CN112946663B - Grading automatic collision alarm method for forward-looking obstacle-detection sonar - Google Patents
Grading automatic collision alarm method for forward-looking obstacle-detection sonar Download PDFInfo
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Abstract
The invention discloses a graded automatic collision alarm method of forward-looking obstacle-exploration sonar, and belongs to the field of sonar exploration. According to the invention, by establishing a collision risk function related to parameters such as the size, the orientation, the distance and the like of the obstacle target, classifying the alarm area, setting the collision alarm threshold value, realizing the classified management and control of the collision alarm information, reducing the false alarm rate of the collision alarm, objectively embodying the critical degree of possible collision and better fitting the application scene of underwater navigation obstacle detection. The underwater safe navigation system integrates the functions of 'detection-perception-judgment-alarm' and the like, obtains parameters such as the number, distance, direction, dimension and the like of obstacle targets in a detection range by means of the two-dimensional forward-looking multi-beam image sonar, judges the collision danger level according to the established graded alarm model, reminds an underwater vehicle in an acousto-optic alarm mode or transmits collision alarm information to a command control machine of the underwater vehicle, and achieves intelligent assistance of the manned/unmanned underwater vehicle in underwater safe navigation.
Description
Technical Field
The invention belongs to the field of sonar detection, and particularly relates to a grading automatic collision alarm method of forward-looking obstacle-detecting sonar.
Background
During underwater navigation, the manned/unmanned underwater vehicle usually performs forward-looking obstacle detection by means of a two-dimensional forward-looking multi-beam image sonar. In the practical application process, the two-dimensional forward-looking multi-beam image sonar warning method is influenced by factors such as microminiature biological noise and environmental noise in water, the false alarm rate of collision warning is high, the collision warning information is too simple, and the danger degree of possible collision is not objectively reflected, so that a large burden is caused to an underwater vehicle, even the underwater vehicle often takes unnecessary obstacle evading actions, and the normal navigation of the underwater vehicle is greatly influenced.
Therefore, how to realize the grading alarm of the forward looking obstacle-detecting sonar is a technical problem to be solved urgently at present.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a grading automatic collision alarm method of forward-looking obstacle-exploring sonar.
The invention adopts the following specific technical scheme:
a graded automatic collision alarm method of foresight obstacle-detection sonar is a two-dimensional foresight multibeam image sonar installed at the bow of an underwater vehicle, and comprises the following steps:
s1: the method comprises the following steps of discretizing a view of the sonar into a plurality of grade areas according to the collision risk of each point in the view, wherein the collision risk of all points in the same grade area is in the same collision risk interval, the collision risk of each point is determined by the dimension l of an obstacle target and the direction theta and the distance r of the point relative to the sonar, and the calculation formula is as follows:
in the formula: theta.theta.0Opening angle for sonar detection r0σ is a standard deviation in normal distribution N (0, σ) that is satisfied by a collision risk random variable with respect to the orientation θ, which is a minimum detection distance of sonar;
and a current grade collision alarm triggering condition and an upgrade collision alarm triggering condition are preset for each grade area; the current grade collision alarm triggering condition is that the number of pixel points of a single barrier target in the grade area exceeds the minimum pixel point number threshold of the grade area; the upgrading collision alarm triggering condition is that the scale of a single barrier target in the grading area exceeds the scale threshold of the grading area;
s2: the method comprises the steps that in the sailing process of the underwater vehicle, acoustic images in the visual field range of sonar in front of the underwater vehicle are obtained in real time through forward-looking obstacle-detecting sonar, connected domain analysis is conducted on the acoustic images in real time to determine the number of obstacle targets in the acoustic images, the scale and the direction of each obstacle target and the distance from the obstacle target to the underwater vehicle are sensed, and a current obstacle detection result in front of the underwater vehicle is formed;
s3: according to a current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting a current level collision alarm triggering condition exists in each level area in the sonar view area is judged respectively, if yes, a collision danger level corresponding to the level area is triggered, and if not, the collision danger level is not triggered;
s4: according to a current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting an upgrading collision alarm triggering condition exists in each level area in the sonar view area is judged respectively, if yes, a collision danger level higher than a collision danger level corresponding to the level area is triggered, and if not, the collision danger level is not triggered;
s5: and selecting the highest collision risk level triggered in S3 and S4 as the current collision risk level of the underwater vehicle, and sending the collision risk level to a signal receiving end for alarming.
