A multi-echo detection method and product of a multi-beam bathymetric system combined with amplitude and phase characteristics

Abstract

This invention discloses a multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase features. The pre-detection step includes: segmenting the beam output signal; for each unit to be detected, obtaining an amplitude detection threshold using the unit average constant false alarm rate (CFAR) method based on background noise estimation from the reference units on the left and right sides; extracting the instantaneous phase from the signals of each receiving channel using Hilbert transform, and obtaining the phase coherence factor between each receiving channel from statistical characteristics; dynamically adjusting the amplitude detection threshold as an adaptive weight to construct a detection threshold for combined amplitude and phase features; initializing weighting coefficients based on echo intensity differences, and dynamically optimizing them in conjunction with the intensity value of the phase coherence factor to obtain an adaptive weighted amplitude and phase joint detection threshold; merging sampling points exceeding the adaptive weighted amplitude and phase joint detection threshold, removing interfering targets, and identifying and extracting multiple independent effective target intervals.

Description

Technical Field

[0001] This invention relates to the field of seabed topography detection technology, and in particular to a multi-echo detection method and product for a multibeam bathymetry system that combines amplitude and phase characteristics. Background Technology

[0002] Multibeam bathymetry systems often encounter situations where underwater targets and seabed echoes coexist in complex marine environments during seabed topographic surveys, requiring simultaneous and accurate detection of both. However, traditional seabed detection methods typically assume only a single bathymetry point within each beam, making it difficult to achieve simultaneous detection of underwater targets and seabed echoes, easily leading to missed target detection or seabed misjudgment. To address this issue, multi-echo detection algorithms capable of detecting multiple echo signals from a single beam have emerged, becoming crucial for achieving integrated underwater target and seabed topographic detection.

[0003] Christoffersen et al. proposed a multi-echo detection method based on a fixed amplitude detection threshold. To improve the algorithm's environmental adaptability, Patel et al. proposed an adaptive detection method based on constant false alarm rate (CFAR) detection using the variability index, which enhances its adaptability to changes in the marine environment by setting an adaptive amplitude detection threshold. However, the detection decisions of the above methods are mostly based on echo amplitude, which limits their detection capability when dealing with multiple targets with significant amplitude differences, and their detection stability is insufficient in edge beam regions where the signal-to-noise ratio decreases. Therefore, it is necessary to develop a multi-echo detection method that can adaptively adjust multiple features of the echo signal to improve the robustness and accuracy of multi-target detection in complex environments. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a multi-echo detection method that combines amplitude and phase characteristics. By fusing the amplitude and phase information of the echo signals, a joint detection threshold that can adaptively adjust according to the amplitude and phase characteristics of the target is constructed, enabling effective separation and detection of multiple echoes within a single beam, thereby significantly improving the accuracy and robustness of multi-target detection in complex environments.

[0005] In view of this, the present invention proposes a multi-echo detection method for a multi-beam echo sounding system that combines amplitude and phase characteristics. The method is characterized by introducing a pre-detection step into the traditional signal processing flow of a multi-beam echo sounding system. The pre-detection step includes: Step 1: The beam output signal is segmented and processed. For each unit to be detected, the amplitude detection threshold is obtained by estimating the background noise of the reference units on the left and right sides and using the unit average constant false alarm rate detection method. Step 2: Extract the instantaneous phase of each received channel signal by performing Hilbert transform, and obtain the phase coherence factor between each received channel by using the statistical characteristics of the channel signals; Step 3: Use the phase coherence factor as an adaptive weight to dynamically adjust the amplitude detection threshold, construct a detection threshold that combines amplitude and phase features, and realize differentiated detection of echoes at different positions within the same beam; Step 4: Initialize the weighting coefficients based on the difference in echo intensity between the central beam and the edge beams, and dynamically optimize them by combining the intensity value of the phase coherence factor to obtain the amplitude-phase joint detection threshold of the adaptive weighting coefficients; Step 5: Merge the sampling points that exceed the amplitude-phase joint detection threshold of the adaptive weighting coefficient into intervals so that each target is in a complete time window. Remove interfering targets in time windows with fewer sampling points and identify and extract multiple independent effective target intervals.

