Method for allocating and scheduling ship-to-air electromagnetic countermeasure jamming resources in complex countermeasure environment

Abstract

The application discloses a method for allocating and scheduling ship-to-air electromagnetic countermeasure jamming resources in a complex countermeasure environment, comprising the following steps: S1: extracting target parameters of each radiation source and instantaneous available power values of each jammer, and combining to obtain a situation matrix; S2: calculating a situation change amount index, and comparing to determine a current electromagnetic environment state; S3: constructing a dynamic game model of our side and the other side; S4: calculating an income value of the other side based on total parameter switching cost; S5: selecting an action with the maximum income value of the other side as the optimal response of the other side, recording a corresponding income value of our side, comparing the income values of our side corresponding to all actions of our side at a root node of our side, and taking an action with the maximum income value of our side as an optimal power allocation scheme. The application can trigger dynamic rescheduling on demand, can determine a global optimal power allocation scheme with the maximum income value of our side under the optimal response of the other side, and improves timeliness and effect stability of jamming in the complex countermeasure environment.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic countermeasures technology, specifically to a method for allocating and scheduling ship-to-air electromagnetic countermeasures and interference resources under complex combat environments. Background Technology

[0002] With the continuous expansion of electromagnetic applications, the modern maritime electronic warfare environment is becoming increasingly complex and volatile. In this complex electromagnetic warfare environment, shipborne electronic warfare systems face an increasing number of threat sources, while shipborne platforms are severely limited by physical constraints such as space and power availability, resulting in highly restricted jamming resources. How to achieve efficient allocation of jamming resources against multiple threat targets under limited resource constraints is a key problem to be solved in the current field of electronic warfare regarding jamming resource allocation and scheduling.

[0003] However, most current ship-to-air electromagnetic countermeasures (ESR) jamming resource allocation and scheduling are typically performed at fixed time intervals. When the signal frequency (Freq) and pulse repetition interval (PRI) of the opposing radiation source undergo abrupt changes, such as when the opposing radar implements frequency hopping or switches its pulse repetition frequency mode, existing methods cannot accurately calculate these frequency and PRI changes. Therefore, these parameter changes cannot be used as a trigger for rescheduling. Such methods can only passively execute according to a preset scheduling cycle, resulting in the continued use of allocation strategies based on previous states in the initial stage after parameter abrupt changes, leading to a significant decrease in jamming effectiveness. Furthermore, existing game theory-based methods mostly use static game matrices (strategic games) for modeling. Although extended game trees exist in game theory to describe sequential decision-making, this framework is not fully utilized in the ESR power allocation problem to characterize the temporal dependencies of the actions of both sides. In real-world adversarial scenarios, our power allocation behavior directly triggers the opponent's instantaneous frequency and PRI agility response. Existing static models cannot map such dynamic response processes into sequential decision interactions, resulting in the generated power allocation scheme lacking the ability to predict the opponent's dynamic evasion behavior. Summary of the Invention

[0004] To address this, the present invention provides a method for allocating and scheduling ship-to-air electromagnetic countermeasures interference resources under complex adversarial environments, in order to solve the problems in the prior art where the interference can only be passively executed according to a preset scheduling cycle, resulting in poor interference effect, and the existing static game moment cannot handle the time-varying interaction process of the behavior of both sides in electromagnetic countermeasures.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for allocating and scheduling ship-to-air electromagnetic countermeasures and jamming resources in complex combat environments, comprising the following steps:

[0007] S1: Receive spatial electromagnetic signals through a wideband antenna array, extract the target parameters of each radiation source and the instantaneous available power value of each jammer, and perform normalization processing on each, then combine them to obtain the situation matrix;

[0008] S2: Based on the situation matrix and the situation matrix of the previous period, calculate the situation change index, and compare the situation change index with the preset sudden change judgment threshold to determine the current electromagnetic environment state.

[0009] S3: Using the current period's situation matrix generated by S1 as the initial information state of the game, construct a dynamic game model between our side and the opponent.

[0010] S4: Calculate the opponent's payoff value by accumulating the preset frequency switching cost and pulse repetition interval switching cost of the candidate actions and pulse repetition interval actions determined by the dynamic game model, respectively;

[0011] S5: Bind the payoff value of our side and the payoff value of the opponent to all leaf nodes of the game tree in the dynamic game model, select the action that maximizes the payoff value of the opponent as the opponent's optimal response and record the corresponding payoff value of our side, compare the payoff values ​​of our side for all our actions at our root node, and take the action that maximizes our payoff value as the optimal power allocation scheme.

