A high-speed and high-precision infrared target position measurement device based on infrared thermal imaging

Abstract

The present invention discloses a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging, which belongs to the field of infrared optical precision measurement technology. The present invention includes an image detection subsystem, an image transmission subsystem, an image processing subsystem, a data transmission subsystem and a power supply subsystem. The present invention detects the scene at a high frame rate through the image detection subsystem; realizes analog-to-digital signal conversion, detector triggering and configuration of the image detection subsystem and the image processing subsystem through the image transmission subsystem; performs target detection and data solution through the image processing subsystem, and calculates the high-precision coordinates of the target movement; and performs standardized output of the solution data through the data transmission subsystem, and sends the high-frame rate and high-precision target azimuth data to the host computer in real time. In the case of a large target movement range, fast movement speed, high data refresh frequency requirement and high data accuracy requirement, real-time recognition and high-precision centroid azimuth measurement of high-speed moving targets are performed.

Description

Technical Field

[0001] The invention belongs to the technical field of infrared optical precision measurement, and relates to a method and a device for quickly measuring an angle position in a field of view by using the temperature measurement principle of a high-speed infrared thermal imager. Background Art

[0002] In the field of high-speed target recognition and tracking, it is necessary to quickly identify the target and provide the position information (angle or spatial coordinates) of the target in the azimuth and pitch direction. It is difficult for general infrared angle measuring devices to provide accurate position information in real time for fast-moving targets. The use of low-cost high-speed infrared focal plane detectors can achieve high-speed and high-precision target position information collection, recognition, processing and output, providing an effective means for the detection and recognition of high-speed targets. Summary of the invention

[0003] The main purpose of the present invention is to provide a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging, which can realize infrared thermal imaging with preset pixel resolution requirements when the target has a large motion range, fast motion speed, high data refresh frequency requirements, and high azimuth measurement accuracy requirements. By processing the sequence images returned by the high-frame-rate infrared acquisition chip, the high-precision center of mass azimuth of the target motion is calculated and output, thereby realizing real-time recognition of high-speed moving targets with a large motion range and high-precision center of mass azimuth measurement.

[0004] The high data refresh frequency refers to a data refresh frequency higher than 300 Hz. The large moving range and high-speed moving target refers to a moving target with a moving range of 10 to 400 meters from the detector and a speed of 100 to 1000 meters per second.

[0005] The objective of the present invention is achieved through the following technical solutions:

[0006] The invention discloses a high-speed and high-precision infrared target position measuring device based on infrared thermal imaging, which is mainly composed of an image detection subsystem, an image transmission subsystem, an image processing subsystem, a data transmission subsystem and a power supply subsystem.

[0007] The image detection subsystem includes an infrared lens and a high frame rate image acquisition chip. The image detection subsystem is used to perform high frame rate detection on the scene, acquire high frame rate infrared thermal images, and return high frame rate image data to the image transmission subsystem.

[0008] The image transmission subsystem includes an ADC chip and a bus. The image transmission subsystem is used for analog-to-digital signal conversion, detector triggering and configuration of the image detection subsystem and the image processing subsystem. The image data returned by the image detection subsystem is obtained through the ADC chip, and the analog signal of the image output to the image processing subsystem is obtained through analog-to-digital conversion, and the camera is powered and externally triggered through the ADC chip. The uncooled high frame rate detector parameter configuration is realized through the bus.

[0009] Preferably, the uncooled high frame rate detector parameter configuration is implemented via the I2C bus.

[0010] The image processing subsystem includes an FPGA data processing core, a DDR3 data cache, and an image processing program. The image processing subsystem is used to perform target detection and data analysis on the images collected by the image transmission subsystem, and calculate the high-precision coordinates of the target movement by processing the high-frame rate sequence images returned by the camera.

[0011] The FPGA processing core in the image processing subsystem is the main computing unit for image processing, and is mainly used for image data processing, target detection, and data calculation.

[0012] The DDR3 data cache in the image processing subsystem is mainly used for data cache in image processing, transmission and data calculation.

[0013] The image processing in the image processing subsystem includes non-uniform correction, image denoising, threshold segmentation, target detection, and centroid calculation.

[0014] Preferably, a two-point correction method is used to correct the non-uniformity of each frame of image, a mean filtering method is used for image denoising, a static suppression method is used to eliminate environmental noise, a threshold segmentation method is used to achieve image segmentation and target detection, and a defocus and subdivision interpolation method is used to calculate the target centroid azimuth.