[0006] As an improvement to the above method, the signal processing flow of the traditional multibeam echo sounding system includes: For each valid target interval, the amplitude method or phase method is used for bottom detection. After depth sounding and positioning processing, the depth sounding point position is obtained, thereby realizing the synchronous detection of water targets and seabed topography.

[0007] As an improvement to the above method, the cell-average constant false alarm rate detection method in step 1 specifically includes: Set the beam output signal to ,in, n Beam number , m Sampling sequence number For beam number Unit to be detected The reference units on its left and right sides are respectively and , where subscript , The length of the left and right reference units; The background noise estimate of the detection unit can be obtained by using the unit average constant false alarm rate (CFAR) detection. for: The amplitude detection threshold is obtained from the following formula. for: in, This is a threshold factor used to control the false alarm rate.

[0008] As an improvement to the above method, the instantaneous phase extracted in step 2 for:

[0009] in, Indicates the first The received channel signal is in the first The sampled values ​​of each sampling point; This is the Hilbert transform operator.

[0010] As an improvement to the above method, the first step 2 yields the... Beam No. Phase coherence factor at each sampling point for:

[0011] in, To ensure that all received channel signals are sampled at the same time Calculate the variance of the instantaneous phase sine and cosine values.

[0012] As an improvement to the above method, the detection threshold for the combined amplitude and phase features constructed in step 3... for:

[0013] in, These are the weighting coefficients.

[0014] As an improvement to the above method, step 4, which initializes the weighting coefficients, specifically includes: Calculate the seabed echo intensity in the central beam region The average value of the seabed echo intensity in the left and right edge beam regions The difference for: in, The unit is dB; Set weighting coefficients initial value The following relationship must be satisfied: in, The typical value of the coherence factor representing the location of the seabed target is taken as a constant of 0.5.

[0015] As an improvement to the above method, the dynamic optimization of step 4 specifically includes: Based on the confidence interval of the phase coherence factor Dynamically optimized adaptive weighting coefficients for: . On the other hand, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0016] Compared with the prior art, the advantages of the present invention are: By combining amplitude and phase characteristics and introducing an adaptive weighting mechanism, the detection capability for multi-target echoes can be enhanced while suppressing incoherent noise interference, achieving robust detection of multiple echoes in a single beam. This invention not only improves the detection capability for multiple targets with significant amplitude differences but also enhances detection stability in edge beam regions where the signal-to-noise ratio decreases, providing an effective technical means for integrated high-precision detection of underwater targets and seabed topography in complex marine environments. Attached Figure Description

[0017] Figure 1 Here is a flowchart of the multi-echo detection algorithm; Figure 2 Here is a flowchart of the pre-detection signal processing; Figure 3 Here is a flowchart of the combined amplitude and phase feature detection method; Figure 4 A comparison of the amplitude and phase characteristics of a single Ping signal from the same seabed beam; Figure 5 A comparison chart of detection thresholds for pinging the same beam signal from the seabed using different methods; Figure 6 The figures show a comparison of traditional methods and the method provided by this invention with the results of single-ping detection of seabed water. The top figure shows the fixed threshold method, the middle figure shows the detection method based on VI-CFAR, and the bottom figure shows the method of this invention. Figure 7 The figures show a comparison of single-ping seabed depth measurement results between traditional methods and the method provided by this invention. The top figure shows the fixed threshold method, the middle figure shows the VI-CFAR-based detection method, and the bottom figure shows the method of this invention. Detailed Implementation