Preferably, the field of view of the sonar is divided into 3 to 5 rank regions.
Furthermore, the collision danger degree value interval of the underwater vehicle is divided into 4 continuous value intervals, and the visual field of the sonar is correspondingly divided into 4 grade areas.
Preferably, the thresholds of the minimum pixel number in different grade areas are different.
Preferably, the scale threshold is different in different rank regions.
Preferably, in S4, if there is an obstacle target meeting the upgrade collision alarm trigger condition in one level region, triggering a collision risk level that is one level higher than the collision risk level corresponding to the level region in which the obstacle target is located; when the collision risk level corresponding to the level region is the highest collision risk level, only the highest collision risk level is triggered.
Preferably, in S5, the signal receiving end is an alarm system and/or a command controller of the underwater vehicle.
Furthermore, the alarm system is provided with alarm sound and alarm light corresponding to different collision danger levels.
Preferably, if no collision risk level is triggered in S3 and S4, a default value representing no collision risk is output.
Preferably, the underwater vehicle iteratively processes S2-S5 on the acoustic images acquired in real time during the process of sailing, senses the real-time dynamic information of the obstacle target and continuously updates the collision danger level.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, by establishing the collision risk function of the parameters of the obstacle target such as the scale, the direction, the distance and the like, dividing the classified alarm area, setting the collision alarm threshold value, realizing the classified control of the collision alarm information, reducing the false alarm rate of the collision alarm, objectively reflecting the emergency degree of possible collision, and better fitting the application scene of underwater navigation obstacle detection.
The invention integrates the functions of 'detection-perception-judgment-alarm' and the like, acquires parameters such as the number, distance, direction, scale and the like of obstacle targets in a detection range by means of a two-dimensional forward-looking multi-beam image sonar, judges the collision danger level according to an established grading alarm model, reminds a diver in an acousto-optic alarm mode or transmits collision alarm information to a command controller of a diver, and realizes intelligent assistance of the manned/unmanned diver to carry out underwater safe navigation.
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FIG. 1 is a schematic view of the impact risk level distribution area within the sonar view field in the example.
FIG. 2 shows the results of the high-risk barrier-detecting alarm test for level I in the examples.
FIG. 3 shows the results of the high risk obstacle-detecting alarm test in level II in the examples.
FIG. 4 shows the results of the level III emergency barrier-exploring alarm test in the examples.
Detailed Description
The invention is further illustrated and described below with reference to the drawings and the detailed description. The technical characteristics of the embodiments of the invention can be correspondingly combined without mutual conflict.
The foresight obstacle-exploring sonar adopts two-dimensional foresight multibeam image sonar which is arranged at the bow part of an underwater vehicle. However, when the two-dimensional forward-looking multi-beam image sonar is applied to realize the forward-looking obstacle-detection alarming function of the underwater manned/unmanned underwater vehicle, the forward-looking obstacle-detection alarming function is influenced by factors such as microminiature organisms in water, environmental noise and the like, the false alarm rate of collision alarming is high, and an underwater vehicle cannot judge the emergency degree of possible collision according to alarming information.