[0012] Furthermore, the target parameters include the signal frequency value and the pulse repetition interval value. By normalizing the signal frequency value, the pulse repetition interval value, and the instantaneous available power value, the frequency factor, the pulse repetition interval factor, and the available power factor can be obtained.

[0013] Furthermore, the specific details of the normalization process are as follows:

[0014] 1) Normalization of signal frequency values: Normalize the signal frequency values ​​according to the maximum adjustable range of its operating frequency band to obtain a frequency factor with a value range of 0 to 1. ;

[0015] 2) Normalization of pulse repetition interval values: The pulse repetition interval values ​​are normalized according to the parameter range of the pulse repetition interval type to obtain a pulse repetition interval factor with a value range of 0 to 1. ;

[0016] 3) Normalization of instantaneous available power: The instantaneous available power is normalized according to the rated maximum transmit power of the jammer to obtain an available power factor ranging from 0 to 1. .

[0017] Furthermore, the specific steps of S2 are as follows:

[0018] S2.1: Read the situation matrix generated by S1 in the current cycle and the situation matrix of the previous cycle, and calculate the absolute value of the difference between the frequency factor and the pulse repetition interval factor between the current cycle and the previous cycle.

[0019] S2.2: Calculate the situation change index based on the absolute value of the difference between the frequency factor of the current period and the previous period and the absolute value of the difference between the pulse repetition interval factor. This is used to quantify the degree of change in the electromagnetic countermeasures environment between two adjacent decision-making weeks;

[0020] S2.3: Indicators of change in situation Compare with the preset mutation detection threshold:

[0021] when When the mutation determination threshold is reached, it is determined that the current electromagnetic environment is in a state of stable change, and the current interference resource allocation scheme remains unchanged;

[0022] when When the mutation determination threshold is reached, a sudden change in the target frequency value or pulse repetition interval value is determined.

[0023] Furthermore, the specific steps of S3 are as follows:

[0024] S3.1: Based on the current period's situation matrix as the initial information state of the game, construct an extended game tree structure for the dynamic game model;

[0025] S3.2: Determine our action space at the root node of the game tree constructed in S3.1. ;

[0026] S3.3: Based on the interference signal parameters that the other party can perceive after the power allocation scheme in S3.2 is implemented, determine the other party's action space. And determine the response frequency factor and pulse repetition interval factor by combining each candidate action of the radiation source target;

[0027] S3.4: Calculate our payoff value on the constructed leaf nodes of the game tree based on the post-response frequency factor and the pulse repetition interval factor. The calculation formula is as follows:

[0028]

[0029] in, For interference performance, This is a power consumption cost item. The cost item for switching solutions, , and These are the three weighting coefficients.

[0030] Furthermore, the action space It consists of a set of interference resource power allocation schemes, and each candidate action Corresponding power allocation matrix, matrix elements Indicates the first The jammer was assigned to the first The power values ​​of the radiation source targets, among which For the first Available power factor of the jammer.

[0031] Furthermore, the specific steps of S4 are as follows:

[0032] S4.1: For the currently traversed leaf node in the extended game tree constructed in S3.1, read the value of our payoff calculated in S3.4. Interference performance terms generated during time synchronization ;

[0033] S4.2: Based on the candidate actions selected by the counterpart in the action space of S3.3 corresponding to the currently traversed leaf node, determine the frequency switching cost and the pulse repetition interval switching cost respectively, and obtain the total parameter switching cost;

[0034] S4.3: Based on the interference effectiveness term obtained in S4.1 and the total parameter switching cost determined in S4.2, calculate the counterparty's gain. The calculation formula is as follows:

[0035]

[0036] in, The preset positive interference damage coefficient, The preset base profit value for the other party. This represents the total cost of switching parameters.

[0037] Furthermore, the specific steps of S5 are as follows:

[0038] S5.1: For all leaf nodes in the extended game tree constructed in S3.1, for each node whose action is performed by our side... and the other party's actions The game path consisting of 2 yields the payoff value calculated by S3.4 for each player. and the counterparty's profit value calculated by S4.3 and will Bind to the leaf node to complete the assignment of the game tree terminal payout;

[0039] S5.2: For a given power allocation action of our side Under the opponent's decision node corresponding to the action, traverse the opponent's action space in S3.3. For all candidate actions in step 2, compare the payoff value of each candidate action bound to the counterparty via S5.1. , choose to The opponent's maximum action is taken as the opponent's optimal response at the current node, and the corresponding profit value for our side under the current optimal response is recorded.