[0018] This invention proposes a multi-echo detection method combining amplitude and phase characteristics. This method introduces a pre-detection step into the signal processing flow of a traditional multibeam echo sounding system. The pre-detection step mainly includes: 1. The beam output signal is segmented and processed. For each unit to be detected, the background noise of the reference units on both sides is estimated, and the amplitude detection threshold is calculated using the unit average constant false alarm rate detection method, which serves as the preliminary basis for multi-echo detection. 2. By performing Hilbert transform on the signals from each receiving channel to extract the instantaneous phase, the phase coherence factor between channels is calculated to characterize the phase consistency of the echo signal and enhance the ability to distinguish between real targets and noise. 3. The phase coherence factor is used as an adaptive weight to dynamically adjust the amplitude detection threshold, and a joint detection threshold for amplitude and phase features is constructed to realize differentiated detection of echoes at different locations within the same beam, supporting the synchronous identification of underwater targets and seabed echoes. 4. The weighting coefficients are initialized based on the difference in echo intensity between the central beam and the edge beams, and dynamically optimized by combining the confidence interval of the phase coherence factor to obtain the amplitude-phase joint detection threshold of the adaptive weighting coefficients.

[0019] 5. Sampling points that exceed the amplitude-phase joint detection threshold of the adaptive weighting coefficient are merged into intervals so that each target is in a complete time window. Interference targets are removed from time windows with fewer sampling points, and multiple independent effective target intervals are identified and extracted.

[0020] After pre-detection, signal processing using a traditional multibeam echo sounder system is employed to perform amplitude or phase-based bottom detection on each effective target interval. This, combined with echo sounding repositioning, yields the echo point location, thereby enabling simultaneous detection of water targets and seabed topography.

[0021] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0022] Example 1 Embodiment 1 of the present invention provides a multi-echo detection method for a multi-beam echo sounding system that combines amplitude and phase characteristics.

[0023] Appendix Figure 1 A flowchart of the multi-echo detection algorithm is provided. Its core lies in introducing the pre-detection stage into the signal processing flow of the traditional multibeam echo sounding system to obtain multiple detection zones containing the target. (Appendix) Figure 2 A flowchart of the signal processing in the pre-detection stage is presented. Pre-detection involves processing the beam data on the same receiving beam and calculating an adaptive detection threshold. Then, sampling points exceeding the detection threshold are merged into intervals to ensure each target is within a complete time window. Interfering targets are removed from time windows with fewer sampling points. Finally, multiple independent and valid target intervals are automatically identified and extracted. Based on this, amplitude-based or phase-based bottom detection is performed on each target interval, and the depth sounding location is obtained through depth sounding repositioning, thereby achieving synchronous detection of water targets and seabed topography.

[0024] Appendix Figure 3 A flowchart of the joint amplitude and phase feature detection method is given. The method for obtaining the joint amplitude and phase detection threshold mainly includes the following steps: First, set the beam output result sequence as follows: Among them, beam number Sampling sequence number In beam number Each unit to be detected Set on both sides and These represent the left and right reference units of the detection unit, respectively. The lengths of the left and right reference cells are used to estimate the cell to be detected. Background noise estimation .set up and The background noise intensity of the left and right reference cells are local estimates, respectively. Using the simple calculation method of cell-averaged constant false alarm rate (CFAR) detection, the estimated background noise value of the detection cell can be obtained as follows: (1) The adaptive detection threshold for amplitude features obtained from equation (1) is: (2) in, For adaptive amplitude detection threshold, The threshold factor is used to control the false alarm rate.

[0025] To improve the detection threshold's ability to detect targets, the amplitude detection threshold is improved by using the phase coherence factor of the echo signal. Assuming the instantaneous phase of the signal... for: (3) in, Indicates the first The received channel signal is in the first The sampled values ​​of each sampling point; This is the Hilbert transform operator.

[0026] The statistical properties of the real and imaginary parts of the channel signal are used to obtain the first Beam No. Phase coherence factor at each sampling point for: (4) in, To ensure that all received channel signals are sampled at the same time Calculate the variance of the instantaneous phase sine and cosine values.

[0027] From the definition of phase coherence factor, we know that The value reflects the phase coherence of each receiving channel signal after delay compensation. When the echo signal comes from a real target, after delay compensation, the phase of each channel signal has a high degree of consistency, and the phase coherence factor value reaches its maximum value; however, when the signal is mainly composed of noise, the phase consistency decreases after delay compensation, and the phase coherence factor value gradually decreases.