[0015] The two-point correction method is used to perform non-uniformity correction on each frame of image. The implementation method is as follows:

[0016] Calibration steps 1. At temperature T 1 At this time, the response of each unit of the detector is measured. Collect M frames of image data and calculate the average value to obtain the response of the ij unit at T 1 The response is Similarly, we get the ij unit in T 2 The response is

[0017] Correction step 2: If The ij units are respectively 1 and T 2 The standard response value, Gij and O ij is the correction coefficient, then:

[0018]

[0019]

[0020] Correction step 3: Set the correction factor G ij and O ij Save it in the form of a file, and after loading it when the system is working, perform real-time correction according to the following formula:

[0021] Y ij =G ij (X ij +O ij / G ij )

[0022] The mean filtering method is used for image denoising. The implementation method is as follows:

[0023] The target pixel is processed according to the template. The mean filter template includes not only the target pixel, but also the N areas centered on the target pixel (x, y). In order to improve the efficiency of calculation, a 4×4 template is used. The mean filter is obtained by the following calculation formula:

[0024]

[0025] According to the above formula, for each pixel I in the template i (x, y) is averaged and the target pixel value is replaced by the average value to achieve a denoising effect.

[0026] Use static suppression to eliminate environmental noise. The implementation method is as follows:

[0027] Subtract the grayscale matrix of the current frame image from the grayscale matrix of the previous frame image to reduce the grayscale value of the static background area to zero, and only retain the grayscale information of the dynamic target.

[0028] The threshold segmentation method is used to realize image segmentation and target detection. The implementation method is as follows:

[0029] Define the input image as f(x,y,k), where the filtered image is f H (x, y, k), the target segmented image is g(x, y, k), the threshold is Th(k), then:

[0030]

[0031] k represents the k-th frame image, and (x, y, k) represents the pixel point (x, y) in the k-th frame image.

[0032] The defocus and subdivision interpolation method is used to calculate the target centroid azimuth angle and achieve sub-pixel angular resolution. The implementation method is as follows:

[0033] Calculation step 1, by defocusing, the imaging point of the target on the photosensitive surface of the infrared camera is dispersed to more pixels;

[0034] Calculation step 2: Use the weighted centroid method to obtain the sub-pixel position coordinates of the target. Suppose the coordinates of the pixel in the i-th row and j-th column in the image are (x i ,y i ), the gray value is I(x i ,y i ), the target image point is contained in a rectangular calculation window, and the centroid position calculation formula can be expressed as:

[0035]

[0036] Calculation step 3, the target (x 0 ,y 0 ), the coordinates of the target's center of mass on the infrared camera imaging plane are known. Let the coordinates of the target's center of mass on the detector plane be (x, y, f), where f is the focal length of the lens. Take the center of the detector as the origin, Positive is the elevation angle, negative is the depression angle; positive θ means right deviation, negative θ means left deviation. and the horizontal deflection angle θ is calculated as:

[0037]

[0038] Through image defocused dispersion imaging and centroid weighted centroid algorithm, it is theoretically and engineering experience can achieve about 4 times the subdivision accuracy, thereby reducing the need for high-precision measurement on the detector array scale, reducing measurement costs, and reducing the data processing volume of the infrared angle measurement device to enable it to meet high frame rate requirements.

[0039] The data transmission subsystem includes a CAN bus. The data transmission subsystem is used to solve the standardized output of data, send high-frame-rate and high-precision target azimuth data to the host computer in real time, and realize data transmission through the CAN bus interface;

[0040] The power subsystem includes an integrated switch and an integrated inductor, and is used to supply power to system hardware devices.

