in the simulation verification provided by the present invention;

[0089] Figure 3 It is a local enlarged water body map of the target sector obtained by conventional processing in the simulation verification provided by the present invention; wherein, Figure 3 (a) is the detection result of target one, Figure 3 (b) is the detection result of target 2;

[0090] Figure 4 The seabed detection results based on multi-source information screening provided by the present invention, wherein: Figure 4 (a) is the initial phase difference sequence, Figure 4 (b) is the amplitude screening result, Figure 4 (c) is the correlation coefficient screening result, Figure 4 (d) is the phase difference sequence after comprehensive screening and the result of curve fitting;

[0091] Figure 5 The phase difference sequence diagram of the near-bottom target at different receiving beam angles in the sector in which the near-bottom target is located during the screening and positioning process of the near-bottom target provided by the present invention; wherein, Figure 5 (a) The receiving beam angle is -34.47°; Figure 5 (b) The receiving beam angle is -36.30°; Figure 5 (c) The receiving beam angle is -36.84°; Figure 5 (d) The receiving beam angle is -37.39°; Figure 5 (e) The receiving beam angle is -40.41°; Figure 5 (f) The receiving beam angle is -41.50°;

[0092] Figure 6 The phase difference mutation detection result diagram provided by the present invention when the receiving beam is pointed at -36.84°; wherein, Figure 6 (a) is an oblique line in front of the seabed line; Figure 6 (b) is the oblique line of the seabed line;

[0093] Figure 7 The seabed and target detection result diagram provided by the present invention when the receiving beam is pointed at -36.84°;

[0094] Figure 8 The phase difference sequence diagram under different receiving beam angles in the sector where the near-bottom target 2 is located during the screening and positioning process of the near-bottom target provided by the present invention; wherein, Figure 8 (a) The receiving beam angle is 66.14°; Figure 8 (b) The receiving beam angle is 65.06°; Figure 8 (c) The receiving beam angle is 64.79; Figure 8 (d) The receiving beam angle is 62.05°; Figure 8 (e) The receiving beam angle is 60.68°; Figure 8 (f) The receiving beam angle is 57.94°;

[0095] Fig. 9 This is a phase difference mutation detection result diagram provided by the present invention when the receiving beam is pointed at 60.68°, wherein: Fig. 9 (a) is an oblique line in front of the seabed line; Fig. 9 (b) is the oblique line of the seabed line;

[0096] Fig.10 The seabed and target detection result diagram provided by the present invention when the receiving beam is pointed at 60.68°;

[0097] Fig.11 This is a diagram of seabed and target detection results provided by the present invention. DETAILED DESCRIPTION

[0098] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0099] The present invention relates to a method for coherent phase difference detection and positioning of near-bottom seabed targets based on a multi-beam system. Aiming at the problem that when the difference between the target backscattering intensity and the seabed receiving sidelobe energy is small, the method based on amplitude threshold detection is difficult to work. In particular, a split-beam coherent phase difference detection algorithm is used to detect the sudden change of the phase characteristic information of the target echo, so as to realize the extraction of near-bottom weak targets under the seabed background, thereby improving the detection capability of the multi-beam system for water targets.

[0100] In view of the shortcomings of the existing algorithms, a method for coherent phase difference detection and depth measurement of near-bottom targets based on a multi-beam system is invented. The method mainly includes three parts: split beam initial phase difference sequence solution, sea depth estimation and near-bottom target screening and positioning. The specific implementation includes:

[0101] (1) Solution of the initial phase difference sequence of split beam

[0102] It is known that in the result of the two beam outputs of the split subarray, the beam outputs between the subarrays with the same number only differ by a phase difference, and the mathematical expression is:

[0103]

[0104] in, is the phase difference between the same-signed beam outputs of the two sub-arrays;

[0105] Where D is the distance between the equivalent acoustic centers of the two subarrays, λ is the wave number, θ is the signal direction, and θ r is the receiving beam steering angle. Specifically, formula (1) is used to illustrate that when the signal azimuth and the beam steering angle are the same, the phase difference value is 0, resulting in a zero-crossing phenomenon of the phase sequence curve.

[0106] When the signal azimuth θ and the receiving beam steering angle θ r When the two subarray signals are the same, the phase difference between them is zero. The moment when the phase difference sequence crosses the zero line is called the zero crossing point, which is the arrival time of the signal corresponding to the rth beam pointing. The arrival time of the beam pointing can be calculated by using the zero crossing time of the phase difference between the two subarray received signals.