[0028] Phase coherence factor based on echo signal As adaptive weights, the detection threshold based on the joint amplitude and phase features is constructed as follows: (5) in, For adaptive amplitude and phase feature joint detection threshold, These are weighting coefficients. Because the phase coherence factor is higher at the location of the target echo, the detection threshold is lowered after weighting, making the target easier to detect. Conversely, because the phase coherence factor is lower at the location of the noise echo, almost zero, the detection threshold changes less after weighting. Therefore, the detection threshold based on combined amplitude and phase features provides favorable conditions for target detection in situations with significant amplitude differences and low signal-to-noise ratios.

[0029] In formula (5), due to the weighting coefficients This is used to adjust the relative weights of amplitude features and phase coherence features in the joint amplitude and phase feature detection threshold; therefore, setting them appropriately is crucial. The numerical values ​​are crucial for ensuring the stability and robustness of detection performance. Considering the significant difference in seabed echo intensity typically between the central beam directly below and the two edge beams in MBES, this invention first utilizes this difference to... Initial values ​​are set. First, the difference in seabed echo intensity between the central beam region and the edge beam region is calculated as follows: (6) in, Indicates the intensity of seabed echoes in the central beam region. This represents the average intensity of the seabed echo in the left and right edge beam regions. The unit is dB.

[0030] Use half of the difference between the two As a standard for the relative weights of the modulation amplitude feature and the phase coherence feature, we can obtain initial value The following relationship must be satisfied: (7) in, Typical values ​​for the coherence factor representing the location of targets such as those on the seabed. In the initial value setting stage, to simplify calculations and ensure numerical stability, The constant value of 0.5 is used to represent the statistical average level of the coherence factor in the seabed target area.

[0031] To optimize the allocation of relative weights for amplitude and phase features in different environments, the initial values ​​of the weighting coefficients are set. Based on this, the weighting coefficients are further adjusted using the intensity of the phase coherence factor to obtain adaptive weighting coefficients. for: (8) in This represents the lower limit of the confidence level for the phase coherence factor. This represents the upper limit of the confidence level of the phase coherence factor. As shown in equation (5), the larger the phase coherence factor, the more obvious the phase characteristics of the target. In this case, the weighting coefficient can be increased to increase the proportion of phase characteristics in the amplitude-phase joint detection threshold, thereby improving the target detection capability. Typically, a setting can be made... , representing when At that time, the confidence level of the phase coherence factor was considered to be low; [the following was set] , representing when The phase coherence factor was considered to have a high confidence level. Therefore, the amplitude-phase joint detection threshold with adaptive weighting coefficients was obtained.

[0032] Appendix Figure 4 This demonstrates the limitations of a single amplitude feature. Within the same beam of a single Ping data stream, the amplitude of the air column echo is significantly lower than that of the seabed echo, but its phase coherence factor still maintains a peak value significantly higher than the background noise. This indicates that phase coherence can still be maintained at a high level when the echo amplitude is low, providing a key feature for effectively identifying low-amplitude targets.

[0033] Appendix Figure 5 A comparison chart of detection thresholds for pinging the same seabed beam signal using different methods is presented. Within this beam, the amplitude threshold failed to effectively detect the air column target; the fixed-weight amplitude-phase joint detection threshold decreased in the target area, detecting most air column targets; the adaptive weighted coefficient amplitude-phase joint detection threshold achieved the highest number of effective detection points by further reducing the detection threshold at the target location.

[0034] Appendix Figure 6 The figures show a comparison between the detection results of the method provided by this invention and traditional methods for single-ping seabed water bodies. As can be seen from the figures, the top figure shows the fixed threshold method, which struggles to effectively extract air column targets in the water, resulting in poor detection performance; the middle figure shows the VI-CFAR-based detection method, which only detects a small number of air column targets, with significant missed detections in the edge beam region; the bottom figure shows the combined amplitude and phase feature detection method of this invention, which can extract continuous air column targets more completely and improves the seabed detection performance at the edge beams.

