A Method for Detecting the Planar Morphology of the Surge Front Based on Multiple Unmanned Aerial Vehicles

Abstract

The present invention discloses a tidal bore plane morphology detection method based on multiple unmanned aerial vehicles. Aiming at the problems of limited shooting range of tidal bore and inability to cover and detect the whole picture of tidal bore morphology in single unmanned aerial vehicle operation in existing tidal bore observation, the present invention designs a tidal bore plane morphology detection method based on multiple unmanned aerial vehicles, and constructs a Qiantang River tidal bore collaborative shooting platform composed of a multi-rotor unmanned aerial vehicle module, a pan-tilt camera module, an onboard computer module NUC, a flight control module, an ad hoc network module and a ground station module. The pan-tilt camera transmits the captured image to the NUC, which first runs a splicing algorithm to synchronously splice the images, and then runs a tracking algorithm to keep dynamic tidal bore tracking in real time. With the help of the tidal bore observation method of multi-unmanned aerial vehicle photogrammetry, it is possible to continuously track and observe the tidal bore in a large scale. The method has the advantages of high work efficiency, high safety, convenience and speed, continuous observation and a large tidal bore coverage.

Description

Technical Field

[0001] The present invention belongs to the field of marine information, and relates to a method for detecting tidal bores, in particular to a method for detecting the planar shape of the tidal bore front based on multiple unmanned aerial vehicles. Background Art

[0002] A tidal bore is a rare natural landscape, and its huge energy has an important impact on estuarine processes and also affects shipping and the estuarine ecosystem. However, due to the rapid onset, fast traveling speed, and great difficulty in observation of tidal bores, the research on tidal bores is still very limited so far. The typical tidal bore is the Qiantang River tidal bore in China. The estuary of the Qiantang River has strong tides and rapid currents, with surging waves, a wide and shallow riverbed, rich external sand in the sea area, easy erosion and deposition of sediment, frequent swing of the main channel, and a large amplitude of riverbed erosion and deposition. Based on the observation of the tidal bore phenomenon, the ancients conducted a long-term exploration of the formation and propagation mechanism of tidal bores. With the development of modern physical science, especially fluid mechanics, a scientific theoretical explanation has been given for the formation, development, and change mechanism of tidal bores, and advanced hydrodynamic observation instruments are constantly verifying these theories. Fixed-point hydrodynamic observation equipment can generally only observe the tidal bore height or flow velocity at one point or one vertical line, which is very suitable for the study of the tidal bore dynamic mechanism. However, the information volume of data at limited points is still very limited for the study of the overall shape of tidal bores. The construction of the Zhan'ao Pagoda in Yanguan Town, although out of awe of nature and gods, objectively also increases the visual height for observing tidal bores, with a larger observation range and a farther observation distance for tidal bores, but it is far from providing comprehensive data support for the study of the morphological characteristics of the Qiantang River tidal bore.

[0003] In addition to the characteristics of flow, the tidal bore also has the characteristics of waves, and the propagation of waves is affected by boundary conditions such as terrain, shoreline and wind. For example, water depth affects the shape and advancing speed of the tidal bore, and wind direction can either stimulate or suppress the tidal bore. By means of the tidal bore observation method using multi-UAV photogrammetry, the morphological changes of the tidal bore in the continuous space-time during the propagation process in the river channel can be obtained. At the same time, combined with conditions such as runoff, terrain and wind, it can provide rich information support for the study of the propagation law of the tidal bore; the research results are also of great significance for the design of flood control and tidal protection dams and the reinforcement of weak links in seawalls. The change of the shoreline boundary will lead to various morphological characteristics of the tidal bore, such as the single-line bore in Haining, the cross bore near Jianshan, the turning bore at the Laoyancang Dam and the Mach knot in the Zheshan Bay section. By means of the tidal bore observation method using multi-UAV photogrammetry, it is helpful to study the morphological changes and propagation law of the tidal bore in these special river sections; During the Tang and Song dynasties, the trend of watching the tidal bore was most popular in the Hangzhou area. In the Ming and Qing dynasties, it moved down to Yanguan, Haining. From September 3 to September 5, 2020, the Zhejiang Qiantang River Tidal Bore Research Association organized a group of tidal bore research experts from units such as the Zhejiang Qiantang River Basin Center and the Zhejiang Institute of Hydraulics and Estuary to conduct a field investigation of the starting point of the Qiantang River tidal bore. Compared with 2010, the current starting point of the tidal bore has moved about 5 km further east and is located east of the line between the Huangshawu Drainage Sluice in Haiyan and the Linhaipu Sluice in Yuyao. The starting point of the tidal bore is affected not only by the periodic changes of the lunar syzygy, but also by the comprehensive influence of various factors such as upstream runoff, river channel terrain and wind.