Based on the problem, the invention concept adopted by the invention is as follows: sensing parameters such as the number of targets, the size and the direction of each target, the distance from each target to a submarine vehicle and the like through an underwater sound image detected by a two-dimensional forward-looking multi-beam image sonar; secondly, establishing a collision risk function related to parameters such as target dimension, azimuth and distance, and determining a grading alarm area and grade by performing discretization block cutting processing on the detection area. And thirdly, setting a collision alarm threshold value for each classified alarm area, and triggering collision alarm of corresponding grade when the number of pixel points of the target image in the area exceeds the collision alarm threshold value. In addition, in order to objectively evaluate the threat of the large target to the navigation safety of the underwater vehicle, a target scale threshold value is set, and when the scale of the obstacle target in a certain classification area is larger than the threshold value, the collision danger level of the underwater vehicle and the obstacle target is adjusted up to one level until the highest level I collision danger is reached. And finally, determining the highest collision danger level by the collision danger classification alarm model according to the obstacle target information in each classification area, automatically calling corresponding built-in alarm sound and flashing light, and reminding an underwater vehicle pilot to pay attention to navigation safety or transmitting collision alarm information to a command control machine of the underwater vehicle.
The specific implementation mode of the grading automatic collision alarm method of the forward-looking obstacle-exploring sonar is described in detail below.
S1: before a sonar is put into practical use, the sight of the sonar (namely, the detection range in a fan shape) needs to be discretized into a plurality of grade areas according to the collision risk of each point in the sight in advance, so that the subsequent graded alarm can be realized.
The view field needs to be reasonably divided according to the collision risk represented by the obstacle object appearing at each point in the view field range, the specific division number n can be adjusted according to actual needs, and the division number n can be generally divided into 3-5 grade areas. The measurement of the collision risk requires that a collision risk function related to parameters such as target scale, azimuth and distance is established in advance, so as to quantify a specific value of the collision risk.
Considering first the contribution of the azimuth θ to the collision risk, generally, the collision risk of an obstacle target located right in front is large, and the collision risk of an obstacle target deviated from right in front is small. Since the detection area of the two-dimensional forward-looking multi-beam image sonar is fan-shaped and has bilateral symmetry distribution characteristics, the random variable of the collision risk degree about the azimuth theta satisfies normal distribution N (0, sigma) with standard deviation sigma, and the probability density function is given by the following formula:
in the formula: theta.theta.0(radian) is the detection opening angle of sonar, and k is a quantization coefficient. The standard deviation σ is a statistical value, and is determined by a sample, and the standard deviation σ may be set to 1 in this embodiment.
The global integral value according to the probability density function is equal to 1, i.e.:
it can be calculated that:
further considering the contribution of two factors such as the dimension l of the obstacle target and the distance r from the obstacle target to the underwater vehicle to the collision risk, wherein l is uniformly distributed on an arc line with the radius r, and the collision probability of the two factors is determined to be approximate to:
in the formula, r0The minimum detection distance of sonar.
Comprehensively considering the contribution of parameters such as the dimension l, the direction theta, the distance r and the like of the obstacle target to the collision risk, establishing a collision risk function in the invention as follows:
based on the collision risk function, the direction theta and the distance r of any point relative to the sonar can be determined according to the position of the point in the visual field, and the collision risk of each point in the visual field of the sonar can be calculated by setting the dimension l of the obstacle target of all the points to a fixed value
The process can be realized by drawing a three-dimensional surface graph of the collision risk function and performing discretization block cutting treatment.
Therefore, the collision danger degree value interval of the underwater vehicle can be divided into n continuous value intervals, each value interval corresponds to one collision danger level, and the larger the collision danger degree value is, the higher the collision danger degree is, the more possible collision is. Therefore, according to the divided collision risk value interval, the whole visual field can be divided into n grade areas in a discretization mode, wherein the collision risk of all the points in the same grade area is in the same collision risk value interval.
After the vision field is divided into the grade areas, the collision danger level can be determined according to the size and the dimension of the obstacle target falling into each grade area in the subsequent actual detection process. The method is characterized in that false alarms easily occur in a detected image under the influence of microminiature organisms and noise in water, so that on one hand, a pixel threshold value of collision alarm needs to be set for each grade, namely, the number of the minimum pixel points of a single target in an area triggering the collision alarm is determined, on the other hand, due to the fact that collision risks are increased when obstacle targets with large dimensions are sensed, an alarm upgrading measure needs to be adopted, a target dimension threshold value needs to be set, and when the sensed dimension of the obstacle targets is larger than the threshold value, the collision danger grade of an underwater vehicle and the obstacle targets needs to be adjusted upwards.
