A multi-target electromagnetic interference synergistic effect evaluation method and system

Abstract

The present application relates to electromagnetic environment effect evaluation and electronic countermeasure technical field, specifically to a kind of multi-target electromagnetic interference cooperative effect evaluation method and system, comprising: waveform data of acquisition wide-area coverage vector and time-domain pulse vector;Total radio frequency energy is obtained;Protocol state machine fragile window is calculated;Optimal cooperative delay is calculated;Link state data of the device under test is collected;Protocol state entropy is calculated based on link state data;The amount of change of protocol state entropy and total radio frequency energy are combined to calculate cooperative efficiency index;If the change range of cooperative efficiency index is greater than preset convergence threshold, optimal cooperative delay is corrected using gradient descent algorithm and returns to execute the step of transmitting;If the change range of cooperative efficiency index is less than or equal to preset convergence threshold, wide-area coverage vector, time-domain pulse vector and optimal cooperative delay are solidified as standard test case;The present application solves the technical problem that traditional test cannot adapt to unknown device characteristics and is difficult to capture dynamic timing vulnerabilities.

Description

Technical Field

[0001] This invention relates to the fields of electromagnetic environment effect assessment and electronic countermeasures technology, specifically to a method and system for assessing the synergistic effect of multi-target electromagnetic interference. Background Technology

[0002] With the rapid evolution of wireless communication technology, the electromagnetic environment is becoming increasingly complex, and the protocol architecture and signal processing mechanisms adopted by communication equipment are becoming more sophisticated. This complexity makes it difficult to evaluate the anti-interference performance of electronic devices, especially in scenarios where multiple target signals work together.

[0003] Currently, the evaluation of interference effectiveness generally relies on the subjective experience of technicians or employs crude methods such as simple high-power suppression, lacking objective quantitative standards. Existing testing methods often involve blind transmission, failing to accurately perceive the vulnerability windows of the protocol state machine of the device under test, and making it difficult to achieve precise coordination of interference signals in the time domain. This approach not only fails to accurately reflect the actual interference output per unit of energy consumption, but also cannot automatically correct the transmission timing through closed-loop control to approximate the actual failure point of the device, resulting in a lack of scientific basis and low efficiency in the formulation of interference strategies. Therefore, how to establish an objective quantitative evaluation system to achieve dynamic optimization and automated evaluation of the coordinated effects of multi-target electromagnetic interference has become an urgent problem to be solved in this field. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for evaluating the cooperative effect of multi-target electromagnetic interference. This method overcomes the technical shortcomings of existing technologies, such as reliance on subjective experience, blind firing, and a lack of quantitative standards in interference evaluation. Furthermore, it can achieve precise coordination and dynamic optimization based on the vulnerable window of the protocol state machine by quantifying the relationship between physical layer energy consumption and protocol layer state disorder, thereby objectively evaluating interference effectiveness in complex electromagnetic environments. Specifically, the technical solution of this invention is as follows:

[0005] A method for evaluating the coordinated effect of multi-target electromagnetic interference includes:

[0006] Obtain waveform data of wide-area coverage vector and time-domain pulse vector;

[0007] The total radio frequency energy is obtained by performing energy integration on the waveform data.

[0008] Based on the protocol feature parameters of the wide-area coverage vector, calculate the vulnerable window of the protocol state machine;

[0009] The optimal cooperative delay is calculated based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain pulse vector.

[0010] Transmit wide-area coverage vector and time-domain pulse vector according to the optimal coordinated delay, and collect link status data of the device under test;

[0011] Calculate the protocol state entropy based on link state data;

[0012] The cooperative efficiency index is calculated by combining the change in protocol state entropy and total radio frequency energy.

[0013] If the change in the collaborative efficiency index exceeds the preset convergence threshold, the optimal collaborative delay is corrected using the gradient descent algorithm and the execution of the launch step is returned.

[0014] If the change in the collaborative efficiency index is less than or equal to the preset convergence threshold, the wide-area coverage vector, temporal impulse vector, and optimal collaborative delay will be solidified as standard test cases.

[0015] Preferably, the configuration rules for the wide-area coverage vector and the temporal impulse vector include:

[0016] Configure a high duty cycle and wide bandwidth modulation signal as a wide-area coverage vector;

[0017] Configure a pulse signal with low duty cycle and narrowband high power as a time-domain pulse vector;

[0018] Among them, the wide-area coverage vector is derived from a preset background traffic model library, and the time-domain pulse vector is derived from a feature library for the device under test.

[0019] Preferably, the waveform data is integrated to obtain the total radio frequency energy, including:

[0020] Obtain the baseband voltage amplitude at any time from the wide-area coverage vector or time-domain pulse vector;

[0021] The instantaneous power is obtained by calculating the ratio of the square of the baseband voltage amplitude to the equivalent load impedance of the system.

