A method and system for multi-spectral comprehensive analysis of smoke screen masking jamming effect

Abstract

The embodiment of the present application discloses a kind of to the method and system of the multi-spectral comprehensive analysis of smoke screen masking interference effect, it is related to civil air defense engineering protection technical field, can automatically evaluate the interference camouflage effect of smoke screen masking.The present application includes: obtaining the image of protected target, and the feature extraction of significant area in image is carried out, then the eigenvalue of significant area is obtained;According to the obtained eigenvalue, the interference detection probability of the protected target under different smoke screen conditions is calculated, wherein the smoke screen condition at least one smoke screen type, smoke screen type corresponds to guidance mode, the guidance mode includes: optical, laser, thermal infrared and radar guidance;The calculation result of interference detection probability is sent to designer terminal.

Description

Technical Field

[0001] This invention relates to the field of civil defense engineering protection technology, and in particular to a method and system for multi-spectral comprehensive analysis of the interference effect of smoke screen shielding. Background Technology

[0002] For the protection of areas with significant economic value, it is necessary to consider not only the protection against reconnaissance / strike equipment in military confrontations (such as reconnaissance satellites and guided weapons), but also the reconnaissance issues of civilian reconnaissance equipment that poses security risks (such as some civilian satellites with imaging and remote sensing capabilities, as well as some civilian drones).

[0003] However, since designers in the civil building sector lack knowledge of military-related fields such as reconnaissance and smoke screen concealment, and designers with relevant knowledge in both military and civilian fields are relatively scarce, it is necessary to solve the problem of evaluating the smoke screen concealment effect under multi-spectral conditions, and to provide designers in the civil sector with fast, efficient and relatively accurate design evaluation results of the smoke screen concealment effect through technical means. Summary of the Invention

[0004] The embodiments of the present invention provide a method and system for multi-spectral comprehensive analysis of the interference effect of smoke screen concealment, which can automatically evaluate the interference camouflage effect of smoke screen concealment.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] In a first aspect, the method provided by embodiments of the present invention includes:

[0007] The image of the protected target is acquired, and the salient regions in the image are extracted. Then the feature values ​​of the salient regions are calculated.

[0008] Based on the obtained feature values, the interference detection probability of the protected target under different smoke screen conditions is calculated, wherein the smoke screen conditions include at least one type of smoke screen, and the smoke screen type corresponds to the guidance method, which includes optical, laser, thermal infrared and radar guidance.

[0009] The calculated interference detection probability is sent to the designer's terminal.

[0010] Secondly, the system provided by the embodiments of the present invention includes: an image capturing platform, a background analysis and processing platform, and a designer terminal.

[0011] The image capturing platform is used to acquire images of the protected target and transmit them to the background analysis and processing platform;

[0012] The background analysis and processing platform is used to extract features from salient regions in the image and calculate the feature values ​​of the salient regions; based on the obtained feature values, it calculates the interference detection probability of the protected target under different smoke screen conditions, wherein the smoke screen conditions include at least one type of smoke screen, and the smoke screen type corresponds to the guidance method, including optical, laser, thermal infrared and radar guidance.

[0013] The designer's terminal is used to receive the calculation results of the interference detection probability sent by the background analysis and processing platform and display them on the display of the designer's terminal.

[0014] The method and system for multi-spectral comprehensive analysis of smoke screen interference effects provided in this invention automatically calculates the physical characteristics of the protected target and adjacent background, as well as the smoke screen interference probability under different smoke screen types, based on the salient area of ​​the image of the protected target. This data is then provided to designers as a basis for subsequent design. Since the calculation process is automated, designers do not need extensive military expertise in reconnaissance and camouflage. This allows for independent design by civilian building engineers without military backgrounds, achieving the goal of providing civilian designers with fast, efficient, and relatively accurate design evaluation results for smoke screen interference effects. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the optical image of the protected target obscured by smoke in a specific example provided in the embodiments of the present invention.

[0017] Figure 2 A flowchart illustrating the salient region algorithm in a specific example provided in this embodiment of the invention.

[0018] Figure 3 This is a schematic diagram of the process for obtaining feature values ​​in a specific example provided in the embodiments of the present invention.

[0019] Figure 4 This is a flowchart illustrating the calculation process in a specific example provided in this embodiment of the invention.

[0020] Figure 5This is a schematic diagram of the overall logical architecture in a specific example provided by an embodiment of the present invention.

[0021] Figure 6 This is a schematic diagram of the method flow provided in an embodiment of the present invention.

[0022] Figure 7 This is a schematic diagram of the system architecture provided for an embodiment of the present invention.