[0107] The signal at the receiving end of the subarray is written in complex form:

[0108]

[0109] Wherein, s1(n) represents the signal received by subarray 1; E1(n) represents the signal received by subarray 1, i.e., the amplitude sequence of the first subarray signal; represents the phase sequence of the signal received by subarray 1, where j represents the imaginary unit, φ1(n) represents the phase value of the signal received by subarray 1, ranging from 0 to 2pi;

[0110]

[0111] Wherein, s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, i.e., the amplitude sequence of the second subarray signal; represents the phase sequence of the signal received by subarray 2, where φ2(n) represents the phase value of the signal received by subarray 2, ranging from 0 to 2pi;

[0112] Since the signals of the two sub-arrays come from the same target, the phase difference between the signals can be obtained through the correlation method. Therefore, the correlation sequence of the two sequences is obtained by multiplying the conjugate of the signal of sub-array 2 by the signal of sub-array 1 as follows:

[0113]

[0114] Wherein, P(n) represents the correlation sequence of the received signals of the two sub-arrays; s1 represents the received signal of sub-array 1; Represents the conjugate signal of the received signal of subarray 2

[0115] In the above formula, the phase is the required phase difference Δφ(n), which can be expressed as:

[0116]

[0117] Among them, arctan represents the inverse tangent operation; Im represents the imaginary part operation; Re represents the real part operation;

[0118] represents the conjugate signal of the received signal of subarray 2;

[0119] Furthermore, in order to better estimate the phase difference at all times To reduce the impact of interference, P(n) can be windowed and moved averaged. The mathematical expression of the moving average is:

[0120]

[0121] in, represents the complex conjugate sequence after sliding average; L is the sliding window length, W(l) is the sliding window weight coefficient sequence; P(n+l) represents the value of the (n+l)th point in the complex conjugate sequence.

[0122] In the formula, W(l) is the sliding window weight coefficient sequence, that is, the response of a certain filter, and L is the sliding window length. When W(l) = 1, it is a general average processing, which is equivalent to low-pass filtering the complex conjugate sequence P(n), which can eliminate the components with drastic changes in the sequence and smooth the phase difference data. Using the above formula to process each sample point in P(n) within the search interval, a new complex conjugate sequence corresponding to the receiving beam can be obtained. Then By calculating the phase, we can get the result of the sliding average of the initial phase difference sequence of the two sub-arrays.

[0123] (2) Ocean depth estimation

[0124] Since the estimated initial phase difference sequence may be affected by the combined influence of various signal decorrelation phenomena such as angle decorrelation, spatial decorrelation, multipath phenomenon, and ocean environmental noise, random jumps may occur in the phase difference sequence, resulting in large errors in the estimated seabed echo DOA value, which ultimately affects the accurate estimation of the sea depth.

[0125] Therefore, in order to reduce noise interference and improve the accuracy of phase difference estimation, the amplitude threshold and correlation coefficient threshold are used to filter out noise interference based on the amplitude and correlation characteristics of the coherent signal, thereby improving the accuracy of seabed detection phase difference and DOA estimation.

[0126] a) Amplitude threshold screening

[0127] When the signal amplitude is too small, it is more susceptible to noise interference, which may cause large errors in the DOA estimation value. Therefore, in order to reduce the possibility of estimation errors, the amplitude threshold is first set to eliminate the measurement data points with too small coherent signal amplitude values. The amplitude threshold can be set to 5 to 30 dB below the maximum amplitude based on experience, and can be reasonably set based on the approximate sea depth and the predicted echo signal-to-noise ratio.

[0128] b) Coherence coefficient screening

[0129] In coherent measurement, the correlation coefficient is one of the important quantitative criteria for data quality evaluation and is defined as

[0130]

[0131] Among them, E{x} represents the expected value of x, and the absolute value of the correlation coefficient, namely |γ|, is also a function of the signal-to-noise ratio SNR, such as

[0132]

[0133] If SNR→0, then |γ|→0, which means that the signals of the two beams are completely uncorrelated, and |γ|→1, which means that they are completely correlated. Therefore, the phase difference sequence data containing large uncorrelated noise can be eliminated by setting a threshold value for the correlation coefficient. The correlation coefficient threshold can be adjusted based on experience or data quality, and is usually set to no less than 0.8.

