Peak point extraction method, system, terminal and medium of seabed echo saturation waveform

Abstract

The present invention provides a method, system, terminal and medium for extracting the peak point of a seabed echo saturation waveform, including: obtaining a first target value based on the maximum undistorted signal of a seabed echo signal receiving device; obtaining seabed echo signal data; obtaining a second target value based on the first target value and the seabed echo signal data, and determining a target data interval based on the first target value and the second target value; extracting the seabed echo signal located in the target data interval to correspond to the ascending segment target data and the descending segment target data; performing linear fitting based on the ascending segment target data and the descending segment target data, respectively, to obtain an ascending segment linear function and a descending segment linear function; obtaining the intersection of the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data. The method for extracting the peak point of a seabed echo saturation waveform provided by the present invention can improve the accuracy and efficiency of extracting the peak point of a seabed echo saturation waveform.

Description

Technical Field

[0001] The present application belongs to the field of marine surveying and mapping technology, and in particular, relates to a method, system, terminal and medium for extracting peak points of a seabed echo saturation waveform. Background Art

[0002] Seabed echo is the waveform signal that is reflected back after the laser pulse emitted encounters the seabed when using lidar technology for detection in an underwater environment. It contains important information about the seabed topography, landforms and physical properties. It is currently widely used in marine engineering, resource exploration and environmental monitoring and other fields.

[0003] Peak extraction is a key step in the seabed echo waveform solution process, which affects the quality and reliability of the effective information extracted from the seabed echo signal. Peak extraction mainly determines the distance of the target by extracting the significant peak in the waveform. However, in the laser radar detection technology, when the emitted light wave encounters the seabed surface, it is affected by the complexity of the seabed topography and the limitation of the dynamic range of the detection system, which often causes the received seabed echo signal intensity to exceed the processing capacity of the detection system, resulting in waveform saturation, and the maximum value of the seabed echo signal cannot be accurately recorded, affecting the accuracy of the extracted seabed echo signal peak. The existing seabed echo waveform saturation correction method usually uses a Gaussian function or its variants to fit the complete seabed echo waveform to achieve the correction of the seabed echo waveform saturation. However, the real seabed echo waveform distribution shows the characteristic of left deviation, and does not follow the distribution characteristics of the Gaussian distribution, that is, it presents a symmetrical bell curve. Therefore, the seabed echo waveform fitted based on the Gaussian function or its variants is different from the real seabed echo waveform, and the peak point of the accurate seabed echo saturation waveform cannot be extracted.

[0004] Based on this, how to improve the accuracy of the acquired seabed echo peak is an important issue that needs to be solved urgently. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a method for extracting the peak point of a seabed echo saturation waveform, which is used to solve the problem that the seabed echo peak point fitted by the existing saturation waveform peak point extraction method is different from the actual seabed echo peak point, and the accurate seabed echo saturation waveform peak point cannot be extracted.

[0006] To achieve the above object and other related objects, the present invention provides a method for extracting the peak point of a seabed echo saturation waveform, comprising the following steps:

[0007] Acquire a maximum undistorted signal of a seabed echo signal receiving device, and acquire a first target value based on a signal strength value of the maximum undistorted signal;

[0008] Acquire seabed echo signal data; obtain a second target value based on the first target value and the seabed echo signal data, and use the first target value and the second target value as interval endpoints to determine a target data interval; the target data interval is a data interval within which the seabed echo signal data meets a preset linear fitting condition; the seabed echo signal data is a time series distribution of signal strength values ​​of the seabed echo signal;

[0009] Extracting seafloor echo signals located in the target data interval from the ascending segment data and the descending segment data of the seafloor echo signal data respectively, so as to correspond to the ascending segment target data and the descending segment target data; performing linear fitting based on the ascending segment target data and the descending segment target data respectively, and correspondingly obtaining the ascending segment linear function and the descending segment linear function;

[0010] The intersection point between the ascending segment linear function and the descending segment linear function is obtained as the peak point of the seabed echo signal data.

[0011] In one embodiment of the present invention, the preset linear fitting condition includes: the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data located in the target data interval are not less than the corresponding preset number thresholds; the obtaining of the second target value based on the first target value and the seabed echo signal data includes:

[0012] Starting from the first target value, in descending time order, waveform linear change judgment is performed on each seabed echo signal in the rising segment data of the seabed echo signal data, so as to obtain a waveform linear change node in the rising segment data of the seabed echo signal data, and determine the second target value based on the waveform linear change node;

[0013] Wherein, the second target value is greater than or equal to the signal strength value corresponding to the waveform linear change node;

[0014] The waveform linear change node is the first seabed echo signal that satisfies the waveform linear change judgment in descending time order in the rising segment data of the seabed echo signal data.

[0015] In one embodiment of the present invention, the implementation method of the waveform linear change judgment includes:

[0016] Calculate the tangent slope corresponding to the seabed echo signal at the current moment, and determine whether the tangent slope is less than a preset slope threshold. If so, determine that the seabed echo signal at the current moment meets the waveform linear change judgment, and obtain the seabed echo signal at the current moment as the waveform linear change node.

