Unmanned aerial vehicle high power microwave protection index level quantization decomposition and optimization design method

Abstract

The present application belongs to the technical field of unmanned aerial vehicle electromagnetic protection, and particularly relates to a method for quantitatively decomposing and optimizing the protection index of unmanned aerial vehicles against high-power microwaves, comprising the following steps: constructing a multi-path coupling threat quantification model of unmanned aerial vehicles, and establishing a total budget formula for the coupling attenuation of the whole machine; based on the physical model of electronic device failure, constructing a quantification formula for the sensitivity threshold of the internal subsystems and core devices of the machine; constructing a three-level protection index hierarchical quantification decomposition model for the whole machine, the subsystems and the devices; establishing a multi-objective optimization function; through a combination of simulation and testing, constructing an index closed-loop verification model, inversely correcting the decomposition parameters and optimization coefficients, and completing the index quantification iterative design. The present application introduces a three-dimensional model of the unmanned aerial vehicle, calculates the multi-path coupling attenuation parameters through electromagnetic coupling theory, substitutes them into the total budget formula for the coupling attenuation of the whole machine, and solves the theoretical benchmark of the protection index of the whole machine.

Description

Technical Field

[0001] This invention belongs to the field of electromagnetic protection technology for unmanned aerial vehicles (UAVs), specifically relating to a method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for UAVs. Background Technology

[0002] High-power microwaves can penetrate the interior of drones through spatial irradiation and conductive coupling, causing degradation of core electronic equipment functions, logical disorder, and even permanent damage, posing a core threat to drone survivability on the battlefield. Existing technologies for protecting drones from high-power microwaves suffer from the following fundamental flaws: 1. Lack of theoretical and quantitative system in indicator design: It mostly adopts empirical assignment and single-point qualitative indicators, without establishing a theoretical mapping relationship between threat characteristics, device sensitivity and protection indicators, and without standardized quantitative decomposition logic. The indicators are highly subjective, untraceable and cannot be accurately verified. 2. Lack of correlation decomposition mechanism for hierarchical indicators: The indicator transfer model of whole machine-subsystem-device is not constructed, and the protection indicators of the whole machine are disconnected from the protection requirements of the underlying devices, which is prone to the two-pronged problem of protection redundancy or protection failure. 3. Lack of quantitative optimization basis for protection strategy: The protection design is carried out only for a single hardware module, without taking into account engineering constraints such as UAV payload, power consumption, and insertion loss, and without performing multi-objective quantitative optimization of the protection strategy, resulting in poor engineering adaptability; 4. Existing technologies have two main shortcomings: First, published patents and literature focus on hardware topology designs such as shielding, filtering, and limiting, or conduct effect experiments on single devices; second, although some studies mention the concept of index allocation, they have not established a complete three-level quantization transfer formula system of whole machine-subsystem-device, and lack an index decomposition model that can be engineered. 5. Sensitive threshold research is limited to single-device experiments: Although existing research involves the concept of sensitive threshold, it mostly focuses on experiments on single devices to obtain empirical values. It has not established a unified quantitative formula system covering multiple types of devices, making it difficult to support system-level index decomposition.

[0003] Currently, there is no complete method for the full-process quantitative decomposition of protection indicators based on theoretical formulas, and there is a significant gap in methodological technology. Summary of the Invention

[0004] To address the aforementioned technical problems in the existing high-power microwave protection of UAVs, this invention provides a method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for UAVs.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A hierarchical quantitative decomposition and optimization design method for high-power microwave protection indicators of unmanned aerial vehicles (UAVs) includes the following steps: S1. Based on the high-power microwave electromagnetic coupling theory, construct a multi-path coupling threat quantification model for UAVs, establish a total budget formula for overall coupling attenuation, and determine the theoretical benchmark for overall protection indicators. S2. Based on the physical model of electronic device failure, construct the sensitivity threshold quantification formula for internal subsystems and core devices to form a bottom-level sensitivity parameter system; S3. Using the combined weighting of the analytic hierarchy process and electromagnetic attenuation budget, a three-level protection index hierarchical quantitative decomposition model of whole machine-subsystem-device is constructed. By constructing subsystem index decomposition formulas and device index decomposition formulas, the accurate numerical transmission and quantitative allocation of indexes at each level are realized. S4. By integrating protection effectiveness, load, power consumption, and RF insertion loss constraints, a multi-objective optimization function is established, which is quantitatively solved and matched with hierarchical protection strategies to achieve balanced optimization of protection strategies. S5. By combining simulation and testing, construct a closed-loop verification model for the indicators, reverse the decomposition parameters and optimization coefficients, and complete the quantitative iterative design of the indicators.

