A point target and background equivalent device and signal-to-noise ratio test method for an airborne infrared search and tracking system

Abstract

An airborne infrared search and tracking system point target and background equivalence device and a signal-to-noise ratio test method. The invention relates to the field of optoelectronic technology, and in particular to the field of signal-to-noise ratio testing. It solves the problem of performing equivalence on point targets and backgrounds of an airborne infrared search and tracking system in a laboratory environment, and accurately calculating the target signal energy through images, thereby accurately calculating the signal-to-noise ratio of the airborne infrared search and tracking system. The device described in the present invention comprises a cavity blackbody, a temperature-controlled aperture, a collimator, and an infrared attenuation plate, wherein the cavity blackbody, temperature-controlled aperture, collimator, and infrared attenuation plate are coaxially arranged; the test method described in the present invention is performed using the device. The device described in the present invention can be applied in the fields of aviation simulation test technology and aviation laboratory simulation technology; the method described in the present invention can be applied in the fields of target energy testing of aircraft tracking systems and signal-to-noise ratio testing of aircraft tracking systems.

Description

Technical Field

[0001] The present invention belongs to the field of optoelectronic technology, and particularly relates to the field of signal-to-noise ratio testing. Background Art

[0002] Airborne infrared search and tracking systems are passive optical remote sensing detection devices used to search, detect, track, and identify target aircraft beyond visual range, thereby forming situational awareness of the aircraft's environment. Under long-range detection conditions, the image of the target aircraft has weak radiation characteristics and small geometric dimensions. Specifically, the number of pixels occupied by the target's projected signal on the detector is close to a single pixel or sub-pixel. At the same time, the signal's grayscale value is small, and its amplitude is close to the detector's thermal noise and background noise, resulting in a low signal-to-noise ratio. Therefore, the signal-to-noise ratio of a point target is an important indicator for measuring the detection capability of an airborne infrared search and tracking system. During the design process of this type of system, the system's signal-to-noise ratio capability must be tested under specific conditions to assess the system's performance and verify its indicators.

[0003] Existing testing methods mainly fall into two categories: real-machine flight tests and laboratory methods. Although real-machine flight tests are more accurate and closer to actual operating environments, they require significant experimental funding and a long time period, making them difficult to operate. Currently, laboratory methods are more widely used. Testing the signal-to-noise ratio of airborne infrared search and tracking systems under laboratory conditions mainly faces the following technical difficulties:

[0004] (1) In a laboratory environment, how can we use appropriate experimental equipment and methods to make point targets and backgrounds equivalent?

[0005] In their book "Airborne Long-Range Infrared Early Warning Radar System" (first edition, December 2017), Cao Chen et al. introduced a laboratory method for testing signal-to-noise ratio. However, this method only provides a brief experimental approach and uses a maximum approximation when calculating the target signal, failing to account for the optical dispersion characteristics of point targets. Furthermore, the blackbody temperature and light barrier temperature are not equivalent to the airborne environment, making them susceptible to errors.

[0006] (2) In a laboratory environment, how can we accurately calculate the target signal energy from images and thus accurately calculate the signal-to-noise ratio of the onboard infrared search and tracking system?

[0007] When designing an airborne infrared search and tracking system, the system's signal-to-noise ratio capability is usually evaluated based on the following formula:

[0008] ;

[0009] in, μ t represents the mean value of the target signal in the time domain, that is, the target signal energy, μ b represents the mean value of the background in the time domain, δ b Represents the root mean square of the background in the time domain. When testing the system, because the background has a certain uniformity, the calculation μ b and δ b It is not complicated. How to accurately calculate from the image μ t It is the key to affecting the accuracy of SNR.

[0010] calculate μ t The difficulty lies in: the airborne infrared search and tracking system is in the long-range observation ( , is the projected area of the target on the visual axis, is the observation distance, is the instantaneous field of view of the system), the geometric size of the target can be ignored, that is, it can be considered as a point target. At this time, due to the diffraction limitation of the optical system, the point target appears as a diffuse spot on the detector. And because the position of the point target relative to the detection system is random, the position of the diffuse spot on the image plane is also random, such as Figure 1 Shown is a comparison of images produced by an airborne infrared search and tracking system for the same point target at different scanning times. The left and right images are the results of imaging the same point target, but because the point target has different pixel offsets, it appears in different shapes on the image.