[0134] The symbol → indicates approaching a certain value;

[0135] c) Curve fitting

[0136] When the phase difference method is applied, a zero-crossing phase difference sequence that changes with time can be obtained. This sequence has a monotonic curve distribution characteristic within the main beam range. By determining the zero-crossing point of the phase difference sequence, the TOA estimation of the corresponding beam can be obtained. However, due to the interference fluctuations of the reverberation echo signal and the changes in the seabed topography, the phase difference sequence curve will have random fluctuations, which makes it difficult to determine the zero-crossing point. Therefore, in order to better determine the zero-crossing point, the phase difference sequence is fitted with a binomial curve.

[0137] (3) Screening and positioning of near-seabed targets

[0138] The next step of near-bottom target detection can be carried out using the initial phase difference sequence obtained above and the seabed depth information obtained.

[0139] First, set the starting position of the phase difference oblique line interception, intercept the phase difference curve where the seabed line is located and the phase difference curve before the seabed line, respectively, and perform mutation detection of suspected targets on these two curves, then smooth and fit the two intercepted curves respectively, and calculate the phase difference before and after fitting to obtain the fitted curve, and select the curve segment with a difference greater than the set threshold as the initial target mutation segment, and then use the correlation coefficient for further screening. If there is still a phase difference sequence and data after screening, it is considered that a suspected near-seabed target has been detected. Next, estimate the position of the suspected target, and use the TOA value corresponding to the phase difference sequence to calculate the average as the echo arrival time of the suspected target. Then, the corresponding DOA value is matched according to the position of the curve where the mutation segment is located. If the mutation segment is on the phase difference curve where the seabed line is located, the DOA value is the angle corresponding to the main beam of the current receiving beam. If the mutation segment is on the previous phase difference curve of the seabed line phase difference line, the DOA value is the angle corresponding to the first side lobe of the current receiving beam. If there is no mutation segment on the phase difference curve where the seabed line is located and on the previous phase difference curve of the seabed line phase difference line, the seabed target is not detected. If the current receiving beam angle is positive, the left first side lobe is taken, and if the current receiving beam angle is negative, the right first side lobe is taken. Finally, the coordinate position of the near-bottom target is obtained according to the TOA and DOA values.

[0140] Specifically, the starting position of the phase difference oblique line interception is obtained based on the split beam initial phase difference sequence; the seabed line curve can be obtained through step S2.

[0141] The next step of near-bottom target detection can be carried out using the initial phase difference sequence obtained above and the seabed depth information obtained.

[0142] Step S3.1: Set the starting position of the phase difference oblique line interception, intercept the phase difference curve where the seabed line is located and the phase difference curve before the seabed line, and perform mutation segment detection of the suspected target on these two curves respectively;

[0143] Step S3.2: Screening the initial phase difference sequence based on multi-source information to obtain the estimated value of the sea depth under the current receiving beam;

[0144] Step S3.3: Perform screening and positioning processing of near-bottom targets.

[0145] First, the simulation application scenario of the specific implementation plan is given. The simulation setting is a flat seabed with a depth of 800m. The multi-beam receiving array is a uniform linear array with a total of 64 elements, 48 ​​split sub-arrays, and an element spacing of 30kHz half wavelength. The real position coordinates of the near-seabed target 1 are (-560, -750), the real angle of the target is -36.74°, and it is located in sector 7; the real position coordinates of the near-seabed target 2 are (1280, -720), the real angle of the target is 60.64°, and it is located in sector 1.

[0146] Here we first give the original multi-beam water image of the whole fan obtained by conventional processing. Figure 2 As shown in the figure, the green circles are the locations of two near-seabed targets. Figure 3 The local enlarged water map of the fan where the two targets are located is given. It can be seen from the figure that the echo intensity of the two targets is weak, almost completely covered by the seabed sidelobe interference, and cannot be distinguished by the naked eye. In this case, it is impossible to effectively extract the two near-seabed targets by conventional amplitude detection methods.

[0147] Next, the method proposed by the present invention is used according to the process Figure 1 The steps given are processed first, and the initial phase difference sequence of the split beam under each receiving beam angle is solved for the simulation data. Taking the result under the receiving beam pointing at 41.5° as an example, the initial phase difference sequence curve obtained is as follows Figure 4 As shown in (a), we can see that there are multiple zero-crossing slopes in the figure.