[0040] S5.3: At the root node of the game tree, traverse our action space in S3.2. 1 All candidate power allocation actions For each Read the value of our gain under the opponent's optimal response obtained through S5.2;

[0041] Compare the payoff values ​​for all candidate actions and select the action that maximizes our payoff value. This represents our globally optimal power allocation scheme under the equilibrium strategy.

[0042] The present invention has the following advantages: The present invention generates a situation change index by calculating the absolute value of the difference between the frequency factor and the pulse repetition interval factor in the situation matrix of the current period and the previous period, and compares it with the change judgment threshold. This enables dynamic rescheduling to be triggered as needed, thus changing the lag problem of fixed-period scheduling still using the old scheme in the early stage of parameter change.

[0043] Meanwhile, at the opponent's decision node, the action that maximizes the opponent's benefit value is selected as the optimal response. Then, at our root node, the global optimal power allocation scheme that maximizes our benefit value under the opponent's optimal response is determined. This scheme has the ability to predict the opponent's dynamic evasion behavior. After being converted into a power allocation command, the transmission power of each jammer to the radiation source target is updated in real time, which improves the timeliness and stability of jamming in complex confrontation environments.

[0044] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. Attached Figure Description

[0045] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0046] Figure 1This is a flowchart illustrating the implementation of the method for allocating and scheduling ship-to-air electromagnetic countermeasures and interference resources under complex combat environments, as described in this invention. Detailed Implementation

[0047] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these embodiments are merely for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Technical engineers in the field can make some non-essential improvements and adjustments to the present invention based on the above-described content. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Please see Figure 1 A method for allocating and scheduling ship-to-air electromagnetic countermeasures and jamming resources under complex combat environments, comprising the following steps:

[0049] S1: Receive spatial electromagnetic signals through a wideband antenna array, extract the target parameters of each radiation source and the instantaneous available power value of each jammer, and normalize them to obtain the frequency factor, pulse repetition interval factor and available power factor. Combine the three normalized factors into a situation matrix according to the radiation source target dimension and the jamming resource dimension to provide a unified data input format for subsequent steps.

[0050] The target parameters include the signal frequency value and the pulse repetition interval value. The signal frequency value is acquired by the frequency measurement receiver of the shipborne electronic reconnaissance equipment. The core phase detector of the frequency measurement receiver constructs two signal branches through a power divider and a 90° bridge. The phase difference is generated by the delay line, and after detection and differential amplification, the voltage signal of the corresponding frequency is output, thereby obtaining the signal frequency value.

[0051] The pulse repetition interval value is acquired by the pulse parameter measurement unit. This unit performs threshold detection on the envelope of the received signal, records the arrival time of each pulse, and then uses a deinterlacing processor to separate pulse sequences belonging to the same radiation source from the overlapping signals, calculates the difference in arrival times of adjacent pulses from the same source, and outputs the pulse repetition interval value in microseconds.

[0052] When extracting the instantaneous available power value, the high-precision current sensor and voltage sensor in each jammer in our interference resource management unit are polled in real time through the internal controller local area network (CAN bus) or gigabit Ethernet interface. The power supply current and drain voltage of the power amplifier module are collected in real time to obtain the currently occupied transmission power value. Combined with the rated maximum transmission power pre-stored in the equipment parameter table and the health coefficient provided by the equipment self-test module, the instantaneous available power is calculated. Instantaneous available power = rated maximum transmission power × equipment health coefficient - current used power value.

[0053] Our jamming resource management unit consists of a communication interface board, an embedded processing module, and a power control interface card. It polls the high-precision current and voltage sensors of each jammer's power amplifier module via a CAN bus or gigabit Ethernet interface. The embedded processing module calculates and reports the instantaneous available power value of each jammer based on the collected real-time current and voltage data, the pre-stored rated maximum transmit power, and the equipment health coefficient. At the same time, this unit can receive power allocation commands generated by S5, and after parsing and verification, convert them into power drive signals for each jammer's power amplifier module through the power control interface card, completing the real-time loading and updating of power.

[0054] The wideband antenna array consists of multiple planar helical antenna elements covering the 2-18 GHz frequency band arranged in a circular array. The spatial electromagnetic signals received by each antenna element are selected and combined by the radio frequency switch matrix, and then wideband amplified by the low noise amplifier. The amplified radio frequency signal is then split into two paths, which are fed into the frequency measurement receiver to extract the signal frequency value and into the pulse parameter measurement unit to extract the pulse repetition interval value.

