A method for detecting a side scan sonar bottom line

Abstract

The present application relates to the technical field of sonar, in particular to a detection method of side scan sonar seabed line. The process of the method is as follows: firstly, acquiring real-time echo signal data of left and right sides of the side scan sonar; then, updating detection parameters of the left and right sides according to the echo signal data; then, detecting the height from the bottom of the left and right sides respectively; judging whether the height from the ground of the left and right sides is symmetrical or not, and correcting the wrong data; obtaining the height from the ground of the left and right sides of the current frame, smoothing the result, and outputting the seabed line tracking result, wherein the smoothing method adopts median filtering method or Kalman filtering method or delay filtering method. The method of the present application can accurately detect the seabed line result in real time instead of post-processing based on the side scan sonar image, can be used for wet end bottom touch early warning, and can provide a basis for real-time slant range correction of the side scan sonar image, image equalization, target real size measurement and real-time inlay of the acoustic image.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonar, in particular to a detection method of a side scan sonar seabed line. BACKGROUND

[0002] The side scan sonar is a slant range imaging mode, and there is a "water column area" on the acoustic image. The obvious boundary line on both sides of the "water column area" is the seabed line. The seabed line reflects the height change of the wet end of the side scan sonar during the movement process and the topography of the high and low undulating seabed. It can be used for wet end bottom warning, and is also the basis for subsequent slant range correction, image equalization, target geometric feature measurement and acoustic image inlay. The existing seabed line detection method is usually carried out during image post-processing. The main methods include edge detection based on image edge technology, neural network model detection method and threshold method. The side scan sonar is a kind of image sonar and is the main equipment for topographic surveying. It has the advantages of high resolution, continuous acquisition of two-dimensional seabed image and low price. It is widely used in fields such as marine surveying and mapping, marine geological survey, marine engineering exploration, underwater search and rescue, underwater archaeology and marine military. The side scan sonar first transmits a short acoustic pulse. The acoustic wave propagates outward in the form of a spherical wave. When it encounters the seabed or a target object in the water, it will produce scattering. The return time of the reflected scattering wave is arranged in turn to form a scanning line. The intensity and time of the reflected scattering wave reflect the position, material, topography and other seabed information of the scattering point. Each scanning line is arranged in a line-by-line manner to form a seabed topographic acoustic image. The acoustic image and the seabed plane have a point-by-point mapping relationship. The brightness of the acoustic image contains the characteristics of the seabed topography and the target. The detection of the seabed line of the side scan sonar is mainly carried out during the post-processing of the sonar image. The main methods include the following three schemes: one is to detect the seabed line based on the edge detection technology of the image. This detection method has high requirements for the quality of the acoustic image and has problems such as large amount of calculation and inability to detect in real time. Another method is to detect the seabed line based on a neural network. Through a pre-trained model, real-time detection of the seabed line is realized. However, due to the complex seabed conditions and the difficulty in obtaining actual measurement data of the side scan sonar, the amount of data used for training the model is small, which reduces the accuracy of the model detection result. Moreover, this method also has the problem of large calculation. The last method is the threshold method, which compares the echo signal with the threshold to determine the position of the seabed line. The threshold is usually set by engineers based on experience. Later, a semi-automatic threshold setting method was developed. However, all these methods are based on post-processing. The threshold method can realize real-time detection of the seabed line, but it is easily affected by the wake, waves, suspended matter in the water, fish and underwater noise, and has the problem of low detection result accuracy.

[0003] As described above, the existing seabed line detection method has the problems of poor real-time performance and low accuracy. Therefore, there is an urgent need for a side scan sonar seabed line detection method that can realize real-time detection with high accuracy. SUMMARY

[0004] The present application aims at providing a real-time high-precision seabed line detection method.

