CN113848556B - Rapid extraction method for water depth range based on multi-beam sounding sonar wave beam image - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
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Abstract
The invention aims to provide a rapid extraction method of a water depth range based on a multi-beam sounding sonar wave beam image, and the extracted depth result can be used for real-time control of working parameters of a multi-beam sounding sonar system, particularly upper and lower limits of depth. The multi-beam system collects the signal echoes of each channel, and a beam image is obtained through beam forming after analog-digital conversion. In order to suppress side lobe leakage of the submarine direct wave and to realize noise suppression, the beam image needs to be preprocessed. And randomly selecting K positions in the beam image as the starting positions of the search points, updating the result matrix by comparing the sizes of the adjacent elements, and updating the positions of the search points until the iteration is stopped. To obtain an accurate depth range, it is necessary to perform a second fit to the extracted depth coordinates of the search points and reject potential outliers. The method is used for processing the whole wave beam image, the extraction result is not influenced by the threshold parameter, and the processing speed is high.
Description
Technical Field
The invention relates to an image processing and signal extraction technology, in particular to a water depth range rapid extraction method based on a multi-beam sounding sonar wave beam image.
Background
The multi-beam system plays an important role in airway measurement and submarine topography drawing, measurement parameters need to be controlled manually in the offshore measurement operation process, one of the most important parameters is the upper and lower limits of depth, and in addition, the other parameters such as power, ping rate, pulse width and the like need to be determined by consulting depth information. While the multi-beam sounding sonar system can acquire depth information in real time, the following problems exist:
(1) The arrangement of the upper and lower limits of the depth ensures that the terrain to be detected is positioned between depth thresholds, but the upper and lower limit difference cannot be set too large in order to capture the effective terrain, because the system obtains accurate sounding results on the premise that the upper and lower limits of the depth are set reasonably, the too large depth difference between the upper and lower limits can lead to the increase of the system operation amount on the one hand, the inaccuracy of the measurement results can be caused on the other hand, and the introduction of secondary echoes, bubbles caused by water surface vessels and fish shoals in the section can all cause the generation of false targets.
(2) The depth result of the multi-beam system is changed along with the terrain, and once the upper and lower limits of the depth are improperly adjusted, error scattered points can occur, and if the depth result is used for determining the depth threshold, the error judgment can be caused.
(3) The depth results of the multi-beam system are sequentially resolved according to the beam sequence, the calculation method fully excavates the useful information of each beam and adjacent beams, and if the depth results are used for determining the depth threshold, the analysis of the whole beam pattern is lacking, and the threshold is greatly influenced by individual beams.
Therefore, a method for rapidly extracting the depth range of the beam signal is required to be developed, the method is different from an accurate depth analysis method with complex operation, the defect of determining a depth threshold according to a depth result is overcome, and the method is applied to systems such as an unmanned platform and the like to control the upper and lower limits of the depth in real time so as to realize parameter autonomous control.
Disclosure of Invention
The depth range extraction method is applied to depth upper and lower limit control, and therefore does not need accurate depth values of each point, but focuses on rapid extraction of an effective depth range in the whole wave beam signal, and meanwhile, considers the relation between wave beams. In order to accurately acquire the depth range, the starting position of the search point can select the currently resolved multi-beam sounding result so that the algorithm can quickly search to the vicinity of the measurement result.
Preferably, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image comprises the following steps:
s1: preprocessing a beam image in order to inhibit sidelobe leakage of the submarine direct wave and realize noise suppression;
Preferably, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image is that in step S2, all wave beams X (n) corresponding to each sampling point n in the wave beam matrix X M×N are processed as follows:
XM×N＝[x1(n),x2(n),…,XM(n)]T
RM×N＝[r1(n),r2(n),…,rM(n)]T
Wherein: m and N are respectively the total number of the preformed beams and the total number of the sampling points formed by the beams, X m (N) is the value of the mth beam of X at the nth sampling point time, R m (N) is obtained after processing, and R is the beam matrix after preprocessing.
S2: creating a result matrix R p with the same scale as the beam matrix X, and randomly selecting K positions as search point starting positions; continuously updating the result matrix and updating the position of the search point by comparing the sizes of surrounding elements until the iteration stops;
preferably, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image, S2 comprises the following steps:
21, creating a result matrix R p with the same scale as the beam matrix X and setting all elements to zero;
Initializing K searching starting points for a beam image matrix R;
And 23, iteratively updating the search point positions to obtain a result matrix R p.