Therefore, in the invention, after the classification of the grade areas is completed in the vision field range, a current grade collision alarm triggering condition and an upgrade collision alarm triggering condition need to be preset for each grade area, and the two triggering conditions are specifically as follows:
a) the current grade collision alarm triggering conditions are as follows: the number of pixels of a single obstacle target in the grade region exceeds the minimum pixel number threshold value W of the grade region1. If the condition is met, the alarm level corresponding to the current level area can be triggered.
b) The upgrade collision alarm triggering conditions are as follows: the scale of the single obstacle object in the grade region exceeds the scale threshold W of the grade region2. When the condition is met, the alarm grade higher than the alarm grade corresponding to the current grade area can be triggered, and early warning feedback is made on the large obstacle target in advance. Dimension threshold W2Can be set artificially, and the value of the obstacle target is required to be larger than the scale of the conventional obstacle target so as to identify the overlarge obstacle target.
In the above two triggering conditions, the threshold value W of the minimum number of pixel points in different hierarchical regions1May be the same or different. Similarly, scale thresholds W in different rank regions2May be the same or different. In general, the threshold W in the different rank regions1、W2The values are different, and the specific values need to be optimized according to the actual conditions.
After the setting of the level area and the two triggering conditions in the vision field range is finished, the information can be embedded into an upper computer of a sonar system and is used for graded automatic collision alarm in the navigation process of the underwater vehicle. See S2-S5, the detailed process is described below.
S2: real-time acquisition of sonar vision field range in front of underwater vehicle by foresight obstacle-finding sonar in underwater vehicle navigation processThe maximum detection distance of sonar and the underwater acoustic image in the surrounding area is recorded as L, and the detection opening angle is recorded as theta0。
In order to eliminate the influence of micro aquatic organisms and noise from the acoustic image and extract a large obstacle target, the acquired acoustic image needs to be further analyzed in a connected domain in real time to determine the number of the obstacle targets in the acoustic image, and the scale, the direction and the distance from each obstacle target to the underwater vehicle are sensed to form a current obstacle detection result in front of the underwater vehicle. The connected domain analysis belongs to the prior art and can be realized by adopting the existing algorithm, wherein the adopted threshold value can be optimized and adjusted according to the actual situation. The scale, the position and the distance from the obstacle target to the underwater vehicle can be sensed by a functional module built in the sonar, and the method also belongs to the prior art and is not described in detail. Therefore, the current obstacle detection result obtained from one acoustic image contains basic information such as the number of obstacle targets in the acoustic image, the scale and the direction of each obstacle target and the distance from the obstacle target to the underwater vehicle, and the current obstacle detection result can be mapped in the view field of sonar according to the information for carrying out hierarchical alarm monitoring in the subsequent step.
S3: according to the current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting the current level collision alarm triggering condition exists in each level area in the sonar view field is judged respectively, namely whether an obstacle target exists in each level area in the sonar view field and the number of pixels occupied by the obstacle target exceeds the preset minimum pixel number threshold value W of the level area1If the collision danger level exists, the collision danger level corresponding to the grade area is triggered, and if the collision danger level does not exist, the collision danger level corresponding to the grade area is not triggered.
For example, for a corresponding class region with a collision risk level A, the minimum pixel number threshold W of the class region1AAccording to the current obstacle detection result, the number of the pixel points occupied by one obstacle target in the grade area is found to exceed W1AThen a collision risk level a needs to be triggered. When multiple grade areasIf there are all obstacle targets meeting the current level collision alarm triggering conditions, then the corresponding collision danger levels need to be triggered respectively. If no obstacle target meeting the triggering condition of the collision alarm of the current grade exists in all grade areas, any collision danger grade is not triggered in the step.
