Monocular vision towed target attitude measurement equipment and method

Abstract

The invention belongs to the field of optical measurement, and particularly relates to monocular vision towed target attitude measurement equipment and a monocular vision towed target attitude measurement method, and the monocular vision towed target attitude measurement equipment comprises a cooperation identifier, an industrial camera, a cable and an image real-time tracking processing system, the industrial camera and the image real-time tracking processing system are both arranged on the winch, the industrial camera is connected with the image real-time tracking processing system through a cable, the view field direction of the industrial camera covers the towed target, and the industrial camera is used for shooting a towed target image containing the towed target and a cooperation identifier and sending the towed target image to the image real-time tracking processing system; the cooperation identifier is arranged around the towed target in a spraying manner and is used as a towed target image identifier of the towed target shot by the industrial camera; and the image real-time tracking processing system is used for receiving the towed target image returned from the industrial camera through the cable and processing and calculating the towed target image to obtain a real-time attitude angle value of the towed target and the cooperation identifier. The system has the characteristics of non-contact measurement, simple layout, high precision, high real-time performance, low cost and automatic measurement.

Description

Technical Field

[0001] The invention belongs to the field of optical measurement, in particular to a monocular vision target dragging posture measurement device and method. Background Art

[0002] The towed target can simulate the physical and motion characteristics of the target, and is reusable, with high target supply flight rate, short test cycle, high target supply efficiency, etc. It has good economy and high practical value, and is widely used in test identification and operation training. The towed target attitude is an important indicator, which requires accurate measurement of the target attitude, assessing whether the towed target attitude has an impact on flight safety, and reporting it to the host in a timely manner to take safety measures.

[0003] Currently, the measurement of towed target attitude is mainly carried out by collecting the internal sensor signals of the towed target and transmitting them through wireless communication. This has the disadvantages of low access data rate and long delay. In addition, during high-speed flight, the signal is unstable and cannot provide reliable target attitude information. Summary of the invention

[0004] The purpose of the present invention is to provide a device and method for measuring the towed target posture with monocular vision. The towed target posture is measured by monocular vision, and the towed target posture can be measured quickly, accurately and stably. The device is suitable for situations where multi-camera shooting is not possible, and the method has good flexibility and practicality, so as to overcome the defects of the above-mentioned towed target posture measurement.

[0005] The technical solution adopted by the present invention to achieve the above-mentioned purpose is: a monocular vision towed target posture measurement device, including: a cooperation mark, an industrial camera, a cable and an image real-time tracking and processing system;

[0006] The towed target is connected to the rotating roller of the winch through a tow rope to drag the towed target to move;

[0007] The industrial camera and the real-time image tracking and processing system are both arranged on the winch, the industrial camera is connected to the real-time image tracking and processing system via a cable, and the field of view of the industrial camera covers the towed target, and is used to capture the towed target image including the towed target and the cooperation mark, and send it to the real-time image tracking and processing system;

[0008] The cooperation logo is sprayed around the tow target and is used as a tow target image logo for an industrial camera to shoot the tow target;

[0009] The image real-time tracking and processing system is used to receive the towed target image transmitted back from the industrial camera through a cable, and process and calculate the towed target image to obtain the real-time posture angle value of the towed target and the cooperation mark.

[0010] The cooperation logo is a spray paint icon, and the spray paint color forms a contrast with the color of the drag target itself;

[0011] The cooperation logo is sprayed around the middle and upper middle part of the tow target.

[0012] The image real-time tracking and processing system comprises: an FPGA module, a SOC processing module, and a main control terminal;

[0013] The FPGA module is used to detect whether the image data is normal and feed it back to the main control terminal. At the same time, it receives the original image from the industrial camera for filtering and converts the YCbCr format to RGB format in real time; encodes the image data stream according to the set timing and sends it to the SOC processing module through the HDMI interface;

[0014] The SOC processing module is connected to the main control terminal through the RS-422 serial port to receive the measurement instructions of the main control terminal, control the industrial camera to adjust the camera exposure time and gain, and receive the processed drag target image sent by the FPGA module to crop and cache the image, perform threshold calculation and segmentation on the drag target image in real time, extract the cooperation mark edge, and perform face-to-face intersection calculation to obtain the attitude angle of the drag target, and transmit it back to the main control terminal for data display;

[0015] The main control terminal is used to receive the image data feedback from the FPGA module and issue measurement instructions to the SOC processing module according to the feedback information; at the same time, it receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

[0016] The cable is a 3G-SDI cable, which is used to provide image information transmission that meets the requirements of 1080P high-resolution, YCbCr format color image data transmission when the camera works in 3G-SDI mode.