Preferably, the position of each search point in the matrix R p in step S2 is recorded as (i, j), the distribution range is 1.ltoreq.i.ltoreq.m, 1.ltoreq.j.ltoreq.n, the abscissa of the search points is uniformly distributed in different beams, the starting point of the ordinate selects the vicinity of the sampling point corresponding to the depth result of the previous frame, and if the result of the previous frame does not exist, the position of the ordinate is randomly selected.
Preferably, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image is characterized in that in step S2, updating iteration of the corresponding abscissa in the horizontal and vertical directions is divided into two cases according to whether the search point is at the boundary, when the search point is at the boundary, the search point moves into the boundary, and when the search point is outside the boundary, the search point moves leftwards and rightwards or upwards and downwards by one lattice with the same probability. Meanwhile, the temperature of the system at the moment T is reduced to T (T) according to T (T) =T (0)/log 2 (T), wherein T (0) is the initial temperature of the system, T (0) =max (R) -min (R), the iteration termination condition is a set threshold T t, if T (T) < T t, the iteration is terminated, at the moment, the average value T r＝(t1,t2,...,tN of each column of R p is taken as the threshold, and elements of each column of R p smaller than the threshold are sequentially set to 0.
S3: and determining the window length according to the number of the beams, performing secondary fitting on the depth coordinate values, and removing potential depth abnormal values to obtain a final depth range extraction result.
Preferably, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image, S3 comprises the following steps:
31: all non-0 elements in the matrix R p are extracted and coordinate transformed.
32: And eliminating abnormal values of all coordinate results in the depth range.
Preferably, the step 32 in S3 performs sliding quadratic fitting on the coordinates x and y of all horizontal and vertical distances and eliminates the outlier to obtain the final depth range information based on the fast extraction method of the water depth range of the multi-beam sounding sonar wave beam image.
The invention has the beneficial effects that:
The rapid extraction method of the water depth range based on the multi-beam sounding sonar wave beam image is improved based on a ridge line extraction method, so that an algorithm can extract depth results in a non-single direction aiming at wave beam signals, the wave beam signals acquired in real time are processed by starting with depth upper and lower limit parameter control, preprocessing is carried out by restraining direct wave side lobe leakage, a current system depth measurement result is used as a search point starting position, depth information is extracted by determining a search rule, and the obtained coordinate results containing the depth range are subjected to secondary fitting to remove abnormal values so as to obtain a final depth estimation result. The algorithm can be used for real-time control of the upper and lower threshold parameters of the depth in the multi-beam system, and the reliability of the depth range result for parameter control is ensured by taking the complete beam signal as a processing object and setting rules of search points.
Drawings
FIG. 1 is a flow chart of a method for rapidly extracting a water depth range based on a multi-beam sounding sonar beam image;
FIG. 2 is a three-dimensional view of an original beam signal to be processed;
FIG. 3 is a three-dimensional view of a preprocessed beam after direct side lobe leakage suppression and noise suppression;
FIG. 4 is a two-dimensional plot of the depth result extracted beam sample point coordinates;
FIG. 5 is a depth result and detected outliers in a coordinate system after homing;
fig. 6 is the final depth range extraction result.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
The purpose of the invention is realized in the following way:
As shown in fig. 1, the overall schematic block diagram of the method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image comprises the following steps:
s1: preprocessing a beam image in order to inhibit sidelobe leakage of the submarine direct wave and realize noise suppression;
S2: creating a result matrix R p with the same scale as the beam matrix X, and randomly selecting K positions as search point starting positions; continuously updating the result matrix and updating the position of the search point by comparing the sizes of surrounding elements until the iteration stops;
S3: and determining the window length according to the number of the beams, performing secondary fitting on the depth coordinate values, and removing potential depth abnormal values to obtain a final depth range extraction result.
S1 comprises the following steps:
All beams X (n) corresponding to each sampling point n in the beam matrix X M×N are processed as follows:
XM×N＝[x1(n),x2(n),…,XM(n)]T
RM×N＝[r1(n),r2(n),…,rM(n)]T
Wherein: m and N are respectively the total number of the preformed beams and the total number of the sampling points formed by the beams, X m (N) is the value of the mth beam of X at the nth sampling point time, R m (N) is obtained after processing, and R is the beam matrix after preprocessing.
