Offshore bottom target coherent phase difference detection method and system based on multi-beam system

Abstract

The application provides a seabed near target coherent phase difference detection method and system based on a multi-beam system, comprising the following steps: S1, collecting target echo and solving a split beam initial phase difference sequence; S2, filtering noise interference of the split beam initial phase difference sequence to obtain a noise reduction result; 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 conventional target detection algorithm based on an amplitude threshold detection, the split beam coherent phase difference detection algorithm can extract a sudden change section by using the phase information difference of two subarray receiving beams, and better detect a seabed near weak target hidden by a seabed sidelobe background.

Description

Technical Field

[0001] This invention belongs to the field of seabed exploration technology, specifically relating to a method and system for detecting coherent phase difference of near-seabed targets based on a multibeam system. Background Technology

[0002] The new generation of multibeam systems, in addition to their seabed detection capabilities, also possess the ability to record water body data. In recent years, researchers have begun to explore the significant practical value of water body data. Analysis of this data allows for the study of the scattering characteristics of suspended sediment layers and zooplankton, the detection of phenomena such as natural gas leaks and internal ocean waves, and the detection of fine targets such as shipwrecks and suspended sediment. However, when using multibeam systems to detect targets in water body images, in addition to the information representing the target's scattering bodies, the images also contain a large amount of noise and sidelobe interference from the seabed receiver. This significantly affects target clarity, reduces the signal-to-noise ratio, and hinders the progress of target identification and related investigations within the water body. Sidelobe interference also continuously stacks in the water body image, forming "false targets." Only after analyzing and processing noise and sidelobe interference can clear water body images be obtained, enabling better subsequent development and research of these images.

[0003] In recent years, researchers have continuously studied and improved target detection methods under sidelobe background interference from seabed receivers to address the aforementioned problems. Currently, commonly used methods include filtering or region segmentation based on water image processing. These algorithms essentially perform pixel-level processing of the image and do not fundamentally solve the problem of weak targets being obscured by the large seabed background, thus their effectiveness is relatively limited. Another approach is to implement proximity constraint control or filtering for sidelobe interference based on adaptive beamforming or other improved beamformers. However, this method requires high computational resources and often suffers from latency and efficiency issues in real-time applications. In recent years, Jiawei Gao from Harbin Engineering University proposed a method based on joint processing of instantaneous frequency variance and echo amplitude, which significantly improves target echo detection capabilities. Therefore, based on the above research results, it is necessary to further utilize phase information beyond echo amplitude in the target detection process to study target detection algorithms with stronger real-time performance and superior capabilities.

[0004] The split-beam phase difference detection algorithm is based on the phase-based direction finding principle of sonar systems. It divides the receiving array into two subarrays of equal length, performs beamforming processing on each subarray, and utilizes the phase difference of the echo signals. By detecting zero-crossing points in the phase difference sequence curve, the time delay value of each beam signal can be obtained, thus achieving depth sounding. The potential abrupt changes in the initial phase difference sequence and the seabed depth information obtained from zero-crossing point detection make it possible to detect near-seabed targets using phase features.

[0005] Patent document CN101718868A discloses a multi-beam bathymetry method based on multiple split-beam phase difference. This scheme provides a high-resolution multi-beam seabed detection technology. By employing multiple split-beam division methods, it generates multiple measurements of the phase difference curve in the direction of arrival. Simultaneously, it introduces least-squares processing to address parameter estimation errors, solving the problem of difficult automatic tracking gate design in traditional phase difference detection methods. This scheme maintains high detection accuracy even when detecting edge beams with low echo signal-to-noise ratios. However, this scheme cannot address the problem of potential abrupt changes in the initial phase difference sequence, nor can it effectively detect near-bottom targets due to weak backscattering capabilities causing significant differences in echo amplitude between the target and the seabed echo.

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

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for detecting coherent phase difference of near-seabed targets based on a multi-beam system.

[0008] A method for detecting coherent phase difference of near-seabed targets based on a multi-beam system, provided by the present invention, includes:

[0009] Step S1: Acquire the target echo and solve for the initial phase difference sequence of the split beam;

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

[0011] Step S3: Based on the noise reduction results, obtain the seabed depth information, and detect the seabed mission target based on the seabed depth information.