[0005] In view of the deficiencies of the prior art, the present application solves the technical problems by employing the technical scheme of a side-scan sonar seabed line detection method, comprising the following steps,

[0006] 1. Acquire side-scan sonar left and right side real-time echo signal data, the echo signal data comprising left and right side quadrature demodulation I and Q signals and ADC sampling signals;

[0007] 2. Update left and right side detection parameters, update the detection parameters according to the working parameters of the ADC sampling signals and the detection results of the previous frame;

[0008] 3. Detect the left and right side off-bottom heights respectively;

[0009] 4. Judge whether the left and right side off-ground heights are symmetrical, and correct the wrong data;

[0010] 5. Obtain the current frame left and right side off-ground heights, smooth the results, and output the seabed line tracking results.

[0011] Preferably, the process of the detection parameter initialization in step 2 is,

[0012] start_point = pluse_width * fs;

[0013] end_point = (work_range-5) / c*fs;

[0014] threshold1 = threshold0;

[0015] In the formula, start_point is a seabed line searching starting point, end_point is a seabed line searching ending point, pluse_width is a side-scan sonar signal pulse width, fs is a sampling rate, work_range is a side-scan sonar working range, c is a sound speed, and threshold0 is an initial threshold value.

[0016] Detection parameter update:

[0017] start_point = (edge0-d0)*2 / c*fs;

[0018] end_point = (edge0+d0)*2 / c*fs;

[0019]

[0020] In the formula, edge0 is the detected height from the ground in the previous frame, d0 is the maximum fluctuation range of the height from the ground in the adjacent two frames, d0 is preset, S0 is the echo signal of the previous frame of the current detected side (left or right side).

[0021] Preferably, the specific content of step 3 is as follows,

[0022] 3.1 Obtain the detection parameters, the size of the sliding window N, the amplitude threshold threshold1, the continuous parameter threshold threshold2, the sea bottom height fluctuation threshold threshold3, and the left and right side parameters are independent;

[0023] 3.2 Start searching the sea bottom line from the search starting point start_point, and search the sea bottom line height until edge=edge0 is searched, edge0 being the detection result of the previous frame of the side;

[0024] 3.3 Compare the average echo intensity data_ave of the echo signal in the sliding window with the threshold threshold1, and the average echo intensity of the nth point signal is calculated according to the formula:

[0025]

[0026] Wherein, S(n) is the echo signal of the current detected side (left or right side), N is the size of the sliding window,

[0027] If data_ave(n)>threshold1, then step 3.4 is entered, otherwise the sliding window is slid by one point and step 3.3 is repeated;

[0028] 3.4 Determine the number n2 of points in the sliding window whose echo intensity is greater than threshold2, and n2 is obtained as follows:

[0029]

[0030] If n2 is greater than N2, then step 3.5 is entered, otherwise the sliding window is slid by one point and step 3.3 is repeated, N2 being the threshold value of the number of sampling points in the sliding window whose echo intensity is greater than threshold1, and N2 being preset in advance;

[0031] 3.5 Determine the difference between the current point n and the last detected sea bottom line edge0 and threshold3, if the difference between the current point n and the last detected sea bottom line edge0 is greater than threshold3, then the sea bottom line detection result of the frame of the side is edge=n.

[0032] Preferably, step 4 sets error threshold4 in left and right side ground clearance data correction, threshold4 is set based on wet end attitude, noise and seafloor topography factors, threshold4 = 0.03*(edge_left0+edge_right0), edge_left0 and edge_right0 are respectively the average of left side seafloor line detection result, which can be updated by sliding average.

[0033] Preferably, step 5 uses median filter method or Kalman filter method or delay filter method.

[0034] The present application has the following advantages: real-time and accurate detection of seafloor line result instead of post-processing based on side scan sonar image, which can be used for wet end bottom touch early warning, and provides basis for real-time slant range correction of side scan sonar image, image equalization, target real size measurement and real-time sound image inlay. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 is a flow chart of the method of the present application;

[0036] Figure 2 is a process chart of step 3 in the method of the present application;

[0037] Figure 3 is a seafloor line detection chart without using the method of the present application;

[0038] Figure 4 is a seafloor line detection chart using the method of the present application. DETAILED DESCRIPTION

[0039] The present application will be further described with reference to the drawings and specific embodiments. The embodiments of the present application are given for illustrative and descriptive purposes only and are not exhaustive or limiting of the present application. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are chosen and described in order to best explain the principles of the present application and its practical application and to enable others skilled in the art to understand the present application for various embodiments with various modifications as are suited to the particular use contemplated.

