Laser weapon striking effect evaluation method
By analyzing the blurriness of the target image through the imaging system and combining it with the correlation model to evaluate the divergence angle increment, the problem of inaccurate evaluation of the strike effect of laser weapons in the existing technology has been solved, and more accurate strike effect evaluation and real-time dynamic environment response have been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SICHUAN CREATION LASER TECH CO LTD
- Filing Date
- 2026-01-27
- Publication Date
- 2026-04-28
AI Technical Summary
Existing technologies for assessing the effectiveness of laser weapons, which rely on environmental perception technology, have large errors and cannot accurately predict the effects of laser strikes, especially under nonlinear effects such as atmospheric turbulence and thermal oscillation, leading to errors in strike decision-making.
By capturing images of the target object through an imaging system, calculating the ambiguity score using ambiguity feature value analysis, and combining this with an association model to calculate the divergence angle increment and environmental parameters, the laser weapon's power density at the target is evaluated, thus achieving an accurate assessment of the strike effect.
It improves the accuracy of laser weapon strike effect assessment, can correct for the effects of dynamic environment in real time, capture local disturbance areas, reduce the error of complex theoretical models, and improve the reliability of strike decision-making.
Smart Images
Figure CN121935472A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of laser weapon effectiveness analysis, and in particular to a method for evaluating the strike effect of laser weapons. Background Technology
[0002] Before or during a laser weapon strike, it is usually necessary to accurately predict the effect of the laser strike.
[0003] In related technologies, environmental perception technology is mainly used to calculate target power density and assess effective strike distance. The principle is to quantitatively measure atmospheric composition and, under the assumption that the path environment is uniform, calculate the power-related attenuation coefficient and strike effect. Therefore, the strike effect calculated by this method may differ significantly from the actual strike effect, affecting subsequent strike decisions. Summary of the Invention
[0004] The main objective of this application is to provide a method for evaluating the impact effect of laser weapons, aiming to solve the technical problem of how to improve the accuracy of laser weapon impact effect evaluation.
[0005] To achieve the above objectives, this application proposes a method for evaluating the strike effect of laser weapons, comprising: To obtain an image of a target object by using an imaging system; The blurriness of the target object image is analyzed using at least one blurriness feature value, and a blurriness score of the target object image is calculated. The blur score of the target object image is input into the association model to calculate the divergence angle increment corresponding to the blur score of the target object image. The association model describes the mapping relationship between blur and divergence angle increment. Based on the divergence angle increment, environmental parameters, and target distance, the target power density of the laser weapon is calculated to assess the strike effect.
[0006] In one embodiment, the observation path of the imaging system and the laser emission path of the laser weapon are the same optical path, or the optical axis of the imaging system is parallel to the laser beam direction of the laser weapon.
[0007] In one embodiment, the establishment of the association model includes: Acquire effective divergence angles and target object images under different turbulence intensities and laser powers; Based on each effective divergence angle and the inherent divergence angle, the divergence angle increment corresponding to each effective divergence angle is calculated; Calculate the blur score for each target object image; Data points are constructed using the blur score of each target object image and the corresponding divergence angle increment, and curve fitting is performed to obtain the correlation model.
[0008] In one embodiment, the step of analyzing the blurriness of the target object image using at least one blurriness feature value and calculating the blurriness score of the target object image includes: Based on the grayscale difference between adjacent pixels in the target object image, the first blur level of the target object image is calculated. The second blur of the target object image is calculated based on the ratio of high-frequency energy to total energy in the target object image. Based on the grayscale distribution in the target object image, the third blur of the target object image is calculated; The first ambiguity, the second ambiguity, and the third ambiguity are normalized and then weighted and fused to calculate the ambiguity score of the target object image.
[0009] In one embodiment, calculating the target power density of the laser weapon based on the divergence angle increment, environmental parameters, and target distance to assess the strike effect includes: Calculate the atmospheric transmittance of the current environment based on environmental parameters; The effective divergence angle is calculated based on the inherent divergence angle and the divergence angle increment of the laser weapon. The spot area is calculated based on the effective divergence angle and the target distance; The target power is calculated based on the atmospheric transmittance and the output power of the laser weapon. The target power density is calculated based on the target power and the spot area. The target distance is determined by comparing the target power density and the damage threshold.
[0010] One or more technical solutions proposed in this application have at least the following technical effects: A method for evaluating the strike effect of laser weapons is proposed. This method involves acquiring an image of the target object using an imaging system; analyzing the ambiguity of the target object image using at least one ambiguity feature value to calculate a ambiguity score; inputting the ambiguity score into an association model to calculate the divergence angle increment corresponding to the ambiguity score; and calculating the target power density of the laser weapon based on the divergence angle increment, environmental parameters, and target distance to achieve strike effect evaluation. This method improves the accuracy of strike effect evaluation. Attached Figure Description
[0011] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0012] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.