[0012] Preferably, in step S1, the mathematical expression for the initial phase difference of the split beam is:

[0013] Step S1.1: Acquire the target echo; the target echo includes the first subarray signal and the second subarray signal;

[0014] Step S1.2: Multiply the conjugate of the second subarray signal by the first subarray signal to obtain the correlation sequence;

[0015] Step S1.3: Apply a windowed moving average to the relevant sequence to obtain the conjugate sequence after moving average;

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

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

[0018]

[0019] Where arctan represents the arctangent operation; Im represents the imaginary part operation; Re represents the real part operation; s1(n) 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);

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

[0021]

[0022] Where s1(n) represents the received signal of subarray 1; E1(n) represents the received signal of subarray 1, that is, the amplitude sequence of the first subarray signal; Let φ1(n) represent the phase sequence of the signal received by subarray 1, where j represents the imaginary unit and φ1(n) represents the phase value of the signal received by subarray 1.

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

[0024]

[0025] Where s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, that is, the amplitude sequence of the second subarray signal; Let φ2(n) represent 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 for the related sequence is:

[0027]

[0028] Where P(n) represents the correlation sequence of the signals received by the two subarrays;

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

[0030]

[0031] in, Let P(n+l) represent the complex conjugate sequence after moving average; L is the sliding window length, and W(l) is the sliding window weighted coefficient sequence; P(n+l) represents the value at point (n+l) in the complex conjugate sequence; W(l) is the sliding window weighted coefficient sequence, and L is the sliding window length.

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

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

[0034] The correlation coefficient threshold is set by determining 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 initial phase difference sequence of the split beam is removed.

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

[0036]

[0037] SNR represents the signal-to-noise ratio.

[0038] Preferably, step S3 includes:

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

[0040] Step S3.2: Using the starting position of the phase difference oblique line, extract the first submarine line phase difference curve and the second submarine line phase difference curve to obtain two extracted curve segments;

[0041] Step S3.3: Smooth and fit the two segments of the cut curve, detect and determine whether the difference between the two segments of the cut curve is greater than a preset threshold; if the result is yes, then prompt that the target has been detected and proceed to step S3.4; if the result is no, then do not process.

[0042] Step S3.4: Based on the truncated curve segment detected in step S3.3, i.e. the abrupt change segment, obtain the TOA and DOA values ​​of the phase sequence of the truncated curve segment; obtain the coordinate position of the seabed mission target based on the TOA and DOA values;

[0043] The DOA value is taken as the angle corresponding to the direction of the main beam of the currently received beam.

[0044] A coherent phase difference detection system for near-seabed targets based on a multi-beam system, provided by the present invention, includes:

[0045] Module M1: Acquires target echoes and solves for the initial phase difference sequence of the split beam;

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

[0047] Module M3: Based on the noise reduction results, it obtains seabed depth information and detects seabed mission targets based on the seabed depth information.

[0048] Preferably, in module M1, the mathematical expression for the initial phase difference of the split beam is:

[0049] Module M1.1: Acquires 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 subarray signal by the first subarray signal to obtain the correlation sequence;

[0051] Module M1.3: Windowed moving average of the relevant sequence to obtain the conjugate sequence after moving average;

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

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

[0054]

[0055] Where arctan represents the arctangent operation; Im represents the imaginary part operation; Re represents the real part operation; s1(n) 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);

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

[0057]

[0058] Where s1(n) represents the received signal of subarray 1; E1(n) represents the received signal of subarray 1, that is, the amplitude sequence of the first subarray signal; Let φ1(n) represent the phase sequence of the signal received by subarray 1, where j represents the imaginary unit and φ1(n) represents the phase value of the signal received by subarray 1.

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

[0060]

[0061] Where s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, that is, the amplitude sequence of the second subarray signal; Let φ2(n) represent 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 module M1.2, the mathematical expression for the related sequence is:

[0063]

[0064] Where P(n) represents the correlation sequence of the signals received by the two subarrays;

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

[0066]

[0067] in, Let P(n+l) represent the complex conjugate sequence after moving average; L is the sliding window length, and W(l) is the sliding window weighted coefficient sequence; P(n+l) represents the value at point (n+l) in the complex conjugate sequence; W(l) is the sliding window weighted coefficient sequence, and L is the sliding window length.