[0011] Currently, industry and academia are μ t There are differences in the way of detecting weak targets in images. μ t There are generally two ways to calculate:

[0012] a) Select the maximum value in an n×n neighborhood;

[0013] b) Select the mean value within an n×n neighborhood.

[0014] We cannot get the same signal energy through these two methods. For example, if we use the maximum value method, then Figure 1 The left side of the figure is obtained μ t Obviously larger, if we use the average method, Figure 1 The left and right sides of the picture μ t It won't be the same.

[0015] Therefore, these two methods are acceptable for evaluating the small target detection capability of an image. However, according to the images produced by the infrared search and tracking system for point targets, these two methods cannot be used to verify the signal-to-noise ratio level of the airborne infrared search and tracking system. Summary of the Invention

[0016] The present invention solves the problem of equating point targets and backgrounds of an airborne infrared search and tracking system in a laboratory environment and accurately calculating target signal energy through images, thereby accurately calculating the signal-to-noise ratio of the airborne infrared search and tracking system.

[0017] Option 1: A point target and background equivalent device for an airborne infrared search and tracking system.

[0018] The device includes a cavity blackbody, a temperature-controlled aperture, a collimator and an infrared attenuation plate. The cavity blackbody, temperature-controlled aperture, collimator and infrared attenuation plate are coaxially arranged. The point target signal emitted by the cavity blackbody passes through the temperature-controlled aperture, collimator and infrared attenuation plate in sequence to form a target equivalent signal and a background equivalent signal output.

[0019] Furthermore, the cavity blackbody is used to simulate a point target and perform radiation equivalence on the point target;

[0020] The temperature-controlled aperture is used to simulate the background, perform radiation equivalence on the background, and set the size of the point target;

[0021] The collimator is used to simulate the transmission path of a point target;

[0022] The infrared attenuation sheet is used to simulate atmospheric attenuation.

[0023] Furthermore, the diameter of the temperature-controlled aperture d ph for:

[0024] ;

[0025] in, d t is the point target width, R To detect the distance, f col is the focal length of the collimator.

[0026] Furthermore, the radiation equivalence of the point target is performed by the following steps:

[0027] S401. Determine the radiant flux of point targets expected to be collected by the airborne infrared search and tracking system sensor Pt ;

[0028] S402, adjust the cavity blackbody temperature so that the point target radiant flux output by the airborne infrared search and tracking system point target and background equivalent device is equal to Pt same;

[0029] The radiation equivalence of the background is performed by the following steps:

[0030] S403: Determine the background radiant flux expected to be collected by the airborne infrared search and tracking system sensor P b ;

[0031] S404, adjust the temperature of the temperature-controlled aperture so that the background radiant flux output by the point target and background equivalent device of the airborne infrared search and tracking system is equal to P b same.

[0032] Solution 2: A method for testing the signal-to-noise ratio of an airborne infrared search and tracking system, the method comprising the following steps:

[0033] S501, using the above-mentioned airborne infrared search and tracking system point target and background equivalent device to transmit a target equivalent signal and a background equivalent signal;

[0034] S502: Use an airborne infrared search and tracking system to scan the optical signal emitted by the device and obtain M × N Frame image, where M Represents the product of the number of row frames and column frames per scan, N Indicates the number of scans;

[0035] S503, determining a filtering area using a filtering method based on an Airy disk prior;

[0036] S504, yes M × N Perform traversal filtering on a single pixel in the frame image to obtain the signal value of the single pixel;

[0037] S505: Calculate the signal value of each scan according to the signal value of the single pixel. M The target signal value and background mean in the frame image;

[0038] S506: Calculate a signal-to-noise ratio test result according to the target signal value and the background mean value.