[0023] Figure 8 This is a schematic diagram of the interaction process in the system provided in an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Embodiments of the present invention will be described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in the specification of the present invention means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or couplings. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0025] This invention provides a method for multi-spectral comprehensive analysis of the interference effect of smoke screen obscuring. In practical applications, this method can be applied to a situation such as... Figure 6 , 8 The system shown includes: an image capture platform, a background analysis platform, and a designer terminal.

[0026] The image capturing platform is used to acquire images of the protected target and transmit them to the background analysis and processing platform.

[0027] The background analysis and processing platform is used to extract features from salient regions in an image and calculate feature values ​​for these salient regions. Based on the obtained feature values, it calculates the interference detection probability of the protected target under different smoke screen conditions. The smoke screen conditions include at least one smoke screen type, which corresponds to a guidance method. The guidance methods include optical, laser, thermal infrared, and radar guidance. In practical applications, the background analysis and processing platform can specifically be a server device that can run virtual modules. These virtual modules can be implemented using computer programs, including:

[0028] The image processing module is used to extract salient regions from images captured by the UAV in the direction of the incoming guided weapon, and to determine the salient regions of the protected target in the direction of the incoming guided weapon.

[0029] The feature extraction module extracts feature values ​​of salient areas of the protected target in the direction of the incoming guided weapon;

[0030] The analysis module is used to calculate the detection probability of the protected target before it is covered by smoke and under different smoke screen types, using the characteristic values ​​of the protected target. There are at least four smoke screen types.

[0031] The sending module is used to send the calculated detection probability results to the designer's terminal.

[0032] The image processing module is specifically used to extract the feature values ​​of the protected target from the image after processing the salient area; the analysis module is specifically used to determine the detection probability of the protected target in the absence of smoke screen obstruction by using the feature values ​​of the salient area of ​​the protected target; and to calculate the detection probability of the protected target under different smoke screen types by using the feature values ​​of the salient area of ​​the protected target, wherein the types associated with the smoke screen index requirements include: optical band, laser, thermal infrared band and radar band.

[0033] The designer's terminal is used to receive the calculated interference detection probability from the background analysis and processing platform and display it on the designer's terminal's screen, thereby characterizing the multi-spectral interference camouflage effect of smoke screen cover. The multi-spectral camouflage effect includes the calculated interference detection probability under various smoke screen types. For example, the image acquisition platform is a drone, and the interaction process between the various terminals in the system can be implemented as follows: the drone can capture images of the protected target in the direction of the guided weapon's attack and send the captured images of the protected target to the background analysis and processing platform. The background analysis and processing platform performs salient region processing on the protected target images captured by the drone to obtain salient region images of the protected target in the direction of the guided weapon's attack. Then, feature values ​​of the protected target are extracted based on the salient region images. Subsequently, using the feature values ​​of the protected target, the interference detection probability of the protected target before smoke screen cover and under different smoke screen types is determined, and the calculated interference detection probability is sent to the designer's terminal, wherein there are at least four smoke screen types. The designer's terminal needs to display and characterize the interference camouflage effect of the smoke screen, which includes the interference detection probability calculation results under various smoke screen types.

[0034] The method for multi-spectral comprehensive analysis of the smoke screen obscuring interference effect is as follows: Figure 7 As shown, it includes:

[0035] S1. Acquire an image of the protected target, extract features from the salient regions in the image, and then calculate the feature values ​​of the salient regions.

[0036] The salient region can be understood as the area in an image with the most obvious color contrast. These areas are often easily targeted by guided weapons. Distinguishing which regions are salient can be done using current techniques for generating saliency maps. The process of extracting features from the salient regions in the image and then calculating their feature values ​​includes: identifying the salient regions in the image, extracting the area containing the protected target and the adjacent background area within the salient regions; extracting image features from the area containing the protected target, and calculating the feature values. For example... Figure 4As shown, since image-based guided weapons generally target the most salient features in an image, for complex civil defense targets with multiple attributes, large size, and intricate composition, smoke screens can be used to obstruct the guided weapon's attack based on the most salient area of ​​such targets. Therefore, salient area processing is performed on images taken in the direction of the guided weapon's attack to provide a basic platform for evaluating smoke screen configuration and jamming camouflage effects. In the target area, salient area processing is performed on images of the protected target taken by the UAV to obtain salient area images of the protected target in the direction of the guided weapon's attack. The size of the salient area image of the protected target must be no less than 10×10 pixels. For example: Figure 1 As shown, the main protected target area is selected, and an image acquisition platform is used to capture images of the area in the direction of the incoming guided weapon to simulate terminal guidance, obtaining images of the protected target. The target smoke screen obscuring area is not less than 10×10 pixels in the entire field of view. Processing is performed using an L*a*b* uniform color space. Since atmospheric attenuation and air curtain brightness only affect brightness, only the brightness component L* in the L*a*b* uniform color space needs to be processed. The calculation process is as follows: Figure 3 .