[0017] A method for testing a monocular vision target dragging posture measurement device comprises the following steps:

[0018] 1) The industrial camera and the real-time image tracking and processing system are fixedly installed on the winch used for retracting and releasing the towed target, and connected via a 3G-SDI cable;

[0019] 2) The industrial camera takes a picture of the towed target on the tow rope and sends it to the real-time image tracking and processing system. The FPGA module of the real-time image tracking and processing system detects whether the image data is normal. If it is normal, it is fed back to the main control terminal, and the main control terminal issues a measurement instruction. At the same time, the FPGA module processes the original image and sends the processed image to the SOC processing module. If it is abnormal, the main control terminal controls the SOC processing module to control the industrial camera to adjust the camera exposure time and gain, and the industrial camera takes pictures again.

[0020] 3) After the main control terminal issues the measurement command, the SOC processing module calculates the processed image sent by the FPGA module, obtains the attitude angle of the dragged target, and sends it to the main control terminal;

[0021] 4) The main control terminal receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

[0022] The FPGA module processes the original image, including the following steps:

[0023] The FPGA module filters the original image of the drag target and converts the YCbCr format to RGB format in real time;

[0024] The FPGA module encodes the image data stream into CEA-861 timing and sends it to the SOC processing module through the HDMI interface.

[0025] The SOC processing module calculates the processed image sent by the FPGA module to obtain the attitude angle of the target towed, including the following steps:

[0026] 1-1) After receiving the processed image sent by the FPGA module, the SOC processing module crops and caches the processed towed target image;

[0027] 1-2) performing threshold calculation and segmentation on the processed drag target image;

[0028] 1-3) Extract the edges of the cooperative markers and perform face-to-face intersection calculations to obtain the attitude angle of the towed target.

[0029] The step (1) is specifically:

[0030] 2-1) According to the color characteristics of the tow target itself, the color components are binarized using a fixed threshold to remove background interference;

[0031] 2-2) In the binary image, obtain the centroid position of the drag target;

[0032] 2-3) Obtain the drag target boundary in the binary image, and set the cropping window width and height larger than the drag target boundary;

[0033] 2-4) Crop the original image with the drag target centroid as the center and the set crop window width and height.

[0034] The threshold value calculation and segmentation of the processed drag target image are specifically performed as follows:

[0035] 3-1) extracting the color component of the cooperation logo (1) according to the color characteristics of the cooperation logo (1);

[0036] 3-2) Count the grayscale histogram of the drag target image and determine the threshold value according to the grayscale value at the bottom of the histogram;

[0037] 3-3) Perform binary segmentation on the processed drag target image according to the threshold value to remove the drag target and background interference.

[0038] The extraction of the cooperation mark edge and the surface-surface intersection calculation are performed to obtain the attitude angle of the drag target, which is specifically:

[0039] 4-1) Extract the edge straight lines on both sides of the cooperation mark in the image. The two straight lines and the optical center determine two intersecting planes. According to the perspective imaging relationship, the two planes will be tangent to the two sides of the drag target respectively, and the two tangent lines are the generatrix of the drag target;

[0040] 4-2) Since the target axis is parallel to the generatrix on both sides, the intersection of the two planes is parallel to the central axis and the attitude angles of the two are consistent;

[0041] 4-3) After calculating the two planes according to the two straight lines and the optical center identified in the image, the normal vectors of the two planes are obtained respectively, and the central axis vector is obtained by cross-producting the two normal vectors;

[0042] 4-4) According to the center axis vector, the attitude angle of the towed target is obtained.

[0043] The present invention has the following beneficial effects and advantages:

[0044] 1. The present invention adopts monocular vision to measure the towed target posture, which can quickly, accurately and stably measure the towed target posture. It is suitable for situations where multi-camera shooting is not possible and has good flexibility and practicality.