[0022] The instantaneous power is integrally calculated over the duration of signal transmission to obtain the single-vector energy.

[0023] The total radio frequency energy is generated by summing the single-vector energy corresponding to the wide-area coverage vector and the single-vector energy corresponding to the time-domain pulse vector.

[0024] Preferably, based on the protocol feature parameters of the wide-area coverage vector, the vulnerability window of the protocol state machine is calculated, including:

[0025] Extract the induced protocol header length from protocol feature parameters;

[0026] Obtain the symbol processing rate of the device under test;

[0027] The processing delay is obtained by calculating the ratio of the induction protocol header length to the symbol processing rate.

[0028] Obtain the launch start time of the wide-area coverage vector;

[0029] The start time of the transmission start time, processing delay, and inherent delay of the device under test are summed to generate the start time of the vulnerable window of the protocol state machine.

[0030] Preferably, the optimal cooperative delay is calculated based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain impulse vector, including:

[0031] Calculate the time difference between the start time of the vulnerable window of the protocol state machine and the start time of the transmission;

[0032] The optimal coordinated delay is generated by subtracting half of the pulse width parameter from the time difference.

[0033] Preferably, based on link state data, the protocol state entropy is calculated, including:

[0034] The probability of each protocol state appearing in the statistical link state data;

[0035] Protocol states include connected state, handshake state, fallback state, or disconnected state;

[0036] The protocol state entropy is generated by summing and inverting the product of the probability and logarithmic probability of each protocol state.

[0037] Preferably, the cooperative performance index is calculated by combining the change in protocol state entropy and total radio frequency energy, including:

[0038] The change is obtained by calculating the difference between the protocol state entropy after interference and the reference system entropy before interference;

[0039] Calculate the ratio of the change to the total radio frequency energy to generate a synergistic performance index;

[0040] Among them, the synergy efficiency index characterizes the degree of system disorder generated per unit of energy consumption.

[0041] Preferably, the optimal cooperative delay is corrected using the gradient descent algorithm, including:

[0042] Calculate the difference between the collaborative effectiveness index of the current test and the previous test to obtain the effectiveness difference value;

[0043] Calculate the difference between the optimal collaborative latency of the current test and the previous test to obtain the latency difference value;

[0044] The performance gradient is obtained by calculating the ratio of the performance difference to the delay difference.

[0045] The corrected step size is obtained by calculating the product of the preset learning rate coefficient and the efficiency gradient.

[0046] The current optimal cooperative delay is summed with the correction step size to generate the corrected optimal cooperative delay.

[0047] A multi-target electromagnetic interference cooperative effect evaluation system, comprising:

[0048] The data acquisition module is used to acquire waveform data of wide-area coverage vector and time-domain pulse vector;

[0049] The energy calculation module is used to perform energy integration calculation on waveform data to obtain the total radio frequency energy.

[0050] The timing calculation module is used to calculate the vulnerable window of the protocol state machine based on the protocol feature parameters of the wide-area coverage vector, and to calculate the optimal cooperative delay based on the vulnerable window of the protocol state machine and the pulse width parameter of the time-domain pulse vector.

[0051] The interference execution module is used to transmit wide-area coverage vectors and time-domain pulse vectors according to the optimal cooperative delay, and to collect link status data of the device under test;

[0052] The entropy evaluation module is used to calculate the protocol state entropy based on link state data, and to calculate the collaborative efficiency index by combining the change in protocol state entropy and total radio frequency energy.

[0053] The closed-loop optimization module is used to correct the optimal collaborative delay and trigger the interference execution module when the change in the collaborative efficiency index exceeds the preset convergence threshold.

[0054] The result solidification module is used to solidify the wide-area coverage vector, temporal impulse vector, and optimal collaborative delay into standard test cases when the change in the collaborative efficiency index is less than or equal to the preset convergence threshold.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. This invention proposes a collaborative efficiency index by quantifying the relationship between physical layer energy consumption and protocol layer state disorder. This index uses the principle of information entropy to transform discrete device operating states into continuous values, objectively reflecting the interference output per unit energy. It overcomes the shortcomings of existing evaluations that rely on subjective experience and simply pursue high power suppression, and realizes a scientific quantitative evaluation of interference efficiency in complex electromagnetic environments.