[0004] At present, the main methods for observing the Qiantang River tidal bore are the near-shore fixed tide gauge and the sea-based X-band radar. The fixed tide gauges distributed on both sides of the Qiantang River provide real-time data of all elements such as the height, shape, advancing speed, tide level, pressure, flow velocity, sediment concentration and riverbed erosion and deposition of the tidal bore through automated monitoring equipment, filling the gap in the automatic observation of the tidal bore in the strong tidal estuary; The search radius of the X-band radar exceeds 20 km, and it can record the morphological and propagation characteristics of the tidal bore within a range of more than 20 km, overcoming the limitations of single-point observation of traditional tidal bore observation stations. However, the above-mentioned observation methods are all single-point observation, vertical observation or local shore observation, and cannot meet the observation requirements of continuous tracking of the large-scale range and morphological changes of the Qiantang River tidal bore and dynamic extraction of the morphological characteristics of the tidal bore.

[0005] In view of the above problems, the present invention constructs a collaborative shooting and photographic observation platform for the Qiantang River tidal bore based on a multi-UAV ad hoc network, and designs a method for detecting the planar shape of the tidal bore head based on multiple UAVs. The observation platform includes a multi-rotor UAV flight module, a gimbal camera module, an on-board computer module NUC, a flight control module, an ad hoc network module, and a ground station module. By means of modern technical means such as UAVs, photogrammetry, and artificial intelligence, functions such as collaborative shooting, image processing, and automatic tracking of the tidal bore are realized. The gimbal camera module transmits the real-time photographed tidal bore photos or videos to the on-board computer module. The NUC uses image processing technology to splice the acquired images, identify the tidal bore line, and then runs a tidal bore tracking algorithm to calculate the current traveling speed of the tidal bore, and then feeds it back to the flight control system to intelligently adjust the UAV flight speed to ensure that the UAV is always directly above the tidal bore. Finally, intelligent tracking observation of the tidal bore by multiple UAVs is realized. During the process of the UAV tracking the tidal bore, it will send a photographing instruction to the gimbal camera module at a fixed distance, and at the same time share the flight data, photographed photos and videos, ground station control instructions, etc. of each UAV; the ground station monitors various state data during the flight of each UAV in real time to ensure flight safety and send control commands. With the method for detecting the planar shape of the tidal bore head based on multiple UAVs, it is possible to continuously observe the spatio-temporal morphological changes of the tidal bore during its propagation in the river channel within a large scale range. At the same time, combined with environmental conditions such as river channel runoff, terrain, and wind, the propagation law of the Qiantang River tidal bore can be explored, the accuracy of tidal bore forecasting can be improved, and scientific basis and technical support are provided for estuary flood control and tide prevention, seawall reinforcement, and tidal bore tourism, etc. Summary of the Invention

[0006] The purpose of the present invention is to make up for the limitations of single-point observation of existing tidal bore observation stations, the limited tidal bore shooting range, limited payload, and low work efficiency of single-UAV operations. Combining multi-UAV collaborative shooting and image processing methods, a method for detecting the planar shape of the tidal bore head based on multiple UAVs is proposed. Based on modern technical means such as UAVs, photogrammetry, and artificial intelligence, the multi-rotor UAV flight module, gimbal camera module, on-board computer module NUC, flight control module, ad hoc network module, and ground station module are innovatively integrated to achieve continuous tracking observation of the tidal bore within a large scale range. This method has the advantages of high work efficiency, high safety, convenience, quickness, continuous observability, and large tidal bore coverage.