[0017] In one embodiment of the present invention, determining the second target value based on the waveform linear change node includes:

[0018] The signal strength value corresponding to the waveform linear change node is obtained as the second target value.

[0019] In one embodiment of the present invention, the preset linear fitting condition further includes: the R-square error of the rising segment data of the seabed echo signal data located in the target data interval is greater than a preset error threshold; the second target value is determined based on the waveform linear change node, including:

[0020] Initial second target value acquisition: obtain the signal strength value corresponding to the waveform linear change node as the initial second target value;

[0021] Fitting verification data determination: based on the first target value and the current initial second target value, determining the current initial target data interval, and acquiring data located in the current initial target data interval from the seabed echo signal data as the current fitting verification data;

[0022] Acquisition of the second target value: determine whether the current fitting verification data meets the preset linear fitting condition; if not, update the current initial second target value based on the preset update threshold to re-execute the fitting verification data determination and acquisition of the second target value; if so, use the current initial second target value as the second target value.

[0023] In one embodiment of the present invention, the second target value includes: an ascending segment second target value and a descending segment second target value; the target data interval includes: an ascending segment target data interval and a descending segment target data interval; the second target value is obtained based on the first target value and the seabed echo signal data, and the first target value and the second target value are respectively used as interval endpoints to determine the target data interval, including:

[0024] Starting from the first target value, in descending order of time, waveform linear change judgment is performed on each seabed echo signal in the ascending segment data of the seabed echo signal data, and waveform linear change judgment is performed on each seabed echo signal in the descending segment data of the seabed echo signal data, so as to obtain corresponding ascending segment waveform linear change nodes and descending segment waveform linear change nodes in the ascending segment data and descending segment data of the seabed echo signal data respectively;

[0025] Based on the linear change nodes of the rising segment waveform, the second target value of the rising segment is determined, and the first target value and the second target value of the rising segment are used as interval endpoints to determine the target data interval of the rising segment; and based on the linear change nodes of the falling segment waveform, the second target value of the falling segment is determined, and the first target value and the second target value of the falling segment are used as interval endpoints to determine the target data interval of the falling segment.

[0026] Correspondingly, the present invention provides a peak point extraction system for a seabed echo saturation waveform, the system comprising:

[0027] A first target value acquisition module is used to acquire a signal strength value of a maximum undistorted signal of a seabed echo signal receiving device, and acquire a first target value based on the signal strength value of the maximum undistorted signal;

[0028] A second target value acquisition module is used to acquire seabed echo signal data; based on the first target value and the seabed echo signal data, a second target value is obtained, and the first target value and the second target value are respectively used as interval endpoints to determine a target data interval; the target data interval is a data interval within which the seabed echo signal data meets a preset linear fitting condition; the seabed echo signal data is a time series distribution of signal strength values ​​of the seabed echo signal;

[0029] A linear fitting module is used to extract the seabed echo signal located in the target data interval from the ascending segment data and the descending segment data of the seabed echo signal data, respectively, to correspond to the ascending segment target data and the descending segment target data; perform linear fitting based on the ascending segment target data and the descending segment target data, respectively, to obtain the ascending segment linear function and the descending segment linear function;

[0030] The extraction module is used to obtain the intersection point between the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data.

[0031] In one embodiment of the present invention, the preset linear fitting condition includes: the R-square error of the rising segment data of the seabed echo signal data located in the target data interval is greater than the preset error threshold, and the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data located in the target data interval are not less than the preset number threshold; the system also includes:

[0032] An initial second target value acquisition submodule is used to acquire a signal strength value corresponding to a waveform linear change node as an initial second target value;

[0033] A fitting verification data determination submodule is used to determine a current initial target data interval based on the first target value and the current initial second target value, and obtain data located in the current initial target data interval from the seabed echo signal data as current fitting verification data;

[0034] The second target value optimization acquisition submodule is used to determine whether the current fitting verification data meets the preset linear fitting condition. If not, based on the preset update threshold, the current initial second target value is updated to re-execute the fitting verification data determination and the second target value acquisition; if so, the current initial second target value is used as the second target value.

[0035] Correspondingly, the present invention provides a terminal for extracting the peak point of a seabed echo saturation waveform, the terminal comprising:

[0036] Memory for storing computer programs;

[0037] The processor is used to execute the computer program stored in the memory so that the terminal executes the peak point extraction method.

[0038] Correspondingly, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the peak point extraction method as described above is implemented.