[0055] To eliminate numerical differences caused by different physical dimensions when obtaining the target parameters and instantaneous available power values, the three data points were normalized to unify them into a numerical space of 0 to 1, providing comparability for subsequent matrix operations and comparisons. The specific details are as follows:

[0056] 1) Normalization of signal frequency values: Normalize the signal frequency values ​​according to the maximum adjustable range of its operating frequency band to obtain a frequency factor with a value range of 0 to 1. The calculation formula is as follows:

[0057]

[0058] in, The signal frequency value. and These are the maximum and minimum adjustable frequency values ​​for this operating frequency band.

[0059] 2) Normalization of pulse repetition interval values: The pulse repetition interval values ​​are normalized according to the parameter range of the pulse repetition interval type to obtain a pulse repetition interval factor with a value range of 0 to 1. The calculation formula is as follows:

[0060]

[0061] in, This is the pulse repetition interval value. and These represent the maximum and minimum values ​​within the parameter range for the pulse repetition interval type.

[0062] 3) Normalization of instantaneous available power: The instantaneous available power is normalized according to the rated maximum transmit power of the jammer to obtain an available power factor ranging from 0 to 1. The calculation formula is as follows:

[0063]

[0064] in, This represents the instantaneous available power value. This is the rated maximum transmit power of the jammer.

[0065] The situation matrix constructed from the frequency factor, pulse repetition interval factor, and available power factor is ultimately stored in the random access memory of the interference resource management unit in the form of binary data frames. It is then combined into a situation matrix according to the radiation source target dimension and the interference resource dimension, providing a unified numerical input for subsequent dynamic game.

[0066] Radiation source target dimension: The first M rows of the situation matrix correspond to M radiation source targets. Each row includes the target's frequency factor, pulse repetition interval factor, and available power factor. Among them, the available power factor of the radiation source target reflects the theoretically available proportion of interference power that the system can call upon when interfering with that target.

[0067] Interference resource dimension: The last K rows of the situation matrix correspond to K jammers. Each row includes the available power factor of the jammer, as well as the frequency factor and pulse repetition interval factor determined by the jammer's current beam resonant frequency and the baseband signal parameters that can be generated. This indicates the frequency and pulse repetition interval capability that the jammer can effectively cover at the current moment.

[0068] S2: Based on the situation matrix and the situation matrix of the previous cycle, calculate the situation change index, and compare the situation change index with a preset abrupt change judgment threshold to determine the current electromagnetic environment state. This facilitates the accurate identification of abrupt changes in frequency and pulse repetition interval parameters and the on-demand triggering of rescheduling. The specific steps of S2 are as follows:

[0069] S2.1: Read the situation matrix generated by S1 for the current period and the situation matrix for the previous period, and calculate the absolute value of the difference between the frequency factors of the current period and the previous period. and pulse repetition interval factor The absolute values ​​of the differences, the two differences mentioned above, reflect the magnitude of parameter changes of a single target in the frequency dimension and the pulse repetition interval dimension.

[0070] S2.2: Calculate the situation change index based on the absolute value of the difference between the frequency factor of the current period and the previous period and the absolute value of the difference between the pulse repetition interval factor. This is used to quantify the degree of change in the electromagnetic countermeasures environment between two adjacent decision-making weeks. The calculation formula is as follows:

[0071]

[0072] in, and These are weighting coefficients, and This is used to impart higher sensitivity to changes in pulse repetition intervals, since changes in the pulse repetition interval pattern indicate changes in the operating mode of the opposing radar. Changes in instantaneous available power values ​​are not included in abrupt change detection because power is a passively constrained resource, not an environmental trigger condition.

[0073] S2.3: Indicators of change in situation By comparing the result with a preset mutation threshold, this step ensures that computationally expensive solutions are only initiated when there is a substantial change in the environment, achieving a balance between response timeliness and computational resource consumption. The initial value of the mutation threshold is preset based on the statistical distribution of parameter changes in typical adversarial scenarios, with a range of 0.1-0.4.

[0074] when When the mutation judgment threshold is reached, it is determined that the current electromagnetic environment is in a stable change state, the frequency value and pulse repetition interval value of the other party's radiation source have not changed substantially, and the system maintains the current interference resource allocation scheme unchanged.

[0075] when When the mutation determination threshold is reached, a sudden change in the target frequency value or pulse repetition interval value is determined, and the dynamic game optimization process is immediately triggered to execute S3.

[0076] S3: Using the current period situation matrix generated by S1 as the initial information state of the game, construct a dynamic game model between our side and the opponent to simulate the confrontation process between our jammer and the opponent's radiation source in the current electromagnetic environment.