[0037] S2. Based on the obtained feature values, calculate the interference detection probability of the protected target under different smoke screen conditions.

[0038] The smoke screen conditions include no smoke screen coverage or at least one type of smoke screen. The smoke screen type corresponds to the guidance method, which includes optical, laser, thermal infrared, and radar guidance. Specifically, the smoke screen types include at least two major categories: smoke agents and chaff; and the smoke agent categories include at least four subcategories: mist oil, red phosphorus, acid mist, and hexachloromethane. Specifically, the protected target and adjacent background are extracted from the image after processing the salient area, and the feature values ​​of the protected target in the direction of the guided weapon's attack are obtained. The feature values ​​of the protected target include those under a preset guidance method. The preset guidance methods include optical, laser, thermal infrared, and radar guidance. Then, the feature values ​​of the protected target are obtained using the feature values ​​of the salient area. For example: Calculating optical characteristic values: L*a*b*, where L* is the lightness coordinate, and a* and b* are the chromaticity coordinates; calculating laser characteristic values: ρ is the characteristic value of the laser reflectivity coefficient; calculating thermal infrared radiation characteristic values: T is the characteristic value of thermal infrared radiation (absolute temperature); calculating radar cross section (RCS) characteristic values: σ is the characteristic value of the radar cross section. Specifically, image conversion techniques are used to convert the image to the L*a*b* color space. The uniform color space L*a*b* values ​​and laser reflectivity coefficients of the salient area of ​​the protected target and the adjacent background are calculated. The radiation temperature values ​​of the salient area of ​​the protected target and the adjacent background are determined based on the temperature scale color. Using the obtained radiation temperature, uniform color space L*a*b* values, laser reflectivity coefficient, and radar cross section (RCS) values, the characteristic values ​​of the salient area of ​​the protected target and the adjacent background are determined.

[0039] By utilizing the characteristic values ​​of the salient area of ​​the protected target, the detection probability of the salient area of ​​the protected target before smoke cover is determined. Using the characteristic values ​​of the smoke cover conditions of the salient area of ​​the protected target, the detection probability of the salient area of ​​the protected target under different smoke cover types is calculated. The types associated with the different smoke cover types include: optical band, laser, thermal infrared band, and radar band. In practical applications, the constructed detection probability of the protected target before smoke cover includes: the detection probability of the protected target before smoke cover under optical, laser, thermal infrared, and radar guidance.

[0040] S3. Send the calculated interference detection probability to the designer's terminal.

[0041] Based on the physical characteristics of a significant area of ​​a protected target, the guidance and identification situation before smoke screen obscuring can be calculated. This guidance and identification includes multiple guidance methods and corresponding detection probabilities. These multiple guidance methods include at least optical, laser, thermal infrared, and radar millimeter-wave guidance. Furthermore, based on the type of smoke screen obscuring the target, the interference probability is calculated. Specifically, for different smoke screen types (four types), the detection probability, identification probability, and interference probability of these smoke screen types under multiple guidance methods are calculated.

[0042] In this embodiment, based on salient area image processing, the uniform color space L*a*b* values ​​and laser reflectance coefficients of the salient area of ​​the protected target and the adjacent background are obtained; the radiation temperature of the salient area of ​​the protected target and the adjacent background is determined according to the temperature scale color. Then, using the obtained radiation temperature, uniform color space L*a*b* values, and laser reflectance coefficients, feature values ​​of the protected target are extracted. For example: Figure 4 As shown, based on salient area image processing, the salient area of ​​the protected target and the adjacent background area are selected respectively. The uniform color space L*a*b* values ​​and laser reflectivity of the salient area of ​​the protected target and the background are calculated. The radiation temperature of the salient area of ​​the protected target and the adjacent background is determined according to the temperature scale color. Based on the salient area of ​​the protected target, the background color is removed, and the radar cross section (RCS) value of the salient area of ​​the protected target is calculated using the pixel method. Specifically:

[0043] The OpenCV-based optical feature extraction method includes: selecting a salient region of the protected target and converting it to the target's L*a*b* value; selecting a background region and converting it to the background's L*a*b* value; and using the formula `Mat Lab = Mat(cvSize(1,1),CV_32FC3)`, where `Lab` is the converted L*a*b* value, and `src.convertTo(Lab,CV_32FC3,1 / 255.0)`, where `src` is the input image, and `cvtColor(src,Lab,COLOR_BGR2Lab)`.