[0057] 2. This invention deduces the internal state machine transition process of the device under test based on protocol characteristic parameters, and accurately calculates the vulnerable window of the protocol state machine. By aligning the energy center of the time-domain pulse vector with this window, precise coordination of the interference signal in the time domain is achieved, avoiding energy waste caused by blind transmission, ensuring that the pulse energy accurately covers the period with the lowest error correction redundancy of the device, and significantly improving the interference success rate and strike accuracy;

[0058] 3. This invention establishes a gradient-based closed-loop optimization mechanism that automatically corrects the transmission timing according to the changes in the collaborative efficiency index. By iteratively approximating the actual paralysis point of the device under test, the system can dynamically optimize along the efficiency gradient direction until it finds the best time point that maximizes the interference effect, thus solving the technical problem that traditional testing cannot adapt to the characteristics of unknown devices and is difficult to capture dynamic timing vulnerabilities.

[0059] 4. This invention automates and standardizes the testing process, enabling the optimal waveform vector and cooperative delay parameters to be solidified into standard test cases after optimization. This not only reduces manual intervention and improves the efficiency of electromagnetic environment effect assessment, but also provides reusable and comparable benchmark data for subsequent anti-interference performance testing of similar equipment, effectively solving the problem of difficulty in generating test cases. Attached Figure Description

[0060] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0061] Figure 1 This is a flowchart of the method of the present invention;

[0062] Figure 2 This is a structural diagram of the system of the present invention. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0064] Example 1:

[0065] Please see Figure 1 A method for evaluating the synergistic effect of multi-target electromagnetic interference, comprising:

[0066] Obtain waveform data of wide-area coverage vector and time-domain pulse vector;

[0067] The total radio frequency energy is obtained by performing energy integration on the waveform data.

[0068] Based on the protocol feature parameters of the wide-area coverage vector, calculate the vulnerable window of the protocol state machine;

[0069] The optimal cooperative delay is calculated based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain pulse vector.

[0070] Transmit wide-area coverage vector and time-domain pulse vector according to the optimal coordinated delay, and collect link status data of the device under test;

[0071] Calculate the protocol state entropy based on link state data;

[0072] The cooperative efficiency index is calculated by combining the change in protocol state entropy and total radio frequency energy.

[0073] If the change in the collaborative efficiency index exceeds the preset convergence threshold, the optimal collaborative delay is corrected using the gradient descent algorithm and the execution of the launch step is returned.

[0074] If the change in the collaborative efficiency index is less than or equal to the preset convergence threshold, the wide-area coverage vector, temporal impulse vector, and optimal collaborative delay will be solidified as standard test cases.

[0075] This embodiment provides a method for evaluating the cooperative effect of multi-target electromagnetic interference. This method achieves objective evaluation and dynamic optimization of interference effectiveness in complex electromagnetic environments by quantifying the relationship between physical layer energy consumption and protocol layer state disorder.

[0076] The system acquires waveform data of wide-area coverage vectors and time-domain pulse vectors, along with their associated waveform description files. In this embodiment, the wide-area coverage vector is used to simulate a signal with high-load background traffic, which occupies the computing and spectrum resources of the device under test. The time-domain pulse vector is used to simulate a signal with high-power transient interference, which is used to precisely inject into specific protocol vulnerabilities. The system reads or generates baseband I / Q data of these two types of orthogonal interference vector groups from a preset waveform database through a radio signal simulation playback subsystem, while simultaneously reading waveform description files containing waveform sampling rate, frame structure definition, and protocol type information.

[0077] The total radio frequency energy is obtained by integrating the waveform data. In order to eliminate the differences in the time domain distribution of different signal standards, the system converts the voltage signal into a physical energy value. This step provides a standardized denominator for subsequent calculation of interference output per unit energy, ensuring that the physical meaning of the evaluation index is clear and comparable.

[0078] Based on the protocol characteristic parameters of the wide-area coverage vector, the vulnerability window of the protocol state machine is calculated. Instead of blindly transmitting, the system analyzes the physical layer parameters of the wide-area coverage vector and deduces the state transition process of the internal state machine of the device under test when processing the signal. The vulnerability window of the protocol state machine refers to the time period when the device under test has the lowest error correction redundancy and is most sensitive to external pulses when performing high-load demodulation or verification tasks.

[0079] Based on the vulnerability window of the protocol state machine and the pulse width parameter of the time-domain pulse vector, the optimal cooperative delay is calculated. After determining the vulnerability window, the system combines the time-domain width of the pulse vector itself to calculate the precise transmission time, so that the pulse energy can accurately cover the vulnerable period of the device under test.

[0080] The system transmits wide-area coverage vectors and time-domain pulse vectors according to the optimal coordinated delay, and collects link status data of the device under test; the system controls the vector signal source to perform coordinated transmission, and records the operating status of the device under test in real time through a protocol analyzer or log probe deployed in the monitoring loop;

[0081] Based on link state data, the protocol state entropy is calculated. The system uses an information theory model to transform the discrete operating state of the device under test into a continuous entropy value index, thereby quantifying the degree of disorder of the system under interference.