[0041] The working method of a high-speed and high-precision infrared target position measuring device based on infrared thermal imaging disclosed by the present invention is as follows:

[0042] Step 1: The image transmission subsystem realizes the power supply and external triggering of the high frame rate image acquisition chip in the image detection subsystem through the ADC chip, and transmits the detector configuration parameters set by the host computer software to the image detection subsystem through the I2C bus to complete the parameter configuration of the high frame rate image acquisition chip;

[0043] Step 2: The image detection subsystem collects high frame rate infrared thermal images to achieve imaging with preset pixel resolution requirements, and returns high frame rate image data to the image transmission subsystem;

[0044] Step 3: The image transmission subsystem obtains the image data returned by the image detection subsystem through the ADC chip, obtains the analog signal of the image through analog-to-digital conversion, and outputs it to the image processing subsystem;

[0045] Step 4: The image processing subsystem performs target detection and data analysis on the image analog signal provided by the image transmission subsystem through the FPGA processing core, DDR3 data cache and image processing program, and calculates the high-precision coordinates of the target movement. Specifically:

[0046] The FPGA processing core in the image processing subsystem is the main computing unit for image processing, and is used for image data processing, target detection, and data calculation;

[0047] The DDR3 data cache in the image processing subsystem is mainly used for data cache in image processing, transmission and data calculation;

[0048] The image processing in the image processing subsystem includes non-uniform correction, image denoising, threshold segmentation, and target detection.

[0049] Step 5: The data transmission subsystem outputs the solution data of the image processing subsystem in a standardized manner through the CAN bus interface, and sends the high-frame-rate and high-precision target azimuth data to the host computer in real time, thereby realizing high-speed and high-precision infrared target position measurement based on infrared thermal imaging.

[0050] Beneficial effects:

[0051] 1. There is no infrared angle measuring device in the prior art that can achieve high data refresh rate and high measurement accuracy for targets with fast movement speed and large movement range. The present invention discloses a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging technology. The image detection subsystem detects the scene at a high frame rate and returns high-frame rate image data; the image transmission subsystem constructs analog-to-digital signal conversion, detector triggering and configuration of the image detection subsystem and the image processing subsystem; the image processing subsystem performs target detection and data solution to calculate the high-precision coordinates of the target movement; the data transmission subsystem performs standardized output of the solution data, and sends the high-frame rate and high-precision target azimuth data to the host computer in real time. In the case of a large target movement range, fast movement speed, high data refresh frequency requirement and high data accuracy requirement, real-time recognition and high-precision centroid azimuth measurement of high-speed moving targets are performed.

[0052] 2. In order to achieve high-precision detection of infrared angle measuring devices in the prior art, it is necessary to increase the size of the detector array, which is costly. In addition, due to the excessive data processing volume of large array infrared detectors, it is difficult to meet the high frame rate requirements. The present invention discloses a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging technology. Through the image defocused dispersion imaging scheme and the centroid weighted centroid algorithm, it can achieve about 4 times the subdivision accuracy in theory and engineering experience, thereby reducing the need for the size of the detector array to achieve high-precision angle measurement, reducing the measurement cost, and reducing the data processing volume of the infrared goniometer, so that it can meet the high frame rate requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic block diagram of a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging technology according to an embodiment of the present invention;

[0054] Figure 2 This is a schematic diagram of the defocused imaging principle of an embodiment of the present invention;

[0055] Figure 3 Schematic diagram of detecting target imaging according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to better illustrate the purpose and advantages of the present invention, the invention is further described below with reference to the accompanying drawings and examples.

[0057] Combination Figure 1 As shown, this embodiment discloses a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging technology, which is mainly composed of an image detection subsystem, an image transmission subsystem, an image processing subsystem, a data transmission subsystem, a power subsystem and a software subsystem.

[0058] The image detection subsystem includes an infrared lens and a high frame rate image acquisition chip. The image detection subsystem is used to perform high frame rate detection on the scene, acquire high frame rate infrared thermal images, and return high frame rate image data to the image transmission subsystem.

[0059] The image transmission subsystem includes an ADC chip and a bus. The image transmission subsystem is used to construct analog-to-digital signal conversion, detector triggering and configuration of the image detection subsystem and the image processing subsystem. The image data returned by the image detection subsystem is obtained through the ADC chip, and the analog signal of the image output to the image processing subsystem is obtained through analog-to-digital conversion, and the camera power supply and external triggering are realized through the ADC chip. The parameter configuration of the non-cooled high frame rate detector is realized through the I2C bus.

[0060] The image processing subsystem includes an FPGA data processing core, a DDR3 data cache and an image processing program. The image processing subsystem is used to perform target detection and data analysis on the images collected by the image transmission subsystem, and calculate the high-precision coordinates of the target movement by processing the high-frame rate sequence images returned by the camera.