In addition, while the determination of S3 is performed, it is necessary to take into account the influence of the scale size of the obstacle target, and an alarm for upgrading the obstacle target having a scale larger than a certain value is issued as in S4.
S4: according to the current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting an upgrading collision alarm triggering condition exists in each level area in the sonar view field is judged respectively, namely whether an obstacle target exists in each level area in the sonar view field and the scale of the obstacle target exceeds the scale threshold value W of the level area2If the collision risk level exists, the collision risk level higher than the collision risk level corresponding to the level area is triggered, and if the collision risk level does not exist, the collision risk level is not triggered.
For example, for a corresponding level region with a collision risk level of C (B and A for the higher level and the second level, respectively), the minimum threshold value W of the number of pixels in the level region2CAccording to the current obstacle detection result, the scale of the obstacle object in the grade area exceeds the scale threshold value W of the grade area2CThen a higher collision risk level than level C needs to be triggered. The collision danger level higher than the level C can be set according to actual needs, and can be higher by one level or more than two levels. Generally speaking, it is sufficient to trigger a collision risk level one level higher than the collision risk level corresponding to the level region in which it is located. So that here the collision risk class B needs to be triggered. When the barrier targets meeting the upgraded collision alarm triggering conditions exist in all the plurality of grade areas, corresponding collision danger grades need to be triggered respectively. If no obstacle target meeting the upgrade collision alarm triggering condition exists in all the grade areas, any upgrade collision danger grade is not triggered in the step.
In addition, it should be noted that, because there is an upper limit to the collision risk level, when the collision risk level corresponding to the level region is the highest collision risk level, only the highest collision risk level needs to be triggered, and there is no need to trigger a higher collision risk level.
S5: after the execution of S3 and S4 is finished, all output results of collision risk levels are obtained, so that the highest collision risk level triggered in S3 and S4 is selected to be used as the current collision risk level of the underwater vehicle. However, if no collision risk level is triggered in S3 and S4, a default value representing no collision risk is output.
In order to realize the alarm function, the current collision danger level of the underwater vehicle needs to be sent to a signal receiving end for alarming. The signal receiving end can be set according to actual conditions as long as the alarm function can be realized, and generally speaking, the signal receiving end can adopt an alarm system or a command controller of an underwater vehicle. The alarm system has alarm sound and alarm light corresponding to different collision danger levels, and can be integrated on a command controller and embodied in a UI interface or other forms.
Because the obstacle in front of the underwater vehicle changes in real time, in the navigation process of the underwater vehicle, the acoustic images acquired in real time need to be iterated to be processed from S2 to S5, so that the real-time dynamic information of the obstacle target can be sensed, the global collision danger level can be continuously updated and judged, and a complete 'detection-sensing-judgment-alarm' closed-loop system is constructed for underwater navigation and forward-looking obstacle detection.
In order to make the present invention more understandable to those skilled in the art, the above-described method is applied to a specific embodiment to show its technical effects.
Example 1
In this embodiment, the specific alarm method is shown in S1-S3, and will not be described again.
In S1, the collision risk value section of the underwater vehicle is divided into 4 consecutive value sections according to the collision risk function, and therefore, the sonar view field with the maximum detection distance L is also divided into 4 rank regions. As shown in fig. 1, the classified collision risk classification alarm area of the present embodiment includes four classification areas, which may be represented by red, orange, yellow and blue colors in practical use, and the classification of collision risk between the underwater vehicle and the blocking object in the area is class i (high risk), class ii (high risk), class iii (medium risk) and class iv (low risk).
In the embodiment, the alarm loudspeaker and the flashing lamp are arranged in the UI interface of the command controller of the underwater vehicle, corresponding built-in alarm sound and flashing light can be automatically called according to the highest collision danger level of each level area (when the collision danger level is risk-free, no sound alarm is given to the outside or the light flashes are prompted), the underwater vehicle is reminded to pay attention to navigation safety or collision alarm information is transmitted to the command controller of the underwater vehicle, and classified automatic collision alarm of forward-looking obstacle-exploring sonar is realized.