[0045] 2. The color of the cooperation mark of the present invention has a large contrast with the drag target itself, and is not easily disturbed by the target itself and other backgrounds. The image processing is easy to identify, and the recognition accuracy is improved.

[0046] 3. The cooperation mark of the present invention is easy to make and has no effect on the weight, shape and aerodynamic characteristics of the towed target.

[0047] 4. The image real-time tracking and processing system (4) of the present invention adopts FPGA in conjunction with the RK3588 high-speed image processing framework mode, making full use of the multi-I / O parallel processing capability of FPGA and the large data volume and high-speed computing capability of RK3588. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of the structure of a target dragging posture measurement device according to an embodiment of the present invention;

[0049] Figure 2 It is the algorithm processing flow chart of the image processing system;

[0050] Among them, 1 is the cooperation logo, 2 is the industrial camera, 3 is the cable, and 4 is the image real-time tracking and processing system. DETAILED DESCRIPTION

[0051] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0052] like Figure 1 As shown, the target dragging posture measurement device based on monocular vision according to this embodiment includes: a cooperation mark 1, an industrial camera 2, a cable 3, and an image real-time tracking processing system 4;

[0053] The towed target is connected to the rotating roller of the winch through a tow rope to drag the towed target to move;

[0054] The industrial camera 2 and the image real-time tracking processing system 4 are both arranged on the winch. The industrial camera 2 is connected to the image real-time tracking processing system 4 through a cable 3, and the field of view of the industrial camera 2 covers the towed target, and is used to capture the towed target image including the towed target and the cooperation mark 1, and send it to the image real-time tracking processing system 4;

[0055] The industrial camera captures the images of the tow target and the cooperation mark, and transmits the real-time information of the image to the image processing system in the form of serially encoded digital signals. The industrial camera has a large field of view, ensuring that the tow target and the cooperation mark can be within a certain field of view.

[0056] The cooperation mark 1 is sprayed around the tow target and is used as the tow target image mark for the industrial camera 2 to shoot the tow target. In this embodiment, the cooperation mark 1 is sprayed with matte paint. The color of the cooperation mark 1 is in sharp contrast with the tow target itself, and it is not easily disturbed by the target itself and other backgrounds. The image processing is easy to identify, and the recognition accuracy is improved. The cooperation mark is made around the target so that when the tow target posture appears at a large angle, the cooperation mark is not blocked and can still be accurately identified by the camera, ensuring the accuracy of the equipment when the tow target posture is measured at a large angle.

[0057] The image real-time tracking and processing system 1 is used to receive the towed target image transmitted back from the industrial camera 2 through the cable 2, and process and calculate the towed target image to obtain the real-time posture angle value of the towed target and the cooperation mark 1.

[0058] The image real-time tracking and processing system 4 includes: an FPGA module, a SOC processing module, and a main control terminal;

[0059] The FPGA module is used to detect whether the image data is normal and feed it back to the main control terminal. At the same time, it receives the original image from the industrial camera for filtering and converts the YCbCr format to RGB format in real time; encodes the image data stream according to the set timing and sends it to the SOC processing module through the HDMI interface;

[0060] The SOC processing module is connected to the main control terminal through the RS-422 serial port to receive the measurement instructions of the main control terminal, control the industrial camera 2 to adjust the camera exposure time and gain, and receive the processed drag target image sent by the FPGA module to crop and cache the image, perform threshold calculation and segmentation on the drag target image in real time, extract the cooperation mark edge, and perform face-to-face intersection calculation to obtain the attitude angle of the drag target, and transmit it back to the main control terminal for data display;

[0061] The main control terminal is used to receive the image data feedback from the FPGA module and issue measurement instructions to the SOC processing module based on the feedback information; at the same time, it receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

[0062] Cable 3 is a 3G-SDI cable that supports 1080P high resolution, color image data transmission in YCbCr format. It has a long transmission distance, stable signal, low attenuation and delay, and the interface is self-locking, stable and reliable, and not easy to fall off.