[0039] Furthermore, in step S502, the airborne infrared search and tracking system is used to scan the optical signal emitted by the device, and the following steps are used:

[0040] S601, adjusting the operating mode of the airborne infrared search and tracking system to search mode;

[0041] S602, proceed N Scan times so that each scan has a frame of image covering the target;

[0042] S603, obtain M×N Frame Image I m,n ( n ∈[1, N ], m ∈[1, M ]);

[0043] S604. Adjust the integration time of the airborne infrared search and tracking system detector to make the image unsaturated.

[0044] Furthermore, in step S503, the filtering method based on the Airy disk prior determines the filtering area, which means dividing the filtering area into regions A ,area B and region C ,area A ,area B and region C The center of each filter area is the same; the division principle of each filter area is:

[0045] The main lobe of the Airy disk of the optical telescope in the airborne infrared search and tracking system is set as the area A ,area A The radius of the main lobe of the Airy disk is r airy ;

[0046] Set the pixel neighborhood occupied by the point target signal as the region C , the area is obtained by calculation C Number of pixels N C ,use

[0047] ;

[0048] Implementation, where b is the pixel size; area C The height and width are pixels;

[0049] Set the background neighborhood of the point target signal as the region B ,area B The height and width are pixels, N B For the region B The number of pixels in , satisfies: N B > NC and N B < N 1, among which N 1 is the number of pixels in each frame.

[0050] Further, in step S504, M × N Perform traversal filtering on a single pixel in the frame image to obtain the signal value of a single pixel; the following steps are used:

[0051] S801, calculation area B Background signal value in ,use:

[0052] ;

[0053] Implementation, where i Represents the horizontal coordinate of the pixel in each frame image, j Indicates the vertical coordinate of the pixel in each frame image, DN (·)express M × N In the frame image, the coordinates are ( i , j )’s pixel digital value;

[0054] S802, calculate the coordinates as ( i , j ) of the pixel's Airy disk energy value ,use:

[0055] ;

[0056] implementation, where M A For the region A The area, M C For the region C area;

[0057] S803, calculate the coordinates as ( i , j ) pixel signal value , That is the signal value of a single pixel, using:

[0058] ;

[0059] Implementation, where A d Represents the area of a single pixel.

[0060] Further, in step S505, the calculation of each scanM The target signal value and background mean in the frame image are calculated using the following steps:

[0061] S901, calculate target signal value ,use:

[0062] ;

[0063] Implementation, where , agrmax (·) means to find the maximum value; Indicates the frame number corresponding to the maximum signal value of a single pixel, The maximum signal value of a single pixel corresponds to the horizontal coordinate of the pixel. The maximum signal value of a single pixel corresponds to the vertical coordinate of the pixel;

[0064] S902, calculate background mean ,use:

[0065] ;

[0066] accomplish.

[0067] Furthermore, in step S506, the signal-to-noise ratio test result is calculated using:

[0068] ;

[0069] implementation, where:

[0070] SNR represents the signal-to-noise ratio;

[0071] μ t Represents the mean value of the target signal in the time domain ;

[0072] μ b Represents the mean value of the background in the time domain ;

[0073] δ b Represents the standard deviation of the background in the time domain

[0074] .

[0075] The beneficial effects of the point target and background equivalent device of the airborne infrared search and tracking system described in the first solution of the present invention are:

[0076] (1) The device can realistically simulate point targets in outdoor environments. It uses a chamber blackbody to simulate point targets, and performs radiation equivalence on the point targets by changing the temperature of the chamber blackbody. It uses a temperature-controlled aperture to simulate the background of the point targets, and performs radiation equivalence on the background by changing the temperature of the temperature-controlled aperture. It uses a parallel light tube to simulate the transmission path of the point targets, and the parallel light emitted by the parallel light tube realistically simulates the transmission path of the long-distance targets in the natural environment. It uses an infrared attenuation sheet to simulate the attenuation effect of the atmosphere in the real environment on the point target signal. By simulating each link in the point target signal transmission process, the radiation characteristics of the point target and the background in the actual working environment are accurately restored. The device has a simple structure and is easy to operate.