[0082] The cooperative performance index is calculated by combining the change in protocol state entropy and total radio frequency energy. This index characterizes the system disorder gain generated per unit of energy consumption and is a core indicator for evaluating the merits of cooperative interference strategies.

[0083] The system executes closed-loop control based on changes in the collaborative efficiency index: if the change in the collaborative efficiency index exceeds a preset convergence threshold, it indicates that the current timing parameters have not yet reached their optimal state. The system then uses a gradient descent algorithm to correct the optimal collaborative delay and returns to execute the transmission step, iteratively approaching the actual failure point of the tested device; if the change in the collaborative efficiency index is less than or equal to the preset convergence threshold, it is determined that the optimal collaborative point has been found. At this point, the wide-area coverage vector, time-domain pulse vector, and optimal collaborative delay are solidified into standard test cases and stored in a complex electromagnetic environment scenario library as a benchmark for subsequent anti-interference performance testing of similar devices; where the preset convergence threshold... Usually set to Or a value set according to the actual test accuracy requirements;

[0084] Through the above steps, the present invention can automatically detect protocol vulnerability windows of unknown devices and generate high-efficiency standardized test waveforms, solving the technical problem that interference assessment in the prior art relies on subjective experience and lacks quantitative standards.

[0085] Example 2:

[0086] The configuration rules for wide-area coverage vectors and temporal impulse vectors include:

[0087] Configure a high duty cycle and wide bandwidth modulation signal as a wide-area coverage vector;

[0088] Configure a pulse signal with low duty cycle and narrowband high power as a time-domain pulse vector;

[0089] Among them, the wide-area coverage vector is derived from a preset background traffic model library, and the time-domain pulse vector is derived from a feature library for the device under test.

[0090] This embodiment specifies the configuration rules for waveform vectors;

[0091] A high duty cycle and wide bandwidth modulation signal is configured as the wide-area coverage vector; in this embodiment, the wide-area coverage vector... Select an orthogonal frequency division multiplexing (OFDM) signal or a high-order QAM modulation signal, with its duty cycle set to... to The bandwidth covers the entire operating frequency band of the device under test; the vector is derived from a preset background traffic model library, which contains high-load service models that conform to standard communication protocols such as LTE, 5G or Wi-Fi; it forces the device under test to start complex channel estimation and equalization algorithms, thereby consuming the computing power margin of its baseband processing unit;

[0092] A low duty cycle and narrowband high power pulse signal is configured as the time-domain pulse vector; in this embodiment, the time-domain pulse vector... Select a single-frequency pulse in the microsecond or nanosecond range, with a duty cycle lower than... However, the instantaneous peak power is higher than the average power of the wide-area coverage vector. The above vector originates from a feature library for the device under test (DUT), which is built based on the DUT's historical vulnerability data or key frame definitions in the protocol specifications. It utilizes the moment when the DUT's processing resources are saturated to precisely cover key protocol fields such as synchronization headers and pilots, inducing demodulation errors or synchronization loss.

[0093] Example 3:

[0094] The total radio frequency energy is obtained by integrating the waveform data, including:

[0095] Obtain the baseband voltage amplitude at any time from the wide-area coverage vector or time-domain pulse vector;

[0096] The instantaneous power is obtained by calculating the ratio of the square of the baseband voltage amplitude to the equivalent load impedance of the system.

[0097] The instantaneous power is integrally calculated over the duration of signal transmission to obtain the single-vector energy.

[0098] The total radio frequency energy is generated by summing the single-vector energy corresponding to the wide-area coverage vector and the single-vector energy corresponding to the time-domain pulse vector.

[0099] This embodiment details the calculation method for total radio frequency energy, ensuring the physical rigor of the energy assessment;

[0100] The system acquires the baseband voltage amplitude at any given time using a wide-area coverage vector or a time-domain pulse vector; the system uses a sampling rate... Read the in-phase component from the waveform file and orthogonal components Calculations yielded Baseband voltage amplitude at time ;

[0101] The instantaneous power is obtained by calculating the ratio of the square of the baseband voltage amplitude to the equivalent load impedance of the system; the instantaneous power of the system is calculated according to Joule's law. ;in, The equivalent load impedance of the system is taken as the standard RF impedance value in this embodiment. ;

[0102] During the signal transmission duration, the instantaneous power is integrally calculated over time for the effective signal segment to obtain a single-vector energy; the system controls the transmission window length. The instantaneous power within is numerically integrated; where Only baseband voltage amplitude is counted An effective duration greater than the noise threshold is used to eliminate the dilution effect of signal intervals on the average energy density.