[0063] like Figure 2 As shown in FIG. 1 , it is an algorithm processing flow chart of the image processing system of the present invention. The present invention provides a testing method for a monocular vision towed target posture measurement device, which is characterized by comprising the following steps:

[0064] 1) An industrial camera (2) and an image real-time tracking processing system (4) are fixedly mounted on a winch for retracting and releasing a towed target, and connected via a 3G-SDI cable;

[0065] 2) The industrial camera (2) takes a picture of the towed target on the tow rope and sends it to the image real-time tracking processing system (4). The FPGA module of the image real-time tracking processing system (4) detects whether the image data is normal. If normal, it is fed back to the main control terminal, and the main control terminal issues a measurement instruction. At the same time, the FPGA module processes the original image and sends the processed image to the SOC processing module.

[0066] 2-1) The FPGA module filters the original image of the drag target and converts the YCbCr format into RGB format in real time;

[0067] 2-2) The FPGA module encodes the image data stream to the CEA-861 timing and sends it to the SOC processing module through the HDMI interface.

[0068] If it is abnormal, the main control terminal controls the SOC processing module to control the industrial camera (2) to adjust the camera exposure time and gain, and the industrial camera (2) takes pictures again;

[0069] 3) After the main control terminal issues the measurement command, the SOC processing module calculates the processed image sent by the FPGA module, obtains the attitude angle of the dragged target, and sends it to the main control terminal;

[0070] 3-1) After receiving the processed image sent by the FPGA module, the SOC processing module crops and caches the processed towed target image;

[0071] 3-1-1) According to the color characteristics of the tow target itself, the color components are binarized using a fixed threshold to remove background interference;

[0072] 3-1-2) In the binary image, obtain the centroid position of the drag target;

[0073] 3-1-3) Obtain the drag target boundary in the binary image, and set the cropping window width and height larger than the drag target boundary;

[0074] 3-1-4) Crop the original image with the drag target centroid as the center and the set crop window width and height.

[0075] 3-2) performing threshold calculation and segmentation on the processed drag target image;

[0076] 3-2-1) extracting the color components of the cooperation logo (1) according to the color characteristics of the cooperation logo (1);

[0077] 3-2-2) Count the grayscale histogram of the drag target image and determine the threshold value according to the grayscale value at the bottom of the histogram;

[0078] 3-2-3) Perform binary segmentation on the processed drag target image according to the threshold value to remove the drag target and background interference.

[0079] 3-3) Extract the edges of the cooperative markers and perform face-to-face intersection calculations to obtain the attitude angle of the towed target.

[0080] 3-3-1) Extract the edge straight lines on both sides of the cooperation mark in the image. The two straight lines and the optical center determine two intersecting planes. According to the perspective imaging relationship, the two planes will be tangent to the two sides of the drag target respectively, and the two tangent lines are the generatrix of the drag target;

[0081] 3-3-2) Since the target axis is parallel to the generatrix on both sides, the intersection of the two planes is parallel to the central axis and the attitude angles of the two are consistent;

[0082] 3-3-3) After calculating the two planes based on the two straight lines and the optical center identified in the image, the normal vectors of the two planes are obtained respectively, and the central axis vector is obtained by cross-producting the two normal vectors;

[0083] 3-3-4) According to the center axis vector, the attitude angle of the towed target is obtained.

[0084] 4) The main control terminal receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

[0085] Example:

[0086] In actual work, the industrial camera 2 and the image real-time tracking and processing system 4 are fixedly installed at corresponding positions on the winch used for retracting and releasing the towed target, and are connected and locked via a 3G-SDI high-speed cable.

[0087] After the system is powered on, the FPGA is used to detect whether the image data is normal. The BOOTROM inside RK3588 starts running, loading the startup code for further initialization and loading the operating system. After that, the operating system starts running, completes the system self-check and reports to the host through the RS-422 serial port, and enters the standby state to wait for the host's instructions.

[0088] After receiving the measurement instruction, the system controls the camera to adjust the camera exposure time and gain to make the image clear, filters the original image through the FPGA processor, and converts the YCbCr format into RGB format in real time; encodes the image data stream into CEA-861 timing and sends it to the RK3588 processor through the HDMI interface.