[0148] The next step is to estimate the sea depth under the current receiving beam. First, the initial phase difference sequence is screened based on multi-source information. The amplitude threshold is set to -25dB and the correlation coefficient threshold is set to 0.9. The amplitude information solution and threshold setting are shown in Figure 4 (b), the solution of correlation coefficient and threshold setting are shown in Figure 4 (c), after multi-source information screening, the phase difference sequence is Figure 4 The blue curve in (d) Figure 4 The red dashed line in (d) is the result of curve fitting for the screened phase difference sequence.

[0149] Afterwards, the fitting curve was tested for zero-crossing points, and the estimated sea depth was 801.2 m.

[0150] Next, the near-bottom target screening and positioning processing is performed: First, the initial phase difference sequence diagram of the near-bottom target at different receiving beam angles in the sector is given, such as Figure 5 As shown in the figure. The green framed part is the phase difference curve segment where the seabed line is located after multi-source information screening in the previous step of sea depth estimation. The true position of the near-seabed target is -36.74°. Figure 5 It can be seen that when the receiving beam is gradually aligned and then gradually deviates from the target's true direction, a sudden change gradually appears on the phase difference curve before the seabed line in the initial phase difference sequence diagram and then gradually disappears. When the receiving beam is aligned with the target's true direction, the initial phase difference sequence is obtained as follows Figure 5 As shown in (c), we can see that there is an obvious mutation segment on the phase difference curve before the seabed line. Figure 6 As shown in the figure, the near-bottom targets are screened. The phase difference curve where the seabed line is located and the phase difference curve before the seabed line are smoothed, curve fitted, and the difference before and after fitting is calculated. First, the initial mutation segment with a difference greater than the set threshold is screened out, and then the correlation coefficient is used for further screening to obtain the suspected target segment. Figure 6 The red curve shown in is the suspected target segment. Take the result of the receiving beam pointing down at -36.84° as an example. Figure 6 As shown in the figure, only the suspected target segment is detected on the phase difference curve before the seabed line. Then, the TOA values ​​corresponding to the suspected target segment are averaged, and the angle -32.1° corresponding to the right first sidelobe is matched, so the suspected target position can be calculated as (-557.1, -750.8). The detected target point position is plotted together with the seabed line detection result under the receiving beam into the sea depth map, as shown in the figure below. Figure 7 As shown, it can be seen that the error between the suspected target position and the real position of target one (-560, -750) is very small, and the seabed detection result is also accurate.

[0151] Specifically, the above processing is also performed on the near-bottom target 2 with a true azimuth of 60.64°.

[0152] First, the initial phase difference sequence diagram under different receiving beam angles in the sector where the near-bottom target 2 is located is given, as follows: Figure 8 The phase difference mutation segment first appears on the phase difference curve before the seabed line, and then gradually moves to the phase difference curve where the seabed line is located.

[0153] Next, if Fig. 9 As shown in the figure, the near-bottom target is screened. Taking the result of the 60.68° receiving beam pointing downward as an example, Fig. 9It can be seen that only the suspected target segment is detected on the phase difference curve where the seabed line is located. Then, the TOA values ​​corresponding to the suspected target segment are averaged, and the angle 60.68° corresponding to the main beam pointing of the current receiving beam is matched to calculate the suspected target position as (1279.9, -718.7). The detected target point position is plotted together with the seabed line detection result under the receiving beam into the sea depth map, as shown in Fig.10 As shown, it can be seen that the error between the suspected target position and the true position of target 2 (1280, -720) is very small, and the seabed detection result is also accurate.

[0154] After traversing all receiving beam angles (-70°, 70°), the final complete seabed and target detection results are as follows: Fig.11 As shown. Fig.11 As shown, the bottom seabed line is clear, and the bathymetric error is very small compared with the actual sea depth of 800m. In addition, the phase coherent detection algorithm can detect near-seabed targets on both sides, and the target position drawn in the end is relatively accurate.

[0155] The present invention also provides a near-seabed target coherent phase difference detection system based on a multi-beam system. The near-seabed target coherent phase difference detection system based on a multi-beam system can be realized by executing the process steps of the near-seabed target coherent phase difference detection method based on a multi-beam system, that is, those skilled in the art can understand the near-seabed target coherent phase difference detection method based on a multi-beam system as a preferred implementation of the near-seabed target coherent phase difference detection system based on a multi-beam system.