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

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

[0070] The correlation coefficient threshold is set by determining 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 initial phase difference sequence of the split beam is removed.

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

[0072]

[0073] SNR represents the signal-to-noise ratio.

[0074] Preferably, module M3 includes:

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

[0076] Module M3.2: Using the starting position of the phase difference oblique line, extract the phase difference curves of the first and second seabed lines to obtain two segmented curves;

[0077] Module M3.3: Smooth and fit the two cut-off curve segments, detect and determine whether the difference between the two cut-off curve segments is greater than a preset threshold; if the result is yes, then prompt that the target has been detected and execute step S3.4; if the result is no, then do not process it.

[0078] Module M3.4: Based on the truncated curve segment detected by Module M3.3, i.e. the abrupt change segment, obtain the TOA and DOA values ​​of the phase sequence of the truncated curve segment; and obtain the coordinate position of the seabed mission target based on the TOA and DOA values.

[0079] The DOA value is taken as the angle corresponding to the direction of the main beam of the currently received beam.

[0080] According to the present invention, a computer-readable storage medium storing a computer program is provided, 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 are implemented.

[0081] An electronic device 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, it implements the steps of the near-seabed target coherent phase difference detection method based on a multi-beam system.

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

[0083] 1. Compared with traditional target detection algorithms based on amplitude threshold detection, the coherent phase difference detection algorithm based on split beams can extract abrupt change segments by utilizing the phase information difference between the two subarray receiving beams, thus better detecting weak near-seabed targets that are obscured by the seabed sidelobe background.

[0084] 2. This invention further improves the accuracy of suspected target locations through a series of screening, fitting and averaging methods, thereby effectively improving the detection and positioning capabilities of multibeam systems for near-seabed targets and making them more suitable for practical application scenarios.

[0085] 3. In view of the problem that the weak backscattering capability of near-bottom targets under the background interference of the seabed receiver sidelobe leads to a large difference in echo amplitude between the near-bottom target and the seabed echo, making it impossible to detect effectively, this invention is based on the use of the receiver array split beam to process the phase information difference, and provides a new method for coherent phase difference detection of near-seabed targets in a multi-beam system, thereby improving the detection performance of multi-beam systems for water targets. Attached Figure Description

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

[0087] Figure 1 The algorithm processing flowchart provided by this invention;

[0088] Figure 2 The full-sector multibeam water body map obtained through conventional processing in the simulation verification provided by this invention;

[0089] Figure 3 This invention provides a locally magnified water body image of the target sector obtained through conventional processing in simulation verification; wherein, Figure 3 (a) shows the detection results for target one. Figure 3 (b) shows the detection results for target two;

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

[0091] Figure 5 The phase difference sequence diagram under different receiving beam angles in the sector where the near-bottom target is located, provided by the present invention, during the near-bottom target screening and positioning process; 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 image shows the phase difference abrupt change detection results at a receiving beam pointing at -36.84°, as provided by this invention; wherein, Figure 6 (a) is a diagonal line preceding the seabed line; Figure 6 (b) is the oblique line containing the seabed line;

[0093] Figure 7 The image shows the seabed and target detection results when the receiving beam is pointed at -36.84°, as provided by this invention.

[0094] Figure 8 The phase difference sequence diagram under different receiving beam angles in the sector where the second near-bottom target is located, provided by the present invention, during the near-bottom target screening and positioning process; 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] Figure 9 The image shows the phase difference abrupt change detection results at a receiving beam pointing at 60.68°, as provided by this invention. Figure 9 (a) is a diagonal line preceding the seabed line; Figure 9 (b) is the oblique line containing the seabed line;

[0096] Figure 10 The image shows the seabed and target detection results when the receiving beam is pointed at 60.68°, as provided by this invention.

[0097] Figure 11 The image shows the seabed and target detection results provided by this invention. Detailed Implementation

[0098] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0099] This invention relates to a method for coherent phase difference detection and localization of near-seabed targets based on a multibeam system. Addressing the problem that amplitude threshold detection methods are ineffective when the difference between the target's backscattering intensity and the energy of the sidelobe received from the seabed is small, this invention utilizes a split-beam coherent phase difference detection algorithm. By detecting abrupt changes in the phase characteristic information of the target echo, it enables the extraction of weak near-seabed targets against a seabed background, thereby improving the detection capability of multibeam systems for water targets.