[0006] The method for constructing the UAV multipath coupling threat quantification model in step S1 is as follows: S1.1, HPM External Threat Parameter Characterization: Defining the High-Power Microwave External Threat Field Vector ,in For threat frequency, For pulse width, To represent the radiated power, a space electromagnetic field propagation model is constructed using Maxwell's equations to characterize the external threat characteristics under different scenarios; S1.2 Multi-path coupling quantization: For typical coupling paths, establish the overall system coupling attenuation total budget formula: In the formula: This represents the total coupling attenuation across the entire frequency band of the device. This is the antenna coupling attenuation. This represents the attenuation of the gap coupling. This refers to the cable conduction coupling attenuation. This refers to the transmission attenuation of the casing. The attenuation characteristics of external microwave threats being transformed into internal interference are quantified by formula, and the theoretical benchmark value of the overall protection index is determined.

[0007] The method for forming the underlying sensitive parameter system in step S2 is as follows: S2.1 Construct a quantitative model of the sensitive characteristics of the subsystem; S2.2 Quantization of Sensitivity Thresholds for Core Components: For core components of digital chips, radio frequency devices, and sensors, establish critical threshold models for component damage, forming a unified quantitative formula system for multiple types of components. Digital chips: Radio frequency devices: sensor: In the formula: This is a correction factor for device material and manufacturing process. This is the chip breakdown voltage. This refers to the noise voltage fluctuation. The power of the radio frequency device was burned out. For device insertion loss, For sensor distortion field strength This represents the change in signal distortion. Such formulas allow for the theoretical quantification of the device's sensitivity threshold, rather than limiting it to measured values.

[0008] The method for constructing the subsystem sensitivity characteristic quantification model in step S2.1 is as follows: For the six core subsystems of flight control, navigation, radio frequency, payload, servo, and power supply, a sensitivity threshold function is constructed. ,in For internal coupling field strength, For conducting interference voltage, To conduct interference current, the critical sensitivity conditions for subsystem functional degradation, failure, and damage are characterized by failure physics formulas: In the formula: For the subsystem's sensitivity threshold, Operating temperature The function is used to determine the critical tolerance value of the subsystem to microwave interference, representing the threat duration.

[0009] The method for constructing the three-level protection index quantification decomposition model of whole machine-subsystem-device in step S3 is as follows: S3.1 Quantitative Modeling of Overall Protection Indicators: Based on the overall coupling attenuation total budget formula and system-level electromagnetic compatibility standards, a quantitative function for overall protection indicators is constructed: In the formula: This is a vector representing the overall protection index of the machine. To meet the system's functional integrity requirements, this function determines the core indicator dimensions and theoretical thresholds for overall system protection, rather than using fixed values. S3.2 Subsystem Indicator Hierarchical Decomposition: An improved analytic hierarchy process is adopted, combined with the importance weights of subsystem functions. Electromagnetic attenuation distribution ratio Construct a subsystem indicator decomposition model; S3.3 Detailed Decomposition of Device-Level Indicators: Based on the subsystem indicators and device sensitivity threshold formulas, a detailed decomposition function for device protection indicators is constructed: In the formula: For the first Protection specifications of individual components Assigning importance weights to devices within the subsystem. This is the device sensitivity threshold.

[0010] By using functions, the subsystem indicators are further decomposed to the core components, forming a three-level quantitative indicator system that links the whole machine, subsystem, and components, making the indicators traceable and verifiable.

[0011] The method for constructing the subsystem index decomposition model in step S3.2 is as follows: In the formula: For the first Individual subsystem protection indicators The importance weights of subsystem functions are quantified and solved by pairwise comparison matrices. Assigning coefficients for coupling attenuation. This refers to the protection margin coefficient. The formula is used to quantitatively allocate the overall system indicators to the subsystem indicators, ensuring that the indicators of each subsystem work together to meet the overall system protection requirements.