[0044] The laser feature extraction method based on OpenCV includes: using the cvtColor(src,XYZ,COLOR_BGR2XYZ) function to calculate the approximate laser reflection coefficient value between the salient area of ​​the protected target and the background = Y / 100.0.

[0045] The methods for thermal infrared feature extraction include: converting the input image to a grayscale image, calculating the average grayscale value of the salient area of ​​the protected target, selecting adjacent background areas, and calculating the average grayscale value of the background areas. Finally, calculating the radiation temperature of the protected target and the background based on the grayscale values ​​on a temperature scale.

[0046] The radar cross section calculation method includes: taking the center point of the salient area of ​​the protected target as the origin, and treating each pixel as an independent scatterer, calculating the radar cross section of each pixel: Where A represents the area of ​​a single pixel, λ represents the radar operating wavelength, and θ represents the angle between a pixel and the origin. The instantaneous effective scattering area of ​​the synthesized salient region of the protected target is then the vector sum of the cross-sections of each component.

[0047] In this embodiment, step S4 includes: obtaining the L*a*b* feature values ​​of the optical features, where L* is the lightness coordinate and a* and b* are the chromaticity coordinates; obtaining the feature value ρ of the laser features; obtaining the feature value T of the thermal infrared features; and obtaining the feature value σ of the radar cross section.

[0048] In this embodiment, the probability of detection of a significant area of ​​the protected target before smoke cover is obtained using the acquired feature values. For example, the evaluation of camouflage effect based on CCD imaging is an evaluation method based on optical image processing. In this method, the target and background are generally given values ​​in the RGB color space, while atmospheric color attenuation occurs in the XYZ colors. Therefore, color space conversion is required before calculation. Specifically, extracting image features of the area where the protected target is located and calculating feature values ​​includes: extracting the RGB color space values ​​of the area where the protected target is located and converting them to tristimulus values, where:

[0049] The tristimulus values ​​of the apparent color of the area where the protected target is located are:

[0050] X OR =100r H (1-e -αR )+e -αR X O

[0051] Y OR =100r H (1-e -αR )+e -αR Y O

[0052] Z OR =100r H (1-e -αR )+e -αR Z O

[0053] Where, r H The brightness coefficient is the value corresponding to the brightness of the air curtain, α is the atmospheric extinction coefficient, R is the detection distance, Y0 is the tristimulus value of the target color (green), Z0 is the tristimulus value of the target color (blue), and X0 is the tristimulus value of the target color (red).

[0054] The tristimulus values ​​of the apparent color of the region containing the background are:

[0055] X BR =100r H (1-e αR )+e -αR X B

[0056] Y BR =100r H (1-e αR )+e -αR Y B

[0057] Z BR =100r H (1-e αR )+e -αR Z B

[0058] Y B The background color is green, Z is the tristimulus value. B The background color is blue (tristimulus value), X B The background color is red (tristimulus value).

[0059] The step of calculating the interference detection probability of the protected target under different smoke screen conditions based on the obtained feature values ​​includes: determining the detection probability of the area where the protected target is located without smoke screen obstruction based on the image feature values ​​of the area where the protected target is located; and determining the detection probability of the protected target under different smoke screen types based on the image feature values ​​of the area where the protected target is located.

[0060] The determination of the detection probability of the area where the protected target is located without smoke screen obscuring, i.e., the calculation of the detection probability of the protected target before smoke screen obscuring, includes:

[0061] Determine the apparent brightness contrast between the protected target and the background: Among them, Y S The brightness value is calculated based on the color difference between the target and the background.

[0062] Obtain the optical guidance detection probability of the area where the protected target is located without smoke screen obstruction: Where K' is the visual brightness contrast between the target and the background, ε is the brightness contrast threshold, σ = 0.39, and x represents the variables in the function calculation process;

[0063] Obtain the probability of laser-guided detection of the area where the protected target is located without smoke screen obstruction: in, P t Let η be the laser power, η be the quantum efficiency, and τ be the quantum efficiency. s r is the system loss factor. o denoted as the target reflectivity, hv as the photon energy, B as the noise bandwidth, A0 as the receiver aperture, L as the detection range, A as the effective reflective area, s as the atmospheric extinction coefficient, and erf() as the compensation error function.