[0100] To address the shortcomings of existing algorithms, a method for coherent phase difference detection and depth sounding of near-seabed targets based on a multi-beam system is invented. This method mainly comprises three parts: solving the initial phase difference sequence of split beams, sea depth estimation, and near-seabed target screening and localization. Specific implementation includes:

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

[0102] Given that the beam outputs of two beams from a split subarray differ by only a phase difference between beams of the same number, the mathematical expression is:

[0103]

[0104] in, The phase difference between the outputs of the same-sign beams of the two subarrays;

[0105] Where D is the distance between the equivalent acoustic centers of the two subarrays, λ is the wavenumber, and θ is the signal azimuth. r The receiving beam control angle. Specifically, Equation (1) is used to explain that when the signal azimuth and the beam control angle are the same, the phase difference is 0, resulting in the zero-crossing phenomenon of the phase sequence curve.

[0106] When the signal azimuth θ is related to the receiving beam control angle θ r At the same time, the phase difference between the two subarray signals is zero. The phase difference sequence crosses the zero line, and the moment of zero crossing is called the zero-crossing point, which is the arrival time of the signal corresponding to the r-th beam pointing. The arrival time of the beam pointing can be calculated using the zero-crossing moment of the phase difference between the received signals of the two subarrays.

[0107] The signal at the subarray receiver is written in complex form:

[0108]

[0109] Where s1(n) represents the received signal of subarray 1; E1(n) represents the received signal of subarray 1, that is, the amplitude sequence of the first subarray signal; Let φ1(n) represent the phase sequence of the signal received by subarray 1, where j represents the imaginary unit and φ1(n) represents the phase value of the signal received by subarray 1, ranging from 0 to 2π.

[0110]

[0111] Where s2(n) represents the received signal of subarray 2; E2(n) represents the received signal of subarray 2, that is, the amplitude sequence of the second subarray signal; Let φ2(n) represent 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 2π.

[0112] Since the signals from both subarrays originate from the same target, the phase difference between the signals can be obtained using correlation methods. Therefore, multiplying the conjugate of the signal from subarray 2 by the signal from subarray 1 yields the following correlation sequence:

[0113]

[0114] Where P(n) represents the correlation sequence of the received signals from the two subarrays; s1 represents the received signal from subarray 1; The conjugate signal of the received signal in subarray 2

[0115] In the above formula, the phase is the phase difference Δφ(n) that we are looking for, which can be expressed as:

[0116]

[0117] Where arctan represents the arctangent operation; Im represents the imaginary part operation; Re represents the real part operation;

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

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

[0120]

[0121] in, Let L represent the complex conjugate sequence after moving average; L is the sliding window length; W(l) is the sliding window weighting 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 weighted coefficient sequence, which is the response of a certain filter, and L is the sliding window length. When W(l) = 1, it is a general averaging process, equivalent to low-pass filtering the complex conjugate sequence P(n), which can eliminate drastically changing components in the sequence and smooth the phase difference data. By processing each sample point in P(n) within the search interval using the above formula, a new complex conjugate sequence under the corresponding receiving beam can be obtained. Then to By determining the phase, we can obtain the result of processing the initial phase difference sequence of the two subarrays after moving average.

[0123] (2) Ocean depth estimation

[0124] The estimated initial phase difference sequence may be affected by a combination of various signal uncorrelation phenomena such as angle uncorrelation, spatial uncorrelation, multipath phenomenon, and marine environmental noise, resulting in random jumps in the phase difference sequence. This can lead to a large error in the estimated seabed echo DOA value and ultimately affect the accurate estimation of sea depth.

[0125] Therefore, in order to reduce noise interference and improve the accuracy of phase difference estimation, noise interference is filtered out by using amplitude thresholds and correlation coefficient thresholds based on the amplitude and correlation characteristics of coherent signals, thereby improving the accuracy of seabed detection phase difference and DOA estimation.