[0089] After receiving the towed target image, the RK3588 processor crops and caches the image. Using its high computing power and multimedia stream processing capabilities, it performs threshold calculation and segmentation, extracts cooperative identification edges, and performs face-to-face intersection calculation on the towed target image in real time to obtain the towed target's attitude angle.

[0090] The present invention performs threshold segmentation based on the color of the cooperation logo 1, eliminates background and target interference, and accurately extracts the edge straight lines on both sides of the cooperation logo 1. The two straight lines and the optical center determine two intersecting planes. According to the perspective imaging relationship, the two planes will be tangent to the two sides of the target respectively, and the two tangents are the generatrix of the target. Since the target axis and the generatrix on both sides are parallel to each other, according to the knowledge of solid geometry, the intersection line of the two planes is parallel to the central axis, and the posture angles of the two are consistent. Therefore, after calculating the two planes according to the two straight lines and the optical center identified in the image, the normal vectors of the two planes can be obtained respectively, and the central axis vector can be obtained by cross-product of the two normal vectors, and then the posture angle of the target can be obtained.

[0091] The main control terminal receives the attitude angle of the towed target sent by the SOC processing module, and displays the data in real time, performs a safety assessment on the towed target attitude through the measured value of the towed target attitude angle and sends the result to the main control terminal.

[0092] The present invention makes a cooperation mark at a suitable position of the drag target, and images the cooperation mark on the CCD image plane through an optical system. When the drag target posture changes, the cooperation mark also changes accordingly. By extracting the edge straight lines on both sides of the cooperation mark on the CCD image plane, corresponding to the two generatrixes of the drag target, and performing a single camera surface-to-surface intersection, the posture angle of the drag target is calculated. It uses monocular vision to measure the drag target posture, and can quickly, accurately and stably measure the drag target posture. It is suitable for situations where multi-camera shooting is not possible, and has good flexibility and practicality.

[0093] The above description is only an embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, expansion, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A monocular vision towed target posture measurement device, characterized in that: include: Cooperation identification (1), industrial camera (2), cable (3) and image real-time tracking and processing system (4); The towed target is connected to the rotating roller of the winch through a tow rope to drag the towed target to move; The industrial camera (2) and the image real-time tracking processing system (4) are both arranged on the winch, the industrial camera (2) is connected to the image real-time tracking processing system (4) via a cable (3), and the field of view of the industrial camera (2) covers the towed target, and is used to capture an image of the towed target including the towed target and the cooperation mark (1), and send the image to the image real-time tracking processing system (4); The cooperation mark (1) is arranged around the towed target spraying and is used as a towed target image mark for the industrial camera (2) to shoot the towed target; The real-time image tracking and processing system (4) is used to receive the towed target image transmitted back from the industrial camera (3) via the cable (3), and to process and calculate the towed target image to obtain the real-time attitude angle value of the towed target and the cooperation mark (1).

2. The monocular vision target dragging posture measurement device according to claim 1 is characterized in that: The cooperation mark (1) is a spray-painted icon, and the sprayed color forms a contrast with the color of the drag target itself; The cooperation logo (1) is sprayed around the middle and upper middle part of the tow target.

3. The monocular vision target dragging posture measurement device according to claim 1, characterized in that: The image real-time tracking and processing system (4) comprises: an FPGA module, a SOC processing module, and a main control terminal; The FPGA module is used to detect whether the image data is normal and feed it back to the main control terminal. At the same time, it receives the original image from the industrial camera for filtering and converts the YCbCr format to RGB format in real time; encodes the image data stream according to the set timing and sends it to the SOC processing module through the HDMI interface; The SOC processing module is connected to the main control terminal via an RS-422 serial port, and is used to receive measurement instructions from the main control terminal, control the industrial camera (2), adjust the camera exposure time and gain, and receive the processed drag target image sent by the FPGA module to crop and cache the image, perform threshold calculation and segmentation on the drag target image in real time, extract the cooperative identification edge, and perform face-to-face intersection calculation to obtain the attitude angle of the drag target, and transmit it back to the main control terminal for data display; The main control terminal is used to receive the image data feedback from the FPGA module and issue measurement instructions to the SOC processing module according to the feedback information; at the same time, it receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

4. The monocular vision target dragging posture measurement device according to claim 1, characterized in that: The cable (3) is a 3G-SDI cable, which is used to provide image information transmission that meets the requirements of 1080P high-resolution, YCbCr format color image data transmission when the camera works in 3G-SDI mode.