[0077] The game model employs an extended game tree structure. The root node of the game tree is our decision node. After our player chooses a power allocation action, the decision node is reached by the opponent. After the opponent chooses a frequency and pulse repetition interval adjustment action, the decision node is reached by the opponent. The leaf nodes output the payoff values ​​for both sides. The game tree depth is set to two levels, each corresponding to a round of sequential decision-making interaction between the two opposing sides.

[0078] The specific steps for S3 are as follows:

[0079] S3.1: Based on the current situation matrix as the initial information state of the game, an extended game tree structure of the dynamic game model is constructed. The root node of the game tree is our decision node, which corresponds to the decision moment when our side selects a power allocation scheme according to the current frequency factor, pulse repetition interval factor and available power factor. After our side selects an action, it reaches the opponent's decision node, which corresponds to the decision moment when the opponent selects an action to adjust the frequency and pulse repetition interval according to the observed power allocation result of our side.

[0080] After the opponent selects an action, they reach a leaf node, which outputs the payoff values ​​for both sides. The game tree depth is set to two levels, each corresponding to a round of sequential decision-making interaction between the opposing sides, providing a decision path framework for subsequent payoff calculations.

[0081] The aforementioned extended game tree structure refers to a standard modeling method used in operations research and game theory to describe sequential decision-making processes. It primarily formalizes dynamic adversarial problems with sequential action orders into a tree diagram model. The model works based on existing game tree construction and solution methods. First, the current period's situation matrix is ​​loaded as initial common information into the root node of the game tree. Then, it expands layer by layer according to the action order of the adversaries: the root node represents our decision set, and its branches correspond to our different power allocation actions under available power constraints; each branch ends in the opponent's decision node, and its sub-branches correspond to the frequency switching and PRI agility strategies the opponent might adopt after observing our actions. Each path from the root node to a leaf node represents a complete adversarial trajectory from the initial state to the final state after alternating actions. The leaf nodes output the payoffs for both parties along this trajectory, providing a representation of the decision process and a payoff calculation path for subsequent steps.

[0082] S3.2: Determine our action space at the root node of the game tree constructed in S3.1. . It consists of a set of interference resource power allocation schemes, and each candidate action Corresponding power allocation matrix, matrix elements Indicates the first The jammer was assigned to the first The power values ​​of the radiation source targets, among which For the first Available power factor of the jammer.

[0083] Action space The generation method is as follows: First, effective pairings are selected based on the coverage relationship between the jammer's frequency band and the target frequency. Interference equipment and the first The effective pairing condition for each target is that the current resonant frequency of the jammer's beam falls within the frequency band of the target signal; then, each effective pairing is combined according to a preset power level. All pairs satisfying the power constraint are combined. The power allocation vector constitutes . The output serves as the power allocation data basis for subsequent revenue calculations.

[0084] S3.3: Based on the interference signal parameters that the other party can perceive after the power allocation scheme in S3.2 is implemented, determine the other party's action space. First, regarding the first... For a single radiation source target, the frequency switching action includes three mutually exclusive options: keep the current frequency factor unchanged, switch to the first preset backup frequency factor, and switch to the second preset backup frequency factor. The current frequency factor is the initial value of the target frequency factor obtained in S3.1, and the first preset backup frequency factor and the second preset backup frequency factor are two preset backup frequency factor values ​​for the target.

[0085] The pulse repetition interval agile action includes three mutually exclusive options: keep the current pulse repetition interval factor unchanged, switch to the preset first group of pulse repetition interval factors, and switch to the preset second group of pulse repetition interval factors. The current pulse repetition interval factor is the initial value of the target pulse repetition interval factor obtained in S3.1, and the preset first group of pulse repetition interval factors and the preset second group of pulse repetition interval factors are two preset agile pulse repetition interval factor values ​​for the target.

[0086] For all M radiation source targets, each target independently selects frequency actions (3 types) and pulse repetition interval actions (3 types). After combination, a single target generates 9 candidate responses, and the opponent's action space... There are a total of 9 candidate actions. Each candidate action corresponds to a defined set of post-response frequency factors and pulse repetition interval factors.

[0087] S3.4: Based on matrix elements The response frequency factor and pulse repetition interval factor are used to calculate our payoff value on the constructed leaf nodes of the game tree. The calculation formula is as follows:

[0088]

[0089] in, For interference performance, This is a power consumption cost item. This refers to the cost of switching solutions. , and These are the three weight coefficients, which satisfy... and Interference effectiveness item The calculation formula is as follows:

[0090]

[0091] in, The total number of radiation source targets. For the first Frequency factor of the response of a radiation source target For the first Initial values ​​of the target frequency factor for each radiation source. The preset frequency variation coefficient, The preset pulse repetition interval variation coefficient satisfies , For the first Pulse repetition interval factor after the response of a radiation source target. For the first Initial value of the pulse repetition interval factor for each radiation source target This is the power gain function, representing the impact of power allocation on interference effectiveness.

