CN111077539A - Bird detection system based on laser radar - Google Patents
Bird detection system based on laser radar Download PDFInfo
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- CN111077539A CN111077539A CN201911401873.2A CN201911401873A CN111077539A CN 111077539 A CN111077539 A CN 111077539A CN 201911401873 A CN201911401873 A CN 201911401873A CN 111077539 A CN111077539 A CN 111077539A
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract
The invention relates to the technical field of bird detection, in particular to a laser radar-based bird detection system, which comprises an acquisition module, a processing module and a bird detection module, wherein the acquisition module acquires an environment image by a laser radar imaging method; the processing module is used for acquiring an environment image to form a point cloud set and sending the point cloud set to the bird detection module; the bird detection module filters the environment image and divides the environment image into dynamic points and static points, the bird detection module clusters the dynamic points by means of a clustering radius to obtain a dynamic point cloud subset, the bird detection module finds out a circumscribed sphere radius of the dynamic point cloud subset and takes the point cloud with the circumscribed sphere radius smaller than a third threshold value as a previous suspected bird point, the bird detection module searches for the suspected bird point in the second threshold value range when the suspected bird point is in the previous moment at the current moment, and judges that birds are found when no static point exists in the first threshold value range of the suspected bird point at the current moment. The invention greatly improves the real-time property, and the bird detection algorithm can be basically carried out synchronously with the laser acquisition without lag.
Description
Technical Field
The invention relates to the technical field of bird detection, in particular to a laser radar-based bird detection system.
Background
With the acceleration of the urbanization process and the increase of the environmental awareness of human beings, birds often fly and seek food in the human living environment, and human beings and birds are harmonious and co-located, but the birds have certain danger for places such as airports, transformer substations and the like, and the birds easily cause the danger of the places such as the airports, the transformer substations and the like due to the randomness of flight tracks, for example, the birds strike airplanes to cause the damage of body parts, or the birds cause the faults of power transmission lines due to nesting or inhabitation, and the like, so the detection of the birds is very important for accurately repelling the birds in some places.
The existing bird detection system is carried out by technologies such as radar, infrared and the like, and radar bird probes generally use Doppler radars which are large in size and poor in mobility.
Disclosure of Invention
The invention aims to provide a bird detection system based on a laser radar so as to solve the problem of poor universality of the existing bird detection technology.
Visit bird system based on laser radar in this scheme, including collection module, processing module and visit bird module:
the acquisition module continuously acquires an environmental image of a target by a laser radar imaging method;
the processing module is used for acquiring an environment image to form a point cloud set and sending the point cloud set to the bird detection module;
the bird detection module filters the environment image and divides the environment image into dynamic points and static points, the bird detection module clusters the dynamic points by a clustering radius to obtain a dynamic point cloud subset, the bird detection module calculates a circumscribed sphere radius of the dynamic point cloud subset and takes point clouds with the circumscribed sphere radius smaller than a third threshold value as early stage suspected bird points, the bird detection module searches whether the early stage suspected bird points at the current moment exist in a second threshold value range at the previous moment, and the bird detection module judges that birds are searched when the early stage suspected bird points at the current moment do not exist in a first threshold value range.
The beneficial effect of this scheme is:
when detecting birds, the acquisition module acquires the environmental image of the target by a laser radar imaging method, for example, images around a transformer substation, the processing module acquires an environment image to form a point cloud set and then sends the point cloud set to the bird detection module, the bird detection module classifies the point cloud of the environment image into dynamic points and static points in a filtering mode, then clustering the classified dynamic points to obtain a dynamic point cloud subset, searching suspected bird points in the dynamic point cloud subset, and judging birds by combining the scheme of distance screening of the clustered suspected bird points and the static point cloud, thereby greatly improving the real-time property, basically realizing synchronous bird detection algorithm with laser acquisition without lag, by finding out the dynamic clustering target and then judging, the calculation amount of judging one by one in the environment image is reduced.