[0035] Bottom detection and depth sounding relocation processing were performed on the target echo intervals extracted by different pre-detection methods, and significant anomalies were removed to obtain the final depth sounding results. (Appendix) Figure 7The figures show a comparison between the method provided by this invention and traditional methods for single-ping seabed depth sounding. The top figure shows the fixed threshold method, the middle figure shows the VI-CFAR-based detection method, and the bottom figure shows the method of this invention. Compared to traditional methods, the combined amplitude and phase characteristic multi-echo method of this invention can obtain more continuous and complete depth sounding points for underwater air column targets, and effectively improves the depth sounding quality in the edge beam region of the sector.

[0036] Example 2 Embodiments of the present invention may also provide a computer program product, including a computer program. When the computer program is executed by a processor, it can implement the various steps in the above method embodiments.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A multi-beam bathymetric system multi-echo detection method combining amplitude and phase characteristics, characterized by, The pre-detection step is introduced into the signal processing flow of a traditional multibeam echo sounding system. The pre-detection step includes: Step 1: The beam output signal is segmented and processed. For each unit to be detected, the amplitude detection threshold is obtained by estimating the background noise of the reference units on the left and right sides and using the unit average constant false alarm rate detection method. Step 2: Extract the instantaneous phase of each received channel signal by performing Hilbert transform, and obtain the phase coherence factor between each received channel by using the statistical characteristics of the channel signals; Step 3: Use the phase coherence factor as an adaptive weight to dynamically adjust the amplitude detection threshold, construct a detection threshold that combines amplitude and phase features, and realize differentiated detection of echoes at different positions within the same beam; Step 4: Initialize the weighting coefficients based on the difference in echo intensity between the central beam and the edge beams, and dynamically optimize them by combining the intensity value of the phase coherence factor to obtain the amplitude-phase joint detection threshold of the adaptive weighting coefficients; Step 5: Merge the sampling points that exceed the amplitude-phase joint detection threshold of the adaptive weighting coefficient into intervals so that each target is in a complete time window. Remove interfering targets in time windows with fewer sampling points and identify and extract multiple independent effective target intervals.

2. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 1, characterized in that, The signal processing flow of the traditional multibeam echo sounding system includes: For each valid target interval, the amplitude method or phase method is used for bottom detection. After depth sounding and positioning processing, the depth sounding point position is obtained, thereby realizing the synchronous detection of water targets and seabed topography.

3. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 1, characterized in that, The cell-average constant false alarm rate (CFAR) detection method in step 1 specifically includes: Set the beam output signal to ,in, n Beam number , m Sampling sequence number For beam number Unit to be detected The reference units on its left and right sides are respectively and , where subscript , The length of the left and right reference units; The background noise estimate of the detection unit can be obtained by using the unit average constant false alarm rate (CFAR) detection. for: The amplitude detection threshold is obtained from the following formula. for: in, This is a threshold factor used to control the false alarm rate.

4. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 1, characterized in that, The instantaneous phase extracted in step 2 for: in, Indicates the first The received channel signal is in the first The sampled values ​​of each sampling point; For Hilbert transformation operators.

5. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 4, characterized in that, The first obtained in step 2 Beam No. Phase coherence factor at each sampling point for: in, To ensure that all received channel signals are sampled at the same time Calculate the variance of the instantaneous phase sine and cosine values.

6. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 5, characterized in that, The detection threshold constructed in step 3 for the combined amplitude and phase features for: in, These are the weighting coefficients.

7. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 6, characterized in that, The initialization of weighting coefficients in step 4 specifically includes: Calculate the seabed echo intensity in the central beam region The average value of the seabed echo intensity in the left and right edge beam regions The difference for: in, The unit is dB; Set weighting coefficients initial value The following relationship must be satisfied: in, The typical value of the coherence factor representing the location of the seabed target is taken as a constant of 0.

5.

8. The multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase characteristics according to claim 7, characterized in that, The dynamic optimization in step 4 specifically includes: Based on the confidence interval of the phase coherence factor Dynamically optimized adaptive weighting coefficients for: 。 9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 1.

Images