[0126] a) Amplitude threshold filtering

[0127] When the signal amplitude is too small, it is more susceptible to noise interference, which can lead to significant errors in the DOA estimation. Therefore, to reduce the possibility of estimation errors, measurement data points with excessively small coherent signal amplitudes are first eliminated by setting an amplitude threshold. The amplitude threshold can be set empirically to 5–30 dB below the maximum amplitude, and can be reasonably set based on the approximate sea depth and the predicted signal-to-noise ratio of the echo signal.

[0128] b) Coherence coefficient screening

[0129] In coherent measurements, the correlation coefficient is one of the important quantitative standards for evaluating data quality, defined as follows:

[0130]

[0131] Here, E{x} represents the expected value of x, and the absolute value of the correlation coefficient, i.e., |γ|, is also a function of the signal-to-noise ratio (SNR), such as...

[0132]

[0133] If SNR→0, then |γ|→0, meaning the signals from the two beams are completely uncorrelated. If |γ|→1, then they are completely correlated. Therefore, phase difference sequence data containing large amounts of 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, but is typically set to no less than 0.8.

[0134] The symbol → indicates that the value approaches a certain value;

[0135] c) Curve fitting

[0136] When applying the phase difference method, a time-varying zero-crossing phase difference sequence can be obtained, which exhibits a monotonic curve distribution within the main beam range. By determining the zero-crossing points of the phase difference sequence, the TOA (Time of Arrival) estimate of the corresponding beam can be obtained. However, due to interference fluctuations in the reverberant echo signal and changes in seabed topography, the phase difference sequence curve will exhibit random fluctuations, making it difficult to determine the zero-crossing point. Therefore, to better determine the zero-crossing point, a binomial curve fitting is performed on the phase difference sequence.

[0137] (3) Near-seabed target screening and positioning

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

[0139] First, the starting position for the phase difference curve interception is set, and the phase difference curve at the seabed line and the one preceding the seabed line are intercepted respectively. Suspected target abrupt change segments are detected on both curves. Then, the two intercepted curve segments are smoothed and fitted. The phase difference value before and after fitting is calculated, and curve segments with a difference greater than a set threshold are selected as initial target abrupt change segments. Further screening is performed using correlation coefficients. If phase difference sequences still exist after screening, a suspected near-seabed target is considered detected. Next, the location of the suspected target is estimated, and the average of the TOA values ​​corresponding to this phase difference sequence is used as the echo arrival time of the suspected target. Then, the corresponding DOA value is matched based on the curve position of the abrupt change segment. If the abrupt change segment is on the phase difference curve where the seabed line is located, the DOA value is taken as the angle corresponding to the direction of the main beam of the current receiving beam. If the abrupt change segment is on the phase difference curve preceding the seabed line phase difference curve, the DOA value is taken as the angle corresponding to the direction of the first sidelobe of the current receiving beam. If there is no abrupt change segment on either the phase difference curve where the seabed line is located or the phase difference curve preceding the seabed line phase difference curve, then no seabed target is detected. Furthermore, if the current receiving beam angle is positive, the left first sidelobe is taken; if the current receiving beam angle is negative, the right first sidelobe is taken. Finally, the coordinate position of the near-bottom target is obtained based on the TOA and DOA values.

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

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

[0142] Step S3.1: Set the starting position for the phase difference oblique line interception, and intercept the phase difference curve where the seabed line is located and the phase difference curve before the seabed line respectively. Then, perform abrupt change segment detection for suspected targets on these two curves respectively.

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

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

[0145] First, a simulation application scenario for the specific implementation plan is given. The simulation is set at a seabed depth of 800m, with a uniform linear array of multibeam receivers, a total of 64 array elements, 48 ​​split subarrays, and an element spacing of 30kHz half wavelength. The actual position coordinates of near-seabed target 1 are (-560, -750), with a true angle of -36.74°, located in sector 7; the actual position coordinates of near-seabed target 2 are (1280, -720), with a true angle of 60.64°, located in sector 1.

[0146] Here, we first present the original multibeam bathybody image of the entire fan-shaped surface obtained through conventional processing, as shown below. Figure 2 As shown in the image, the green circles indicate the locations of two near-seabed targets. Figure 3 A magnified water image of the sector containing the two targets is provided. The image shows that the echo intensity of both targets is very weak, almost completely masked by seabed sidelobe interference, making them indistinguishable to the naked eye. Under these conditions, conventional amplitude detection methods cannot effectively extract the two near-seabed targets.