[0040] The present application aims at the problems of poor real-time performance and low precision of existing submarine cable detection methods, and provides a real-time high-precision submarine cable detection method. The submarine cable echo signal is the intersection point of the water column area and the submarine area, and has the characteristics of mutation. However, the water column area echo signal may also have mutation due to factors such as suspended matter, fish, waves and underwater noise. After the mutation of the water column area echo signal, the average energy of the sliding window and the number of points greater than the threshold value in the sliding window are used for submarine cable detection. And based on the fact that the submarine cable does not mutate, the abnormal points are removed. After the left and right submarine cable detection is completed, the abnormal points are further removed according to the principle of left-right symmetry of the submarine cable and the attitude of the side-scan sonar. Finally, Kalman filtering, median filtering and other methods are used to smooth the results.

[0041] The method of the present application comprises the following processes:

[0042] 1. Obtain the real-time echo signal data of the left and right sides of the side-scan sonar, which is usually the I and Q signals of the left and right sides of the quadrature demodulation, denoted as I L , Q L , I R and Q R , which can also be ADC sampling signals, and synchronously obtain the working parameters of the sonar such as working frequency, signal form, pulse width, bandwidth and action distance; attitude data such as roll, pitch and yaw, for the form of the transmitted signal, which is a CW signal:

[0043]

[0044] For the form of the transmitted signal, which is an LFM signal:

[0045] S R = conv (I R +i*Q R , S lfm )

[0046] S L = conv (I L +i*Q L , S lfm )

[0047] Wherein, S R is the right echo signal, S L is the left echo signal, i is the imaginary unit, I R is the I channel signal of the right side of the quadrature demodulation, Q R is the Q channel signal of the right side of the quadrature demodulation, Q L is the Q channel signal of the left side of the quadrature demodulation, I L is the I channel signal of the left side of the quadrature demodulation, and S lfm is the transmitted signal, S lfmIt can be generated according to pulse width, working frequency, bandwidth and other parameters, or obtained through actual measurement data, and conv represents the convolution of two signals;

[0048] 2. Update the left and right side detection parameters, specifically update the detection parameters according to the working parameters of the side scan sonar and the detection results of the previous frame:

[0049] Detection parameter initialization:

[0050] start_point = pluse_width * fs;

[0051] end_point = (work_range-5) / c*fs;

[0052] threshold1 = threshold0;

[0053] In the formula, start_point is the seabed line search starting point, end_point is the seabed line search ending point, pluse_width is the side scan sonar signal pulse width, fs is the sampling rate, work_range is the side scan sonar working range, c is the sound speed, threshold0 is the initial threshold value, which is preset, for example, 8-bit signal can be set to 5-20.

[0054] Detection parameter update:

[0055] start_point = (edge0-d0)*2 / c*fs;

[0056] end_point = (edge0+d0)*2 / c*fs;

[0057]

[0058] In the formula, edge0 is the detection height above the ground of the previous frame, d0 is the maximum fluctuation range of the height above the ground of the adjacent two frames, d0 is preset, and S0 is the echo signal of the previous frame of the current detection side (left and right side);

[0059] 3. Detect the height above the bottom of the left and right sides respectively, and the detection process is as shown in Figure 2 , and the specific steps are as follows:

[0060] 3.1 Obtain the detection parameters, the sliding window size N, the amplitude threshold threshold1, the continuous parameter threshold threshold2, the seabed height fluctuation threshold threshold3, and the left and right side parameters are independent;