[0103] The total radio frequency energy is generated by summing the single-vector energy corresponding to the wide-area coverage vector and the single-vector energy corresponding to the time-domain pulse vector. The calculation formula is as follows:

[0104] ;

[0105] in, For vectors or vector exist The baseband voltage amplitude at time 10:00. The signal transmission duration is set by the host computer. Through this formula, the system converts the time-domain voltage fluctuations of different waveforms into a unified energy scalar, eliminating the influence of waveform format differences on the evaluation results.

[0106] Example 4:

[0107] Based on the protocol feature parameters of the wide-area coverage vector, the vulnerability window of the protocol state machine is calculated, including:

[0108] Extract the induced protocol header length from protocol feature parameters;

[0109] Obtain the symbol processing rate of the device under test;

[0110] The processing delay is obtained by calculating the ratio of the induction protocol header length to the symbol processing rate.

[0111] Obtain the launch start time of the wide-area coverage vector;

[0112] The start time of the transmission start time, processing delay, and inherent delay of the device under test are summed to generate the start time of the vulnerable window of the protocol state machine.

[0113] This embodiment details the calculation logic of the fragile window of the protocol state machine, and realizes timing prediction based on protocol characteristics;

[0114] The system extracts the induced protocol header length from the protocol feature parameters; it also retrieves the frame structure definition from the waveform description file associated with the wide-area coverage vector, identifies the protocol header field used to trigger receiver synchronization or signaling parsing, and extracts its bit length. ;

[0115] Obtain the symbol processing rate of the device under test; the system reads the technical specifications of the device under test or obtains its physical layer symbol processing rate through pre-tested benchmarks. The unit is bit / s;

[0116] The processing delay is obtained by calculating the ratio of the induction protocol header length to the symbol processing rate; this ratio... Physically, it represents the theoretical time required for the device under test to receive the complete protocol header;

[0117] Obtain the launch start time of the wide-area coverage vector; at this time... Determined by the master clock of the test system;

[0118] The start time of the transmission start time, processing delay, and inherent delay of the device under test are summed to generate the start time of the vulnerable window of the protocol state machine; the vulnerable window start time. The calculation formula is as follows:

[0119] ;

[0120] in, This is due to the inherent latency of the internal hardware processing of the device under test; in this embodiment, The acquisition methods include the following two: For known device models, historical test databases can be accessed; for unknown devices, the system performs a pre-calibration step: sending multiple frames, such as M>100 induced probe signals, to the device under test and monitoring its physical layer feedback signals, such as ACK or NACK, and statistically measuring the time difference from the end of signal transmission to the receipt of the feedback signal. The distribution of the vector, after removing outliers, is used as the mean or median as the measurement result. Let... ,in This calibration step is used to calculate the air interface transmission time based on distance. It enables the actual measurement and calibration of the internal processing delay of unknown devices, or to obtain the result by calibrating the device's GPIO toggle signals using an oscilloscope. This step can accurately locate the critical time node when the device under test switches from physical layer reception to link layer processing.

[0121] Example 5:

[0122] Based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain pulse vector, the optimal cooperative delay is calculated, including:

[0123] Calculate the time difference between the start time of the vulnerable window of the protocol state machine and the start time of the transmission;

[0124] The optimal coordinated delay is generated by subtracting half of the pulse width parameter from the time difference.

[0125] This embodiment illustrates the method for calculating the optimal coordination delay, ensuring precise alignment of interference signals in the time domain;

[0126] Calculate the time difference between the start time of the vulnerable window of the protocol state machine and the start time of the transmission;

[0127] The optimal coordinated delay is generated by subtracting half of the pulse width parameter from the time difference. The calculation formula is as follows:

[0128] ;

[0129] in, The pulse width parameter of the time-domain pulse vector is derived from the waveform configuration file. This calculation adopts a center alignment strategy, which aligns the energy center of the interference pulse with the start time of the vulnerable window of the device under test, rather than simply aligning the pulse leading edge. This design can maximize the overlap probability between the interference pulse and the critical moment of the protocol, significantly improving the interference success rate.

[0130] Example 6:

[0131] Based on link state data, the protocol state entropy is calculated, including:

[0132] The probability of each protocol state appearing in the statistical link state data;

[0133] Protocol states include connected state, handshake state, fallback state, or disconnected state;

[0134] The protocol state entropy is generated by summing and inverting the product of the probability and logarithmic probability of each protocol state.