[0039] As described above, the method, system, terminal and medium for extracting the peak point of the seabed echo saturation waveform described in the present application have the following beneficial effects:

[0040] By acquiring a first target value and a second target value, a target data interval is determined based on the first target value and the second target value; and based on the target data interval, an ascending segment target data and a descending segment target data are extracted from the seabed echo signal data, and linear fitting is performed on the ascending segment data and the descending segment data respectively to acquire an ascending segment linear function and a descending segment linear function, and based on the ascending segment linear function and the descending segment linear function, a peak point of the seabed echo signal data is obtained, thereby improving the accuracy and efficiency of extracting the peak point of the seabed echo saturation waveform. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic flow chart of a method for extracting the peak point of a seafloor echo saturation waveform provided by the present application in one embodiment is shown.

[0042] Figure 2 The figure shows the comparison of the peak point extraction results of each algorithm for the seabed echo saturation waveform at a depth of 30 meters.

[0043] Figure 3 Shown is a scatter plot between sonar depth data and lidar depth data obtained based on various algorithms.

[0044] Figure 4 A module structure diagram of a peak point extraction system for a seabed echo saturation waveform provided by the present application in one embodiment is shown.

[0045] Figure 5 A submodule structure diagram of a second target value acquisition module provided in the present application in one embodiment is shown.

[0046] Figure 6 A schematic structural diagram of a peak point extraction terminal for a seafloor echo saturation waveform provided by the present application in one embodiment is shown.

[0047] Description of Reference Numerals

[0048] S1~S4, steps; 200, peak point extraction system; 201, first target value acquisition module; 202, second target value acquisition module; 2021, initial second target value acquisition submodule; 2022, fitting verification data determination submodule; 2023, second target value optimization acquisition submodule; 203, linear fitting module; 204, extraction module; 300, peak point extraction terminal; 301, memory; 302, processor. DETAILED DESCRIPTION

[0049] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0050] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0051] To facilitate the understanding of the technical solutions provided by the present application, the relevant terms in the present application are explained before the specific embodiments, as follows:

[0052] Linear dynamic range: refers to the range of signal strengths that the seabed echo signal receiving device can handle, from the signal strength of the smallest detectable signal to the signal strength of the largest undistorted signal.

[0053] Water backscattering: refers to the phenomenon that after light waves are incident on the surface of water and enter the water, due to the presence of suspended particles, plankton and dissolved substances in the water, the light waves interact with these particles or molecules and are scattered, and part of the light waves are returned in the opposite direction of the incident light.

[0054] PD: Peak position detection algorithm, peak position detection algorithm, is a computational method used to identify and locate the peak position in a signal or data set.

[0055] GF: Gaussian fitting, Gaussian fitting algorithm, is a method of fitting data points using a Gaussian function (also known as a normal distribution function).

[0056] EMG: Exponentially modified Gaussian algorithm, exponentially modified Gaussian fitting algorithm, is a method that combines the characteristics of Gaussian distribution (normal distribution) and exponential decay to simulate and predict data distribution.

[0057] The embodiments of the present application are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the features of the following embodiments and implementations can be combined with each other.

[0058] The following embodiments of the present application provide a method for extracting the peak points of a seabed echo saturation waveform, by obtaining a first target value and a second target value, and determining a target data interval based on the first target value and the second target value; and based on the target data interval, extracting ascending segment target data and descending segment target data from the seabed echo signal data, performing linear fitting on the ascending segment data and the descending segment data respectively, obtaining an ascending segment linear function and a descending segment linear function, and obtaining the peak point of the seabed echo signal data based on the ascending segment linear function and the descending segment linear function, thereby improving the accuracy and efficiency of extracting the peak points of the seabed echo saturation waveform.

[0059] See also Figure 1 , showing a schematic flow chart of a method for extracting a peak point of a seafloor echo saturation waveform provided by the present invention in one embodiment;

[0060] like Figure 1 As shown, in this embodiment, the peak point extraction method of the seabed echo saturation waveform provided by the present invention includes the following steps:

[0061] Step S1, obtaining a linear dynamic range of a seabed echo signal receiving device, obtaining a signal strength value of a maximum undistorted signal of the seabed echo signal receiving device based on the linear dynamic range, and obtaining a first target value based on the signal strength value of the maximum undistorted signal;

[0062] In one implementation, the obtaining a first target value based on the signal strength value of the maximum undistorted signal includes:

[0063] The signal strength value of the maximum undistorted signal is subtracted from a preset buffer threshold to obtain a difference between the two as the first target value.

[0064] Optionally, the seabed echo signal receiving device includes: a laser radar receiver, etc.

[0065] Optionally, the first target value is 800.

[0066] Step S2, acquiring seabed echo signal data; the seabed echo signal data includes ascending segment data and descending segment data; based on the first target value and the seabed echo signal data, obtaining a second target value, taking the first target value and the second target value as interval endpoints, respectively, to determine a target data interval; the target data interval is a data interval within which the seabed echo signal data satisfies a preset linear fitting condition; the seabed echo signal data is a time series distribution of signal strength values ​​of the seabed echo signal;

[0067] Wherein, the preset linear fitting condition includes: the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data located in the target data interval are not less than the corresponding preset number thresholds.