[0061] 3.2 Starting from the search starting point start_point, search the seabed line point by point until the seabed line height is searched, if edge = edge0, edge0 is the detection result of the side of the last frame;

[0062] 3.3 The average echo intensity data_ave of the echo signal in the sliding window is compared with the threshold threshold1, in order to avoid that the target in the water column area is misidentified as the seabed line in the threshold method, the average echo intensity data_ave of the echo signal in the sliding window is compared with the threshold threshold1, the average echo intensity calculation formula of the nth point signal is:

[0063]

[0064] Wherein, S(n) is the echo signal of the current detection side (left and right side), N is the size of the sliding window,

[0065] If data_ave(n)>threshold1, then step 3.4 is entered, otherwise the sliding window slides one point and step 3.3 is repeated;

[0066] 3.4 The number n2 of points in the sliding window whose echo intensity is greater than threshold2 is judged, in order to avoid that the target with large target intensity in the sliding window leads to misjudgment, the number n2 of points in the sliding window whose echo intensity is greater than threshold2 is further judged, and the acquisition method of n2 is as follows:

[0067]

[0068] If n2 is greater than N2, then step 3.5 is entered, otherwise the sliding window slides one point and step 3.3 is repeated, N2 is the threshold value of the number of sampling points in the sliding window whose echo intensity is greater than threshold1, and N2 is preset in advance;

[0069] 3.5 The difference between the current point n and the last detected seabed line edge0 is judged with threshold3, the water depth and the side scan sonar towing depth are gradually changed, so the seabed line height is also gradually changed, whether the difference between the current point n and the last detected seabed line edge0 is greater than threshold3 is judged, if it is greater than threshold3, it is considered that the seabed line detection result of the side of the frame is edge = n;

[0070] 4. Determine if the left and right side clearance heights are symmetrical, and correct the wrong data: the left and right side transducers of the wet end of the side scan sonar are symmetrically installed and have a small distance, and the echo signals of the seabed line are all from the wet end directly below. The heights of the left and right seabed lines should theoretically be equal, but considering the influence of the wet end attitude, noise and seabed topography, a certain error threshold4 is allowed to exist between the two, which can be taken as 0.03*(edge_left0+edge_right0), edge_left0 and edge_right0 are the average values of the left seabed line detection results, which can be updated by moving average. Further consideration can be given to the influence of the wet end attitude on the error. If the detection results of the left and right sides abs(edge_left-edge_right)>threshold4, edge_left and edge_right are the left and right seabed lines detected in step 3, respectively, the detection results of the left and right sides are compared with the average values of the detection results of the left and right sides of the previous frame, respectively, and the result of the side with larger deviation is corrected to the average value of the detection results of the left and right sides of the previous frame;

[0071] 5. Get the left and right side clearance heights of the current frame, smooth the results, and output the seabed line tracking results: the seabed line detection results of the left and right sides are smoothed respectively to eliminate abnormal points and improve the accuracy of the detection results. The smoothing method can be median filtering, Kalman filtering and delay filtering, etc. Taking Kalman filtering as an example, the detection results are updated by the following formula,

[0072] kalman_edge k|k-1 =A*kalman_edge k-1 +w k-1

[0073] P k|k-1 =AP k-1 A T +Q

[0074] K k =P k|k-1 H T (HP k|k-1 H T +R) -1

[0075] kalman_edge k =kalman_edge k|k-1 +K k (edge k -H*kalman_edge k|k-1 )

[0076] P k =(I-K k H)P k|k-1

[0077] where kalman_edge k|k-1 is the seabed line state of the current frame according to the previous state prediction, kalman_edge k is the result of the Kalman filtering of the kth frame, A is the transition matrix, P k|k-1 is the predicted system covariance of the kth frame, P k is the system covariance of the kth frame, the matrix H is the prediction matrix of the object, w k-1 is the state noise, K k is the Kalman gain, R is the covariance matrix of the measurement noise, Q is the covariance of the system process noise, I is the unit matrix, edge k is the seabed line result detected in step 4, T represents the matrix transpose.