[0156] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0157] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for detecting coherent phase difference of near-seabed targets based on a multi-beam system, characterized in that: include: Step S1: Collect target echoes and solve the initial phase difference sequence of split beams; Step S2: filtering out the noise interference of the split beam initial phase difference sequence to obtain a noise reduction result; Step S3: Obtaining seabed depth information based on the noise reduction result, and detecting seabed mission targets based on the seabed depth information.

2. The method for detecting coherent phase difference of near-seabed targets based on a multi-beam system according to claim 1, characterized in that: In the step S1, the mathematical expression of the initial phase difference of the split beam is: Step S1.1: collecting target echoes; the target echoes include a first subarray signal and a second subarray signal; Step S1.2: multiply the conjugate of the second sub-array signal by the first sub-array signal to obtain a correlation sequence; Step S1.3: performing windowed sliding average on the correlation sequence to obtain a complex conjugate sequence after sliding average; Step S1.4: Calculate the phase of the complex conjugate sequence after the sliding average to obtain the initial phase difference sequence of the split beam after the sliding average processing; In step S1.4, the mathematical expression of the split beam initial phase difference sequence is: Among them, arctan represents the inverse tangent operation; Im represents the imaginary part operation; Re represents the real part operation; represents the conjugate signal of the signal received by subarray 2; s1(n) represents the complex form of the signal at the receiving end of the first subarray; Based on s2(n), we get: The mathematical expression of s1(n) is: Wherein, s1(n) represents the signal received by subarray 1; E1(n) represents the signal received by subarray 1, i.e., the amplitude sequence of the first subarray signal; represents the phase sequence of the signal received by subarray 1, where j represents an imaginary unit, and φ1(n) represents the phase value of the signal received by subarray 1; The mathematical expression of s2(n) is: Wherein, s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, i.e., the amplitude sequence of the second subarray signal; represents the phase sequence of the signal received by subarray 2, where φ2(n) represents the phase value of the signal received by subarray 2; In step S1.2, the mathematical expression of the correlation sequence is: Wherein, P(n) represents the correlation sequence of the received signals of the two sub-arrays; In step S1.3, the mathematical expression for the complex conjugate sequence is: in, represents the complex conjugate sequence after sliding averaging; L is the sliding window length, W(l) is the sliding window weight coefficient sequence; P(n+l) represents the value of the (n+l)th point in the complex conjugate sequence; W(l) is the sliding window weight coefficient sequence, and L is the sliding window length.

3. The method for detecting coherent phase difference of near-seabed targets based on a multi-beam system according to claim 2 is characterized in that: In the step S2, the method of filtering out the noise interference of the split beam initial phase difference sequence includes setting an amplitude threshold and setting a correlation coefficient threshold; The setting of the amplitude threshold is to determine whether the maximum amplitude of the split beam initial phase difference sequence meets the set amplitude threshold. If the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated; Setting the correlation coefficient threshold, i.e. judging whether the absolute value of the correlation coefficient is greater than or equal to 0.8; if the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated; The absolute value of the correlation coefficient is expressed mathematically as follows: Here, SNR stands for signal-to-noise ratio.

4. The method for detecting coherent phase difference of near-seabed targets based on a multi-beam system according to claim 1, characterized in that: In the step S3, it includes: Step S3.1: based on the split beam initial phase difference sequence, obtain the starting position of the phase difference oblique line interception; based on the noise reduction result, obtain the seabed line curve as the seabed depth information; the seabed line curve includes: a first seabed line phase difference curve and a second seabed line phase difference curve; Step S3.2: intercepting the first seabed line phase difference curve and the second seabed line phase difference curve through the starting position of the phase difference oblique line interception to obtain two intercepted segment curves; Step S3.3: Smoothing and fitting the two intercepted segment curves, detecting and judging whether the difference between the two intercepted segment curves is greater than a preset threshold; if the result is yes, it is prompted that the target is detected and step S3.4 is executed; if the result is no, no processing is performed; Step S3.4: According to the intercepted segment curve detected in step S3.3, i.e., the mutation segment, the TOA value and the DOA value of the phase sequence of the intercepted segment curve are obtained; and the coordinate position of the seabed mission target is obtained according to the TOA value and the DOA value; The DOA value is the angle corresponding to the main beam pointing of the current receiving beam.