[0013] Figure 1 A flowchart illustrating the first embodiment of the laser weapon strike effect evaluation method provided in this application; The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0014] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application. To better understand the technical solutions of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.
[0015] Current high-energy laser weapon systems mainly rely on the following environmental perception technologies for target power density calculation and effective strike range assessment: 1) Local meteorological parameter measurement method: Deploy sensors on the laser emission platform to measure parameters such as visibility, relative humidity, temperature, and air pressure around the emission point. Calculate the linear attenuation coefficient of laser transmission using an atmospheric attenuation model to estimate the effective strike distance.
[0016] 2) Path integral measurement method: A low-power detection laser is emitted towards the target direction, and the comprehensive attenuation coefficients such as aerosol concentration and water vapor content along the entire path are inverted by receiving backscattered signals or using differential absorption radar.
[0017] The above method is mainly based on the quantitative measurement of atmospheric composition and assumes that the path environment is uniform, thereby calculating the laser energy transmission efficiency.
[0018] However, this type of method has the following drawbacks: 1) Existing technologies cannot effectively detect and quantify the beam spread, drift, and scintillation effects caused by atmospheric turbulence.
[0019] 2) Local meteorological measurements only reflect the micro-environment around the launch point (laser weapon) and cannot capture sudden changes at the far end of the path.
[0020] 3) The path integral method returns the average value of the entire path and cannot identify areas of strong disturbance, such as thin clouds or dust clouds in front of the target.
[0021] 4) Strong model dependency: Strike distance prediction relies heavily on empirical atmospheric models, and model errors can directly lead to decision-making mistakes. Modeling nonlinear effects such as thermal halos is extremely complex and difficult to apply in real time.
[0022] This application provides a method for evaluating the strike effect of a laser weapon. In the first embodiment of this laser weapon strike effect evaluation method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the laser weapon strike effect evaluation method of this application. The laser weapon strike effect evaluation method may include steps S10 to S40: Step S10: Use an imaging system to photograph the target object to obtain an image of the target object.
[0023] It should be noted that the target image is an image that at least contains the area to be struck by the target object. This could be an image including both the background and the target object, or an image containing only the target object (extracted from the original image), or an image containing only the area to be struck by the target object. The imaging system can be a high-resolution optoelectronic imaging system, which can be installed coaxially or adjacent to the laser weapon to ensure maximum overlap between the observation path and the laser emission path.
[0024] Specifically, before or during a laser weapon strike, an imaging system can be used to image the target object in the target area in real time to obtain an image of the target object.
[0025] In one feasible implementation, the observation path of the imaging system and the laser emission path of the laser weapon are the same optical path, or the optical axis of the imaging system is parallel to the laser beam direction of the laser weapon.
[0026] It should be noted that this setup ensures that the imaging beam and the laser beam experience the same atmospheric disturbances, such as turbulence and thermal corona.
[0027] Step S20: Analyze the blurriness of the target object image using at least one blurriness feature value, and calculate the blurriness score of the target object image.
[0028] It should be noted that fuzziness feature values refer to parameters that can quantify the fuzziness of an image. The fuzziness score is calculated based on one or more fuzziness feature values. It should also be noted that using multiple fuzziness feature values to calculate the fuzziness score can further improve the accuracy of fuzziness recognition.
[0029] In one feasible implementation, step S20 may include steps S201 to S204: Step S201: Calculate the first blur of the target object image based on the grayscale difference between adjacent pixels in the target object image.
[0030] In one specific implementation, the Brenner gradient function can be used to calculate the first blur of the target image. The first blur is the mean of the sum of the squared gray-level differences between each pixel and the pixels two pixels to its right. The expression is as follows:
[0031] In the formula, Let M represent the mean of the sum of squared grayscale differences between each pixel I(i,j) and the pixels at positions two adjacent to it, i.e., the first blur. M and N represent the number of row pixels and column pixels of the image, respectively. The larger the value, the clearer the image. This calculation method is simple, fast, and suitable for real-time systems.
[0032] Step S202: Based on the ratio of high-frequency energy to total energy in the target object image, calculate the second blur of the target object image.
[0033] In one specific implementation, a two-dimensional fast Fourier transform is first performed on the target image to obtain a spectrum. The origin of the spectrum is then moved to the center, and a radius r (e.g., 1 / 10 of the image's width and height) is set to calculate the proportion of high-level energy. That is, the ratio of the energy in the region outside radius r in the spectrum to the total energy is calculated using the following formula:
[0034]
[0035] In the formula, This represents the ratio of the energy in the region outside radius r in the calculated spectrum to the total energy, where M and N represent the number of row pixels and column pixels in the image.