[0147] Next, the method proposed in this invention is used according to the process. Figure 1 The given steps are followed, firstly to solve for the initial phase difference sequence of the split beam under each receiving beam angle in the simulation data. Taking the result under the 41.5° receiving beam direction as an example, the obtained initial phase difference sequence curve is as follows: Figure 4 As shown in (a), there are multiple zero-crossing diagonal lines in the figure.

[0148] The next step is to estimate the ocean depth under the current receiving beam. First, the initial phase difference sequence is filtered based on multi-source information, with the amplitude threshold set to -25dB and the correlation coefficient threshold set to 0.9. The solution for the amplitude information and the threshold settings are detailed in [link to documentation]. Figure 4 (b) The solution for the correlation coefficient and the setting of the threshold are shown in [reference]. Figure 4 (c) After multi-source information filtering, the phase difference sequence is: Figure 4 The blue curve in (d) Figure 4 (d) The red dashed line represents the result of curve fitting of the filtered phase difference sequence.

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

[0150] Next, the near-bottom target screening and localization process is performed: First, the initial phase difference sequence diagrams under different receiving beam angles in the sector where the near-bottom target is located are given, such as... Figure 5 As shown. The green box indicates the phase difference curve segment of the seabed line obtained after filtering multi-source information in the previous depth estimation step. The true bearing of the near-seabed target is -36.74°. Figure 5 As can be seen from the diagram, during the process of the receiving beam gradually aligning with and then gradually deviating from the target's true orientation, abrupt changes gradually appear on the phase difference curve preceding the seabed line in the initial phase difference sequence diagram, and then gradually disappear. When the receiving beam is aligned with the target's true orientation, the resulting initial phase difference sequence is as follows: Figure 5 As shown in (c), a clear abrupt change segment can be seen on the phase difference curve preceding the seabed line. Next, as... Figure 6 The method for screening near-bottom targets involves smoothing the phase difference curve of the seabed line and the phase difference curve preceding the seabed line, fitting the curves, and calculating the difference before and after fitting. Initial abrupt change segments with differences exceeding a set threshold are first identified. Then, correlation coefficients are used for further screening to obtain potential target segments. Figure 6 The red curve shown represents the suspected target segment. Taking the result of a beam pointing downwards at -36.84° as an example, as... Figure 6 As shown, a suspected target segment was detected only on one phase difference curve ahead of the seabed line. The TOA values ​​corresponding to the suspected target segment were then averaged and matched with the angle -32.1° corresponding to the right first sidelobe, thus calculating the suspected target location as (-557.1, -750.8). This detected target location was then plotted together with the seabed line detection results under this receiving beam on the depth map, as shown below. Figure 7 As shown, the suspected target location has a very small error compared to the actual target location (-560, -750), and the seabed detection results are also accurate.

[0151] Specifically, the same processing was applied to the near-bottom target 2 with a true azimuth of 60.64°.

[0152] First, the initial phase difference sequence diagrams under different receiving beam angles in the sector where the near-bottom target 2 is located are given, as follows: Figure 8 As shown, the phase difference abrupt change segment initially appears on the phase difference curve preceding the seabed line, and then gradually moves to the phase difference curve where the seabed line is located.

[0153] Next, as Figure 9 As shown, the screening of near-bottom targets is performed. Taking the results of the 60.68° receiving beam pointing downwards as an example, from... Figure 9As can be seen, only the suspected target segment was detected on the phase difference curve where the seabed line is located. Then, by averaging the TOA values ​​corresponding to the suspected target segment and matching them with the pointing angle of the main beam of the current receiving beam (60.68°), the location of the suspected target can be calculated as (1279.9, -718.7). This detected target point location, along with the seabed line detection results under this receiving beam, is plotted on the depth map, as shown below. Figure 10 As shown, the suspected target location has a very small error compared to the actual location of target two (1280, -720), and the seabed detection results are also accurate.

[0154] By traversing all receiving beam angles (-70°, 70°), the final complete seabed and target detection results are as follows: Figure 11 As shown. Figure 11 As shown, the seabed line at the bottom is clear, and the depth measurement error is very small compared with the actual sea depth of 800m. Furthermore, the phase coherence detection algorithm can detect near-seabed targets on both the left and right sides, and the final target position 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 implemented 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 embodiment of the near-seabed target coherent phase difference detection system based on a multi-beam system.