[0012] The method for quantizing and matching the hierarchical protection strategy in step S4 is as follows: S4.1 Construction of Multi-Objective Optimization Function: A multi-objective optimization function is established with the objectives of maximizing protection effectiveness and minimizing engineering constraints. In the formula: To optimize the objective function, The target weight coefficient, For protective effectiveness, To protect the structural weight, To protect module power consumption, This refers to the insertion loss of the radio frequency (RF) link. Constraints include performance requirements, maximum drone payload, power consumption limits, and RF insertion loss limits. S4.2 Quantitative matching of protection strategies based on multi-objective optimization: Highly sensitive core subsystem: The required protection attenuation and response time are quantified and solved by optimizing the function; RF Link: The ratio of out-of-band rejection depth to link insertion loss is optimized through a multi-objective function balance. Overall casing: The optimal combination of shielding effectiveness and structural weight is quantified and matched through constraints; This optimization model enables the quantitative selection of protection strategy parameters, rather than simply listing protection technology solutions, thereby resolving the contradiction between protection effectiveness and engineering application and improving the engineering practicality of the method.

[0013] The method for constructing the indicator closed-loop verification model in step S5 is as follows: S5.1. Based on electromagnetic simulation software, substitute the three-level index parameters to verify the synergy of the overall machine, subsystem, and component indexes. S5.2 Establish an indicator correction formula; if the verification fails, adjust the weighting coefficients. , With residual coefficient The indicators were then re-decomposed. S5.3 Iteratively optimize the protection strategy until all levels of indicators meet the theoretical requirements and engineering constraints, forming a complete quantitative design closed loop.

[0014] Compared with the prior art, the beneficial effects of this invention are: 1. This invention imports a three-dimensional model of a UAV, calculates multi-path coupling attenuation parameters through electromagnetic coupling theory, substitutes them into the overall coupling attenuation budget formula, and solves for the theoretical benchmark of the overall protection index. 2. This invention selects six subsystems and core components, substitutes them into the failure physics formula, and quantitatively solves the sensitivity threshold parameters of the subsystems and components; 3. This invention constructs a hierarchical analysis weight matrix, combines it with electromagnetic attenuation budget coefficients, and completes the allocation of indicators from the whole machine to the components through a three-level indicator decomposition formula, thereby determining the theoretical range of indicators at each level. 4. This invention incorporates engineering constraints such as UAV payload, power consumption, and insertion loss to solve a multi-objective optimization function, matches corresponding hierarchical protection strategies, and determines the optimal protection scheme; 5. This invention verifies the effectiveness of the indicators through electromagnetic simulation, adjusts the decomposition coefficients and optimizes the weights, iteratively corrects the indicator system until all constraints are met, and completes the quantitative design of the protection indicators. Attached Figure Description

[0015] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0016] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0017] Figure 1 This is a flowchart of the steps of the present invention; Figure 2 This is a schematic diagram of the three-level index hierarchy quantification decomposition model of the whole machine-subsystem-device of the present invention; Figure 3 This is a schematic diagram illustrating the principle of high-power microwave multipath coupling threat quantification modeling in this invention. Figure 4 This is a block diagram of the multi-target protection strategy optimization function of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. These descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the claims of the present invention. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0020] This embodiment provides a hierarchical quantitative decomposition and optimization design method for high-power microwave protection indicators of unmanned aerial vehicles (UAVs), such as... Figure 1 As shown, it includes the following core steps: I. Quantitative Modeling of High-Power Microwave Threat Characteristics Based on the theory of high-power microwave electromagnetic radiation and coupling, a multi-path coupling threat quantification model for UAVs is constructed, which transforms space microwave threats into equivalent interference parameters within the UAV, providing input basis for index decomposition.

[0021] 1. Characterization of external threat parameters in HPM Define the external threat field vector of high-power microwaves ,in For threat frequency, For pulse width, To represent the radiated power, a space electromagnetic field propagation model is constructed using Maxwell's equations to characterize the external threat characteristics under different scenarios.

[0022] 2. Multi-path coupled quantization For typical coupling paths, a total budget formula for overall system coupling attenuation is established. Unlike existing technologies that qualitatively analyze coupling paths or evaluate single paths, this invention achieves a quantitative superposition budget for multi-path coupling attenuation through the following formula, providing a calculable input benchmark for overall system protection performance: In the formula: This represents the total coupling attenuation across the entire frequency band of the device. This is the antenna coupling attenuation. This represents the attenuation of the gap coupling. This refers to the cable conduction coupling attenuation. This represents the transmission attenuation of the casing.