In the embodiment, a two-dimensional foresight multi-beam image sonar obstacle-exploring alarm test applied to an underwater navigation scene is developed in an actual water area environment, and scale thresholds W of various grade areas such as I grade (high risk), II grade (high risk), III grade (medium risk), IV grade (low risk) and the like are set2Respectively 50m, 100m, 150m and 200m, to verify the effectiveness of the hierarchical automatic collision warning method according to the present invention, and the results are shown in fig. 2 to 4.
As shown in fig. 2, the acoustic image of the obstacle target obtained by the two-dimensional forward-looking multi-beam image sonar detection in this embodiment is shown. And respectively triggering a level I high risk alarm, a level II high risk alarm and a level III medium risk alarm according to the sensed target parameters and by combining the collision risk level distribution area diagram in the figure 1. The invention relates to a foresight obstacle-exploring sonar graded automatic collision alarm method, which automatically alarms the outside at a high risk level I, displays a collision danger grade as high at the upper right corner of a UI display area, and flashes and displays a red indicator lamp at the lower part of a parameter setting and display area.
As shown in fig. 3, the high risk alarm in class ii and the low risk alarm in class iii are triggered according to the sensed target parameters and the collision risk level distribution area diagram in fig. 1. It should be noted that although there are several micro-objects in the i-level high-risk collision level (red) region, the image pixel points are lower than the set collision alarm threshold, and the i-level high-risk collision level is not triggered. The foresight obstacle-finding sonar graded automatic collision alarming method provided by the invention automatically alarms the outside at a level-II middle-high risk, displays the collision danger grade as 'middle-high' at the upper right corner of a UI display area, and flashes and displays an orange indicator lamp at the lower part of a parameter setting and display area.
As shown in FIG. 4, a class III risk alert is triggered based on the sensed target parameters in conjunction with the collision risk level distribution plot of FIG. 1. It should be noted that although there are several micro targets in the i-level high-risk collision level (red) region and the ii-level medium-high-risk collision level (orange) region, the image pixel points are lower than the set collision alarm threshold, and the i-level high-risk or ii-level medium-high-risk collision level is not triggered. The forward-looking obstacle-exploring sonar grading automatic collision alarming method automatically alarms outwards by using class III middle dangers, displays the collision danger grade as 'middle' at the upper right corner of a UI display area, and flashes and displays a yellow indicator lamp at the lower part of a parameter setting and display area.
The above-described embodiments are merely preferred embodiments of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, those skilled in the relevant art will recognize that the present invention is not limited to the specific embodiments of the present invention, but rather, all embodiments of the present invention are within the scope of the present invention.