[0061] The FPGA processing core in the image processing subsystem is the main computing unit for image processing, and is used for image data processing, target detection, data calculation, etc.

[0062] The DDR3 data cache in the image processing subsystem is mainly used for data cache in image processing, transmission and data calculation;

[0063] The image processing procedures in the image processing subsystem include non-uniform correction, image denoising, threshold segmentation, target detection and centroid calculation.

[0064] The data transmission subsystem includes a CAN bus. The data transmission subsystem is used to solve the standardized output of data, send high-frame-rate and high-precision target azimuth data to the host computer in real time, and realize data transmission through the CAN bus interface;

[0065] The power subsystem includes an integrated switch and an integrated inductor, and is used to supply power to system hardware devices.

[0066] Combination Figure 2 As shown, the software processing flow of this embodiment includes device initialization, image processing and target centroid azimuth calculation. The device initialization mainly sets the detection parameters of the infrared camera, including setting the window size (ROI), exposure time, trigger delay, etc. The parameters are directly sent to the infrared camera through the I2C bus interface.

[0067] The image processing procedure includes non-uniform correction, image denoising, threshold segmentation, and target detection. Preferably, a two-point correction method is used to correct the non-uniformity of each frame of image, a mean filtering method is used to denoise the image, a static suppression method is used to eliminate environmental noise, and a threshold segmentation method is used to achieve image segmentation and target detection.

[0068] The two-point correction method is used to perform non-uniformity correction on each frame of image. The implementation method is as follows:

[0069] Calibration steps 1. At temperature T 1 At this time, the response of each unit of the detector is measured. Collect M frames of image data and calculate the average value to obtain the response of the ij unit at T 1 The response is Similarly, we can get the ij unit in T 2 The response is

[0070] Correction step 2: If The ij units are respectively 1 and T 2 The standard response value, G ij and O ij is the correction coefficient, then:

[0071]

[0072]

[0073] Correction step 3: The correction coefficient can be saved in the form of a file and loaded for real-time correction when the system is working:

[0074] Y ij =G ij (X ij +O ij / G ij )

[0075] The mean filtering method is used for image denoising. The implementation method is as follows:

[0076] The target pixel is processed according to the template. The mean filter template includes not only the target pixel, but also the N areas centered on the target pixel (x, y). In order to improve the efficiency of calculation, a 4×4 template is used. The mean filter can be obtained by the following calculation formula:

[0077]

[0078] According to the above formula, for each pixel I in the template i (x, y) is averaged and the target pixel value is replaced by the average value to achieve a denoising effect.

[0079] Use static suppression to eliminate environmental noise. The implementation method is as follows:

[0080] Subtract the grayscale matrix of the current frame image from the grayscale matrix of the previous frame image to reduce the grayscale value of the static background area to zero, and only retain the grayscale information of the dynamic target.

[0081] The threshold segmentation method is used to realize image segmentation and target detection. The implementation method is as follows:

[0082] Let the input image be f(x,y,k), where the filtered image is f H (x, y, k), the target segmented image is g(x, y, k), the threshold is Th(k), then:

[0083]

[0084] k represents the k-th frame image, and (x, y, k) represents the pixel point (x, y) in the k-th frame image.

[0085] The target centroid azimuth angle calculation adopts the method of defocusing and subdivision interpolation to realize the target centroid azimuth angle calculation, and achieves sub-pixel angular resolution. The implementation method is as follows:

[0086] Calculation step 1, combined Figure 3 As shown, the imaging point of the target on the photosensitive surface of the infrared camera is dispersed to more pixels by defocusing;

[0087] Calculation step 2: Use the weighted centroid method to obtain the sub-pixel position coordinates of the target. Suppose the coordinates of the pixel in the i-th row and j-th column in the image are (x i ,y i ), the gray value is I(x i ,y i ), the target image point is contained in a rectangular calculation window, and the centroid position calculation formula can be expressed as:

[0088]

[0089] Calculation step 3, combined with Figure 3 As shown, the target (x 0 ,y 0 ), the coordinates of the target's center of mass on the infrared camera imaging plane are known. Let the coordinates of the target's center of mass on the detector plane be (x, y, f), where f is the focal length of the lens. Take the center of the detector as the origin, Positive is the elevation angle, negative is the depression angle; positive θ means right deviation, negative θ means left deviation. and the horizontal deflection angle θ can be calculated as:

[0090]

[0091] Through the image defocused dispersion imaging scheme and the centroid weighted centroid algorithm, it is theoretically and empirically possible to achieve a subdivision accuracy of about 4 times, thereby reducing the need for detector array size for high-precision detection, reducing measurement costs, and reducing the amount of data processing for infrared detectors, allowing them to meet high frame rate requirements.