[0135] This embodiment introduces a method for quantifying the disorder of a system state using information entropy;

[0136] The system calculates the probability of each protocol state appearing in the statistical link status data. To accurately reflect the disruption of service continuity caused by interference, a time-weighted method is used to calculate the probability. This is done within a preset observation time window. Within, the system has accumulated tested devices in the first... Total duration of each state Then the statistical probability The calculation formula is:

[0137] ;

[0138] This calculation method ensures that the sum of the probabilities of all states is 1, and eliminates statistical bias caused by frequent short-term state switching.

[0139] Protocol states include connected, handshake, fallback, or disconnected states; where connected state indicates normal data transmission; handshake state indicates signaling interaction is in progress; fallback state indicates that the ARQ retransmission mechanism has been triggered or the rate has decreased; and disconnected state indicates that the link is completely interrupted.

[0140] The protocol state entropy is generated by summing and inverting the product of the probability and logarithmic probability of each protocol state. The calculation formula is as follows:

[0141] ;

[0142] in, The total number of states defined for the protocol state machine of the device under test. The total number of states in the protocol state set, in this embodiment These correspond to the connected state, handshake state, fallback state, and disconnected state, respectively, but in practical applications, they can be extended according to the characteristics of the device. For the first This indicator utilizes the Shannon entropy principle to transform the discrete distribution of device states into a continuous value that reflects the uncertainty of the system, and can keenly capture the micro-jitter at the protocol layer that traditional bit error rate indicators cannot reflect.

[0143] Example 7:

[0144] The cooperative performance index is calculated by combining the change in protocol state entropy and total radio frequency energy, including:

[0145] The change is obtained by calculating the difference between the protocol state entropy after interference and the reference system entropy before interference;

[0146] Calculate the ratio of the change to the total radio frequency energy to generate a synergistic performance index;

[0147] Among them, the synergy efficiency index characterizes the degree of system disorder generated per unit of energy consumption.

[0148] This embodiment defines a collaborative efficiency index and constructs an energy efficiency ratio evaluation system;

[0149] The change is obtained by calculating the difference between the protocol state entropy after interference and the reference system entropy before interference;

[0150] Calculate the ratio of the change to the total radio frequency energy to generate the synergistic performance index. The calculation formula is as follows:

[0151] ;

[0152] in, The system entropy after applying the disturbance. The entropy of the reference system before the disturbance is applied is usually measured in an interference-free environment and is close to 0. The physical dimensions are This metric represents the degree of system disruption caused by consuming 1 joule of radio frequency energy; it objectively reflects the technical level of the interference strategy and avoids the crude evaluation that relies solely on high-power suppression.

[0153] Example 8:

[0154] Correcting the optimal cooperative delay using the gradient descent algorithm includes:

[0155] Calculate the difference between the collaborative effectiveness index of the current test and the previous test to obtain the effectiveness difference value;

[0156] Calculate the difference between the optimal collaborative latency of the current test and the previous test to obtain the latency difference value;

[0157] The performance gradient is obtained by calculating the ratio of the performance difference to the delay difference.

[0158] The corrected step size is obtained by calculating the product of the preset learning rate coefficient and the efficiency gradient.

[0159] The current optimal cooperative delay is summed with the correction step size to generate the corrected optimal cooperative delay.

[0160] This embodiment details the closed-loop optimization process of correcting collaborative delay using the gradient descent algorithm;

[0161] Before performing iterative corrections, the system performs an initialization test: using the calculated initial optimal cooperative delay. The first launch was carried out, and the performance index was obtained. Apply a preset small time perturbation ,by The second launch was carried out, and the effectiveness index was obtained. This initiates subsequent gradient iteration calculations;

[0162] Calculate the difference between the collaborative effectiveness index of the current test and the previous test to obtain the effectiveness difference value. ;

[0163] Calculate the difference between the optimal collaborative latency of the current test and the previous test to obtain the latency difference value. ;

[0164] The performance gradient is obtained by calculating the ratio of the performance difference to the delay difference; this gradient... This reflects the sensitivity and direction of the delay parameter variation to the interference effectiveness;

[0165] The corrected step size is obtained by calculating the product of the preset learning rate coefficient and the efficiency gradient.