[0036] Step S203: Based on the grayscale distribution in the target object image, calculate the third blur of the target object image.
[0037] In one feasible implementation, the grayscale histogram of the target object image is first calculated to obtain the probability p of each grayscale level k (0~255) appearing. k Then the information entropy is:
[0038] The third ambiguity is represented by information entropy. The higher the information entropy, the more dispersed the gray-scale distribution, the more information the image contains, and the clearer it is.
[0039] Step S204: After normalizing the first ambiguity, the second ambiguity, and the third ambiguity, perform weighted fusion to calculate the ambiguity score of the target object image.
[0040] It should be noted that after calculating the first ambiguity, the second ambiguity, and the third ambiguity, based on the pre-calibrated maximum and minimum values of each ambiguity on the training dataset, the minimum-maximum normalization method is used to linearly map each ambiguity to the [0,1] interval. For feature values that exceed the range of the training set, truncation is performed.
[0041] The mathematical expression for calculating fuzziness score is:
[0042] In the formula, S represents the ambiguity score, and a, b, and c represent the weighting coefficients. This represents the first ambiguity after normalization. E represents the second ambiguity after normalization, and E represents the third ambiguity after normalization.
[0043] Preferably, a=0.5, b=0.3, c=0.2.
[0044] Step S30: Input the blur score of the target object image into the association model to calculate the divergence angle increment corresponding to the blur score of the target object image, wherein the association model describes the mapping relationship between blur and divergence angle increment.
[0045] It should be noted that the imaging beam and the laser emission beam experience the same or similar atmospheric disturbances (turbulence, thermal halo) under common or near-common optical path conditions. These disturbances cause wavefront distortion, which manifests as broadening of the point spread function and image blurring for the imaging beam, and as the far-field spot size exceeding its inherent diffraction angle for the laser beam. Therefore, image blurring is strongly correlated with the increase in divergence angle caused by turbulence and thermal halo. An experimentally calibrated correlation model can be established to describe the mapping relationship between blurring and the increase in divergence angle. After calculating the blurring score of the target image, the pre-calibrated correlation model can be used to solve for the divergence angle increment corresponding to the blurring score.
[0046] In one feasible implementation, the establishment of the association model includes steps A11 to A14: Step A11: Acquire the effective divergence angle and target object images under different turbulence intensities and different laser powers.
[0047] Specifically, under a controllable path, a turbulence simulator or different natural conditions are selected to simulate different turbulence intensities and different laser powers to excite thermal halo effects of different intensities. The target plate is then imaged and irradiated with laser. An imaging system is used to acquire images of the target plate, and a beam quality analyzer is used to measure the effective divergence angle of the light spot.
[0048] Step A12: Calculate the divergence angle increment corresponding to each effective divergence angle based on each effective divergence angle and the inherent divergence angle.
[0049] It should be noted that the effective divergence angle of the laser beam after transmission consists of a fixed divergence angle and an increment in the divergence angle. The mathematical expression for the effective divergence angle is:
[0050] In the formula, i eff Indicates the effective divergence angle. i 0 represents the inherent diffraction-limited divergence angle of a laser, determined by the aperture and wavelength of the emitting system, i.e., the inherent divergence angle. i t This represents the increment of the divergence angle along the transmission path caused by turbulence and thermal corona effects.
[0051] Therefore, the mathematical expression for calculating the divergence angle increment is:
[0052] Step A13: Calculate the blur score for each target object image.
[0053] Step A14: Construct data points using the blur score of each target object image and the corresponding divergence angle increment, and perform curve fitting to obtain the association model.
[0054] Specifically, with (S, θ) t Data points are constructed, and curve fitting is performed on each data point to obtain the correlation model. i t = f (S), this model quantifies the additional effects of path turbulence and thermal corona on beam spread.
[0055] Step S40: Calculate the target power density of the laser weapon based on the divergence angle increment, environmental parameters, and target distance to assess the strike effect.
[0056] In one feasible implementation, step S40 may include steps S401 to S406: Step S401: Calculate the atmospheric transmittance of the current environment based on environmental parameters.
[0057] Specifically, the mathematical expression for step S401 is:
[0058] In the formula, τ represents atmospheric transmittance, α represents attenuation coefficient, and L is target distance.
[0059] It should be noted that the attenuation coefficient can be calculated using one or more existing methods, which will not be elaborated upon here.
[0060] Step S402: Calculate the effective divergence angle based on the inherent divergence angle and divergence angle increment of the laser weapon.
[0061] Step S403: Calculate the spot area based on the effective divergence angle and the target distance.