The bird detection module comprises a filtering unit, wherein the filtering unit is used for filtering in the horizontal direction of each pixel point of the environment image through a filtering window, the filtering unit sends a static signal when the distance between the current time point cloud and the previous time point cloud in the filtering window is smaller than a first threshold value, and the filtering unit sends a dynamic signal when the distance between the current time point cloud and the previous time point cloud in the filtering window is larger than the first threshold value.
The beneficial effects are that: and filtering the pixel points in the environment image, comparing and classifying the distance between the current moment point cloud and the previous moment point cloud of the filtering window, searching the pixel points in the environment image one by one, and avoiding missing the characteristics of the pixel points.
The bird detection module further comprises a tag unit, the processing module acquires static signals and dynamic signals and sends the static signals and the dynamic signals to the tag unit, the tag unit adds static tags to the current point cloud according to the static signals, the tag unit adds dynamic tags to the current point cloud according to the dynamic signals, the processing module forms a static point cloud set according to the static tags, and the processing module forms a dynamic point cloud set according to the dynamic tags.
The beneficial effects are that: the method has the advantages that the pixels in the environment image are classified and then are added with the labels, different point cloud sets are formed, the dynamic point cloud sets can be conveniently processed in a follow-up concentration mode, and the data volume of processing is reduced.
Further, the bird detection module further comprises a clustering unit, and the clustering unit clusters the dynamic point cloud set by a clustering radius to obtain a dynamic point cloud subset.
The beneficial effects are that: because the laser beam is emitted in a fan shape when the acquisition module probes the birds, the closer the acquisition module is, the smaller the point cloud distance between adjacent laser beams vertically projected on a target is, and the clustering unit clusters through the changed clustering radius, thereby improving the accuracy of bird probing compared with the existing clustering mode of fixing the clustering radius.
The processing module finds out the circumscribed sphere radius of the dynamic point cloud subset and takes the point cloud with the circumscribed sphere radius smaller than a third threshold value as a previous suspected bird point, the first screening unit searches whether the previous suspected bird point at the current moment is a suspected bird point in a second threshold value range at the previous moment, and the first screening unit searches whether the static point is not in the first threshold value range of the previous suspected bird point at the current moment and sends a confirmation signal to the processing module, and the processing module judges the target as a bird according to the confirmation signal.
The beneficial effects are that: static points are searched by traversing the dynamic point cloud of the suspected birds, so that the interference of the static points in the environmental image is prevented, and the accuracy of bird detection is improved.
The bird detection module further comprises a second screening unit, the processing module acquires the reflectivity of the reflected light of the acquisition module from the environment image and sends the reflectivity to the second screening unit, the second screening unit sends a noise signal to the processing module when the reflectivity is smaller than a preset value, and the processing module records the point cloud as a noise.
The beneficial effects are that: since reflectors such as glass and the like can form isolated noise points in space, the reflectors can be misjudged as suspected bird point clouds, the noise points are screened, and the bird detection accuracy is improved.
Further, the clustering radius is obtained by calculation according to the distance between the target and the acquisition module, and the clustering radius is in direct proportion to the distance between the target and the acquisition module.
The beneficial effects are that: the clustering radius is set in a direct proportion according to the distance from the target to the acquisition module, so that the bird detection accuracy is improved.
Further, the third threshold is adaptively determined by the processing module according to bird size.
The beneficial effects are that: the suspected bird points are divided according to the sizes of the birds, interference factors such as people and moving vehicles are eliminated, and the accuracy of analyzing the positions of the birds according to the suspected bird points is improved.
Further, the first threshold is calculated by the processing module according to the laser vertical angle resolution and the detection range.
The beneficial effects are that: and (4) searching the dead point of the suspected bird point in the first threshold range, eliminating interference factors and improving bird detection accuracy.
Further, the bird detection module comprises a speed measurement unit, the speed measurement unit is used for measuring the flying speed of the birds, and the second threshold is calculated by the processing module according to the flying speed of the birds and the last moment.
The beneficial effects are that: the suspected bird point at the previous moment is searched according to the range determined by the bird flying speed, so that the continuity is improved, and the bird detection is more accurate.