[0023] This formula quantifies the attenuation characteristics of external microwave threats transforming into internal interference, thus determining the theoretical benchmark value for the overall protection index.

[0024] II. Quantitative Modeling of Sensitive Thresholds for Internal Equipment and Components Based on the electromagnetic damage mechanism and failure physics model of electronic devices, a sensitivity threshold quantification model of core equipment and devices of UAVs is constructed, and the mapping relationship between sensitive parameters and microwave interference is established to form the underlying basis for index decomposition.

[0025] 1. Construction of a Quantitative Model for Sensitive Characteristics of Subsystems Sensitive threshold functions are constructed for the six core subsystems: flight control, navigation, radio frequency, payload, servo, and power supply. ,in For internal coupling field strength, For conducting interference voltage, To conduct interference current, the critical sensitivity conditions for subsystem functional degradation, failure, and damage are characterized by failure physics formulas: In the formula: For the subsystem's sensitivity threshold, Operating temperature The function is used to determine the critical tolerance value of the subsystem to microwave interference, representing the threat duration.

[0026] 2. Quantization of Sensitive Thresholds for Core Components For core components such as digital chips, radio frequency devices, sensors, and power chips, a critical threshold model for device damage is established, forming a unified quantitative formula system for multiple types of devices: Digital chips: Radio frequency devices: sensor: In the formula: This is a correction factor for device material and manufacturing process. This is the chip breakdown voltage. This refers to the noise voltage fluctuation. The power of the radio frequency device was burned out. For device insertion loss, For sensor distortion field strength This represents the change in signal distortion. Such formulas allow for the theoretical quantification of the device's sensitivity threshold, rather than limiting it to measured values.

[0027] III. Quantitative Decomposition of Three-Level Protection Indicators for Whole Machine, Subsystem, and Components The core innovation of this invention differs from existing technologies that merely establish an evaluation hierarchy framework or assign conceptual indicators. This invention combines the Analytic Hierarchy Process (AHP) with electromagnetic attenuation budget theory to construct a three-level indicator decomposition model with explicit mathematical expressions, thereby enabling the calculable numerical transfer from overall system indicators to device indicators.

[0028] 1. Quantitative modeling of overall protection indicators Based on the overall coupling attenuation budget formula and system-level electromagnetic compatibility standards, a quantitative function for overall protection indicators is constructed: In the formula: This is a vector representing the overall protection index of the machine. To meet the system's functional integrity requirements, this function determines the core indicator dimensions and theoretical thresholds for overall system protection, rather than fixed values.

[0029] 2. Subsystem Indicator Hierarchical Decomposition An improved analytic hierarchy process (AHP) was adopted, incorporating the importance weights of subsystem functions. Electromagnetic attenuation distribution ratio Construct a subsystem indicator decomposition model: In the formula: For the first Individual subsystem protection indicators The importance weights of subsystem functions are determined by pairwise comparison matrices. Assigning coefficients for coupling attenuation. This is a protection margin coefficient (theoretical range, not a fixed value).

[0030] This formula enables the quantitative allocation of overall system indicators to subsystem indicators, ensuring that the indicators of each subsystem work together to meet the overall system protection requirements.

[0031] 3. Detailed breakdown of device-level indicators Based on the formulas for subsystem indicators and device sensitivity thresholds, a refined decomposition function for device protection indicators is constructed: In the formula: For the first Protection specifications of individual components Assigning importance weights to devices within the subsystem. This is the device sensitivity threshold.

[0032] This function further decomposes subsystem indicators to core components, forming a three-level quantitative indicator system that links the whole machine, subsystem, and components, making the indicators traceable and verifiable.

[0033] IV. Multi-constraint protection strategy with consideration for quantitative optimization By combining the constraints of UAV engineering applications, a multi-objective optimization model of protection effectiveness and engineering parameters is constructed to achieve quantitative optimization of protection strategies, taking into account both protection effectiveness and engineering practicality, which is different from existing technologies that focus solely on protection effectiveness design.

[0034] 1. Construction of multi-objective optimization function To achieve optimal protection effectiveness and minimize engineering constraints, a multi-objective optimization function is established: In the formula: To optimize the objective function, The target weight coefficient, For protective effectiveness, To protect the structural weight, To protect module power consumption, This refers to the insertion loss of the radio frequency (RF) link. Constraints include performance requirements, maximum drone payload, power consumption limits, and RF insertion loss limits.