[0092] Power consumption cost item The calculation formula is as follows:

[0093]

[0094] in, The preset power consumption penalty coefficient, The total number of jammers. For the first One jammer, For matrix elements, Let be the total number of radiation source targets. Change the linear summation to a sum of squares to normalize the total power of each jammer. Under the conditions, No longer a constant: the more dispersed the power distribution, the smaller the sum of squares; the more concentrated the power distribution, the larger the sum of squares (maximum 1), thus retaining the punitive meaning.

[0095] Cost of switching solutions The calculation formula is as follows:

[0096]

[0097] in, The preset switching penalty coefficient, Let be a flattened one-dimensional vector of the current candidate power allocation scheme, with each element representing a different power allocation scheme. Arranged in order, This is a flattened one-dimensional vector representing the power allocation scheme executed in the previous decision cycle. This is for Euclidean distance calculation.

[0098] S4: Based on the candidate actions and pulse repetition interval actions selected by the opponent in the action space determined by the dynamic game model, the total parameter switching cost obtained by adding the preset frequency switching cost and pulse repetition interval switching cost respectively is used to calculate the opponent's payoff. This enables a quantitative evaluation of the overall gains and losses of the opponent when facing our interference and suppression, as well as the costs of their own agile evasion. It represents the trade-off behavior of the opponent's radiation source in dynamic confrontation, where the gains decrease as our interference effectiveness increases, and the additional costs incurred due to agile frequency and pulse repetition interval changes. This compensates for the shortcomings of static models in reflecting the opponent's immediate evasion response and its costs.

[0099] The specific steps for S4 are as follows:

[0100] S4.1: For the currently traversed leaf node in the extended game tree constructed in S3.1, read the value of our payoff calculated in S3.4. Interference performance terms generated during time synchronization .

[0101] S4.2: Determine the counterpart's parameter switching cost. Based on the candidate actions selected by the counterpart in the action space of S3.3 corresponding to the currently traversed leaf node, determine the frequency switching cost and the pulse repetition interval switching cost respectively.

[0102] If the other party chooses to maintain the current frequency factor, the cost of frequency switching is zero.

[0103] If the other party chooses to switch to the first preset backup frequency factor, the frequency switching cost is a preset constant.

[0104] If the other party chooses to switch to the second preset backup frequency factor, the frequency switching cost is a preset constant.

[0105] Similarly, if the other party chooses to maintain the current pulse repetition interval factor, the pulse repetition interval switching cost is zero.

[0106] If the other party chooses to switch to the preset first group of pulse repetition interval factors, the pulse repetition interval switching cost is a preset constant; if it chooses to switch to the preset second group of pulse repetition interval factors, the pulse repetition interval switching cost is a preset constant. The total parameter switching cost of the other party is obtained by adding the two preset groups together. .

[0107] S4.3: Interference effectiveness term obtained from S4.1 and total parameter switching cost determined from S4.2 Calculate the other party's profit value The other party's profit value This indicates that during dynamic countermeasures, the overall benefit to the opponent's radiation source decreases as our jamming effectiveness increases, and additional switching costs are incurred due to agile evasion maneuvers involving frequency and pulse repetition intervals. This reflects the opponent's dynamic trade-offs when facing our power suppression, resolving the problem that existing static models cannot characterize the opponent's immediate response and its costs. The calculation formula is as follows:

[0108]

[0109] in, The preset positive interference damage coefficient, This is the preset base profit value for the other party.

[0110] S5: Bind our payoff value to all leaf nodes of the game tree in the dynamic game model. and the other party's profit value The process involves selecting the action that maximizes the opponent's gain as the opponent's optimal response and recording the corresponding gain for our side. At our root node, we compare the gain values ​​corresponding to all our actions and select the action with the highest gain as the optimal power allocation scheme. This facilitates the generation of interference resource allocation schemes that can predict the opponent's dynamic frequency and pulse repetition interval agile evasion behavior, overcoming the shortcomings of traditional static methods in predicting the opponent's dynamic evasion. The specific steps of S5 are as follows:

[0111] S5.1: For all leaf nodes in the extended game tree constructed in S3.1, for each node whose action is performed by our side... and the other party's actions The game path consisting of 2 yields the payoff value calculated by S3.4 for each player. and the counterparty's profit value calculated by S4.3 and will Bind to this leaf node to complete the assignment of the game tree terminal payout.