[0068] It should be noted that, according to the distribution characteristics of the seabed echo signal, the seabed echo signal data is divided into rising segment data, saturation segment data and falling segment data; the rising segment data of the seabed echo signal data is the data in which the signal distribution presents an rising trend in the seabed echo signal data; the saturation segment data of the seabed echo signal data is the data in which the signal distribution presents a flat trend in the seabed echo signal data; the falling segment data of the seabed echo signal data is the data in which the signal distribution presents a falling trend in the seabed echo signal data.

[0069] Optionally, the second target value is 500; the preset quantity threshold is 3.

[0070] In one embodiment, obtaining a second target value based on the first target value and the seabed echo signal data includes:

[0071] Starting from the first target value, in descending time order, waveform linear change judgment is performed on each seabed echo signal in the rising segment data of the seabed echo signal data, so as to obtain a waveform linear change node in the rising segment data of the seabed echo signal data, and determine the second target value based on the waveform linear change node;

[0072] The waveform linear change node is the first seabed echo signal that satisfies the waveform linear change judgment in descending time order in the rising segment data of the seabed echo signal data.

[0073] Specifically, starting from the first target value, the waveform linear change judgment is performed on each seabed echo signal in the rising segment data of the seabed echo signal data in descending order of time. When the current seabed echo signal satisfies the waveform linear change judgment, the waveform linear change judgment is stopped, and the current seabed echo signal is obtained as the waveform linear change node. Based on the waveform linear change node, the second target value is determined.

[0074] In one implementation, the implementation of the waveform linear change judgment includes:

[0075] Calculate the tangent slope corresponding to the seabed echo signal at the current moment, and determine whether the tangent slope is less than a preset slope threshold. If so, determine that the seabed echo signal at the current moment meets the waveform linear change judgment, and obtain the seabed echo signal at the current moment as the waveform linear change node.

[0076] Optionally, the preset slope threshold is 0.

[0077] In one embodiment, determining the second target value based on the waveform linear change node includes: using the signal strength value corresponding to the waveform linear change node as the second target value.

[0078] In another embodiment, the preset linear fitting condition further includes: if the R-square error of the rising segment data of the seabed echo signal data within the target data interval is greater than a preset error threshold, then determining the second target value based on the waveform linear change node includes:

[0079] Step S21, obtaining the signal strength value corresponding to the waveform linear change node as the initial second target value;

[0080] Step S22, based on the first target value and the current initial second target value, determine the current initial target data interval, and obtain data located in the current initial target data interval from the seabed echo signal data as current fitting verification data;

[0081] Step S23, determine whether the current fitting verification data meets the preset linear fitting condition; if not, update the current initial second target value based on the preset update threshold to re-execute steps S22 to S23; if so, use the current initial second target value as the second target value.

[0082] Optionally, the preset error threshold is 0.92.

[0083] Optionally, the judging whether the current fitting verification data satisfies the preset linear fitting condition includes: judging whether the R-square error of the rising segment data of the current fitting verification data is greater than a preset error threshold, and whether the number of signals in the rising segment data and the number of signals in the falling segment data of the current fitting verification data are both not less than the corresponding preset number thresholds; if so, it is determined that the current fitting verification data satisfies the preset linear fitting condition.

[0084] Optionally, updating the current initial second target value based on a preset update threshold value includes: adding the preset update threshold value to the current initial second target value to update the current initial second target value.

[0085] Optionally, by performing linear fitting on the rising segment data of the current fitting verification data, fitting data is obtained, and the R-squared error between the fitting data and the rising segment data of the current fitting verification data is calculated as the R-squared error of the rising segment data of the current fitting verification data.

[0086] It should be noted that the R-squared error corresponding to other data can be calculated using the above method or other existing methods, and this application does not limit this.

[0087] Optionally, the method for obtaining the second target value further includes: obtaining a preset ratio threshold, multiplying the first target value by the preset ratio threshold to obtain a product value of the two, and determining the second target value based on the product value.

[0088] Optionally, the preset ratio threshold is 50%.

[0089] In one embodiment, determining the second target value based on the product value includes: using the product value as the second target value.

[0090] In another embodiment, determining the second target value based on the product value further includes: using the product value as the initial second target value, and executing steps S22 to S23 based on the initial second target value.

[0091] It should be noted that, considering that light waves will be affected by absorption and scattering when propagating in water, resulting in a flat waveform of the descending segment data of the seabed echo data, in this embodiment, calculations are only performed based on the rising segment data of the seabed echo signal data to quickly obtain the second target value applicable to the rising segment data and the descending segment data of the seabed echo data; and, considering that the waveform of the seabed echo will be distorted by backscattering of the water body, in this embodiment, a preset error threshold is set, and the R-squared error corresponding to the seabed echo signal data in the current initial target data interval is compared with the preset error threshold to determine the second target value, so as to improve the reliability of the target data interval finally selected.

