A UAV FOD detection system based on radar and camera

Abstract

The present invention relates to the technical field of airport FOD detection, and more particularly to a radar- and camera-based unmanned aerial vehicle (UAV) FOD detection system, comprising a background central radar, a camera, and a detection UAV. The present invention optimizes radar detection when the UAV is equipped with the radar and camera. First, range migration correction is performed on the radar echo signal to compensate for interference with radar detection (echo) caused by the flight speed of the UAV equipped with the radar. Simultaneously, a secondary confirmation is performed on the radar detection. By comparing a large amount of data, secondary screening of FOD detection is performed, reducing invalid detections, increasing detection accuracy, and saving detection time. A fixed-focus camera is used to perform detailed identification of suspected FOD objects by category, size, risk level, etc. after preliminary radar detection, thereby improving detection efficiency and accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of airport FOD detection, and in particular to a radar and camera-based FOD detection system for unmanned aerial vehicles. Background Art

[0002] FOD (Foreign Object Debris), also known as foreign matter, debris, or objects, can damage aircraft. Examples include metal parts, tarpaulins, gravel, newspapers, bottles, luggage tags, plants, and animals. Runway FOD causes up to 4,000 tire failures nationwide each year, while thousands of runway incursions occur worldwide each year. Globally, runway FOD incurs direct losses at least $3-4 billion annually. With busy runways experiencing up to 30 takeoffs and landings per hour, manual monitoring alone is no longer sufficient to meet runway safety and maintenance requirements.

[0003] First, based on the degree of harm that FOD in the airfield may cause to the safe operation of aircraft, FOD in the airfield can be roughly divided into three categories: high-risk foreign objects, medium-risk foreign objects, and low-risk foreign objects. The specific classification of FOD hazard levels is as follows:

[0004] (1) High-risk foreign objects: metal parts, objects with sharp edges, heavy or extremely hard foreign objects that may cause serious damage to the aircraft;

[0005] (2) Medium-risk foreign objects: debris, plastic bottles, newspapers, packaging boxes, strapping tape, etc. that pose a certain threat to the safe operation of aircraft;

[0006] (3) Low-risk foreign objects: non-metallic debris, paper scraps, dead grass, leaves, etc. that have little impact on the safe operation of aircraft.

[0007] Currently, there are numerous FOD detection methods on the market, including drones, smart carts, low-pile edge lights, and track-based detection. However, there is a lack of technical solutions for efficient and accurate FOD detection. Therefore, this article proposes a hybrid detection mechanism combining radar and cameras to achieve accurate and efficient FOD detection. Summary of the Invention

[0008] In view of the shortcomings of the existing technology, the present invention provides a UAV FOD detection system based on radar and camera to solve the above problems.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0010] The present invention provides a UAV FOD detection system based on radar and camera, comprising

[0011] The backend center is used to control the issuance of instructions and the sending, receiving and storing of data. It also processes and stores the received data and displays it in the background.

[0012] Radar, used to form a radar detection coverage area, identify FOD in the area, generate a radar FOD detection report, and transmit the radar FOD detection report to the background center and camera;

[0013] A camera is used to form a camera detection coverage area, receive the FOD position coordinates sent by the radar, accurately identify the FOD under the position coordinates, generate a FOD event report, and forward the FOD event report to the backend center;

[0014] The detection drone is used to carry the radar and camera, communicate data with the background center, and control the operation of the camera and radar.

[0015] Furthermore, when the radar is detecting, the radar echo within the radar coverage area is corrected for range migration and then identified, and the result is output after comparing the sample echo data, thereby detecting the presence of the target FOD.

[0016] Furthermore, after the radar amplifies and transforms the radar echo within the radar detection coverage area, it performs a deep secondary precise judgment through a deep learning algorithm to confirm whether the FOD initially identified by the radar is real.

[0017] Furthermore, the radar makes a second accurate depth determination to confirm the true judgment of FOD, calculates the pitch and azimuth angle data, and uses the navigation data to obtain the FOD position coordinate information.

[0018] Furthermore, the lateral width of the radar detection coverage area and the camera detection coverage area is equal to the width of the airport runway, and the longitudinal width is determined by the specific detection task.

[0019] Furthermore, the radar detection coverage area and the camera detection coverage area move forward in a propulsive manner as the drone flies, and the radar detection coverage area is located directly in front of the camera detection coverage area, and the distance between them is n meters, where n is greater than 0 meter.