[0064] Obtain the probability of thermal infrared guided detection of the area where the protected target is located without smoke screen cover. Where ε is the emissivity of the resolution cell, λ1 and λ2 are the operating wavelengths of the thermal imaging system, α is the atmospheric extinction index, R is the detection range, and T is the radiation temperature of the resolution cell. a For temperature, Y ae Let M(λ,T) and M(λ,T) represent the apparent ambient temperature. ae M(λ, T) a These represent the radiative exitance of the resolution unit itself, the environment, and the atmosphere, respectively.

[0065] It also includes: obtaining the radar-guided detection probability of the area where the protected target is located under no smoke screen cover. P fa This represents the radar false alarm probability. P t G is the peak power of the transmitter. t =G r Let σ be the main lobe gain of the transceiver antenna, σ be the target's RCS value, λ be the radar operating wavelength, k be the Boltzmann constant, T0 be the internal noise temperature, and B be the base plate. n For receiver bandwidth, F n L is the noise figure of the receiver. s The loss coefficients introduced for the losses of various parts of the radar are α, where α is the atmospheric extinction coefficient, and R is the loss coefficient. T Indicates the radar detection range.

[0066] Determining the detection probability of the protected target under different smoke screen types includes:

[0067] The apparent brightness contrast between the protected target and the background is changed to

[0068] In the process of obtaining the probability of thermal infrared guided detection of the area where the protected target is located under the cover of the smoke screen created by the smoke agent, the following updates are made: β s C is the infrared smoke extinction coefficient; D is the infrared smoke concentration; and D is the infrared smoke thickness.

[0069] In the process of obtaining the probability of laser-guided detection in the area where the protected target is located under the cover of the smoke screen created by the smoke agent, the following updates are made: β f C is the extinction coefficient of the laser smoke screen; D is the concentration of the laser smoke screen; and D is the thickness of the laser smoke screen.

[0070] In the process of obtaining the radar guidance detection probability of the area where the protected target is located under the smoke screen created by the chaff, the update ρ is the foil volume; n is the number of foils; D is the foil thickness.

[0071] Specifically, in this embodiment, the acquired feature values ​​can be used to calculate the detection probability of a salient area of ​​the protected target before it is obscured by smoke under optical, laser, thermal infrared, and radar guidance. For example, the evaluation of camouflage effect based on CCD imaging is an evaluation method based on optical image processing. In this method, the target and background are generally given values ​​in the RGB color space, while atmospheric color attenuation occurs in the XYZ colors. Therefore, color space conversion is required before calculation. The method for calculating the detection probability of the protected target before it is obscured by smoke is as follows:

[0072] The apparent color tristimulus values ​​of the salient area of ​​the protected target are:

[0073] X OR =100r H (1-e -αR )+e -αR X O

[0074] Y OR =100r H (1-e -αR )+e -αR Y O

[0075] Z OR =100r H (1-e -αR )+e -αR Z O

[0076] r H The value is the brightness coefficient corresponding to the brightness of the air curtain, α is the atmospheric extinction coefficient, R is the detection distance, Y0 is the tristimulus value of the target color (green), Z0 is the tristimulus value of the target color (blue), and X0 is the tristimulus value of the target color (red).

[0077] The apparent color tristimulus values ​​for the background are:

[0078] X BR =100r H (1-e αR )+e -αR X B

[0079] Y BR =100r H (1-e αR )+e -αR Y B

[0080] Z BR =100r H (1-e αR)+e -αR Z B

[0081] Y B The background color is green, Z is the tristimulus value. B The background color is blue (tristimulus value), X B The background color is red (tristimulus value).

[0082] Target and background apparent brightness contrast: Y S This is the brightness value calculated based on the color difference between the target and the background.

[0083] Based on the probability of optically guided detection:

[0084]

[0085] In the formula: K' is the visual brightness contrast between the target and the background, ε is the brightness contrast threshold, and σ = 0.39.

[0086] ε=0.325θ 0.819 θ<30'

[0087] ε=0.02 θ≥30' (2)

[0088] In the formula: θ is the angle subtended by the target at the human eye. θ≥30' indicates a large target, θ<30' indicates a small target, d is the target size, n is the number of line pairs (1 for detection, 4 for identification), and l is the detection distance.

[0089] Based on the probability of laser-guided detection:

[0090]

[0091]

[0092] In the formula: P t Let be the laser power, h be the quantum efficiency, and t be the laser power. s denoted as the system loss factor, r0 as the target reflectivity, hn as the photon energy, B as the noise bandwidth, A0 as the receiver aperture, L as the reconnaissance range, A as the effective reflective area, and s as the atmospheric extinction coefficient.