[0007] A method for detecting the planar shape of the tidal bore head based on multiple UAVs, the process is as Figure 1 shown, and includes the following steps:

[0008] Step 1: Power-on self-check of each module. Power on and perform self-check on the UAV module, gimbal camera module, NUC, ad hoc network module, and ground station module;

[0009] Step 2: Collect initial waypoints, and the flight control module generates waypoint information for each waypoint;

[0010] Step 3: The ground station controls each UAV to take off to the initial waypoint, hover, and adjust the attitude;

[0011] Step 4: When the tidal bore enters the field of view of the pan-tilt camera, the UAV switches to the tidal bore photography mode, uses the pan-tilt camera module to collect tidal bore images, and transmits them to the NUC module in real time;

[0012] Step 5: The NUC module runs the tidal bore stitching algorithm to synchronously stitch the tidal bore images;

[0013] Step 6: The NUC module runs the tracking algorithm to continuously maintain dynamic tidal bore tracking in real time;

[0014] Step 7: At every given distance interval, the flight control module sends a photo-taking command to the pan-tilt camera module, and repeats Steps 4 - 6;

[0015] Step 8: When the task is completed, each UAV returns.

[0016] The specific steps in Step 1 are as follows: Turn on the aircraft, connect the mobile device to the APP, enter the video transmission interface, click on the top of the video transmission interface to enter the aircraft status list, where you can see the module self-check and the status of each module of the aircraft. Pay special attention to checking whether there are abnormalities in the module self-check, compass, IMU, ESC status, and gimbal status.

[0017] The detailed steps of Step 2 are as follows: Send the initial coordinates, desired heading, desired distance, and the number of UAVs to the ad-hoc network module through the ground station node, and then the ad-hoc network module distributes them to all UAV nodes. The flight control module of each UAV node runs the waypoint generation algorithm to generate waypoint information.

[0018] The detailed steps of Step 3 are as follows: Before the tidal bore arrives, send a "takeoff" control command to the ad-hoc network module through the ground station module. Each UAV node will fly to hover above the starting point of the mission according to the generated waypoint information, and adjust the attitude of the UAV and control the three-axis aerial photography angle of the pan-tilt camera module.

[0019] The detailed steps of Step 4 are as follows: Turn on the pan-tilt camera carried by the UAV and wait for the tidal bore to arrive. When the tidal bore enters the field of view of the pan-tilt camera, the ground station switches the flight mode of the UAV to the tidal bore photography mode. The pan-tilt camera module collects tidal bore images in the photography mode and transmits the collected tidal bore images to the NUC module in real time.

[0020] The detailed steps of Step 5 are as follows: The NUC module runs the tidal bore stitching algorithm to synchronously stitch the tidal bore images collected by each UAV along the width direction of the tidal bore. The specific steps of the tidal bore stitching algorithm are as follows:

[0021] 5-1: First, load the image and remove the environmental noise to lay the foundation for subsequent image registration;

[0022] 5-2: Then, use the invariant-based SIFT algorithm for image registration;

[0023] 5-3: Next, use the brute-force matching method to match the feature points of the tidal bore;

[0024] 5-4: Then, use the RANSAC algorithm to eliminate the false matches of the feature points;

[0025] 5-5: Finally, use the method of weighted pixel distance to fuse the stitched images.

[0026] The detailed steps of step 6 are as follows: The NUC module runs the tidal bore tracking algorithm to calculate the current advancing speed of the tidal bore, and then feeds it back to the flight control system to intelligently adjust the flight speed of the UAV to ensure that the UAV is always directly above the tidal bore, and finally realizes the intelligent tracking observation of the tidal bore by multiple UAVs. The detailed steps of the tidal bore tracking algorithm are as follows: 6-1: First, grayscale the stitched tidal bore image, then use median filtering to eliminate the noise in the image, then use the edge detection algorithm to obtain a binary image, after edge dilation, extract the contour information of the image through the findContours function, and select the contour with the largest area as the contour of the tidal bore head to be obtained. Finally, set the pixel points in this area to 255, that is, white, and the pixel points in other places to 0, that is, black;

[0027] 6-2: Calculate the advancing speed of the tidal bore. The calculation formula for the advancing speed of the tidal bore is as follows:

[0028] V = ΔX / Δt * GSD

[0029] In the formula, ΔX is the displacement difference of pixel points in the X-axis direction, Δt is the time difference between taking two pictures, and GSD is the ground resolution of the image. It is assumed that the tidal bore advances in the X-axis direction;

[0030] 6-3: Send the advancing speed of the tidal bore to the flight control module, and after being processed by the flight control algorithm, output a control signal to control the UAV to achieve tidal bore tracking.