[0166] The current optimal collaborative delay is summed with the corrected step size to generate the corrected optimal collaborative delay. When calculating the performance gradient, a smoothing factor is introduced into the denominator to prevent the delay difference from approaching zero and causing computational overflow. Corrected optimal cooperative delay The iterative formula is as follows:

[0167] ;

[0168] in, This is a smoothing factor used to prevent the denominator from being zero; This is the sign function, used to maintain the directionality of gradient updates; To prevent the minimum value where the denominator is zero, the value is taken as... The formula directly utilizes the delay difference. The sign of the gradient is used to determine the direction of the gradient, ensuring that the gradient direction correctly points in the direction of increasing efficiency exponent, i.e., the gradient ascent method. This is the learning rate coefficient, and its unit is 1000 ppm. This is used to balance the dimensions and control the iteration speed; The value range is set to to The specific value is inversely proportional to the symbol rate of the device under test; when the symbol rate is greater than 10 Msps, A lower limit value is selected to avoid excessively large iteration step sizes that could lead to non-convergence; when the symbol rate is less than 1 Msps, Selecting an upper limit value can speed up the optimization process; The value of is usually obtained through offline simulation training to prevent oscillations or overfitting during the iteration process; through this algorithm, the system can automatically adjust the launch timing along the direction of the efficiency gradient until the optimal time point that maximizes the interference effect is found.

[0169] Example 9:

[0170] Please see Figure 2 A multi-target electromagnetic interference cooperative effect evaluation system, comprising:

[0171] The data acquisition module is used to acquire waveform data of wide-area coverage vector and time-domain pulse vector;

[0172] The energy calculation module is used to perform energy integration calculation on waveform data to obtain the total radio frequency energy.

[0173] The timing calculation module is used to calculate the vulnerable window of the protocol state machine based on the protocol feature parameters of the wide-area coverage vector, and to calculate the optimal cooperative delay based on the vulnerable window of the protocol state machine and the pulse width parameter of the time-domain pulse vector.

[0174] The interference execution module is used to transmit wide-area coverage vectors and time-domain pulse vectors according to the optimal cooperative delay, and to collect link status data of the device under test;

[0175] The entropy evaluation module is used to calculate the protocol state entropy based on link state data, and to calculate the collaborative efficiency index by combining the change in protocol state entropy and total radio frequency energy.

[0176] The closed-loop optimization module is used to correct the optimal collaborative delay and trigger the interference execution module when the change in the collaborative efficiency index exceeds the preset convergence threshold.

[0177] The result solidification module is used to solidify the wide-area coverage vector, temporal impulse vector, and optimal collaborative delay into standard test cases when the change in the collaborative efficiency index is less than or equal to the preset convergence threshold.

[0178] This embodiment provides a multi-target electromagnetic interference cooperative effect evaluation system for performing the above method, the system comprising:

[0179] The data acquisition module is used to acquire waveform data of wide-area coverage vector and time-domain pulse vector from a preset database or simulation engine;

[0180] The energy calculation module is used to perform integration calculations, calculate the total radio frequency energy by integrating the waveform data. ;

[0181] The timing calculation module is used to parse protocol parameters, calculate the protocol state machine vulnerability window based on the protocol feature parameters of the wide-area coverage vector, and calculate the optimal cooperative delay based on the protocol state machine vulnerability window and the pulse width parameter of the time-domain pulse vector.

[0182] The interference execution module is used to control the radio frequency front end to transmit wide-area coverage vectors and time-domain pulse vectors according to the optimal cooperative delay, and to collect link status data of the device under test through monitoring probes;

[0183] The entropy evaluation module is used for data processing, calculating the protocol state entropy based on link state data, and calculating the collaborative efficiency index by combining the change in protocol state entropy and total radio frequency energy.

[0184] The closed-loop optimization module is used for logical judgment and feedback. When the change in the collaborative efficiency index is greater than the preset convergence threshold, the gradient descent algorithm is used to correct the optimal collaborative delay and trigger the interference execution module to conduct the next round of testing.

[0185] The result solidification module is used for data storage. When the change in the collaborative efficiency index is less than or equal to the preset convergence threshold, the wide-area coverage vector, temporal impulse vector and optimal collaborative delay are packaged and solidified into standard test cases for subsequent use.

[0186] Through the organic combination of the above modules, this system achieves full-process automation from signal generation, timing control, state monitoring to performance evaluation, significantly improving the efficiency and accuracy of electromagnetic environment effect assessment.