Claims (10)
1. A grading automatic collision alarm method of a forward-looking obstacle-exploring sonar is disclosed, wherein the forward-looking obstacle-exploring sonar is a two-dimensional forward-looking multi-beam image sonar arranged on the bow of an underwater vehicle, and is characterized by comprising the following steps:
s1: the method comprises the following steps of carrying out discretization on a view field of the sonar according to the collision risk of each point in the view field to form a plurality of grade areas, wherein the collision risk of all points in the same grade area is in the same collision risk interval, the collision risk of each point is determined by the scale l of an obstacle target, the direction theta and the distance r of the point relative to the sonar, and the calculation formula is as follows:
in the formula: theta0Angle of opening, r, of detection for sonar0σ is a standard deviation in a normal distribution N (0, σ) that is satisfied by a collision risk degree random variable with respect to the azimuth θ, which is a minimum detection distance of the sonar;
and a current grade collision alarm triggering condition and an upgrade collision alarm triggering condition are preset for each grade area; the current grade collision alarm triggering condition is that the number of pixel points of a single barrier target in the grade area exceeds the minimum pixel point number threshold of the grade area; the upgrading collision alarm triggering condition is that the scale of a single obstacle target in the grading area exceeds the scale threshold of the grading area;
s2: the method comprises the steps that in the sailing process of the underwater vehicle, acoustic images in the visual field range of sonar in front of the underwater vehicle are obtained in real time through forward-looking obstacle-detecting sonar, connected domain analysis is conducted on the acoustic images in real time to determine the number of obstacle targets in the acoustic images, the scale and the direction of each obstacle target and the distance from the obstacle target to the underwater vehicle are sensed, and a current obstacle detection result in front of the underwater vehicle is formed;
s3: according to the current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting the current-level collision alarm triggering condition exists in each level area in the sonar visual field is respectively judged, if yes, the collision danger level corresponding to the level area is triggered, and if not, the collision danger level is not triggered;
s4: according to the current obstacle detection result in front of the underwater vehicle, whether an obstacle target meeting the condition of upgrading collision alarm triggering exists in each level area in the sonar visual field is respectively judged, if yes, a collision danger level higher than the collision danger level corresponding to the level area is triggered, and if not, the collision danger level is not triggered;
s5: and selecting the highest collision risk level triggered in S3 and S4 as the current collision risk level of the underwater vehicle, and sending the collision risk level to a signal receiving end for alarming.
2. The graded automatic collision warning method of forward-looking barrier sonar according to claim 1, wherein a visual field of the sonar is divided into 3 to 5 graded regions.
3. The method for classified automatic collision warning of forward-looking barrier sonar according to claim 2, wherein the interval of collision risk values of the underwater vehicle is divided into 4 consecutive value intervals, and the field of view of the sonar is divided into 4 classified areas.
4. The method for hierarchical automatic collision warning of forward looking barrier sonar according to claim 1, wherein the minimum number of pixel points thresholds are different in different hierarchical regions.
5. The method for hierarchical automatic collision warning of forward looking barrier sonar according to claim 1, wherein the scale threshold is different in different hierarchical regions.
6. The graded automatic collision warning method of the forward-looking barrier sonar of claim 1, wherein in S4, if there is an obstacle target satisfying an upgrade collision warning trigger condition in a grade area, a collision risk level one grade higher than a collision risk level corresponding to the grade area in which it is located is triggered; when the collision risk level corresponding to the level region is the highest collision risk level, only the highest collision risk level is triggered.
7. The graded automatic collision warning method of forward looking barrier sonar of claim 1, wherein in S5, the signal receiving end is a warning system and/or a command controller of an underwater vehicle.
8. The graded automatic collision warning method of forward looking barrier sonar according to claim 7, wherein the warning system has a warning sound and a warning light corresponding to different collision danger grades.
9. The graded automatic collision warning method of forward-looking barrier sonar of claim 1, wherein if any collision risk grade is not triggered in S3 and S4, a default value representing no collision risk is outputted.
10. The graded automatic collision warning method of the forward-looking barrier-exploration sonar of claim 1, wherein the underwater vehicle iteratively processes the acoustic images acquired in real time from S2 to S5 during the course of the voyage, senses the real-time dynamic information of the obstacle target, and continuously updates the collision danger grade.
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| CN105589464B (en) * | 2016-03-28 | 2019-02-26 | 哈尔滨工程大学 | A kind of UUV dynamic obstacle avoidance method based on Speed Obstacles method |
| CN107870621B (en) * | 2016-10-25 | 2018-12-25 | 中国科学院沈阳自动化研究所 | Autonomous underwater robot collision prevention method in unknown complex sea-floor relief environment |
| KR102064202B1 (en) * | 2018-01-16 | 2020-01-09 | (주)이씨스 | Marin collision prevention system and method the same |
| CN111999735B (en) * | 2020-09-11 | 2023-10-03 | 杭州瑞利海洋装备有限公司 | Dynamic and static target separation method based on radial speed and target tracking |
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