[0031] The specific steps of step 8 are as follows: When the detection task is completed, send a "return" control command through the ground station, and all UAVs return to the take-off point autonomously in turn, and the task ends.

[0032] The beneficial effects of the present invention are as follows:

[0033] The present invention extends the single UAV tracking and observing of tidal bores to multi-UAV tracking and observing of tidal bores, which solves to a certain extent the disadvantages of single UAV operation, such as limited shooting range of tidal bores, restricted terrain environment, limited carried payload, low working efficiency, etc. It has a larger photographing field of view, can realize the overall detection of the large-range tidal bore morphology, and provides more comprehensive data for the study of the propagation law of tidal bores.

[0034] The present invention realizes the rapid transmission and sharing of information among multi-UAVs through multi-UAV ad hoc network technology, completes the large-range monitoring of the tidal bore reach, and can achieve dead-angle-free coverage through multi-aircraft relay when line-of-sight communication falls into the blind area.

[0035] The present invention does not require the setting of fixed tide gauges at the near-shore points of the tidal bore reach, belongs to a non-contact observation method, and has high observation safety, which is extremely important for the observation of tidal bores with strong power and great destructive power.

[0036] The present invention uses multi-UAVs as the observation platform, and utilizes the mutual cooperation of multi-UAVs to complete the tracking and observation of tidal bores. The multi-UAV ad hoc network structure can effectively prevent the collision of members within the cluster, effectively coordinate each member, and thus complete various tasks. Therefore, the tidal bore observation is more convenient and fast, and the working efficiency is higher.

[0037] The multi-UAVs of the present invention always maintain synchronous flight with the tidal bore front, so the present invention can perform dynamic and continuous tidal bore tracking and observation.

[0038] The multi-UAV ad hoc network of the present invention makes the relationship between all UAV clusters no longer a simple chain structure. Even if any link in the chain fails, the entire UAV system will not be paralyzed, and the anti-interference ability of the multi-UAVs during flight has been greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is the flowchart of the method for detecting the planar morphology of the tidal bore front based on multi-UAVs;

[0040] Figure 2 is the flowchart of the tidal bore image stitching;

[0041] Figure 3 is the stitched tidal bore image;

[0042] Figure 4 is the identification diagram of the tidal bore front line;

[0043] Figure 5 is the flowchart of the identification of the tidal bore front line. DETAILED DESCRIPTION OF THE INVENTION

[0044] The present invention will be further clarified below in conjunction with the drawings and specific embodiments.

[0045] Step 1: Turn on the aircraft, connect the mobile device to the APP, enter the video transmission interface, click on the top of the video transmission interface to enter the aircraft status list, where you can view the module self-check and the status of each module of the aircraft. Pay special attention to checking whether there are any abnormalities in the module self-check, compass, IMU, ESC status, and gimbal status;

[0046] Step 2: Send the initial coordinates, desired heading, desired distance, and the number of drones to the ad-hoc network module through the ground station node, and then the ad-hoc network module distributes them to all drone nodes. The flight control module of each drone node runs the waypoint generation algorithm to generate waypoint information;

[0047] Step 3: Before the tidal bore arrives, send the "takeoff" control command to the ad-hoc network module through the ground station module. Each drone node will fly to hover above the starting point of the mission one by one according to the waypoint information generated in Step 2, and adjust the attitude of the drone and control the three-axis aerial photography angle of the gimbal camera module;

[0048] Step 4: Turn on the gimbal camera carried by the drone and wait for the tidal bore to arrive. When the tidal bore enters the field of view of the gimbal camera, the ground station switches the flight mode of the drone to the tidal bore photography mode. The gimbal camera module collects tidal bore images in the photography mode and transmits the collected tidal bore images to the NUC module in real time;