[0078] Figure 3 is the detection result obtained by using the threshold method and smoothing the result, since the water column area exists, the seabed line has detection errors caused by the target, Figure 4 is the detection method provided by the present application, has the advantages of small calculation amount, high detection precision, etc., can detect the seabed line in real time and accurately, can be used for wet end bottom touch early warning, and provides the basis for real-time slant range correction of side scan sonar image, image equalization, real size measurement of the target and real-time inlay of the acoustic image.

Claims

1. A method of detecting a side scan sonar seabed line, characterized by: The method comprises the following steps, Step 1. Acquiring side-scan sonar left and right side real-time echo signal data, the echo signal data comprising left and right side quadrature demodulation I and Q signals and ADC sampling signals; Step 2. Updating left and right side detection parameters, updating the detection parameters according to ADC sampling signal working parameters and last frame detection results; Step 3. Detecting left and right side heights from the ground respectively; Step 4. Judging whether the left and right side heights from the ground are symmetrical, and correcting wrong data; Step 5. Obtaining current frame left and right side heights from the ground, smoothing the results, and outputting seabed line tracking results; The process of detection parameter initialization in step 2 is as follows, start_point=pluse_width×fs; end_point=(work_range-5) / c×fs; threshold1=threshold0; In the formula, start_point is a seabed line searching starting point, end_point is a seabed line searching ending point, pluse_width is a side-scan sonar signal pulse width, fs is a sampling rate, work_range is a side-scan sonar working range, c is a sound speed, and threshold0 is an initial threshold value; Detection parameter updating: start_point=(edge0-d0)×2 / c×fs; end_point=(edge0+d0)×2 / c×fs; ； In the formula, edge0 is the height from the ground in the last frame, d0 is the maximum fluctuation range of the height from the ground in adjacent two frames, and d0 is preset, is the last frame echo signal of the current detected side. The specific content of step 3 is as follows, Step 3.1 Acquiring detection parameters, a sliding window size N, an amplitude threshold value threshold1, a continuous parameter threshold value threshold2, a seabed height fluctuation threshold value threshold3, and left and right side parameters being independent; Step 3.2 Starting to search for a seabed line from the searching starting point start_point, and searching until the seabed line height is searched, if not, edge=edge0, and edge0 is a detection result of the side in the last frame; Step 3.3 Comparing the average echo intensity data_ave(n) of the echo signal in the sliding window with the threshold value threshold1, and the average echo intensity calculation formula of the nth point signal is as follows: ， wherein, S(n) is the current detected side echo signal, N is the size of the sliding window ， If data_ave(n)>threshold1, step 3.4 is entered, otherwise, the sliding window is slid by one point, and step 3.3 is repeated; Step 3.4 Judging the number n2 of points in the sliding window whose echo intensity is greater than threshold2, and the number n2 is acquired in the following way: ； If n2 is greater than N2, step 3.5 is entered, otherwise, the sliding window is slid by one point, and step 3.3 is repeated, N2 is a threshold value of the number of sampling points in the sliding window whose echo intensity is greater than threshold2, and N2 is preset in advance; Step 3.5 Judging the difference between the current point n and the last detected seabed line edge0 and the threshold value threshold3, if the difference between the current point n and the last detected seabed line edge0 is greater than threshold3, it is considered that the seabed line detection result of the side in the frame is edge=n.

2. The method of detecting a side scan sonar seabed line according to claim 1, characterized in that: In step 4, the error threshold4 is set for the left and right side ground clearance data correction, which is based on the wet end attitude, noise and seabed terrain factors, threshold4 = 0.03 x (edge_left0 + edge_right0), edge_left0 and edge_right0 are the average values of the left and right side seabed line detection results, which are updated by sliding average.

3. The method of detecting a side scan sonar seabed line of claim 1, wherein: In step 5, the smoothing method is median filtering method or Kalman filtering method or delay filtering method.

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