[0077] (2) The temperature-controlled aperture is multifunctionally reused. The temperature-controlled aperture can not only simulate the point target background, but also control the size of the chamber blackbody output point target by controlling the diameter of the temperature-controlled aperture, thereby saving the original components of the device. The above device can achieve the equivalence of point targets and backgrounds in the airborne infrared search and tracking system under laboratory conditions through a simple combination of components. When calculating the signal-to-noise ratio of the airborne infrared search and tracking system, it saves resources and is easy to operate.

[0078] (3) When performing point target and background equivalence, the device utilizes the principle of radiant flux equivalence to infer the radiant flux of the cavity blackbody and the temperature-controlled aperture from the target radiant flux and background radiant flux expected to be collected by the airborne infrared search and tracking system sensor. The equivalence method can ensure accurate simulation of the radiation characteristics of the point target and background with high simulation accuracy.

[0079] The signal-to-noise ratio testing method for an airborne infrared search and tracking system according to the second solution of the present invention has the following beneficial effects:

[0080] In an airborne infrared search and tracking system, a point target is a circular spot (similar to the light emitted by a flashlight), and its intensity at each position is different, with the center of the circle being particularly "bright" and the periphery of the circle being particularly "dark"; after the point target is irradiated onto the detector, the detector receives the target's energy (light) and then converts it into an image that we can see (similar to an electrical signal), but the basic unit of the detector is a square pixel of a certain size, and it is impossible to accurately segment the shape of the incident target circular spot. The method described in the present invention adopts the principle of indirect solution, and divides the energy area of the point target into the main energy area, the background neighborhood, and the pixel neighborhood. The main energy area is the area where the main lobe of the Airy disk is located, and the radius of the main lobe of the Airy disk can be obtained, so the area of the main energy area can also be obtained; and traversal filtering is performed to indirectly calculate the signal estimation value of the main energy area through the signal estimation value and area relationship of the background neighborhood and the pixel neighborhood, that is, the mean value of the target signal in the time domain. μ t Compared with the existing technology μ t The calculation method is as follows: a) select the maximum value in an n×n neighborhood; b) select the average value in an n×n neighborhood; the signal-to-noise ratio test method of the airborne infrared search and tracking system of the present invention is calculated μ t It is more accurate and will not produce different calculation results due to different offsets of point targets on pixels, thereby making the calculation of the signal-to-noise ratio of the airborne infrared search and tracking system more accurate.

[0081] The airborne infrared search and tracking system point target and background equivalent device described in the present invention can be applied in the fields of aviation simulation test technology and aviation laboratory simulation technology; the signal-to-noise ratio test method described in the present invention can be applied in the fields of target energy test and signal-to-noise ratio test of aircraft tracking systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 This is a comparison of images produced by the airborne infrared search and tracking system for the same target at different scanning moments;

[0083] Figure 2 This is a structural diagram of a point target and background equivalent device in an embodiment of the present invention;

[0084] Figure 3 Schematic diagram of the signal transmission relationship between the point target and background equivalent device and the airborne infrared search and tracking system in an embodiment of the present invention;

[0085] Figure 4 Schematic diagram of the number of row frames and column frames in each scan in an embodiment of the present invention;

[0086] Figure 5 This is a schematic diagram of area division during filtering in an embodiment of the present invention;

[0087] Figure 6 A schematic diagram of an image containing a target according to an embodiment of the present invention;

[0088] Figure 7 Schematic diagram of the filtering area determined in an embodiment of the present invention. DETAILED DESCRIPTION

[0089] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all 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.

[0090] Example 1.

[0091] This embodiment provides an airborne infrared search and tracking system point target and background equivalent device, the device is as follows Figure 2 As shown, it includes a cavity blackbody, a temperature-controlled aperture, a collimator, and an infrared attenuation plate. The centers of the cavity blackbody, the temperature-controlled aperture, the collimator, and the infrared attenuation plate are located on a horizontal line. The point target signal emitted by the cavity blackbody passes through the temperature-controlled aperture, the collimator, and the infrared attenuation plate in sequence and then enters the airborne infrared search and tracking system.