[0062] Specifically, the mathematical expression for step S403 is:
[0063] In the formula, L represents the area of the light spot, and L represents the distance to the target. i eff Indicates the effective divergence angle.
[0064] Step S404: Calculate the target power based on the atmospheric transmittance and the output power of the laser weapon.
[0065] Step S405: Calculate the target power density based on the target power and the spot area.
[0066] Specifically, the mathematical expression for step S405 is:
[0067] In the formula, Φ target P represents the power density to the target, and P is the output power of the laser weapon.
[0068] Step S406: Compare the target power density and damage threshold to determine whether the target distance is within the effective strike range.
[0069] Specifically, when the target power density is greater than or equal to the damage threshold, the target distance is determined to be within the effective strike range; when the target power density is less than the damage threshold, the target distance is determined to be outside the effective strike range. When the target distance is within the effective strike range, the decision is output to the fire control system.
[0070] This embodiment provides a method for evaluating the strike effect of a laser weapon. It involves using an imaging system to capture an image of the target object; analyzing the ambiguity of the target object image using at least one ambiguity feature value to calculate a ambiguity score; inputting the ambiguity score into an association model to calculate the divergence angle increment corresponding to the ambiguity score; and calculating the target power density of the laser weapon based on the divergence angle increment, environmental parameters, and target distance to achieve strike effect evaluation, thereby improving the accuracy of strike effect evaluation. Specifically, by utilizing an imaging system sharing the same optical path as the laser emission, the comprehensive wavefront distortion effect along the transmission path is quantified by analyzing the blurriness of the target image. Combined with laser energy attenuation measured by traditional methods, the predicted energy density at the target is calculated, serving as the fundamental basis for decision-making regarding the strike distance. Simultaneously, both linear attenuation and nonlinear effects are quantified. The integral perturbation effect along the entire laser beam transmission path is reflected, enabling the capture of localized strong turbulence or thermal halo regions, rather than solely relying on edge detection data. The correlation model is experimentally calibrated, providing a more direct approach and avoiding errors from complex theoretical models. Based on millisecond-level image processing, real-time corrections can be made during the strike process, significantly enhancing the ability to cope with dynamic environments and offering strong real-time performance.
[0071] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.
Claims
1. A method for evaluating the strike effect of a laser weapon, characterized in that, The method includes: To obtain an image of a target object by using an imaging system; The blurriness of the target object image is analyzed using at least one blurriness feature value, and a blurriness score of the target object image is calculated. The blur score of the target object image is input into the association model to calculate the divergence angle increment corresponding to the blur score of the target object image. The association model describes the mapping relationship between blur and divergence angle increment. Based on the divergence angle increment, environmental parameters, and target distance, the target power density of the laser weapon is calculated to assess the strike effect.
2. The laser weapon strike effect evaluation method as described in claim 1, characterized in that, The observation path of the imaging system and the laser emission path of the laser weapon are the same optical path, or the optical axis of the imaging system is parallel to the laser beam direction of the laser weapon.
3. The laser weapon strike effect evaluation method as described in claim 1, characterized in that, The establishment of the association model includes: Acquire effective divergence angles and target object images under different turbulence intensities and laser powers; Based on each effective divergence angle and the inherent divergence angle, the divergence angle increment corresponding to each effective divergence angle is calculated; Calculate the blur score for each target object image; Data points are constructed using the blur score of each target object image and the corresponding divergence angle increment, and curve fitting is performed to obtain the correlation model.
4. The laser weapon strike effect evaluation method as described in claim 1, characterized in that, The step of analyzing the blurriness of the target object image using at least one blurriness feature value and calculating the blurriness score of the target object image includes: Based on the grayscale difference between adjacent pixels in the target object image, the first blur level of the target object image is calculated. The second blur of the target object image is calculated based on the ratio of high-frequency energy to total energy in the target object image. Based on the grayscale distribution in the target object image, the third blur of the target object image is calculated; The first ambiguity, the second ambiguity, and the third ambiguity are normalized and then weighted and fused to calculate the ambiguity score of the target object image.
5. The laser weapon strike effect evaluation method as described in claim 1, characterized in that, The calculation of the laser weapon's power density at the target, based on the divergence angle increment, environmental parameters, and target distance, to assess the strike effect includes: Calculate the atmospheric transmittance of the current environment based on environmental parameters; The effective divergence angle is calculated based on the inherent divergence angle and the divergence angle increment of the laser weapon. The spot area is calculated based on the effective divergence angle and the target distance; The target power is calculated based on the atmospheric transmittance and the output power of the laser weapon. The target power density is calculated based on the target power and the spot area. The target distance is determined by comparing the target power density and the damage threshold.