5. The testing method of a monocular vision target dragging posture measurement device according to claim 1, characterized in that: The following steps are involved: 1) An industrial camera (2) and an image real-time tracking processing system (4) are fixedly mounted on a winch for retracting and releasing a towed target, and connected via a 3G-SDI cable; 2) The industrial camera (2) takes a picture of the towed target on the tow rope and sends it to the image real-time tracking processing system (4). The FPGA module of the image real-time tracking processing system (4) detects whether the image data is normal. If it is normal, it is fed back to the main control terminal, and the main control terminal issues a measurement instruction. At the same time, the FPGA module processes the original image and sends the processed image to the SOC processing module. If it is abnormal, the main control terminal controls the SOC processing module to control the industrial camera (2) to adjust the camera exposure time and gain, and the industrial camera (2) takes pictures again. 3) After the main control terminal issues the measurement command, the SOC processing module calculates the processed image sent by the FPGA module, obtains the attitude angle of the dragged target, and sends it to the main control terminal; 4) The main control terminal receives the attitude angle of the towed target sent by the SOC processing module and displays the data in real time for the staff to conduct safety assessment.

6. The testing method of a monocular vision target dragging posture measurement device according to claim 5 is characterized in that: The FPGA module processes the original image, including the following steps: The FPGA module filters the original image of the drag target and converts the YCbCr format to RGB format in real time; The FPGA module encodes the image data stream into CEA-861 timing and sends it to the SOC processing module through the HDMI interface.

7. The testing method of a monocular vision target dragging posture measurement device according to claim 5, characterized in that: The SOC processing module calculates the processed image sent by the FPGA module to obtain the attitude angle of the target towed, including the following steps: 1-1) After receiving the processed image sent by the FPGA module, the SOC processing module crops and caches the processed towed target image; 1-2) performing threshold calculation and segmentation on the processed drag target image; 1-3) Extract the edges of the cooperative markers and perform face-to-face intersection calculations to obtain the attitude angle of the towed target.

8. The testing method of a monocular vision target dragging posture measurement device according to claim 7 is characterized in that: The step (1) is specifically: 2-1) According to the color characteristics of the tow target itself, the color components are binarized using a fixed threshold to remove background interference; 2-2) In the binary image, obtain the centroid position of the drag target; 2-3) Obtain the drag target boundary in the binary image, and set the cropping window width and height larger than the drag target boundary; 2-4) Crop the original image with the drag target centroid as the center and the set crop window width and height.

9. The testing method of a monocular vision target dragging posture measurement device according to claim 7, characterized in that: The threshold value calculation and segmentation of the processed drag target image are specifically performed as follows: 3-1) extracting the color component of the cooperation logo (1) according to the color characteristics of the cooperation logo (1); 3-2) Count the grayscale histogram of the drag target image and determine the threshold value according to the grayscale value at the bottom of the histogram; 3-3) Perform binary segmentation on the processed drag target image according to the threshold value to remove the drag target and background interference.

10. The testing method of a monocular vision target dragging posture measurement device according to claim 7, characterized in that: The extraction of the cooperation mark edge and the surface-surface intersection calculation are performed to obtain the attitude angle of the drag target, which is specifically: 4-1) Extract the edge straight lines on both sides of the cooperation mark in the image. The two straight lines and the optical center determine two intersecting planes. According to the perspective imaging relationship, the two planes will be tangent to the two sides of the drag target respectively, and the two tangent lines are the generatrix of the drag target; 4-2) Since the target axis is parallel to the generatrix on both sides, the intersection of the two planes is parallel to the central axis and the attitude angles of the two are consistent; 4-3) After calculating the two planes according to the two straight lines and the optical center identified in the image, the normal vectors of the two planes are obtained respectively, and the central axis vector is obtained by cross-producting the two normal vectors; 4-4) According to the center axis vector, the attitude angle of the towed target is obtained.

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