[0092] The cavity blackbody is used to simulate a point target and perform radiation equivalence on the point target;

[0093] The temperature-controlled aperture is used to simulate the background and perform radiation equivalence on the background;

[0094] The collimator is used to simulate the transmission path of a point target;

[0095] The infrared attenuation sheet is used to simulate atmospheric attenuation.

[0096] The radiation equivalent of point targets is achieved using a cavity blackbody, the radiation equivalent of the background is achieved using a temperature-controlled aperture, and the radiation equivalent of the atmosphere is achieved using an attenuator. The blackbody can be adjusted in temperature to simulate the target temperature; the temperature-controlled aperture is adjusted in temperature using a semiconductor cooler and closed-loop temperature control by a controller, thereby improving the aperture temperature control accuracy and accurately simulating the background temperature; the attenuator is used to simulate atmospheric attenuation. Furthermore, based on the simulated atmospheric path radiation and the calibrated collimator radiation, the blackbody and temperature-controlled aperture are further corrected through temperature equivalence.

[0097] Example 2.

[0098] This embodiment is a further limitation of the first embodiment, and the temperature-controlled diaphragm is multifunctionally multiplexed. The temperature-controlled diaphragm can not only simulate the point target background, but also control the size of the chamber blackbody output point target by controlling the diameter of the temperature-controlled diaphragm, thereby saving the original components of the device.

[0099] The diameter of the temperature-controlled aperture d ph use:

[0100] ;

[0101] Implementation, where d t is the point target width, R To detect the distance, f col is the focal length of the collimator.

[0102] The above device can realize the equivalence of point targets and backgrounds of airborne infrared search and tracking systems under laboratory conditions through a simple combination of devices, and realizes resource conservation and simple operation when calculating the signal-to-noise ratio of the airborne infrared search and tracking system.

[0103] Example 3.

[0104] This embodiment is a further limitation of the embodiment 1. The radiation equivalent of the point target is performed, and the signal transmission relationship between the point target and the background equivalent device and the airborne infrared search and tracking system is as follows: Figure 3 As shown, the detector in the airborne infrared search and tracking system collects point targets through an optical telescope, and the radiation equivalent of the point target is performed using the following steps:

[0105] S301. Determine the radiant flux of the point target expected to be collected by the airborne infrared search and tracking system sensor Pt ,use:

[0106] ;

[0107] implementation, where is the background radiant flux expected to be collected by the airborne infrared search and tracking system sensor,

[0108] is the radiation intensity of the target, is the radiance of the sky background, is the projected area of the target on the optical axis, is the aperture of the sensor optical telescope, is the atmospheric transmittance, is the transmittance of the optical telescope system, is the energy concentration, is the atmospheric path radiation, The instantaneous field of view of a detector pixel.

[0109] S302, adjust the cavity blackbody temperature so that the point target radiant flux output by the airborne infrared search and tracking system point target and background equivalent device is and Pt Similarly, the point target radiant flux output by the point target and background equivalent device of the airborne infrared search and tracking system is ,use:

[0110] ;

[0111] Implementation, where is the radiance of the black body, is the radiance of the temperature-controlled aperture, is the area of the aperture, is the focal length of the collimator, is the exit pupil area of the collimator, is the collimator transmittance, is the transmittance of the attenuator, is the radiant flux of the collimator, The background radiant flux output by the point target and background equivalent device of the airborne infrared search and tracking system is is the projected area of one pixel of the airborne infrared search and tracking system sensor on the focal plane of the light tube ( ,in is the area of a single pixel, is the focal length of the optical telescope in the airborne infrared search and tracking system).

[0112] By making , and the blackbody radiance is obtained , and then through Planck's law, using

[0113] ;

[0114] Get blackbody temperature ,in, h represents Planck's constant, c represents the speed of light, v Indicates the frequency of infrared radiation, k represents the Boltzmann constant.

[0115] Example 4.