[0156] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0157] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for detecting near-bottom targets based on the difference in coherent phase of a multi-beam system, characterized in that, The method comprises the following steps: Step S1: collecting target echo, and solving split beam initial phase difference sequence; Step S2: filtering noise interference of the split beam initial phase difference sequence to obtain a noise reduction result; Step S3: obtaining seabed depth information according to the noise reduction result, and detecting a seabed task target according to the seabed depth information; In the step S3, the method comprises the following steps: Step S3.1: obtaining a starting position of phase difference diagonal intercepting based on the split beam initial phase difference sequence, and obtaining a seabed line curve as the seabed depth information based on the noise reduction result; the seabed line curve comprises 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 diagonal intercepting to obtain two segment curves; Step S3.3: smoothing and fitting the two segment curves, and detecting and judging whether a difference between the two segment curves is greater than a preset threshold value; if the result is yes, it is prompted that a target is detected, and step S3.4 is performed; if the result is no, it is not processed; Step S3.4: obtaining a TOA value and a DOA value of a phase sequence of the segment curve, i.e. a mutation segment, according to the segment curve detected in step S3.3, and obtaining a coordinate position of the seabed task target according to the TOA value and the DOA value; The DOA value takes an angle corresponding to a main beam direction of a current receiving beam.

2. The method of claim 1, wherein the method is a multi-beam system based near bottom target coherent phase difference detection method. In the step S1, the split beam initial phase difference sequence has a mathematical expression as follows: Step S1.1: collecting target echo; the target echo comprises a first subarray signal and a second subarray signal; Step S1.2: multiplying a conjugate of the second subarray signal by the first subarray signal to obtain a correlation sequence; Step S1.3: windowed sliding average processing of the correlation sequence to obtain a sliding average conjugate sequence; Step S1.4: phase calculation of the sliding average conjugate sequence to obtain a sliding average processed split beam initial phase difference sequence; In the step S1.4, the split beam initial phase difference sequence has a mathematical expression as follows: wherein, denotes an inverse tangent operation; denotes a take imaginary part operation; denotes a take real part operation; denotes a conjugate signal of the subarray 2 received signal; denotes a complex form of the signal received at the first subarray end; based on obtained; The Mathematical expression for the above is: (2) wherein denotes the subarray 1 received signal; denotes the amplitude sequence of the subarray 1 received signal, i.e. the first subarray signal; denotes the phase sequence of the subarray 1 received signal, wherein denotes the imaginary unit, denotes the phase value of the subarray 1 received signal; The The mathematical expression is: (3) wherein denotes the subarray 2 received signal; denotes the amplitude sequence of the subarray 2 received signal, i.e. the second subarray signal; denotes the phase sequence of the subarray 2 received signal, wherein denotes the phase value of the subarray 2 received signal; In the step S1.2, the correlation sequence has a mathematical expression as follows: (4) wherein denotes the correlation sequence of the two subarray received signals; In the step S1.3, the conjugate sequence has a mathematical expression as follows: (6) in, This represents the conjugate sequence after moving average; For the length of the sliding window, For the sliding window weighted coefficient sequence; In the complex conjugate sequence, the (th)th... The value of the point; For the sliding window weighted coefficient sequence, The length of the sliding window.

3. The method of claim 2, wherein the method is a method of detecting a near bottom target using a multi-beam system, and wherein the method comprises: In the step S2, the method for filtering noise interference of the split beam initial phase difference sequence comprises setting an amplitude threshold and setting a correlation coefficient threshold; The amplitude threshold is set, that is, whether a maximum amplitude of the split beam initial phase difference sequence meets the set amplitude threshold is judged; if the result is yes, it is not processed; if the result is no, the corresponding split beam initial phase difference sequence is removed; The correlation coefficient threshold is set, that is, whether an absolute value of a correlation coefficient is greater than or equal to 0.8 is judged; if the result is yes, it is not processed; if the result is no, the corresponding split beam initial phase difference sequence is removed; The absolute value of the correlation coefficient has a mathematical expression as follows: (8) wherein represents the signal-to-noise ratio.