Drawings
FIG. 1 is a logic block diagram of a first embodiment of a bird detection system based on a lidar;
fig. 2 is a flowchart of an embodiment of a bird detection system based on a lidar.
Detailed Description
The following is a more detailed description of the present invention by way of specific embodiments.
Example one
A laser radar-based bird detection system is shown in figure 1 and comprises an acquisition module, a processing module and a bird detection module, wherein the acquisition module is in signal connection with the processing module, and the bird detection module is in signal connection with the processing module.
The acquisition module continuously acquires an environment image of a target by a laser radar imaging method, the acquisition module can use the existing RS-LiDAR-16 type laser radar, and the acquisition module transmits a plurality of laser beams which generate reflected beams after meeting the target and acquires the environment image according to the reflected beams.
The bird detection module comprises a filtering unit, a label unit, a clustering unit, a first screening unit and a second screening unit.
The processing module forms a point cloud set after acquiring an environment image and sends the point cloud set to the filtering unit, the filtering unit filters in the horizontal direction of each pixel point of the environment image through the filtering window, the filtering unit sends a static signal when the distance between the current-time point cloud and the previous-time point cloud in the filtering window is smaller than a first threshold, and the filtering unit sends a dynamic signal when the distance between the current-time point cloud and the previous-time point cloud in the filtering window is larger than the first threshold.
The processing module acquires static signals and sends the static signals to the tag unit, the tag unit adds static tags to the current point cloud according to the static signals, the processing module acquires dynamic signals and sends the dynamic signals to the tag unit, the tag unit adds dynamic tags to the current point cloud according to the dynamic signals, the static tags and the dynamic tags can be represented by different English letters, for example, the static tags are J, the dynamic tags are D, the processing module forms a static point cloud set according to the static tags, the processing module forms a dynamic point cloud set according to the dynamic tags, and the processing module can use a server of the existing background cloud.
The processing module sends the dynamic point cloud set to the clustering unit, the clustering unit clusters the dynamic point cloud set by a clustering radius to obtain a dynamic point cloud subset, the clustering radius is obtained by calculation according to the distance between the target and the acquisition module, and the clustering radius is in direct proportion to the distance between the target and the acquisition module.
The processing module obtains a dynamic point cloud subset, calculates the circumscribed sphere radius of the dynamic point cloud subset, takes the point cloud with the circumscribed sphere radius smaller than a third threshold value as a previous suspected bird point, sends the previous suspected bird point to a first screening unit, the first screening unit searches whether the previous suspected bird point at the current moment is a suspected bird point in a second threshold value range at the previous moment, and sends a confirmation signal to the processing module when the first screening unit does not have a static point in the first threshold value range of the previous suspected bird point at the current moment, namely, judges whether the previous suspected bird point exists in the images at the previous moment and the next moment, the processing module judges the target of the previous suspected bird point as a bird according to the confirmation signal, the processing module obtains the reflectivity of the reflected light when the acquisition module acquires the environment image from the environment image and sends the reflectivity to a second screening unit, and the second screening unit sends a noise point signal to the processing module when the reflectivity is smaller than a preset value, the reflectivity is 0-255, for example, if the reflectivity is more than 100, the point cloud is considered as a noise point, and the processing module records the point cloud as a noise point.
As shown in fig. 2, the specific implementation process is as follows:
when bird detection is carried out around an airport or a transformer substation, a plurality of radar lasers emitted by an acquisition module generate reflected beams when the radar laser beams meet a target, the acquisition module forms an environment image according to the reflected beams, for example, the environment image around the airport or the transformer substation is acquired, the environment image mainly uses a UDP protocol, an Ethernet medium is adopted to transmit data packets, then a processing module analyzes an MSOP packet to extract laser ranging values, echo reflectivity, horizontal rotation angles and time stamps, the horizontal and angular resolution is 0.18 degrees when a sampling frequency of 10Hz is used, the time in the embodiment I is 0.1s, each circle of laser data is 2000 sampling points, therefore, the number of the sampling points of one circle of 16 laser beams, namely one frame, is 16 x 2000, image data similar to 16 x 2000 pixels can be organized, and during specific operation, 12 times of continuous acquisition are carried out on a time domain, the first 11 16 x 2000 images were used.