[0093] Based on the probability of thermal infrared guided detection:

[0094]

[0095] In the formula: ε is the emissivity of the resolution cell; λ1 and λ2 are the operating wavelengths of the thermal imaging system; α is the atmospheric extinction index; R is the detection range; T is the radiation temperature of the resolution cell; T a For temperature; Y aeFor apparent ambient temperature; M(λ,T), M(λ,T) ae M(λ, T) a These represent the radiative exitance of the resolution unit itself, the environment, and the atmosphere, respectively.

[0096] In the formula:

[0097]

[0098]

[0099] T a Rh is the atmospheric temperature. T0 is the triple point temperature. C1 and C2 are the first and second radiation constants, respectively.

[0100] For thermal infrared detection of targets, the key scene parameter is the apparent radiation contrast at the detector lens, i.e., the difference in radiative exitance between two resolution units. The instantaneous field of view is first calculated based on the thermal imager's field of view and resolution. Then, the number of pixels the target occupies on the thermal image is calculated based on the instantaneous field of view, target size, and detection distance. Next, the dynamic range of temperature is calculated based on the thermal resolution. Finally, the probability of visual detection and recognition is calculated based on the grayscale brightness contrast between the target and the background.

[0101] Based on the probability of radar-guided detection:

[0102]

[0103] In the formula: P fa The false alarm probability of radar is typically taken as 10. -6 erf(x) is the complement error function, and its calculation formula is:

[0104]

[0105]

[0106] In the formula, P t G is the peak power of the transmitter. t =G r Let σ be the main lobe gain of the transceiver antenna, σ be the target's RCS value, λ be the radar operating wavelength, k be the Boltzmann constant, T0 be the internal noise temperature, and B be the base plate. n For receiver bandwidth, F n L is the noise figure of the receiver. s The loss coefficient is introduced for the losses of various parts of the radar, and α is the atmospheric extinction coefficient.

[0107] The method for calculating the detection probability after the target is obscured by a smoke screen needs to be improved based on the method for calculating the detection probability before the target is obscured by a smoke screen. Specifically, the relevant mathematical model after the target is obscured by a smoke screen is modified as follows:

[0108] Optical smoke screen:

[0109]

[0110] Infrared smoke screen:

[0111]

[0112] Where: β s C is the infrared smoke extinction coefficient; D is the infrared smoke concentration; and D is the infrared smoke thickness.

[0113] Laser smoke screen:

[0114]

[0115] Where: β f C is the extinction coefficient of the laser smoke screen; D is the concentration of the laser smoke screen; and D is the thickness of the laser smoke screen.

[0116] Radar chaff:

[0117]

[0118] In the formula: ρ is the volume of the foil strip; n is the number of foil strips; D is the thickness of the foil strip.

[0119] Specifically, in the preferred embodiment, as shown in Table 1, the smoke screen types mainly include:

[0120] Optical band specifications: extinction coefficient of mist oil 3.20, red phosphorus 3.36, acid mist 3.48 and hexachloromethane 2.36, concentration 0.6, thickness 3m;

[0121] Laser specifications: Extinction coefficient of mist oil 3.54, red phosphorus 1.93, acid mist 2.19 and hexachloromethane 2.20, concentration 0.6, thickness 3m;

[0122] Thermal infrared band indicators: extinction coefficient of mist oil 0.10, red phosphorus 0.27, acid mist 0.23 and hexachloromethane 0.53, concentration 0.6, thickness 3m;

[0123] Radar band specifications: 50 foil strips, 1m thickness.

[0124] Table 1 Extinction coefficients of smoke agents for different wavelengths of light radiation

[0125]

[0126]

[0127] Specific implementation as follows Figure 5As shown, the probability of detection (identification) due to interference from optically guided smoke screens is calculated as follows: The detection (identification) probability is calculated under four different smoke screen types (see Table 1), and then the interference detection (identification) probability is calculated using the following formula: P 干 =(P 前 -P 后 ) / P 前 , where P 前 The probability of detection (recognition) before being obscured by smoke, P 后 The probability of detection (recognition) after being obscured by smoke, P 干 The probability of interference detection (identification).

[0128] Calculation of laser-guided smoke screen interference detection probability: The laser detection probability is calculated for each of the four smoke screen types (see Table 1), and then the interference probability is calculated using the following formula: P 干 =(P 前 -P 后 ) / P 前 , where P 前 The probability of laser detection before being obscured by smoke, P 后 The probability of laser detection after being obscured by smoke, P 干 This represents the probability of interference detection.