5. A near-seabed target coherent phase difference detection system based on a multi-beam system, characterized in that: include: Module M1: collect target echoes and solve the initial phase difference sequence of split beams; Module M2: filtering out the noise interference of the initial phase difference sequence of the split beam to obtain a noise reduction result; Module M3: Obtaining seabed depth information according to the noise reduction result, and detecting seabed mission targets according to the seabed depth information.

6. The near-seabed target coherent phase difference detection system based on a multi-beam system according to claim 5 is characterized in that: In the module M1, the mathematical expression of the initial phase difference of the split beam is: Module M1.1: collecting target echo; the target echo includes a first subarray signal and a second subarray signal; Module M1.2: multiply the conjugate of the second sub-array signal by the first sub-array signal to obtain a correlation sequence; Module M1.3: performing windowed sliding average on the correlation sequence to obtain a complex conjugate sequence after sliding average; Module M1.4: Calculate the phase of the complex conjugate sequence after the sliding average to obtain the initial phase difference sequence of the split beam after the sliding average processing; In the module M1.4, the mathematical expression of the split beam initial phase difference sequence is: Among them, arctan represents the inverse tangent operation; Im represents the imaginary part operation; Re represents the real part operation; represents the conjugate signal of the signal received by subarray 2; s1(n) represents the complex form of the signal at the receiving end of the first subarray; Based on s2(n), we get: The mathematical expression of s1(n) is: Wherein, s1(n) represents the signal received by subarray 1; E1(n) represents the signal received by subarray 1, i.e., the amplitude sequence of the first subarray signal; represents the phase sequence of the signal received by subarray 1, where j represents an imaginary unit, and φ1(n) represents the phase value of the signal received by subarray 1; The mathematical expression of s2(n) is: Wherein, s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, i.e., the amplitude sequence of the second subarray signal; represents the phase sequence of the signal received by subarray 2, where φ2(n) represents the phase value of the signal received by subarray 2; In the module M1.2, the mathematical expression of the correlation sequence is: Wherein, P(n) represents the correlation sequence of the received signals of the two sub-arrays; In the module M1.3, the mathematical expression for the complex conjugate sequence is: in, represents the complex conjugate sequence after sliding averaging; L is the sliding window length, W(l) is the sliding window weight coefficient sequence; P(n+l) represents the value of the (n+l)th point in the complex conjugate sequence; W(l) is the sliding window weight coefficient sequence, and L is the sliding window length.

7. The near-seabed target coherent phase difference detection system based on a multi-beam system according to claim 6 is characterized in that: In the module M2, the method of filtering out the noise interference of the split beam initial phase difference sequence includes setting an amplitude threshold and setting a correlation coefficient threshold; The setting of the amplitude threshold is to determine whether the maximum amplitude of the split beam initial phase difference sequence meets the set amplitude threshold. If the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated; Setting the correlation coefficient threshold, i.e. judging whether the absolute value of the correlation coefficient is greater than or equal to 0.8; if the result is yes, no processing is performed; if the result is no, the corresponding split beam initial phase difference sequence is eliminated; The absolute value of the correlation coefficient is expressed mathematically as follows: Here, SNR stands for signal-to-noise ratio.

8. The near-seabed target coherent phase difference detection system based on a multi-beam system according to claim 7 is characterized in that: The module M3 includes: Module M3.1: based on the split beam initial phase difference sequence, obtain the starting position of the phase difference oblique line interception; based on the noise reduction result, obtain the seabed line curve as the seabed depth information; the seabed line curve includes: a first seabed line phase difference curve and a second seabed line phase difference curve; Module M3.2: intercepting the first seabed line phase difference curve and the second seabed line phase difference curve through the starting position of the phase difference oblique line interception to obtain two intercepted segment curves; Module M3.3: Smoothing and fitting the two intercepted segment curves, detecting and judging whether the difference between the two intercepted segment curves is greater than a preset threshold; if the result is yes, it prompts that the target is detected and executes step S3.4; if the result is no, no processing; Module M3.4: according to the intercepted segment curve detected by module M3.3, the TOA value and the DOA value of the phase sequence of the intercepted segment curve, i.e., the mutation segment, are obtained; and the coordinate position of the seabed mission target is obtained according to the TOA value and the DOA value; The DOA value is the angle corresponding to the main beam pointing of the current receiving beam.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the near-seabed target coherent phase difference detection method based on a multi-beam system according to any one of claims 1 to 4 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the near-seabed target coherent phase difference detection method based on a multi-beam system according to any one of claims 1 to 4 are implemented.

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