[0020] Furthermore, when the radar is a millimeter-wave radar, a plurality of millimeter-wave radars are arranged to jointly form the radar detection coverage area; when the radar is a multi-band radar, the radar detection coverage area is formed by the collaboration of multiple bands.

[0021] Furthermore, when the camera is a monocular camera, the camera detection coverage area is formed by arranging multiple monocular cameras together. When the camera is a multi-camera camera, the camera detection coverage area is formed by collaborating multiple camera lenses.

[0022] Furthermore, after receiving the FOD event report, the background center controls the cleaning drone to perform FOD cleaning operations.

[0023] The present invention provides a radar- and camera-based FOD detection system for drones. This technology optimizes radar detection when the drone is equipped with a radar and a camera. First, range migration correction is performed on the radar echo signal to compensate for interference with radar detection (echo) caused by the flight speed of the drone equipped with the radar. At the same time, a secondary confirmation is performed on the radar detection. By comparing a large amount of data, secondary screening of FOD detection is performed, which reduces invalid detections, increases detection accuracy, and saves detection time. A fixed-focus camera is used to finely identify the category, size, risk level, etc. of suspected FOD objects after preliminary radar detection, thereby improving detection efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 This is a block diagram of the FOD detection system for drones based on radar and camera;

[0026] Figure 2 It is the implementation flow chart of the UAV FOD detection system based on radar and camera. Implementation Method

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention. Example

[0028] Reference Figure 1As shown, this embodiment provides a UAV FOD detection system based on radar and camera, including a background center for controlling the issuance of instructions and the transmission, reception and storage of data, and storing the received data after processing and displaying it in the background.

[0029] This embodiment is also provided with a radar for forming a radar detection coverage area, and identifying the FOD in the area to generate a radar FOD detection report and FOD position coordinates, and at the same time transmitting the radar FOD detection report to the background center and the FOD position coordinates to the camera.

[0030] This embodiment is also provided with a camera for forming a camera detection coverage area, receiving the FOD position coordinates sent by the radar, and accurately identifying the FOD under the position coordinates to generate a FOD event report, and at the same time forwarding the FOD event report to the background center.

[0031] This embodiment also provides a detection drone for carrying radar and camera, communicating data with the background center, and controlling the operation of the camera and radar.

[0032] This embodiment performs a secondary confirmation on the radar detection, and performs secondary screening of FOD detection by comparing a large amount of data, thereby reducing invalid detections, increasing detection accuracy, and saving detection time. The fixed-focus camera is used to perform fine identification of the category, size, risk level, etc. of suspected FOD objects after the initial radar detection, thereby improving detection efficiency and accuracy. Example

[0033] Based on Example 1, this embodiment chooses to use a multi-band radar to form a radar detection coverage area through the collaboration of multiple bands. When the multi-band radar performs detection, the radar echo within the radar coverage area is corrected for distance migration and then identified, and the result is output after comparing the sample echo data, thereby detecting the presence of target FOD.

[0034] As a preferred embodiment of this embodiment, the multi-band radar of this embodiment amplifies and transforms the radar echo within the radar detection coverage area, and then performs a deep secondary precise judgment through a deep learning algorithm to confirm whether the FOD initially identified by the radar is real.

[0035] In this embodiment, the multi-band radar makes a second accurate depth determination to confirm the true judgment of FOD, calculates the pitch and azimuth angle data, and uses the navigation data to obtain the FOD position coordinate information.

[0036] When optimizing this embodiment, the radar detection coverage area is set to 45 meters to 60 meters, which is preferably enough to cover the width of the entire runway.

[0037] This embodiment chooses to use a multi-camera, and forms a camera detection coverage area through the collaboration of multiple camera lenses. According to the FOD position coordinate information detected by the multi-band radar of this embodiment, accurate detection is performed through an algorithm, and then a FOD event report is generated.

[0038] When optimizing this embodiment, the camera detection coverage area is set to 45 meters to 60 meters, and in principle it is best to cover the width of the entire runway.

[0039] In this embodiment, the radar detection coverage area and the camera detection coverage area move forward in a propulsive manner as the drone flies, and the radar detection coverage area is located directly in front of the camera detection coverage area.

[0040] In this embodiment, after receiving the FOD event report, the backend center controls the cleaning drone to perform FOD cleaning operations. Example

[0041] Based on Example 1, this embodiment chooses to use millimeter-wave radar, and arranges multiple millimeter-wave radars to jointly form a radar detection coverage area. When the millimeter-wave radar performs detection, the radar echo within the radar coverage area is corrected for distance migration and then identified, and the result is output after comparing the sample echo data, thereby detecting the presence of target FOD.