4. A near bottom target coherent phase difference detection system based on a multi-beam system, characterized in that, The method comprises the following steps: Module M1: collecting target echo, and solving split beam initial phase difference sequence; Module M2: filtering noise interference of the split-beam initial phase difference sequence to obtain a noise reduction result; Module M3: obtaining seabed depth information according to the noise reduction result, and detecting a seabed task target according to the seabed depth information; In the module M3, comprising: Module M3.1: obtaining a phase difference slope intercept start position based on the split-beam initial phase difference sequence, and obtaining a seabed line curve as the seabed depth information based on the noise reduction result; the seabed line curve comprises 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 phase difference slope intercept start position to obtain two segments of intercept segment curves; Module M3.3: smoothing and fitting the two segments of intercept segment curves, detecting and judging whether the difference of the two segments of intercept segment curves is greater than a preset threshold; if the result is yes, it is prompted that a target is detected, and step S3.4 is executed; if the result is no, it is not processed; Module M3.4: obtaining TOA value and DOA value of the phase sequence of the intercept segment curve, i.e. the abrupt segment, according to the intercept segment curve detected by module M3.3, and obtaining coordinate position of the seabed task target according to the TOA value and the DOA value; The DOA value takes the corresponding angle of the main beam direction of the current receiving beam.

5. The multi-beam system based near-bottom target coherent phase difference detection system of claim 4, wherein, In the module M1, the mathematical expression of the split-beam initial phase difference is: Module M1.1: collecting target echoes; the target echoes comprise a first subarray signal and a second subarray signal; Module M1.2: multiplying the conjugate of the second subarray signal by the first subarray signal to obtain a correlation sequence; Module M1.3: windowed sliding average of the correlation sequence to obtain a sliding average of the complex conjugate sequence; Module M1.4: phase of the sliding average of the complex conjugate sequence to obtain a sliding average of the split-beam initial phase difference sequence; In the module M1.4, the mathematical expression of the split-beam initial phase difference sequence is: wherein, represents an inverse tangent operation; represents a take imaginary part operation; represents a take real part operation; represents a conjugate signal of the subarray 2 received signal; represents a complex form of the signal received at the first subarray end; based on obtained; The The mathematical expression is: (2) wherein denotes the subarray 1 received signal; denotes the amplitude sequence of the subarray 1 received signal, i.e. the first subarray signal; denotes the phase sequence of the subarray 1 received signal, wherein denotes the imaginary unit, denotes the phase value of the subarray 1 received signal; The The mathematical expression is: (3) wherein denotes the subarray 2 received signal; denotes the amplitude sequence of the subarray 2 received signal, i.e. the second subarray signal; denotes the phase sequence of the subarray 2 received signal, wherein denotes the phase value of the subarray 2 received signal; In the module M1.2, the mathematical expression of the correlation sequence is: (4) wherein denotes the correlation sequence of the two subarray received signals; In the module M1.3, the mathematical expression of the complex conjugate sequence is: (6) wherein, represents a sliding average of the pair complex conjugate sequence; is a sliding window length, is a sliding window weighting coefficient sequence; represents a value of the (i-1)th point in the complex conjugate sequence; is a sliding window length, is a sliding window weighting coefficient sequence, is a sliding window length.

6. The multi-beam system based near-bottom target coherent phase difference detection system of claim 5, wherein, In the module M2, the way of filtering noise interference of the split-beam initial phase difference sequence comprises setting an amplitude threshold and setting a correlation coefficient threshold; The setting of the amplitude threshold, i.e. judging whether the maximum amplitude of the split-beam initial phase difference sequence meets the set amplitude threshold, if the result is yes, it is not processed; if the result is no, the corresponding split-beam initial phase difference sequence is removed; The setting of 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, it is not processed; if the result is no, the corresponding split-beam initial phase difference sequence is removed; The absolute value of the correlation coefficient, the mathematical expression is: (8) wherein represents the signal-to-noise ratio.

7. A computer readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the near-seabed target coherent phase difference detection method based on the multi-beam system in any one of claims 1 to 3.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The computer program, when executed by a processor, implements the steps of the method for detecting a near-bottom target coherent phase difference based on a multi-beam system according to any one of claims 1 to 3.

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