[0092] Further, in order to improve the matching degree between the target data interval and the ascending segment data and descending segment data of the seabed echo signal data, and thus improve the accuracy of the peak point obtained by the method, the second target value includes: an ascending segment second target value and a descending segment second target value; the target data interval includes: an ascending segment target data interval and a descending segment target data interval; the second target value is obtained based on the first target value and the seabed echo signal data, and the first target value and the second target value are respectively used as interval endpoints to determine the target data interval, including:

[0093] Starting from the first target value, in descending order of time, waveform linear change judgment is performed on each seabed echo signal in the ascending segment data of the seabed echo signal data, and waveform linear change judgment is performed on each seabed echo signal in the descending segment data of the seabed echo signal data, so as to obtain corresponding ascending segment waveform linear change nodes and descending segment waveform linear change nodes in the ascending segment data and descending segment data of the seabed echo signal data respectively;

[0094] Based on the linear change nodes of the rising segment waveform, the second target value of the rising segment is determined, and the first target value and the second target value of the rising segment are used as interval endpoints to determine the target data interval of the rising segment; and based on the linear change nodes of the falling segment waveform, the second target value of the falling segment is determined, and the first target value and the second target value of the falling segment are used as interval endpoints to determine the target data interval of the falling segment.

[0095] Optionally, when the target data interval includes: an ascending segment target data interval and a descending segment target data interval, when executing steps S21 to S23, the preset linear fitting conditions also include: the R-square error of the ascending segment data of the seabed echo signal data located in the ascending segment target data interval, and the R-square error of the descending segment data of the seabed echo signal data located in the descending segment target data interval are both greater than the preset error threshold.

[0096] In this embodiment, the peak point extraction method of the seabed echo saturation waveform provided by the present application obtains the second target value of the ascending segment and the second target value of the descending segment based on the ascending segment data and the descending segment data of the seabed echo signal data, respectively, and determines the ascending segment target data interval based on the first target value and the ascending segment second target value, and determines the descending segment target data interval based on the first target value and the descending segment second target value, thereby respectively obtaining the ascending segment target data interval and the descending segment target data interval that are highly matched with the ascending segment data and the descending segment data of the seabed echo signal data, so as to improve the accuracy of the extracted peak point of the seabed echo saturation waveform.

[0097] Step S3, extracting the seabed echo signal data located in the target data interval from the ascending segment data and the descending segment data of the seabed echo signal data, so as to correspond to the ascending segment target data and the descending segment target data; performing linear fitting based on the ascending segment target data and the descending segment target data, respectively, to obtain the ascending segment linear function and the descending segment linear function;

[0098] The target data interval is a data interval for performing seabed echo peak fitting in the seabed echo signal data.

[0099] Optionally, when the target data interval includes: an ascending segment target data interval and a descending segment target data interval, extracting the seafloor echo signal located in the target data interval from the ascending segment data and the descending segment data of the seafloor echo signal data, respectively, to correspond to the ascending segment target data and the descending segment target data, including:

[0100] In the ascending segment data of the seabed echo signal data, the seabed echo signal located in the ascending segment target data interval is extracted as the ascending segment target data; and in the descending segment data of the seabed echo signal data, the seabed echo signal located in the descending segment target data interval is extracted as the descending segment target data.

[0101] Step S4, obtaining the intersection point between the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data.

[0102] Optionally, after obtaining the peak point of the seabed echo signal data, the method further includes: obtaining a time point corresponding to the peak point based on the ascending segment linear function and the descending segment linear function.

[0103] Exemplarily, the time point corresponding to the peak point is calculated as follows:

[0104]

[0105] In the above formula, t p represents the time point corresponding to the peak point; b1 represents the intercept of the linear function of the rising segment; b2 represents the intercept of the linear function of the falling segment; a1 represents the slope of the linear function of the rising segment; a2 represents the slope of the linear function of the falling segment.

[0106] It should be noted that the waveform distributions of the rising segment data and the falling segment data of the seabed echo signal data both have a linear trend and are less affected by waveform saturation. In addition, due to the influence of the backscattering effect of the water body, the waveform change trend of the falling segment data is gentle due to the superposition of the water body backscattering signal, forming a waveform characteristic of a steep rising segment and a gentle falling segment, resulting in the waveform curve of the seabed echo being biased to the left, with the peak located to the left of the center of the seabed echo waveform. Since the linear trends of the rising segment and the falling segment can reflect the waveform change characteristics of the real seabed echo, the intersection point obtained by the linear function corresponding to the rising segment data and the falling segment data in the present application conforms to the characteristic of the left bias of the real peak point position of the seabed echo saturation waveform.

[0107] In order to verify the performance of the peak point extraction method of the seabed echo saturation waveform provided in this application in the problem of seabed echo saturation waveform peak point extraction, the following experiments were conducted:

[0108] Among them, in order to ensure the fairness of the results, experiments were carried out on PD, GF, EMG and the peak point extraction method of the seabed echo saturation waveform provided in this application (hereinafter referred to as "this method") under the same hardware environment and software environment. The running code of each algorithm was written in C programming language. The hardware environment used included: Lenovo workstation, including: two IntelXeon E5-2680 v4 (2.40GHz processor) and 64.0GB RAM.