S2 comprises the following steps:
21-creating a result matrix R p which has the same scale as the beam matrix X and setting all elements to zero;
Initializing K searching starting points for the beam image matrix R, wherein K is 5-8 times of M, the horizontal coordinates of the searching points are uniformly distributed in different beams, the vertical coordinate starting points are near sampling points corresponding to the depth result of the previous frame, and if the depth result of the previous frame does not exist, the vertical coordinate positions are randomly selected.
And 23-iteratively updating the search point positions to obtain a result matrix R p.
The updating of the corresponding abscissa i in the vertical direction is divided into two cases, when the search point is not on the boundary, that is 1<i < M, the search point is moved up or down by one lattice with the same probability P, that is, P { i ' =i+1 } =p { i ' =i-1 } =0.5, where i ' is the updated abscissa; when the search points are on the upper and lower boundaries, they are caused to move in opposite directions by one lattice, i.e., when the upper boundary i=1, move downward by one lattice i '=2, and when the lower boundary i=m, move downward by one lattice i' =m-1;
The updating method of the corresponding ordinate j in the horizontal direction is the same as that of the abscissa, when the search point is not on the boundary, namely 1 < j < N, the search point is moved leftwards or rightwards by one lattice with the same probability, namely P { j '=j+1 } =P { j' =j-1 } =0.5; wherein j' is the updated ordinate; when the search points are on the left and right boundaries, they are made to move one cell in the opposite direction, i.e., when the left boundary j=1, move one cell j '=2 to the right, and when the right boundary j=n, move one cell j' =n-1 to the left;
then, the values before and after updating are examined, the abscissa after updating is first kept unchanged, and the following variables are calculated in consideration of the updated ordinate positions, i.e., (i ', j) and (i', j '), if R (i', j ') < R (i', j):
Pr＝rand(0,I)
P t is the updated difference, P r =rand (0, 1) is a random number between 0 and 1, comparing the sizes of P t and P r, and updating according to the following formula:
T(t)＝T(0)/log2(t)
After each update is completed, the temperature of the system is reduced to T (T) at the time T, wherein T (0) is the initial temperature of the system, T (0) =max (R) -min (R), the iteration termination condition is a set threshold T t, and the iteration is terminated when the T (T) < T t is satisfied, so that an extracted matrix R p is obtained; taking the average value T r＝(t1,t2,...,tN of each column of R p) as a threshold value, and sequentially setting 0 for elements of each column of R p which are smaller than the threshold value.
S3 comprises the following steps:
31-all non-0 elements in matrix R p are extracted and coordinate transformed. And extracting coordinates z [ i ] = { b [ i ], d [ i ] } of all non-0 elements in the matrix R p, wherein i=1, 2, … and v, z is a coordinate result, b and d are corresponding horizontal and vertical coordinates of v non-0 elements respectively, and b and d are changed into horizontal and vertical distance coordinates x and y respectively.
And 32, eliminating abnormal values of all coordinate results in the depth range. And performing sliding quadratic fitting on the coordinates x and y of all the horizontal and vertical distances, and eliminating the abnormal value to obtain final depth range information.
Extracting coordinates z [ i ] = { b [ i ], d [ i ] }, i=1, 2, …, v of all non-0 elements in the matrix R p, wherein z is a coordinate result, b and d are corresponding horizontal and vertical coordinates of v non-0 elements respectively, and converting the coordinates of b and d into horizontal and vertical distance coordinates x and y respectively according to the following formula:
y[i]＝d[i]*0.5*c*cos(θi)/fs
x[i]＝y[i]*tan(θi)
wherein c is the sound velocity in the sea water, f s is the sampling rate of a sonar system, and theta i is the incident angle corresponding to the ith wave beam;
According to 5% of the total number M of the beams, adjusting and determining the window length L to be an odd number, performing secondary fitting on the sequence in the window according to the least square principle, wherein the mth point in the window is the point to be measured, and the fitting result is that And repeating the process from the sliding window to the next sampling point until all sequences are fitted, removing potential abnormal values in the fitting result according to a 3-time standard deviation principle, wherein the steps are as follows:
where σ is the standard deviation of the sequence within the window, for the fit result And (5) eliminating coordinates meeting the abnormal value condition to obtain final depth range information.