[0129] Calculation of the probability of detection interference from thermal infrared guided smoke screen: Based on the types of thermal infrared smoke screens (see Table 1), the probability of thermal infrared detection (identification) under four smoke screen types is calculated respectively. Then, the probability of interference detection (identification) is calculated using the following formula: P 干 =(P 前 -P 后 ) / P 前 , where P 前 The probability of thermal infrared detection (identification) before being obscured by smoke, P 后 The probability of thermal infrared detection (identification) after being covered by smoke screen, P 干 The probability of interference detection (identification).

[0130] Calculation of radar-guided chaff cloud interference detection probability: The detection probability of the chaff cloud is calculated based on the number and thickness of the chaff (see Table 1), and then the interference probability is calculated using the following formula: P 干 =(P 前 -P 后 ) / P 前 , where P 前 For the probability of detecting chaff, P 后 For the probability of detection behind the chaff, P 干 This represents the probability of interference detection.

[0131] Finally, the interference detection probability for the specified smoke screen type is determined. Tables 2 and 3 are then output to the designer's terminal, and displayed to the technical staff.

[0132] Table 2 Example Calculation Results

[0133]

[0134]

[0135] The output displayed to the designer's terminal is a multi-spectral guidance comprehensive evaluation of the smoke screen interference effect: Designer Terminal P 综合 =P1×P2×P3×P4, where P1 is the probability of detecting (identifying) optical guidance interference, P2 is the probability of detecting laser guidance interference, P3 is the probability of detecting (identifying) thermal infrared guidance interference, and P4 is the probability of detecting radar guidance interference.

[0136] Table 3 Multi-spectral comprehensive evaluation of the concealment effect of artificial camouflage.

[0137]

[0138]

[0139]

[0140]

[0141] This embodiment designs a multi-spectral comprehensive evaluation and calculation method for smoke screen masking interference effects based on image processing to obtain the optical reflection, thermal infrared radiation, and radar scattering characteristics of the target and background. The interference probability of the smoke screen masking effect is calculated for different physical characteristics of the protected target and smoke screen types, thus providing basic data for adopting appropriate smoke screen masking techniques. Specifically, based on the processing of salient areas of the protected target image, the L*a*b* values ​​and laser back reflectivity of the target and its adjacent background in a uniform color space are automatically calculated; the radiation temperature of the target and its adjacent background is automatically calculated based on thermal images under different conditions; and the radar cross section (RCS) value of the salient area of ​​the protected target is calculated based on a pixel-based method.

[0142] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The above descriptions are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for multi-spectral comprehensive analysis of the interference effect of smoke screen obscuring, characterized in that, include: The image of the protected target is acquired, and the salient regions in the image are extracted. Then the feature values ​​of the salient regions are calculated. Based on the obtained feature values, the interference detection probability of the protected target under different smoke screen conditions is calculated, wherein the smoke screen conditions include at least one type of smoke screen, and the smoke screen type corresponds to the guidance method, including optical, laser, thermal infrared and radar guidance. The types of smoke screens include foil strips; The calculated interference detection probability is sent to the designer's terminal; The probability of radar-guided detection in the area where the protected target is located without smoke screen obstruction is as follows: P fa This represents the radar false alarm probability. P t G is the peak power of the transmitter. t =G r Let σ be the main lobe gain of the transceiver antenna, σ be the target's RCS value, λ be the radar operating wavelength, k be the Boltzmann constant, T0 be the internal noise temperature, and B be the base plate. n For receiver bandwidth, F n L is the noise figure of the receiver. s Let α be the loss coefficient of each component of the radar, and α be the atmospheric extinction coefficient. This represents the radar detection range, and erf() is the error compensation function. When determining the detection probability of the protected target under different smoke screen types, the apparent brightness contrast between the protected target and the background is changed to... r H Here, r0 is the luminance coefficient corresponding to the gas curtain brightness, r0 is the target reflectance coefficient, and R is the detection range; during the process of obtaining the thermal infrared guided detection probability of the protected target area under the cover of the smoke curtain created by the smoke agent, the following updates are made: ,β s λ1 and λ2 represent the infrared smoke extinction coefficients, and represent two thermal imaging operating bands with wavelengths different from λ. The emissivity of the resolving element is T, and the radiation temperature of the resolving element is T. a For temperature, T ae For ambient temperature, Here, C represents the radiative exitance of the resolution unit itself, the environment, and the atmosphere, respectively; D represents the smoke concentration; and D represents the smoke thickness. During the process of obtaining the laser-guided detection probability of the protected target area under the smoke screen created by the smoke agent, the following parameters are updated: ,β f The extinction coefficient of the laser smoke screen. For quantum efficiency, As the system loss factor, Where B is the photon energy, A0 is the noise bandwidth, L is the receiver aperture, and A is the detection range. In the process of obtaining the radar guidance detection probability of the protected target area under the smoke screen created by the chaff, the update ρ is the volume of the foil strip; n is the number of foil strips.