[0109] The performance of each algorithm is evaluated using evaluation parameters such as MADB, MRDB and RMSE to obtain evaluation results of each algorithm. The evaluation results are specifically shown in Table 1.

[0110] Table 1

[0111]

[0112] In the above table, MADB is the mean absolute depth error, which reflects the average absolute error between the predicted depth value and the actual depth value. The smaller the value, the higher the prediction accuracy of the algorithm; MRDB is the mean relative depth error, which reflects the relative error between the predicted depth value and the actual depth value. The smaller the value, the higher the prediction accuracy of the algorithm; RMSE is the root mean square error, which measures the deviation between the predicted depth value and the actual depth value. The smaller the value, the higher the prediction accuracy of the algorithm.

[0113] See also Figure 2 , showing the comparison of the results of each algorithm for peak point extraction of the seabed echo saturation waveform at a depth of 30 meters;

[0114] like Figure 2 As shown, Figure 2 From left to right in the figure are sub-figure a, sub-figure b and sub-figure c; wherein the abscissa in each sub-figure represents time in nanoseconds (ns), the ordinate represents signal strength, and the green curve in each sub-figure is the seabed echo waveform of the shallow water channel, the blue curve is the seabed echo waveform of the deep water channel, the red curve is the fitted seabed echo waveform, the intersection point of the red dotted line and the red curve is the peak point of the fitted seabed echo waveform, and the intersection point of the green dotted line and the green curve is the peak point of the seabed echo waveform of the deep water channel. The red curves in the sub-figure a, the sub-figure b and the sub-figure c are the seabed echo waveforms fitted based on GF, EMG and the present method, respectively; Figure 2 It can be seen that at a depth of 30 meters, the seabed echo waveform of the deepwater channel is saturated, while the seabed echo waveform of the shallowwater channel is not saturated. There is a large deviation between the time point corresponding to the peak point of the seabed echo waveform fitted based on GF and EMG and the time point corresponding to the actual seabed echo peak point, which are 10ns and 6ns respectively. The deviation between the time point corresponding to the seabed echo peak point fitted by this method and the time point corresponding to the actual seabed echo peak point is only 1.7ns. In addition, in this experiment, when GF, EMG and this method are used to extract the peak points of 5000 seabed echo saturation waveforms respectively, the total extraction time corresponding to GF, EMG and this method are 12.99s, 20.65s and 0.73s respectively. It can be seen that compared with GF and EMG, this method not only improves the accuracy of the obtained seabed echo saturation waveform peak point, but also has a higher extraction efficiency for the seabed echo saturation waveform peak point, which greatly improves the speed of obtaining the seabed echo peak point.

[0115] It should be noted that, since the seabed echo of the shallow water channel has not experienced waveform saturation, the time point corresponding to the peak point of the seabed echo waveform of the shallow water channel is the time point corresponding to the peak point of the seabed echo of the deep water channel.

[0116] See also Figure 3 , shown as a scatter plot between sonar depth data and lidar depth data obtained based on various algorithms, wherein the sonar depth data is used to represent the true seabed depth;

[0117] like Figure 3 As shown, Figure 3The first row from left to right is sub-image d and sub-image e, and the second row from left to right is sub-image f and sub-image g; the algorithms for extracting the peak points of the seabed echo saturation waveform in sub-image d, sub-image e, sub-image f and sub-image g are PD, GF, EMG and this method respectively; in each sub-image, the horizontal axis represents the depth corresponding to the sonar signal, in meters (m), the vertical axis represents the depth corresponding to the lidar signal, in meters (m), RMAE_S represents the root mean square error of the predicted depth value in the depth range of 10m to 28m, RMAE_D represents the root mean square error of the predicted depth value in the depth range of 28m to 50m, R 2 R represents the predicted depth value within the depth range of 10m to 50m 2 , RMSE represents the RMSE of the predicted depth value in the depth range of 10m to 50m; Figure 2 It can be seen that compared with PD, GF and EMG, the root mean square error of the depth values ​​predicted by this method in the depth range of 10m to 50m is the smallest, which is only 0.57m, and the root mean square error of the depth values ​​predicted in the depth range of 28m to 50m is the smallest, which is only 0.56m, which further verifies the accuracy of the saturated waveform peak point extracted by the peak point extraction method provided in this application.

[0118] Above Figures 2 to 3 The displayed results demonstrate the superior performance of the method described in the present application in the problem of extracting the peak point of the seabed echo saturation waveform, and verify the accuracy of the peak point of the seabed echo saturation waveform extracted by the method described in the present application.