[0049] Step 5: The NUC module runs the tidal bore stitching algorithm to synchronously stitch the tidal bore images collected by each drone in the width direction of the tidal bore in Step 3. The specific steps of the tidal bore stitching algorithm are as follows: 5-1: First, load the images and use median filtering to eliminate the noise in the images to lay the foundation for subsequent image registration; 5-2: Then, use the invariant SIFT algorithm for image registration, establish the DOG scale space, extract the key points in the scale space, and generate the feature point descriptors of the reference image and the image to be registered. The reference image and the image to be registered are as Figure 2 shown in (a) of Figure 2 ;

[0050] 5-3: Then, use the brute-force matching method to match the tidal bore feature points. Calculate the distance between a certain feature point descriptor and all other feature point descriptors, and then sort the obtained distances. Take the one with the closest distance as the matching point. By sorting the distances of all matching sets, select the 50 with the closest distances as the matching point set;

[0051] 5-4: Use the RANSAC algorithm to eliminate the false matching of feature points during the matching process. The image matching and stitching effect is as Figure 2 shown in (c) of

[0052] 5-5: Finally, the method of weighting the distance between pixels is adopted to fuse the spliced images, eliminate problems such as exposure differences existing between the spliced image sequences, improve the quality of the panoramic image, and the splicing result is as shown in Figure 3 as follows.

[0053] Step 6: The NUC module runs the tidal bore tracking algorithm to calculate the current traveling speed of the tidal bore, and then feeds it back to the flight control system to intelligently adjust the flight speed of the UAV, so as to ensure that the UAV is always directly above the tidal bore, and finally realize the intelligent tracking observation of the tidal bore by multiple UAVs. The detailed steps of the tidal bore tracking algorithm are as follows: 6-1: First, grayscale the spliced tidal bore image, and the effect is as shown in Figure 5 (a) of the figure. Then, use median filtering to eliminate the noise in the image, and the effect is as shown in Figure 5 (b) of the figure. Then, use the edge detection algorithm to obtain a binary image, and the effect is as shown in Figure 5 (c) of the figure. Then, perform edge dilation on the binary image, and the effect is as shown in Figure 5 (d) of the figure. Finally, extract the contour information of the image through the findContours function, and screen out the contour with the largest area, which is the contour of the tidal bore head to be obtained. Set the pixel points in this area to 255, that is, white, and the pixel points in other places to 0, that is, black. The recognition effect of the tidal bore line is as shown in Figure 4 as follows.

[0054] 6-2: Calculate the traveling speed of the tidal bore. The calculation formula for the traveling speed of the tidal bore is as follows:

[0055] V = ΔX / Δt * GSD

[0056] In the formula, ΔX is the displacement difference of pixel points in the X-axis direction, Δt is the time difference between taking two pictures, and GSD is the ground resolution of the image. Assume that the tidal bore advances in the X-axis direction;

[0057] 6-3: Send the traveling speed of the tidal bore to the flight control module. After being processed by the flight control algorithm, a control signal is output to control the UAV to achieve tidal bore tracking.

[0058] Step 7: At intervals of a given distance, the flight control module sends a photo-taking instruction to the pan-tilt camera module, and repeat the above steps 4-step 6;

[0059] Step 8: When the detection task is completed, send a "return" control instruction through the ground station, and all UAVs return to the take-off point autonomously in sequence, and the task ends.