The depth information extraction process of the beam signals recorded by the multi-beam sounding sonar system is simulated. The system parameters corresponding to the acquired beam signals are a coverage angle of 130 degrees, a pulse width of 70 mu s, a signal sampling rate of 50kHz, a sound velocity of 1500m/s, a beam number of 512 and a total number of sampling points of 6720. Fig. 2 gives the original beam pattern. The 512 beams are respectively subjected to mean square summation and preprocessing aiming at 6720 sampling points to inhibit side lobe leakage caused by direct waves and to denoise a beam pattern, and fig. 2 and fig. 3 show beam patterns before and after processing. And uniformly placing search points in the preprocessed beam matrix from the beam direction and the sampling point direction respectively, wherein the number of the search points is 2024, moving and repeatedly updating the search points with the same probability to obtain a result matrix, averaging all the sampling points corresponding to each beam in the matrix, and setting elements lower than 50 times of the average value to obtain an extraction result as shown in figure 3. The search points are randomly selected when there is no depth result, but note that in this simulation, each beam has 4 search points and is random in the direction of the sampling points because each beam has only one depth theoretically, however, if the system has the last depth result, in order to improve the accuracy of the algorithm, the search points of each beam can be set to be near the sampling points corresponding to the detection results. And extracting coordinates of non-0 elements in the matrix to obtain an extraction result under a beam sampling point coordinate system, as shown in fig. 3. And (3) returning the depth information to a horizontal depth coordinate system, selecting window length to be 21 according to a rule of 5% of the number of approximate beams, performing sliding window secondary fitting on the extracted result coordinate containing the depth range information, detecting abnormal values according to a 3-time mean square error principle in the window, as shown in fig. 5, and removing all detected abnormal values to obtain a final depth extraction result in fig. 6.
In summary, the method for rapidly extracting the water depth range based on the multi-beam sounding sonar beam image can effectively extract depth information in the beam signal.
Claims (3)
1. The rapid extraction method of the water depth range based on the multi-beam sounding sonar wave beam image is characterized by comprising the following steps:
s1: preprocessing a beam image in order to inhibit sidelobe leakage of the submarine direct wave and realize noise suppression;
All beams X (n) corresponding to each sampling point n in the beam matrix X M×N are processed as follows:
XM×N＝[x1(n),x2(n),…,xM(n)]T
RM×N＝[r1(n),r2(n),…,rM(n)]T
Wherein: m and N are respectively the total number of preformed beams and the total number of sampling points formed by the beams, X m (N) is the value of the mth beam of X at the nth sampling point moment, R m (N) is obtained after processing, and R is the beam matrix after preprocessing;
S2: creating a result matrix R p with the same scale as the beam matrix X, and randomly selecting K positions as search point starting positions; continuously updating the result matrix and updating the position of the search point by comparing the sizes of surrounding elements until the iteration stops;
the method specifically comprises the following steps:
21: creating a result matrix R p which has the same scale as the beam matrix X and setting all elements to zero;
22: initializing K searching starting points for a beam image matrix R;
the position of each search point in the matrix R p is marked as (i, j), the distribution range is 1-1M, 1-1 j-N, the abscissa of the search points is uniformly distributed in different beams, the starting point of the ordinate selects the vicinity of the sampling point corresponding to the depth result of the previous frame, and if the result of the previous frame does not exist, the position of the ordinate is randomly selected;
23: iteratively updating the search point positions to obtain a result matrix R p;
Updating iteration of corresponding abscissa in horizontal and vertical directions is divided into two cases according to whether the search point is positioned at the boundary or not, when the search point is positioned at the boundary, the search point moves inwards the boundary, and when the search point is positioned outside the boundary, the search point moves leftwards and rightwards or upwards and downwards by one lattice with the same probability; meanwhile, reducing the temperature of the system at the moment T to T (T) according to T (T) =T (0)/log 2 (T), wherein T (0) is the initial temperature of the system, T (0) =max (R) -min (R), the iteration termination condition is a set threshold value T t, if T (T) < T t, the iteration is terminated, at the moment, the average value T r＝(t1,t2,...,tN of each column of R p is taken as the threshold value, and elements of each column of R p smaller than the threshold value are sequentially set to 0;
S3: and determining the window length according to the number of the beams, performing secondary fitting on the depth coordinate values, and removing potential depth abnormal values to obtain a final depth range extraction result.
2. The method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image according to claim 1, wherein the step S3 specifically comprises the following steps:
31: extracting all non-0 elements in the matrix R p and performing coordinate transformation;
32: and eliminating abnormal values of all coordinate results in the depth range.
3. The method for rapidly extracting the water depth range based on the multi-beam sounding sonar wave beam image according to claim 2, wherein coordinates x and y of all horizontal and vertical distances are subjected to sliding quadratic fitting in 32, and abnormal values are eliminated to obtain final depth range information.
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