[0092] The working method of a high-speed and high-precision infrared target position measurement device based on infrared thermal imaging disclosed in this embodiment is:

[0093] Step 1: The image transmission subsystem realizes the power supply and external triggering of the high frame rate image acquisition chip in the image detection subsystem through the ADC chip, and transmits the detector configuration parameters set by the host computer software to the image detection subsystem through the I2C bus to complete the parameter configuration of the high frame rate image acquisition chip;

[0094] Step 2: The image detection subsystem collects high frame rate infrared thermal images to achieve imaging with preset pixel resolution requirements, and returns high frame rate image data to the image transmission subsystem;

[0095] Step 3: The image transmission subsystem obtains the image data returned by the image detection subsystem through the ADC chip, obtains the analog signal of the image through analog-to-digital conversion, and outputs it to the image processing subsystem;

[0096] Step 4: The image processing subsystem performs target detection and data analysis on the image analog signal provided by the image transmission subsystem through the FPGA processing core, DDR3 data cache and image processing program, and calculates the high-precision coordinates of the target movement. Specifically:

[0097] The FPGA processing core in the image processing subsystem is the main computing unit for image processing, and is used for image data processing, target detection, and data calculation;

[0098] The DDR3 data cache in the image processing subsystem is mainly used for data cache in image processing, transmission and data calculation;

[0099] Step 5: The data transmission subsystem outputs the solution data of the image processing subsystem in a standardized manner through the CAN bus interface, and sends the high-frame-rate and high-precision target azimuth data to the host computer in real time, thereby realizing high-speed and high-precision infrared target position measurement based on infrared thermal imaging.

[0100] The specific description above further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-speed and high-precision infrared target position measurement device based on infrared thermal imaging, characterized in that: It is mainly composed of image detection subsystem, image transmission subsystem, image processing subsystem, data transmission subsystem and power supply subsystem; The image detection subsystem includes an infrared lens and a high frame rate image acquisition chip; the image detection subsystem is used to perform high frame rate detection on the scene, collect high frame rate infrared thermal images, and return high frame rate image data to the image transmission subsystem; The image transmission subsystem includes an ADC chip and a bus; the image transmission subsystem is used for analog-to-digital signal conversion, detector triggering and configuration of the image detection subsystem and the image processing subsystem; the image data returned by the image detection subsystem is obtained through the ADC chip, and the analog signal of the image output to the image processing subsystem is obtained through analog-to-digital conversion, and the camera is powered and externally triggered through the ADC chip; the uncooled high frame rate detector parameter configuration is realized through the bus; The image processing subsystem includes an FPGA data processing core, a DDR3 data cache, and an image processing program; the image processing subsystem is used to perform target detection and data analysis on the images collected by the image transmission subsystem, and calculate the high-precision coordinates of the target movement by processing the high-frame rate sequence images returned by the camera; The FPGA processing core in the image processing subsystem is the main computing unit for image processing, and is mainly used for image data processing, target detection, and data calculation; Image processing in the image processing subsystem includes non-uniform correction, image denoising, threshold segmentation, target detection, and centroid calculation; The DDR3 data cache in the image processing subsystem is mainly used for data cache in image processing, transmission and data calculation; The data transmission subsystem includes a CAN bus; the data transmission subsystem is used to solve the standardized output of the data, send the high frame rate and high precision target azimuth data to the host computer in real time, and realize data transmission through the CAN bus interface; The power subsystem includes an integrated switch and an integrated inductor, and is used to supply power to system hardware devices.

2. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 1, characterized in that: The working method is: Step 1: The image transmission subsystem realizes the power supply and external triggering of the high frame rate image acquisition chip in the image detection subsystem through the ADC chip, and transmits the detector configuration parameters set by the host computer software to the image detection subsystem through the I2C bus to complete the parameter configuration of the high frame rate image acquisition chip; Step 2: The image detection subsystem collects high frame rate infrared thermal images to achieve imaging with preset pixel resolution requirements, and returns high frame rate image data to the image transmission subsystem; Step 3: The image transmission subsystem obtains the image data returned by the image detection subsystem through the ADC chip, obtains the analog signal of the image through analog-to-digital conversion, and outputs it to the image processing subsystem; Step 4: The image processing subsystem performs target detection and data analysis on the image analog signal provided by the image transmission subsystem through the FPGA processing core, DDR3 data cache and image processing program, and calculates the high-precision coordinates of the target movement; Step 5: The data transmission subsystem outputs the solution data of the image processing subsystem in a standardized manner through the CAN bus interface, and sends the high-frame-rate and high-precision target azimuth data to the host computer in real time, thereby realizing high-speed and high-precision infrared target position measurement based on infrared thermal imaging.

3. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 2, characterized in that: The uncooled high frame rate detector parameters are configured via the I2C bus.

4. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 1, 2 or 3, characterized in that: The two-point correction method is used to correct the non-uniformity of each frame of image, the mean filtering method is used for image denoising, the static suppression method is used to eliminate environmental noise, the threshold segmentation method is used to achieve image segmentation and target detection, and the defocus and subdivision interpolation method is used to calculate the target centroid azimuth.

5. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 4, characterized in that: The two-point correction method is used to perform non-uniformity correction on each frame of image. The implementation method is as follows: Correction steps 1. At temperature T1, measure the response of each detector unit; collect M frames of image data and calculate the average value, and get the response of ij unit at T1: Similarly, the response of the ij unit at T2 is Correction step 2: If are the standard response values ​​of the ij unit at T1 and T2, G ij and O ij is the correction factor, then: Correction step 3: Set the correction factor G ij and O ij Save it in the form of a file, and after loading it when the system is working, perform real-time correction according to the following formula: Y ij =G ij (X ij +O ij / G ij ) 。 6. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 4, characterized in that: The mean filtering method is used for image denoising. The implementation method is as follows: The target pixel is processed according to the template; the mean filter template includes not only the target pixel, but also the N areas centered on the target pixel (x, y). In order to improve the efficiency of calculation, a 4×4 template is used; the mean filter is obtained by the following calculation formula: According to the above formula, for each pixel I in the template i (x, y) is averaged and the target pixel value is replaced by the average value to achieve a denoising effect.

7. A high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 4, characterized in that: The static suppression method is used to eliminate environmental noise. The implementation method is as follows: Subtract the grayscale matrix of the current frame image from the grayscale matrix of the previous frame image to reduce the grayscale value of the static background area to zero, and only retain the grayscale information of the dynamic target; The threshold segmentation method is used to realize image segmentation and target detection. The implementation method is as follows: Define the input image as f(x,y,k), where the filtered image is f H (x, y, k), the target segmented image is g(x, y, k), the threshold is Th(k), then: k represents the k-th frame image, and (x, y, k) represents the pixel point (x, y) in the k-th frame image.

8. The high-speed and high-precision infrared target position measuring device based on infrared thermal imaging as claimed in claim 4, characterized in that: The defocus and subdivision interpolation method is used to calculate the target centroid azimuth angle and achieve sub-pixel angular resolution; the implementation method is as follows: Calculation step 1, by defocusing, the imaging point of the target on the photosensitive surface of the infrared camera is dispersed to more pixels; Calculation step 2: Use the weighted centroid method to obtain the sub-pixel position coordinates of the target. Suppose the coordinates of the pixel in the i-th row and j-th column in the image are (x i ,y i ), the gray value is I(x i ,y i ), the target image point is contained in a rectangular calculation window, and the centroid position calculation formula can be expressed as: Calculation step 3: After the target (x0, y0) in the image is detected by the algorithm, the coordinates of the target's center of mass in the infrared camera imaging plane are known. Let the coordinates of the target's center of mass in the spatial rectangular coordinate system of the detector plane be (x, y, f), where f is the focal length of the lens; take the center of the detector as the origin, Positive is the elevation angle, negative is the depression angle; positive θ means right deviation, negative θ means left deviation; the pitch angle of the target and the horizontal deflection angle θ is calculated as: Through image defocused dispersion imaging and centroid weighted centroid algorithm, the need for detector array size for high-precision measurement is reduced, the measurement cost is reduced, and the data processing amount of the infrared angle measurement device can be reduced to meet the high frame rate requirements.

Images