[0119] The above-mentioned embodiment provides a method for extracting the peak point of a seabed echo saturation waveform, by obtaining a first target value and a second target value, and determining a target data interval based on the first target value and the second target value; and based on the target data interval, extracting ascending segment target data and descending segment target data from the seabed echo signal data, performing linear fitting on the ascending segment data and the descending segment data respectively, obtaining an ascending segment linear function and a descending segment linear function, and obtaining the peak point of the seabed echo signal data based on the ascending segment linear function and the descending segment linear function, thereby improving the accuracy and efficiency of extracting the peak point of the seabed echo saturation waveform.

[0120] like Figure 4 As shown, in this embodiment, the present invention provides a peak point extraction system for a seabed echo saturation waveform, comprising:

[0121] A first target value acquisition module 201 is used to acquire a signal strength value of a maximum undistorted signal of a seabed echo signal receiving device, and acquire a first target value based on the signal strength value of the maximum undistorted signal;

[0122] The second target value acquisition module 202 is used to acquire seabed echo signal data; based on the first target value and the seabed echo signal data, a second target value is obtained, and the first target value and the second target value are respectively used as interval endpoints to determine a target data interval; the target data interval is a data interval within which the seabed echo signal data meets a preset linear fitting condition; the seabed echo signal data is a time series distribution of the signal strength value of the seabed echo signal;

[0123] The linear fitting module 203 is used to extract the seafloor echo signal located in the target data interval from the ascending segment data and the descending segment data of the seafloor echo signal data, so as to correspond to the ascending segment target data and the descending segment target data; perform linear fitting based on the ascending segment target data and the descending segment target data, respectively, to obtain the ascending segment linear function and the descending segment linear function;

[0124] The peak point extraction module 204 is used to obtain the intersection point between the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data.

[0125] like Figure 5 As shown, in this embodiment, the preset linear fitting condition includes: the R-square error of the rising segment data of the seabed echo signal data located in the target data interval is greater than the preset error threshold, and the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data located in the target data interval are not less than the preset number threshold; the second target value acquisition module also includes:

[0126] The initial second target value acquisition submodule 2021 is used to acquire the signal strength value corresponding to the waveform linear change node as the initial second target value;

[0127] The fitting verification data determination submodule 2022 is used to determine the current initial target data interval based on the first target value and the current initial second target value, and obtain data located in the current initial target data interval from the seabed echo signal data as the current fitting verification data;

[0128] The second target value optimization acquisition submodule 2023 is used to determine whether the current fitting verification data meets the preset linear fitting condition. If not, based on the preset update threshold, the current initial second target value is updated to re-execute the fitting verification data determination and the second target value acquisition; if so, the current initial second target value is used as the second target value.

[0129] like Figure 6As shown, in this embodiment, the present invention provides a peak point extraction terminal for a seabed echo saturation waveform, the peak point extraction terminal 300 includes a memory 301 and a processor 302, the memory 301 is used to store a computer program; the processor 302 is used to execute the computer program stored in the memory 301, so that the peak point extraction terminal 300 executes the peak point extraction method for a seabed echo saturation waveform of any of the above embodiments of the present application. Since the specific implementation process of the steps of the peak point extraction method for a seabed echo saturation waveform has been described in detail in the above embodiments, it will not be repeated here.

[0130] The memory 301 includes: ROM (Read Only Memory image), RAM (Random Access Memory), a disk, a USB flash drive, a memory card, or an optical disk, etc., which can store program codes.

[0131] The processor 302 is connected to the memory 301 and is used to execute the computer program stored in the memory 301 so that the peak point extraction terminal 300 executes the above peak point extraction method.

[0132] Preferably, the processor 302 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0133] The present application embodiment also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiment can be completed by a program to instruct the processor, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state hard disk (SSD)), etc.

[0134] The present application embodiment may also provide a computer program product, the computer program product including one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the process or function described in the embodiment of the present application is generated in whole or in part. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer or data center.

[0135] When the computer program product is executed by a computer, the computer executes the method described in the above method embodiment. The computer program product may be a software installation package, and when the above method is required, the computer program product may be downloaded and executed on a computer.

[0136] The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0137] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for extracting the peak point of a seafloor echo saturation waveform, characterized in that: The method comprises: Acquire a maximum undistorted signal of a seabed echo signal receiving device, and acquire a first target value based on a signal strength value of the maximum undistorted signal; Acquire seabed echo signal data; obtain a second target value based on the first target value and the seabed echo signal data, and use the first target value and the second target value as interval endpoints to determine a target data interval; the target data interval is a data interval within which the seabed echo signal data meets a preset linear fitting condition; the seabed echo signal data is a time series distribution of signal strength values ​​of the seabed echo signal; Extracting seafloor echo signals located in the target data interval from the ascending segment data and the descending segment data of the seafloor echo signal data respectively, so as to correspond to the ascending segment target data and the descending segment target data; performing linear fitting based on the ascending segment target data and the descending segment target data respectively, and correspondingly obtaining the ascending segment linear function and the descending segment linear function; Obtaining the intersection point between the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data; The preset linear fitting condition includes: the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data within the target data interval are not less than the corresponding preset number thresholds; the obtaining of the second target value based on the first target value and the seabed echo signal data includes: Starting from the first target value, in descending time order, waveform linear change judgment is performed on each seabed echo signal in the rising segment data of the seabed echo signal data, so as to obtain a waveform linear change node in the rising segment data of the seabed echo signal data, and determine the second target value based on the waveform linear change node; Wherein, the second target value is greater than or equal to the signal strength value corresponding to the waveform linear change node; The waveform linear change node is the first seabed echo signal that satisfies the waveform linear change judgment in descending time order in the rising segment data of the seabed echo signal data.