[0060] The above are the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, who makes changes or substitutions according to the technical solution of the present invention, shall be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles, characterized in that, It includes the following steps: Step 1: Power on and perform self-check on each module, including the drone module, gimbal camera module, NUC, ad-hoc network module, and ground station module; Step 2: Collect initial waypoints, and the flight control module generates waypoint information for each; Step 3: The ground station controls each drone to take off to the initial waypoint and hover, and adjusts the attitude; Step 4: When the tidal bore enters the field of view of the gimbal camera, the drone switches to the tidal bore photography mode, uses the gimbal camera module to collect tidal bore images, and transmits them to the NUC module in real time; Step 5: The NUC module runs the tidal bore stitching algorithm to synchronously stitch the tidal bore images; Step 6: The NUC module runs the tracking algorithm to maintain real-time dynamic tidal bore tracking; Step 7: At intervals of a given distance, the flight control module sends a photo-taking command to the gimbal camera module, and repeats Steps 4 - 6; Step 8: The task is completed, and each drone returns; The specific steps of the tidal bore stitching algorithm are as follows: 1-1: First, load the images, and use median filtering to eliminate the noise in the images, laying a foundation for subsequent image registration; 1-2: Then, use the invariant-based SIFT algorithm for image registration, establish a DOG scale space, extract key points in the scale space, and generate feature point descriptors for the reference image and the image to be registered; 1-3: Then, use the brute-force matching method to match the tidal bore feature points, calculate the distance between a certain feature point descriptor and all other feature point descriptors, sort the obtained distances, take the one with the closest distance as the matching point, and select the 50 with the closest distances as the matching point set by sorting the distances of all matching sets; 1-4: Use the RANSAC algorithm to eliminate the false matching of feature points during the matching process; 1-5: Finally, use the method of weighted pixel distance to fuse the stitched images, eliminate problems such as exposure differences between the stitched image sequences, and improve the quality of the panoramic image; The specific steps of Step 6 are as follows: The NUC module runs the tidal bore tracking algorithm, calculates the current traveling speed of the tidal bore, and then feeds it back to the flight control system to intelligently adjust the flight speed of the drone, so as to ensure that the drone is always directly above the tidal bore, and finally realizes the intelligent tracking observation of the tidal bore by multiple drones.

2. The method for detecting the planar shape of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, wherein The specific steps of Step 1 are as follows: Turn on the aircraft, connect the mobile device to the APP, enter the video transmission interface, click on the top of the video transmission interface to enter the aircraft status list, and you can see the module self-check and the status of each module of the aircraft. Focus on checking whether there are abnormalities in the module self-check, compass, IMU, ESC status, and gimbal status.

3. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, characterized in that, The specific steps of Step 2 are as follows: Send the initial coordinates, desired heading, desired distance, and the number of drones to the ad-hoc network module through the ground station node, and then the ad-hoc network module distributes them to all drone nodes. The flight control module of each drone node runs the waypoint generation algorithm to generate waypoint information.

4. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, characterized in that, The specific steps of step 3 are as follows: Before the tidal bore arrives, the ground station module sends a "takeoff" control command to the ad hoc network module. Each UAV node will fly to hover above the starting point of the mission on the river surface in sequence according to the generated waypoint information, and adjust the attitude of the UAV and control the three-axis aerial photography angle of the gimbal camera module.

5. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, characterized in that The specific steps of step 4 are as follows: Turn on the gimbal camera carried by the UAV and wait for the tidal bore to arrive. When the tidal bore enters the field of view of the gimbal camera, the ground station switches the flight mode of the UAV to the tidal bore photography mode. The gimbal camera module collects tidal bore images in the photography mode and transmits the collected tidal bore images to the NUC module in real time.

6. The method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, wherein The specific steps of step 5 are as follows: The NUC module runs the tidal bore stitching algorithm to synchronously stitch the tidal bore images collected by each UAV along the width direction of the tidal bore.

7. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, characterized in that, The specific steps of the tidal bore tracking algorithm are as follows: 7-1: First, perform grayscale processing on the stitched tidal bore image, then use median filtering to eliminate the noise in the image, then use the edge detection algorithm to obtain a binary image, then perform edge dilation on the binary image, and finally extract the contour information of the image through the findContours function. The contour with the largest area is selected as the contour of the tidal bore head to be obtained. Set the pixel points of the contour of the tidal bore head to 255, that is, white, and the pixel points in other places to 0, that is, black; 7-2: Calculate the advancing speed of the tidal bore. The calculation formula for the advancing speed of the tidal bore is as follows: V = ΔX / Δt * GSD In the formula, ΔX is the displacement difference of pixel points in the X-axis direction, Δt is the time difference between taking two pictures, and GSD is the ground resolution of the image. Assume that the tidal bore advances in the X-axis direction; 7-3: Send the advancing speed of the tidal bore to the flight control module. After being processed by the flight control algorithm, a control signal is output to control the UAV to achieve tidal bore tracking.

8. A method for detecting the planar morphology of the tidal bore front based on multiple unmanned aerial vehicles according to claim 1, characterized in that, The specific steps of step 8 are as follows: When the detection task is completed, send a "return" control instruction through the ground station. All UAVs return to the takeoff point autonomously in sequence, and the task ends.

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