[0116] This embodiment further limits the embodiment 1, wherein the radiation equivalence of the background is performed by the following steps:

[0117] S401: Determine the background radiant flux expected to be collected by the airborne infrared search and tracking system sensor P b ,use:

[0118] ;

[0119] Implementation, where is the atmospheric path radiation, is the instantaneous field of view of the airborne infrared search and tracking system detector pixel.

[0120] S402, adjust the temperature of the temperature-controlled aperture to make the background radiant flux output by the point target and background equivalent device of the airborne infrared search and tracking system and P b Same, that is P b , calculate the radiance of the temperature-controlled aperture , and then through Planck's law, using

[0121]

[0122] Get the temperature of the temperature-controlled aperture .

[0123] Example 5.

[0124] This embodiment provides a method for testing the signal-to-noise ratio of an airborne infrared search and tracking system, the method comprising the following steps:

[0125] S501. Use the airborne infrared search and tracking system point target and background equivalent device described in Solution 1 to launch a point target.

[0126] S502, use the airborne infrared search and tracking system to scan and obtain M × N Frame image, where M Represents the product of the number of row frames and column frames per scan, N Indicates the number of scans;

[0127] S503, determining a filtering area using a filtering method based on an Airy disk prior;

[0128] S504, yes M × N Perform traversal filtering on a single pixel in the frame image to obtain the signal value of the single pixel;

[0129] S505, calculate each scan M The target signal value and background mean in the frame image;

[0130] S506: Calculate the signal-to-noise ratio test result.

[0131] Example 6.

[0132] This embodiment is a further limitation of embodiment 5. In step S2, the scanning is performed using an airborne infrared search and tracking system using the following steps:

[0133] S601, adjusting the operating mode of the airborne infrared search and tracking system to search mode;

[0134] S602, proceed N Scan multiple times, so that each scan has a frame of image covering the target, and each scan will scan a certain number of row frames and a certain number of column frames, such as Figure 4 As shown;

[0135] S603, obtain M×N Frame Image I m,n (n ∈[1, N ], m ∈[1, M ]);

[0136] S604. Adjust the integration time of the airborne infrared search and tracking system detector to make the image unsaturated.

[0137] Example 7.

[0138] This embodiment further limits the embodiment 5. In step S503, the filtering area is determined by the following steps:

[0139] S701, dividing the filtering area into regions A ,area B and region C ,area A ,area B and region C The center of is the same as Figure 5 The diagram shown is a schematic diagram of the divided areas.

[0140] The main lobe of the Airy disk of the optical telescope in the airborne infrared search and tracking system is set as the area A ,area A The radius of the main lobe of the Airy disk is r airy ,

[0141] ;

[0142] in, is the maximum wavelength of an optical telescope. It can be seen that is 、 、 Certainly, these three parameters are known parameters of the optical telescope, so they can be called "Airy disk priors".

[0143] Set the pixel neighborhood occupied by the point target signal as the region C , the area is obtained by calculation C Number of pixels N C ,use

[0144] ;

[0145] Implementation, where b is the pixel size; area C The height and width are pixels;

[0146] Set the background neighborhood of the point target signal as the region B,area B The height and width are pixels, N B For the region B The number of pixels in , satisfies: N B > N C and N B < N 1, among which N 1 is the number of pixels in each frame.

[0147] Example 8.

[0148] This embodiment is a further limitation of embodiment 5. In step S504, M × N Perform traversal filtering on a single pixel in the frame image to obtain the signal value of a single pixel; the following steps are used:

[0149] S801, calculation area B Background signal value in ,use:

[0150] ;

[0151] Implementation, where i Represents the horizontal coordinate of the pixel in each frame image, j Indicates the vertical coordinate of the pixel in each frame image, DN (·)express M × N In the frame image, the coordinates are ( i , j )’s pixel digital value;

[0152] like Figure 3 As shown, the airborne infrared search and tracking system has a detector, which is similar to the CCD or CMOS in a digital camera. It is used to perform photoelectric conversion and output images. After opening the image with image processing software, the digital value of each pixel (also called grayscale value, the so-called DN is the abbreviation of Digital Number) can be obtained.