2. The method according to claim 1, characterized in that, Smoke screen types also include the category of smoke agents; The major categories of smoke agents include: mist oil, red phosphorus, acid mist, and at least four subcategories of hexachloromethane.

3. The method according to claim 1, characterized in that, The process of extracting features from salient regions in the image and then calculating the feature values ​​of those salient regions includes: Identify salient regions in the image, and extract the region containing the protected target and the region containing the background adjacent to the protected target from the salient regions; Extract image features of the area where the protected target is located and calculate feature values.

4. The method according to claim 3, characterized in that, The step of extracting image features of the area where the protected target is located and calculating feature values ​​includes: extracting the RGB color space values ​​of the area where the protected target is located and converting them into tristimulus values, wherein: The tristimulus values ​​of the apparent color of the area where the protected target is located are: , where r H The brightness coefficient is the value corresponding to the brightness of the air curtain, α is the atmospheric extinction coefficient, R is the detection distance, Y0 is the tristimulus value of the target color (green), Z0 is the tristimulus value of the target color (blue), and X0 is the tristimulus value of the target color (red). The tristimulus values ​​of the apparent color of the region containing the background are: Y B The background color is green, Z is the tristimulus value. B The background color is blue (tristimulus value), X B The background color is red (tristimulus value).

5. The method according to claim 4, characterized in that, The step of calculating the interference detection probability of the protected target under different smoke screen conditions based on the obtained feature values ​​includes: Based on the image feature values ​​of the area where the protected target is located, determine the detection probability of the area where the protected target is located without smoke screen obstruction; Based on the image feature values ​​of the area where the protected target is located, the detection probability of the protected target under different smoke screen types is determined.

6. A system for multi-spectral comprehensive analysis of the interference effect of smoke screen obscuring, characterized in that, include: Image capture platform, back-end analysis and processing platform, and designer terminal The image capturing platform is used to acquire images of the protected target and transmit them to the background analysis and processing platform; The background analysis and processing platform is used to extract features from salient regions in the image and calculate the feature values ​​of the salient regions; based on the obtained feature values, it calculates the interference detection probability of the protected target under different smoke screen conditions, wherein the smoke screen conditions include at least one type of smoke screen, and the smoke screen type corresponds to the guidance method, including optical, laser, thermal infrared and radar guidance. The designer's terminal is used to receive the calculation results of the interference detection probability sent by the background analysis and processing platform and display them on the display of the designer's terminal. The types of smoke screens include foil strips; The calculated interference detection probability is sent to the designer's terminal; The probability of radar-guided detection in the area where the protected target is located without smoke screen obstruction is as follows: P fa This represents the radar false alarm probability. P t G is the peak power of the transmitter. t =G r Let σ be the main lobe gain of the transceiver antenna, σ be the target's RCS value, λ be the radar operating wavelength, k be the Boltzmann constant, T0 be the internal noise temperature, and B be the base plate. n For receiver bandwidth, F n L is the noise figure of the receiver. s Let α be the loss coefficient of each component of the radar, and α be the atmospheric extinction coefficient. This represents the radar detection range, and erf() is the error compensation function. When determining the detection probability of the protected target under different smoke screen types, the apparent brightness contrast between the protected target and the background is changed to... r H r0 is the target reflectance coefficient, corresponding to the brightness of the air curtain; during the process of obtaining the thermal infrared guided detection probability of the protected target area under the cover of the smoke curtain created by the smoke agent, the following is updated: ,β s λ is the extinction coefficient of the infrared smoke screen; λ1 and λ2 represent two thermal imaging operating bands with wavelengths different from λ. The emissivity of the resolving element is T, and the radiation temperature of the resolving element is T. a For temperature, T ae For ambient temperature, Here, C represents the radiative exitance of the resolution unit itself, the environment, and the atmosphere, respectively; D represents the smoke concentration; and D represents the smoke thickness. During the process of obtaining the laser-guided detection probability of the protected target area under the smoke screen created by the smoke agent, the following parameters are updated: ,β f The extinction coefficient of the laser smoke screen. For quantum efficiency, As the system loss factor, Where B is the photon energy, A0 is the noise bandwidth, L is the receiver aperture, and A is the detection range. In the process of obtaining the radar guidance detection probability of the protected target area under the smoke screen created by the chaff, the update ρ is the volume of the foil strip; n is the number of foil strips.

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