[0042] As a preferred embodiment of this embodiment, the millimeter-wave radar of this embodiment amplifies and transforms the radar echo within the radar detection coverage area, and then performs a deep secondary precise judgment through a deep learning algorithm to confirm whether the FOD initially identified by the radar is real.

[0043] In this embodiment, the millimeter-wave radar accurately determines the depth twice to confirm the true judgment of FOD, calculates the pitch and azimuth angle data, and uses the navigation data to obtain the FOD position coordinate information.

[0044] When optimizing this embodiment, the radar detection coverage area is set to 45 meters to 60 meters, which is preferably enough to cover the width of the entire runway.

[0045] This embodiment chooses to use a monocular camera. By arranging multiple monocular cameras to jointly form a camera detection coverage area, based on the FOD position coordinate information detected by the multi-band radar of this embodiment, accurate detection is performed through an algorithm to generate a FOD event report.

[0046] When optimizing this embodiment, the camera detection coverage area is set to 45 meters to 60 meters, and in principle it is best to cover the width of the entire runway.

[0047] In this embodiment, the radar detection coverage area and the camera detection coverage area move forward in a propulsive manner as the drone flies, and the radar detection coverage area is located directly in front of the camera detection coverage area.

[0048] In this embodiment, after receiving the FOD event report, the backend center controls the cleaning drone to perform FOD cleaning operations.

[0049] In summary, the present invention optimizes radar detection when the drone is equipped with a radar and a camera. First, the radar echo signal is corrected for distance migration, thereby compensating for the interference of the flight speed on the radar detection (echo) when the drone is equipped with a radar. At the same time, the radar detection is reconfirmed. By comparing a large amount of data, a secondary screening of FOD detection is performed, which reduces invalid detections, increases detection accuracy and saves detection time. The fixed-focus camera is used to perform fine identification of the category, size, risk level, etc. of suspected FOD objects after preliminary radar detection, thereby improving detection efficiency and accuracy.

[0050] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0051] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A radar and camera-based UAV FOD detection system, characterized by: include: The backend center is used to control the issuance of instructions and the sending, receiving and storing of data. It also processes and stores the received data and displays it in the background. Radar, used to form a radar detection coverage area, identify FOD in the area, generate a radar FOD detection report, and transmit the radar FOD detection report to the background center and camera; When the radar is detecting, it performs range migration correction on the radar echo within the radar coverage area and then identifies it. It outputs the result after comparing the sample echo data, thereby detecting the presence of target FOD. After the radar amplifies and transforms the radar echo within the radar detection coverage area, it uses a deep learning algorithm to perform a second, accurate judgment to confirm whether the FOD initially identified by the radar is real. A camera is used to form a camera detection coverage area, receive the FOD location coordinates sent by the radar, and accurately identify the FOD under the location coordinates by type, size, and risk level to generate a FOD event report, and transmit the FOD event report to the backend center; The radar detection coverage area and the camera detection coverage area move forward in a propulsive manner as the UAV flies, and the radar detection coverage area is located directly in front of the camera detection coverage area, and the distance between them is n meters, where n is greater than 0 meters; The detection drone is used to carry the radar and camera, communicate data with the background center, and control the operation of the camera and radar.

2. The radar and camera-based UAV FOD detection system according to claim 1, characterized in that: The radar makes a second accurate depth determination to confirm the true judgment of FOD, calculates the pitch angle and azimuth angle data, and uses the navigation data to obtain the FOD position coordinate information.

3. The radar and camera-based FOD detection system for drones according to claim 1, characterized in that: The lateral width of the radar detection coverage area and the camera detection coverage area is equal to the width of the airport runway, and the longitudinal width is determined by the specific detection task.

4. The radar and camera-based UAV FOD detection system according to claim 1, characterized in that: When the radar is a millimeter-wave radar, the radar detection coverage area is formed by arranging multiple millimeter-wave radars together. When the radar is a multi-band radar, the radar detection coverage area is formed by the collaboration of multiple bands.

5. The radar and camera-based UAV FOD detection system according to claim 1, characterized in that: When the camera is a monocular camera, the camera detection coverage area is formed by arranging multiple monocular cameras together. When the camera is a multi-camera camera, the camera detection coverage area is formed by the collaboration of multiple camera lenses.

6. The radar and camera-based FOD detection system for drones according to claim 1, characterized in that: After receiving the FOD event report, the background center controls the cleaning drone to perform FOD cleaning operations.

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