[0112] S5.2: For a given power allocation action of our side Under the opponent's decision node corresponding to the action, traverse the opponent's action space in S3.3. For all candidate actions in step 2, compare the payoff value of each candidate action bound to the counterparty via S5.1. , choose to The opponent's action with the greatest impact is taken as the opponent's optimal response at that node, and the corresponding profit value for our side under that optimal response is recorded. This process simulates the rational behavior of the opposing force, after sensing our power allocation, to instantly choose a quick-change evasion strategy in terms of frequency and pulse repetition interval in order to maximize its own gains.

[0113] S5.3: At the root node of the game tree, i.e., our decision node, traverse our action space in S3.2. 1 All candidate power allocation actions For each Read the payoff value obtained in S5.2 under the opponent's optimal response. Compare the payoff values ​​corresponding to all candidate actions and select the action that maximizes the payoff value. This represents our globally optimal power allocation scheme under the equilibrium strategy.

[0114] The power allocation matrix corresponding to the optimal action is the interference resource allocation and scheduling scheme generated in the current cycle. Through sequential game theory, the dynamic frequency and pulse repetition interval agile behavior of the opponent's interference against us are predicted, which effectively overcomes the shortcomings of traditional static methods that lack the ability to predict the opponent's dynamic avoidance.

[0115] The power allocation matrix is ​​then converted into power allocation instructions that can be executed by the jamming resource management unit, updating the transmission power of each jammer for each radiation source target, thus completing this rescheduling.

[0116] Specifically, each element in the power allocation matrix is... The signal is converted into physical control commands executable by the interference resource management unit (IRM). These commands, using a 0-10V analog voltage signal (linearly mapped from 0 to full power) or a serial digital control word format, are sent to the corresponding jammer's solid-state power amplifier via the IRM's output interface. The power amplifier adjusts its gate bias voltage based on the received control signal, thereby changing the RF signal power output to the antenna array element, thus controlling the signal output to the antenna array element. The interference energy of each radiation source target is precisely delivered. Simultaneously, the matrix elements allocated in this operation... The actual response values ​​of the opponent's frequency factor and pulse repetition interval factor observed after execution are stored in the historical database as the basis for updating the situation matrix in the next cycle S1.

[0117] This invention generates a situation change index by calculating the absolute difference between the frequency factor and the pulse repetition interval factor in the situation matrix of the current period and the previous period, and compares it with the mutation judgment threshold. This enables dynamic rescheduling to be triggered as needed, thus changing the lag problem of fixed-cycle scheduling still using the old scheme in the early stage of parameter mutation.

[0118] Meanwhile, by combining the interference effectiveness term in our payout with the opponent's total parameter switching cost, we can calculate the opponent's payout, thus fully representing the sequential decision-making process of the opponent's immediate frequency and pulse repetition interval response triggered by our interference behavior. This makes up for the inadequacy of traditional static game matrices in expressing the temporal dependence of the two sides' behaviors.

[0119] Based on this, the action that maximizes the opponent's benefit value is selected as the optimal response at the opponent's decision node. Then, the global optimal power allocation scheme that maximizes our benefit value under the opponent's optimal response is determined at our root node. This scheme has the ability to predict the opponent's dynamic evasion behavior. After being converted into a power allocation command, the transmission power of each jammer to the radiation source target is updated in real time, which improves the timeliness and stability of jamming in complex confrontation environments.

[0120] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments, characterized in that, Includes the following steps: S1: Receive spatial electromagnetic signals through a wideband antenna array, extract the target parameters of each radiation source and the instantaneous available power value of each jammer, and perform normalization processing on each, then combine them to obtain the situation matrix; S2: Based on the situation matrix and the situation matrix of the previous period, calculate the situation change index, and compare the situation change index with the preset sudden change judgment threshold to determine the current electromagnetic environment state. S3: Using the current period's situation matrix generated by S1 as the initial information state of the game, construct a dynamic game model between our side and the opponent, and calculate our side's payoff value. S4: Calculate the opponent's payoff value by accumulating the preset frequency switching cost and pulse repetition interval switching cost of the candidate actions and pulse repetition interval actions determined by the dynamic game model, respectively; S5: Bind the payoff value of our side and the payoff value of the opponent to all leaf nodes of the game tree in the dynamic game model, select the action that maximizes the payoff value of the opponent as the opponent's optimal response and record the corresponding payoff value of our side, compare the payoff values ​​of our side for all our actions at our root node, and take the action that maximizes our payoff value as the optimal power allocation scheme.

2. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 1, characterized in that, The target parameters include the signal frequency value and the pulse repetition interval value. The signal frequency value, pulse repetition interval value, and instantaneous available power value can be normalized to obtain the frequency factor, pulse repetition interval factor, and available power factor.

3. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 2, characterized in that, The specific details of the normalization process are as follows: 1) Normalization of signal frequency values: Normalize the signal frequency values ​​according to the maximum adjustable range of its operating frequency band to obtain a frequency factor with a value range of 0 to 1. ; 2) Normalization of pulse repetition interval values: The pulse repetition interval values ​​are normalized according to the parameter range of the pulse repetition interval type to obtain a pulse repetition interval factor with a value range of 0 to 1. ; 3) Normalization of instantaneous available power: The instantaneous available power is normalized according to the rated maximum transmit power of the jammer to obtain an available power factor ranging from 0 to 1. .

4. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 1, characterized in that, The specific steps of S2 are as follows: S2.1: Read the situation matrix generated by S1 in the current cycle and the situation matrix of the previous cycle, and calculate the absolute value of the difference between the frequency factor and the pulse repetition interval factor between the current cycle and the previous cycle. S2.2: Calculate the situation change index based on the absolute value of the difference between the frequency factor of the current period and the previous period and the absolute value of the difference between the pulse repetition interval factor. This is used to quantify the degree of change in the electromagnetic countermeasures environment between two adjacent decision-making weeks; S2.3: Indicators of change in situation Compare with the preset mutation detection threshold: when When the mutation determination threshold is reached, it is determined that the current electromagnetic environment is in a state of stable change, and the current interference resource allocation scheme remains unchanged; when When the mutation determination threshold is reached, a sudden change in the target frequency value or pulse repetition interval value is determined.

5. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 1, characterized in that, The specific steps of S3 are as follows: S3.1: Based on the current period's situation matrix as the initial information state of the game, construct an extended game tree structure for the dynamic game model; S3.2: Determine our action space at the root node of the game tree constructed in S3.

1. ; S3.3: Based on the interference signal parameters that the other party can perceive after the power allocation scheme in S3.2 is implemented, determine the other party's action space. And determine the response frequency factor and pulse repetition interval factor by combining each candidate action of the radiation source target; S3.4: Calculate our payoff value on the constructed leaf nodes of the game tree based on the post-response frequency factor and the pulse repetition interval factor. The calculation formula is as follows: in, For interference performance, This is a power consumption cost item. The cost item for switching solutions, , and These are the three weighting coefficients.

6. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 5, characterized in that, The action space It consists of a set of interference resource power allocation schemes, and each candidate action Corresponding power allocation matrix, matrix elements Indicates the first The jammer was assigned to the first The power values ​​of the radiation source targets, among which For the first Available power factor of the jammer.

7. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 1, characterized in that, The specific steps of S4 are as follows: S4.1: For the currently traversed leaf node in the extended game tree constructed in S3.1, read the value of our payoff calculated in S3.

4. Interference performance terms generated during time synchronization ; S4.2: Based on the candidate actions selected by the counterpart in the action space of S3.3 corresponding to the currently traversed leaf node, determine the frequency switching cost and the pulse repetition interval switching cost respectively, and obtain the total parameter switching cost; S4.3: Based on the interference effectiveness term obtained in S4.1 and the total parameter switching cost determined in S4.2, calculate the counterparty's gain. The calculation formula is as follows: in, The preset positive interference damage coefficient, The preset base profit value for the other party. This represents the total cost of switching parameters.

8. The method for resource allocation and scheduling of ship-to-air electromagnetic countermeasures and jamming in complex combat environments according to claim 1, characterized in that, The specific steps of S5 are as follows: S5.1: For all leaf nodes in the extended game tree constructed in S3.1, for each node whose action is performed by our side... and the other party's actions The game path consisting of 2 yields the payoff value calculated by S3.4 for each player. and the counterparty's profit value calculated by S4.3 and will Bind to the leaf node to complete the assignment of the game tree terminal payout; S5.2: For a given power allocation action of our side Under the opponent's decision node corresponding to the action, traverse the opponent's action space in S3.

3. For all candidate actions in step 2, compare the payoff value of each candidate action bound to the counterparty via S5.

1. , choose to The opponent's maximum action is taken as the opponent's optimal response at the current node, and the corresponding profit value for our side under the current optimal response is recorded. S5.3: At the root node of the game tree, traverse our action space in S3.

2. 1 All candidate power allocation actions For each Read the value of our gain under the opponent's optimal response obtained through S5.2; Compare the payoff values ​​for all candidate actions and select the action that maximizes our payoff value. This represents our globally optimal power allocation scheme under the equilibrium strategy.

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