[0153] S802, calculate the coordinates as ( i , j ) of the pixel's Airy disk energy value ,use:

[0154] ;

[0155] implementation, where M A For the regionA The area, , M C For the region C The area, ;

[0156] S803, calculate the coordinates as ( i , j ) pixel signal value , That is the signal value of a single pixel, using:

[0157] ;

[0158] Implementation, where A d Represents the area of a single pixel.

[0159] Example 9.

[0160] This embodiment is a further limitation of embodiment 5. In step S505, the calculation of each scan is M The target signal value and background mean in the frame image are calculated using the following steps:

[0161] S901, calculate target signal value ,use:

[0162] ;

[0163] Implementation, where , agrmax (·) means to find the maximum value; Indicates the frame number corresponding to the maximum signal value of a single pixel, The maximum signal value of a single pixel corresponds to the horizontal coordinate of the pixel. The maximum signal value of a single pixel corresponds to the vertical coordinate of the pixel;

[0164] S902, calculate background mean ,use:

[0165] ;

[0166] Computational implementation.

[0167] Example 10.

[0168] This embodiment further limits the embodiment 5. In step S506, the calculation of the signal-to-noise ratio test result is performed using:

[0169] ;

[0170] Implementation, where SNR represents the signal-to-noise ratio;

[0171] μ t represents the mean value of the target signal in the time domain, ;

[0172] μ b represents the mean value of the background in the time domain, ;

[0173] δ b represents the standard deviation of the background in the time domain,

[0174] .

[0175] Example 11.

[0176] This embodiment introduces the practical application of the signal-to-noise ratio test method of the airborne infrared search and tracking system described in Examples 5-8.

[0177] The environmental parameters of the airborne infrared search and tracking system during actual operation are shown in Table 1:

[0178] Table 1:

[0179]

[0180] The parameters of the point target and background equivalent device of the airborne infrared search and tracking system are shown in Table 2;

[0181] Table 2:

[0182]

[0183] The signal-to-noise ratio test method of the airborne infrared search and tracking system described in Examples 5-8 can be obtained:

[0184] Using the airborne infrared search and tracking system point target and background equivalent device described in Scheme 1, a point target is launched, wherein the diameter of the aperture is calculated to be 66.7 μm The radiance of the blackbody is 5.5152 W / (m2·sr), and the radiance of the temperature-controlled aperture is 4.7600 W / (m2·sr). It can be further calculated that the temperatures of the blackbody and the temperature-controlled aperture are 267.4K and 260.3K respectively. The airborne infrared search and tracking system is used to scan and obtain an image containing the target. Figure 6 As shown, the target image center coordinates are determined by the target detection algorithm as The filtering area is determined by the filtering method based on the Airy disk prior, and the calculated , assuming that the background area (area B) is 5×5, we can get area C and area B as follows Figure 7 As shown, based on the known data, the final test result of the signal-to-noise ratio is .

Claims

1. A method for testing the signal-to-noise ratio of an airborne infrared search and tracking system, characterized in that: The method comprises the following steps: S501. Use the airborne infrared search and tracking system point target and background equivalent device to transmit target equivalent signals and background equivalent signals; S502: Use an airborne infrared search and tracking system to scan the optical signal emitted by the device and obtain M × N Frame image, where M Represents the product of the number of row frames and column frames per scan, N Indicates the number of scans; S503, using the filtering method based on the Airy disk prior to determine the filtering area: the filtering area is divided into regions A ,area B and region C ,area A ,area B and region C The center of each filter area is the same; the division principle of each filter area is: The main lobe of the Airy disk of the optical telescope in the airborne infrared search and tracking system is set as the area A ,area A The radius of the main lobe of the Airy disk is r airy ; Set the pixel neighborhood occupied by the point target signal as the region C , the area is obtained by calculation C Number of pixels N C ,use ； Implementation, where b is the pixel size, area C The height and width are pixels; Set the background neighborhood of the point target signal as the region B ,area B The height and width are pixels, N B For the region B The number of pixels in , satisfies: N B > N C and N B < N 1, among which N 1 is the number of pixels in each frame; S504, yes M × N A single pixel in the frame image is filtered to obtain the signal value of the single pixel. Use the following steps: S801, calculation area B Background signal value in ,use: ； Implementation, where i Represents the horizontal coordinate of the pixel in each frame image, j Indicates the vertical coordinate of the pixel in each frame image, DN (·)express M × N In the frame image, the coordinates are ( i , j )’s pixel digital value; S802, calculate the coordinates as ( i , j ) of the pixel's Airy disk energy value ,use: ； implementation, where M A For the region A The area, M C For the region C area; S803, calculate the coordinates as ( i , j ) pixel signal value , That is the signal value of a single pixel, using: ； Implementation, where A d Represents the area of a single pixel; S505: Calculate the signal value of each scan according to the signal value of the single pixel. M The target signal value and background mean in the frame image; S506: Calculate a signal-to-noise ratio test result according to the target signal value and the background mean value.