[0187] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for evaluating a synergistic effect of multi-target electromagnetic interference, characterized in that, include: Obtain waveform data of wide-area coverage vector and time-domain pulse vector; The total radio frequency energy is obtained by performing energy integration on the waveform data. Based on the protocol feature parameters of the wide-area coverage vector, calculate the vulnerable window of the protocol state machine; The optimal cooperative delay is calculated based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain pulse vector. Transmit wide-area coverage vector and time-domain pulse vector according to the optimal coordinated delay, and collect link status data of the device under test; Calculate the protocol state entropy based on link state data; The cooperative efficiency index is calculated by combining the change in protocol state entropy and total radio frequency energy. If the change in the collaborative efficiency index exceeds the preset convergence threshold, the optimal collaborative delay is corrected using the gradient descent algorithm and the execution of the launch step is returned. If the change in the collaborative efficiency index is less than or equal to the preset convergence threshold, the wide-area coverage vector, the temporal impulse vector, and the optimal collaborative delay will be solidified as standard test cases. Based on the protocol feature parameters of the wide-area coverage vector, the vulnerability window of the protocol state machine is calculated, including: Extract the induced protocol header length from protocol feature parameters; Obtain the symbol processing rate of the device under test; The processing delay is obtained by calculating the ratio of the induction protocol header length to the symbol processing rate. Obtain the launch start time of the wide-area coverage vector; The start time of the launch, the processing delay, and the inherent delay of the device under test are summed to generate the start time of the vulnerable window of the protocol state machine; Based on the fragile window of the protocol state machine and the pulse width parameter of the time-domain pulse vector, the optimal cooperative delay is calculated, including: Calculate the time difference between the start time of the vulnerable window of the protocol state machine and the start time of the transmission; The optimal coordinated delay is generated by subtracting half of the pulse width parameter from the time difference. Based on link state data, the protocol state entropy is calculated, including: The probability of each protocol state appearing in the statistical link state data; Protocol states include connected state, handshake state, fallback state, or disconnected state; The protocol state entropy is generated by summing and inverting the product of the probability and logarithmic probability of each protocol state. The cooperative performance index is calculated by combining the change in protocol state entropy and total radio frequency energy, including: The change is obtained by calculating the difference between the protocol state entropy after interference and the reference system entropy before interference; Calculate the ratio of the change to the total radio frequency energy to generate a synergistic performance index; Among them, the synergy efficiency index characterizes the degree of system disorder generated per unit of energy consumption.

2. The method for evaluating the synergistic effect of multi-target electromagnetic interference according to claim 1, characterized in that, The configuration rules for wide-area coverage vectors and temporal impulse vectors include: Configure a high duty cycle and wide bandwidth modulation signal as a wide-area coverage vector; Configure a pulse signal with low duty cycle and narrowband high power as a time-domain pulse vector; Among them, the wide-area coverage vector is derived from a preset background traffic model library, and the time-domain pulse vector is derived from a feature library for the device under test.

3. The method for evaluating the synergistic effect of multi-target electromagnetic interference according to claim 1, characterized in that, The total radio frequency energy is obtained by integrating the waveform data, including: Obtain the baseband voltage amplitude at any time from the wide-area coverage vector or time-domain pulse vector; The instantaneous power is obtained by calculating the ratio of the square of the baseband voltage amplitude to the equivalent load impedance of the system. The instantaneous power is integrally calculated over the duration of signal transmission to obtain the single-vector energy. The total radio frequency energy is generated by summing the single-vector energy corresponding to the wide-area coverage vector and the single-vector energy corresponding to the time-domain pulse vector.

4. The method for evaluating the coordinated effect of multi-target electromagnetic interference according to claim 1, characterized in that, Correcting the optimal cooperative delay using the gradient descent algorithm includes: Calculate the difference between the collaborative effectiveness index of the current test and the previous test to obtain the effectiveness difference value; Calculate the difference between the optimal collaborative latency of the current test and the previous test to obtain the latency difference value; The performance gradient is obtained by calculating the ratio of the performance difference to the delay difference. The corrected step size is obtained by calculating the product of the preset learning rate coefficient and the efficiency gradient. The current optimal cooperative delay is summed with the correction step size to generate the corrected optimal cooperative delay.

5. A multi-target electromagnetic interference cooperative effect evaluation system, applied to the multi-target electromagnetic interference cooperative effect evaluation method according to any one of claims 1-4, characterized in that, include: The data acquisition module is used to acquire waveform data of wide-area coverage vector and time-domain pulse vector; The energy calculation module is used to perform energy integration calculation on waveform data to obtain the total radio frequency energy. The timing calculation module is used to calculate the vulnerable window of the protocol state machine based on the protocol feature parameters of the wide-area coverage vector, and to calculate the optimal cooperative delay based on the vulnerable window of the protocol state machine and the pulse width parameter of the time-domain pulse vector. The interference execution module is used to transmit wide-area coverage vectors and time-domain pulse vectors according to the optimal cooperative delay, and to collect link status data of the device under test; The entropy evaluation module is used to calculate the protocol state entropy based on link state data, and to calculate the collaborative efficiency index by combining the change in protocol state entropy and total radio frequency energy. The closed-loop optimization module is used to correct the optimal collaborative delay and trigger the interference execution module when the change in the collaborative efficiency index exceeds the preset convergence threshold. The result solidification module is used to solidify the wide-area coverage vector, temporal impulse vector, and optimal collaborative delay into standard test cases when the change in the collaborative efficiency index is less than or equal to the preset convergence threshold.

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