After data are collected, a processing module acquires an environment image and then forms a point cloud set which is sent to a filtering unit, the filtering unit carries out filtering through a window with 1 pixel on the left and the right of each pixel point in the image data which are adjacent in the horizontal direction, when the distance between the current point cloud in the filtering window and the cloud of the previous time point is smaller than a first threshold value, the filtering unit sends a static signal to the processing module, the processing module sends the static signal to a label unit, the label unit adds a static label to the cloud of the previous time point according to the static signal, otherwise, the filtering unit sends a dynamic signal to the processing module, the processing module sends the dynamic signal to the label unit, and the label unit adds a dynamic label to the cloud of the previous time point.
After a label is added to the point cloud, the processing module divides the point cloud set into a dynamic point cloud set and a static point cloud set according to the type of the label, the processing module sends the dynamic point cloud set to a clustering unit for clustering analysis, and during clustering analysis, a dynamic point cloud subset is obtained by clustering with a changed clustering radius, wherein the clustering radius can be represented as r ═ 2 × PI/360 × d + s, 2 represents the vertical angular resolution of a laser beam, d represents the distance between the laser point and a light source, and s represents a small distance noise, for example, the clustering radius calculated at 50m is 1.717m, the measured vertical height is 1.728m, so s can be 1.728-1.717m, and a series of pixel points with the clustering radius r form the dynamic point cloud subset.
After the dynamic point cloud subset is obtained, the processing module calculates the circumscribed spherical radius of the dynamic point cloud subset, the processing module takes the point cloud with the circumscribed spherical radius smaller than a third threshold value as a previous suspected bird point, the previous suspected bird point is sent to a first screening unit, the first screening unit searches for suspected bird points in a second threshold value range when the previous suspected bird point is in the previous time at the current time, the first screening unit simultaneously searches for no static point in the first threshold value range of the previous suspected bird point at the current time, at the moment, the first screening module sends a confirmation signal to the processing module, and the processing module judges that birds exist according to the confirmation signal.
The processing module obtains the reflectivity of the reflected light of the acquisition module from the image data and sends the reflectivity to the second screening unit, the reflectivity can be obtained when the image data is acquired, the second screening unit sends a noise point signal to the processing module when the reflectivity is smaller than a preset value, and the processing module records the point cloud as a noise point.
In the first embodiment, after the environmental image is acquired, the point cloud set of the environmental image is filtered and classified, then the dynamic point cloud set is subjected to cluster analysis by means of the changed cluster radius, and by combining the scheme of static point cloud distance screening, the real-time performance is greatly improved, and the bird detection algorithm can be basically performed synchronously with laser acquisition without delay.
Example two
The difference from the first embodiment is that the first threshold is calculated by the processing module according to the laser vertical angle resolution and the detection range, the vertical angle resolution is 0.18 °, the detection range takes 50m as an example, the detection range is taken as a radius, the vertical angle resolution is a central angle, and then the first threshold is (0.18 × pi/180) × 50 according to the fan-shaped arc length calculation formula; the second threshold value is obtained by multiplying and calculating the flying speed of the bird and the laser sampling period by the processing module, the bird detection module comprises a speed measurement unit, the speed measurement unit is used for measuring the flying speed of the bird, for example, the flying speed of the bird is 9m/s, and the flying speed of the bird can be 32-48 km/h of the flying speed of a common bird; the third threshold is determined by the processing module in a self-adaptive mode according to the size of the birds, suspected bird points are divided according to the size of the birds, for example, the size of the birds is 0.3m, the third threshold can be set to be 0.3m, interference factors of people, moving vehicles and the like are eliminated, accuracy of analyzing positions of the birds according to the suspected bird points in the follow-up mode is improved, the dead points of the suspected bird points in the first threshold range are searched, the interference factors are eliminated, the suspected bird points at the previous moment are searched according to the range determined by the flying speed of the birds, continuity is improved, and bird detection is more accurate.