2. The signal-to-noise ratio testing method according to claim 1, wherein: The point target and background equivalent device of the airborne infrared search and tracking system includes a cavity blackbody, a temperature-controlled aperture, a collimator and an infrared attenuation plate. The cavity blackbody, temperature-controlled aperture, collimator and infrared attenuation plate are coaxially arranged. The point target signal emitted by the cavity blackbody passes through the temperature-controlled aperture, collimator and infrared attenuation plate in sequence to form a target equivalent signal and a background equivalent signal output.

3. The signal-to-noise ratio testing method according to claim 2, wherein: The cavity blackbody is used to simulate a point target and perform radiation equivalence on the point target; The temperature-controlled aperture is used to simulate the background, perform radiation equivalence on the background, and set the size of the point target; The collimator is used to simulate the transmission path of a point target; The infrared attenuation sheet is used to simulate atmospheric attenuation.

4. The signal-to-noise ratio testing method according to claim 3, wherein: The diameter of the temperature-controlled aperture d ph for: ； in, d t is the point target width, R To detect the distance, f col is the focal length of the collimator.

5. The signal-to-noise ratio testing method according to claim 4, wherein: The radiation equivalence of the point target is performed by the following steps: S401. Determine the radiant flux of point targets expected to be collected by the airborne infrared search and tracking system sensor Pt ; S402, adjust the cavity blackbody temperature so that the point target radiant flux output by the airborne infrared search and tracking system point target and background equivalent device is equal to Pt same; The radiation equivalence of the background is performed by the following steps: S403: Determine the background radiant flux expected to be collected by the airborne infrared search and tracking system sensor P b ; S404, adjust the temperature of the temperature-controlled aperture so that the background radiant flux output by the point target and background equivalent device of the airborne infrared search and tracking system is equal to P b same.

6. The signal-to-noise ratio testing method according to claim 5, characterized in that: In step S502, the airborne infrared search and tracking system is used to scan the optical signal emitted by the device, and the following steps are used: S601, adjusting the operating mode of the airborne infrared search and tracking system to search mode; S602, proceed N Scan times so that each scan has a frame of image covering the target; S603, obtain M×N Frame Image I m,n ( n ∈[1, N ], m ∈[1, M ]); S604. Adjust the integration time of the airborne infrared search and tracking system detector to make the image unsaturated.

7. The signal-to-noise ratio testing method according to claim 6, wherein: In step S505, the calculation of each scan M The target signal value and background mean in the frame image are calculated using the following steps: S901, calculate target signal value ,use: ； Implementation, where , agrmax (·) means to find the maximum value; Indicates the frame number corresponding to the maximum signal value of a single pixel, The maximum signal value of a single pixel corresponds to the horizontal coordinate of the pixel. The maximum signal value of a single pixel corresponds to the vertical coordinate of the pixel; S902, calculate background mean ,use: ； accomplish.

8. The signal-to-noise ratio testing method according to claim 7, wherein: In step S506, the signal-to-noise ratio test result is calculated using: ； implementation, where: SNR represents the signal-to-noise ratio; μ t Represents the mean value of the target signal in the time domain ; μ b Represents the mean value of the background in the time domain ; δ b Represents the standard deviation of the background in the time domain 。

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