[0035] 2. Quantitative matching of protection strategies based on multi-objective optimization Unlike existing technologies that select hardware protection schemes based on experience, this invention quantifies and matches the parameters of each level of protection strategy based on the results of optimization function solutions. Highly sensitive core subsystem: The required protection attenuation and response time are quantified and solved by optimizing the function; RF Link: The ratio of out-of-band rejection depth to link insertion loss is optimized through a multi-objective function balance. Overall casing: The optimal combination of shielding effectiveness and structural weight is quantified and matched through constraints.

[0036] This optimization model enables the quantitative selection of protection strategy parameters, rather than simply listing protection technology solutions, thereby resolving the contradiction between protection effectiveness and engineering application and improving the engineering practicality of the method.

[0037] V. Quantitative Closed-Loop Verification and Iterative Correction of Indicators A closed-loop model combining indicator simulation verification and test validation is constructed to verify the quantitatively decomposed indicators, and the decomposition parameters are corrected and the model is optimized in reverse to ensure the accuracy and feasibility of the method.

[0038] 1. Based on electromagnetic simulation software, substitute the three-level index parameters to verify the synergy of the overall machine, subsystem, and component indexes; 2. Establish an indicator correction formula; if the verification fails, adjust the weighting coefficients. , With residual coefficient The indicators were then re-decomposed. 3. Iteratively optimize the protection strategy until all levels of indicators meet the theoretical requirements and engineering constraints, forming a complete quantitative design closed loop.

[0039] The above description only illustrates the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention, and all such changes should be included within the protection scope of the present invention.

Claims

1. A method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles (UAVs), characterized in that, Includes the following steps: S1. Based on the high-power microwave electromagnetic coupling theory, construct a multi-path coupling threat quantification model for UAVs, establish a total budget formula for overall coupling attenuation, and determine the theoretical benchmark for overall protection indicators. S2. Based on the physical model of electronic device failure, construct the sensitivity threshold quantification formula for internal subsystems and core devices to form a bottom-level sensitivity parameter system; S3. Using the combined weighting of the analytic hierarchy process and electromagnetic attenuation budget, a three-level protection index hierarchical quantitative decomposition model of whole machine-subsystem-device is constructed. By constructing subsystem index decomposition formulas and device index decomposition formulas, the accurate numerical transmission and quantitative allocation of indexes at each level are realized. S4. By integrating protection effectiveness, load, power consumption, and RF insertion loss constraints, a multi-objective optimization function is established, which is quantitatively solved and matched with hierarchical protection strategies to achieve balanced optimization of protection strategies. S5. By combining simulation and testing, construct a closed-loop verification model for the indicators, reverse the decomposition parameters and optimization coefficients, and complete the quantitative iterative design of the indicators.

2. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for UAVs according to claim 1, characterized in that, The method for constructing the UAV multipath coupling threat quantification model in step S1 is as follows: S1.1, HPM External Threat Parameter Characterization: Defining the High-Power Microwave External Threat Field Vector ,in For threat frequency, For pulse width, To represent the radiated power, a space electromagnetic field propagation model is constructed using Maxwell's equations to characterize the external threat characteristics under different scenarios; S1.2 Multi-path coupling quantization: For typical coupling paths, establish the overall system coupling attenuation total budget formula: In the formula: This represents the total coupling attenuation across the entire frequency band of the device. This is the antenna coupling attenuation. This represents the attenuation of the gap coupling. This refers to the cable conduction coupling attenuation. This refers to the transmission attenuation of the casing. The attenuation characteristics of external microwave threats being transformed into internal interference are quantified by formula, and the theoretical benchmark value of the overall protection index is determined.

3. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles according to claim 1, characterized in that, The method for forming the underlying sensitive parameter system in step S2 is as follows: S2.1 Construct a quantitative model of the sensitive characteristics of the subsystem; S2.2 Quantization of Sensitivity Thresholds for Core Components: For core components of digital chips, radio frequency devices, and sensors, establish critical threshold models for component damage, forming a unified quantitative formula system for multiple types of components. Digital chips: Radio frequency devices: sensor: In the formula: This is a correction factor for device material and manufacturing process. This is the chip breakdown voltage. This refers to the noise voltage fluctuation. The power of the radio frequency device was burned out. For device insertion loss, For sensor distortion field strength This represents the change in signal distortion. Such formulas allow for the theoretical quantification of the device's sensitivity threshold, rather than limiting it to measured values.

4. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for UAVs according to claim 3, characterized in that, The method for constructing the subsystem sensitivity characteristic quantification model in step S2.1 is as follows: For the six core subsystems of flight control, navigation, radio frequency, payload, servo, and power supply, a sensitivity threshold function is constructed. ,in For internal coupling field strength, For conducting interference voltage, To conduct interference current, the critical sensitivity conditions for subsystem functional degradation, failure, and damage are characterized by failure physics formulas: In the formula: For the subsystem's sensitivity threshold, Operating temperature The function is used to determine the critical tolerance value of the subsystem to microwave interference, representing the threat duration.

5. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles according to claim 1, characterized in that, The method for constructing the three-level protection index quantification decomposition model of whole machine-subsystem-device in step S3 is as follows: S3.1 Quantitative Modeling of Overall Protection Indicators: Based on the overall coupling attenuation total budget formula and system-level electromagnetic compatibility standards, a quantitative function for overall protection indicators is constructed: In the formula: This is a vector representing the overall protection index of the machine. To meet the system's functional integrity requirements, this function determines the core indicator dimensions and theoretical thresholds for overall system protection, rather than using fixed values. S3.2 Subsystem Indicator Hierarchical Decomposition: An improved analytic hierarchy process is adopted, combined with the importance weights of subsystem functions. Electromagnetic attenuation distribution ratio Construct a subsystem indicator decomposition model; S3.3 Detailed Decomposition of Device-Level Indicators: Based on the subsystem indicators and device sensitivity threshold formulas, a detailed decomposition function for device protection indicators is constructed: In the formula: For the first Protection specifications of individual components Assigning importance weights to devices within the subsystem. This is the device sensitivity threshold.

6. By using functions, the subsystem indicators are further decomposed to the core components, forming a three-level quantitative indicator system that links the whole machine, subsystem, and components, making the indicators traceable and verifiable.

7. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles according to claim 5, characterized in that, The method for constructing the subsystem index decomposition model in step S3.2 is as follows: In the formula: For the first Individual subsystem protection indicators The importance weights of subsystem functions are quantified and solved using pairwise comparison matrices. Assigning coefficients for coupling attenuation. This refers to the protection margin coefficient. The formula is used to quantitatively allocate the overall system indicators to the subsystem indicators, ensuring that the indicators of each subsystem work together to meet the overall system protection requirements.

8. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles according to claim 1, characterized in that, The method for quantizing and matching the hierarchical protection strategy in step S4 is as follows: S4.1 Construction of Multi-Objective Optimization Function: A multi-objective optimization function is established with the objectives of maximizing protection effectiveness and minimizing engineering constraints. In the formula: To optimize the objective function, The target weight coefficient, For protective effectiveness, To protect the structural weight, To protect module power consumption, This refers to the insertion loss of the radio frequency (RF) link. Constraints include performance requirements, maximum drone payload, power consumption limits, and RF insertion loss limits. S4.2 Quantitative matching of protection strategies based on multi-objective optimization: Highly sensitive core subsystem: The required protection attenuation and response time are quantified and solved by optimizing the function; RF Link: The ratio of out-of-band rejection depth to link insertion loss is optimized through a multi-objective function balance. Overall casing: The optimal combination of shielding effectiveness and structural weight is quantified and matched through constraints; This optimization model enables the quantitative selection of protection strategy parameters, rather than simply listing protection technology solutions, thereby resolving the contradiction between protection effectiveness and engineering application and improving the engineering practicality of the method.

9. The method for hierarchical quantitative decomposition and optimization design of high-power microwave protection indicators for unmanned aerial vehicles according to claim 1, characterized in that, The method for constructing the indicator closed-loop verification model in step S5 is as follows: S5.

1. Based on electromagnetic simulation software, substitute the three-level index parameters to verify the synergy of the overall machine, subsystem, and component indexes. S5.2 Establish an indicator correction formula; if the verification fails, adjust the weighting coefficients. , With residual coefficient The indicators were then re-decomposed. S5.3 Iteratively optimize the protection strategy until all levels of indicators meet the theoretical requirements and engineering constraints, forming a complete quantitative design closed loop.

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