The foregoing is merely an example of the present invention and common general knowledge of known specific structures and features of the embodiments is not described herein in any greater detail. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. Visit bird system based on laser radar, its characterized in that includes collection module, processing module and visits the bird module:
the acquisition module continuously acquires an environmental image of a target by a laser radar imaging method;
the processing module is used for acquiring an environment image to form a point cloud set and sending the point cloud set to the bird detection module;
the bird detection module filters the environment image and divides the environment image into dynamic points and static points, the bird detection module clusters the dynamic points by a clustering radius to obtain a dynamic point cloud subset, the bird detection module calculates a circumscribed sphere radius of the dynamic point cloud subset and takes point clouds with the circumscribed sphere radius smaller than a third threshold value as early stage suspected bird points, the bird detection module searches whether the early stage suspected bird points at the current moment exist in a second threshold value range at the previous moment, and the bird detection module judges that birds are searched when the early stage suspected bird points at the current moment do not exist in a first threshold value range.
2. The lidar based bird detection system of claim 1, wherein: the bird detection module comprises a filtering unit, wherein the filtering unit is used for filtering in the horizontal direction of each pixel point of the environment image through a filtering window, the filtering unit sends a static signal when the distance between the current time point cloud and the previous time point cloud in the filtering window is smaller than a first threshold value, and the filtering unit sends a dynamic signal when the distance between the current time point cloud and the previous time point cloud in the filtering window is larger than the first threshold value.
3. The lidar based bird detection system of claim 2, wherein: the bird detection module further comprises a tag unit, the processing module acquires static signals and dynamic signals and sends the static signals and the dynamic signals to the tag unit, the tag unit adds static tags to the current point cloud according to the static signals, the tag unit adds dynamic tags to the current point cloud according to the dynamic signals, the processing module forms a static point cloud set according to the static tags, and the processing module forms a dynamic point cloud set according to the dynamic tags.
4. The lidar based bird detection system of claim 3, wherein: the bird detection module further comprises a clustering unit, and the clustering unit clusters the dynamic point cloud set by a clustering radius to obtain a dynamic point cloud subset.
5. The lidar based bird detection system of claim 4, wherein: the bird detection module further comprises a first screening unit, the processing module finds out the circumscribed sphere radius of the set of the dynamic point cloud subsets and takes the point cloud with the circumscribed sphere radius smaller than a third threshold value as a previous suspected bird point, the first screening unit searches whether the previous suspected bird point at the current moment is a suspected bird point in a second threshold value range at the previous moment, and the first screening unit searches whether a static point is in a first threshold value range of the suspected bird point at the current moment and sends a confirmation signal to the processing module, and the processing module judges the target as a bird according to the confirmation signal.
6. The lidar based bird detection system of claim 5, wherein: the bird detection module further comprises a second screening unit, the processing module acquires the reflectivity of the reflected light of the acquisition module from the environment image and sends the reflectivity to the second screening unit, the second screening unit sends a noise point signal to the processing module when the reflectivity is smaller than a preset value, and the processing module records the point cloud as a noise point.
7. The lidar based bird detection system of claim 5, wherein: the clustering radius is obtained by calculation according to the distance between the target and the acquisition module, and the clustering radius is in direct proportion to the distance between the target and the acquisition module.
8. The lidar based bird detection system of claim 1, wherein: the third threshold is adaptively determined by the processing module based on bird size.
9. The lidar based bird detection system of claim 8, wherein: the first threshold is calculated by the processing module according to the vertical angular resolution of the laser and the detection range.
10. The lidar based bird detection system of claim 9, wherein: the bird detection module comprises a speed measurement unit, the speed measurement unit is used for measuring the flying speed of birds, and the second threshold value is calculated by the processing module according to the flying speed of the birds and the last moment.
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| CN111077539B (en) | 2023-06-02 |
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