2. The method according to claim 1, characterized in that The implementation method of the waveform linear change judgment includes: Calculate the tangent slope corresponding to the seabed echo signal at the current moment, and determine whether the tangent slope is less than a preset slope threshold. If so, determine that the seabed echo signal at the current moment meets the waveform linear change judgment, and obtain the seabed echo signal at the current moment as the waveform linear change node.

3. The method according to claim 1, characterized in that: The determining of the second target value based on the waveform linear change node comprises: The signal strength value corresponding to the waveform linear change node is obtained as the second target value.

4. The method according to claim 1, characterized in that: The preset linear fitting condition also includes: the R-square error of the rising segment data of the seabed echo signal data located in the target data interval is greater than a preset error threshold; the second target value is determined based on the waveform linear change node, including: Initial second target value acquisition: obtain the signal strength value corresponding to the waveform linear change node as the initial second target value; Fitting verification data determination: based on the first target value and the current initial second target value, determining the current initial target data interval, and acquiring data located in the current initial target data interval from the seabed echo signal data as the current fitting verification data; Acquisition of the second target value: determine whether the current fitting verification data meets the preset linear fitting condition; if not, update the current initial second target value based on the preset update threshold to re-execute the fitting verification data determination and acquisition of the second target value; if so, use the current initial second target value as the second target value.

5. A peak point extraction system for seabed echo saturation waveform, characterized in that: The system comprises: A first target value acquisition module, used to acquire a maximum undistorted signal of a seabed echo signal receiving device, and acquire a first target value based on a signal strength value of the maximum undistorted signal; The second target value acquisition module is used to acquire seabed echo signal data; based on the first target value and the seabed echo signal data, a second target value is acquired, and the first target value and the second target value are respectively used as interval endpoints to determine a target data interval; the target data interval is a data interval in which the seabed echo signal data within the interval meets a preset linear fitting condition; the seabed echo signal data is a time series distribution of signal strength values ​​of the seabed echo signal; the preset linear fitting condition includes: the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data within the target data interval are both not less than the corresponding preset number thresholds; the acquisition of the second target value based on the first target value and the seabed echo signal data includes: Starting from the first target value, in descending time order, waveform linear change judgment is performed on each seabed echo signal in the rising segment data of the seabed echo signal data, so as to obtain a waveform linear change node in the rising segment data of the seabed echo signal data, and determine the second target value based on the waveform linear change node; Wherein, the second target value is greater than or equal to the signal strength value corresponding to the waveform linear change node; The waveform linear change node is the first seabed echo signal that satisfies the waveform linear change judgment in descending time order in the rising segment data of the seabed echo signal data; A linear fitting module is used to extract the seabed echo signal located in the target data interval from the ascending segment data and the descending segment data of the seabed echo signal data, respectively, to correspond to the ascending segment target data and the descending segment target data; perform linear fitting based on the ascending segment target data and the descending segment target data, respectively, to obtain the ascending segment linear function and the descending segment linear function; The extraction module is used to obtain the intersection point between the ascending segment linear function and the descending segment linear function as the peak point of the seabed echo signal data.

6. The system according to claim 5, characterized in that The preset linear fitting condition includes: the R-square error of the rising segment data of the seabed echo signal data located in the target data interval is greater than the preset error threshold, and the number of signals in the rising segment data and the number of signals in the falling segment data of the seabed echo signal data located in the target data interval are not less than the preset number threshold; the system also includes: An initial second target value acquisition submodule is used to acquire a signal strength value corresponding to a waveform linear change node as an initial second target value; A fitting verification data determination submodule is used to determine a current initial target data interval based on the first target value and the current initial second target value, and obtain data located in the current initial target data interval from the seabed echo signal data as current fitting verification data; The second target value optimization acquisition submodule is used to determine whether the current fitting verification data meets the preset linear fitting condition. If not, based on the preset update threshold, the current initial second target value is updated to re-execute the fitting verification data determination and the second target value acquisition; if so, the current initial second target value is used as the second target value.

7. A terminal for extracting the peak point of a seabed echo saturation waveform, characterized in that: The terminal comprises: Memory for storing computer programs; A processor, configured to execute the computer program stored in the memory, so that the terminal executes the method according to any one of claims 1 to 4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed, the method according to any one of claims 1 to 4 is implemented.

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