CN118152725B - Killing chain closure evaluation method based on equipment system model - Google Patents

Abstract

The present invention relates to the field of kill chain closure evaluation methods, and is a kill chain closure evaluation method based on an equipment system model. To calculate the kill chain closure probability according to known information, it is necessary to calculate the efficiency of the interaction relationship of each link in the chain, calculate the reconnaissance probability, the communication probability, the command probability, the strike probability and the kill chain closure time. According to the above calculation results, all initially generated kill chains are calculated, and then screening rules are designed. According to certain closure probability and closure time thresholds, screening is performed. The obtained screening results are effective kill chains. The collection of effective kill chains constitutes a kill network of a combat network. The method for calculating closure proposed by the present invention starts from an ADC effectiveness evaluation method, fully considers the influence of each combat link of the kill chain on closure, and constructs a set of clear kill chain closure calculation and analysis models, which can accurately reflect the closure of the combat network and provide guidance for deployment allocation and optimization.

Description

A kill chain closure evaluation method based on equipment system model

Technical Field

The present invention relates to the field of kill chain closure evaluation methods, and in particular to a kill chain closure evaluation method based on an equipment system model.

Background Art

The equipment system complex network modeling theory is a set of modeling theories for evaluating the combat effectiveness formed against enemy targets in specific strategic missions. In it, the various interactive relationships generated between entities in our equipment system, including reconnaissance, communication, command and control, and attack, are organized into a network composed of nodes and edges according to scope and capability attributes, which is called a combat network. The nodes in the network represent the equipment entities of both the enemy and us, and the edges represent the interactive relationship between two nodes.

The kill chain is a combat loop established in the combat network according to the OODA (Observation, Orientation, Decision, Action) cycle theory, which can form effective combat power against enemy targets. The premise for the formation of the kill chain is that the combat activities of the entire chain can be successfully closed. The network composed of the collection of successfully closed kill chains in the combat network is called a kill web. The quality of the closure performance of the kill chain is mainly reflected by the closure probability and closure time. Therefore, it is very important to construct an evaluation method for the closure of the kill chain based on combat activities and the kill chain model, which can directly affect the subsequent deployment and allocation of our battlefield equipment. However, there is currently a lack of clear and effective models for the calculation of closure. At the same time, many models do not fully consider the possible factors that may affect closure in combat activities, resulting in the difficulty of closure calculation results in guiding the optimization of subsequent deployment and allocation. First, with regard to the kill chain evaluation method, the current mainstream idea is based on various existing node basic indicators, and uses methods such as hierarchical analysis to aggregate and obtain corresponding evaluation results. The analysis and construction methods of basic indicators are unclear, and the designed basic indicators cannot fully describe the characteristics of the kill chain; in terms of closure analysis, the current main method is to conduct a specific analysis of each combat link, but lacks the consideration of connecting each combat link in series as a whole. At the same time, the effectiveness calculation of each combat activity only considers the capability attributes of our equipment, and lacks the calculation of the impact of the battlefield environment and the enemy's deployed equipment on our equipment. For this reason, the present invention proposes a kill chain closure evaluation method based on an equipment system model to solve the above problems. For this reason, the present invention proposes a kill chain closure evaluation method based on an equipment system model to solve the above problems.

Summary of the invention

The purpose of the present invention is to provide a kill chain closure evaluation method based on an equipment system model to solve the problems raised in the above background technology.

To achieve the above purpose, a kill chain closure evaluation method based on an equipment system model includes the following steps:

Step S1, calculating the kill chain closure probability based on known information requires calculating the effectiveness of the interaction relationship of each link in the chain, first calculating the reconnaissance effectiveness P(INV);

Step S2, calculating the communication performance P(COM);

Step S3, calculating the charge effectiveness P(DEC);

Step S4, calculating the attack effectiveness P (ATT);

Step S5, calculating the kill chain closing time;

Step S6, calculating all initially generated kill chains according to the above calculation results, and then designing screening rules to screen according to certain closing probability and closing time thresholds, and the obtained screening results are effective kill chains;

Step S7, after screening out effective kill chains, the set of effective kill chains constitutes the kill web of the combat network.

Preferred: The calculation method of availability P(A) is as follows:

Where _t1 is the mean time between failures and _t2 is the mean time between repairs. The reliability P(D) is calculated as follows:

Where t is the platform operation time. The calculation method of effectiveness P(C) is as follows: the effectiveness between the equipment is calculated based on the combat activities (reconnaissance, communication, command and control, and strike) completed by two adjacent equipment in the kill chain, and then the effectiveness of the kill chain is obtained.

Where _Pability is the kill chain effectiveness; n is the number of equipment in the kill chain; (P _INV ) _i,i+1 is the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment; (P _COM ) _i,i+1 is the communication effectiveness between the i-th equipment and the i+1-th equipment; (P _DEC ) _i,i+1 is the command and control effectiveness between the i-th equipment and the i+1-th equipment; (P _ATT ) _i,i+1 is the strike effectiveness between the i-th equipment and the i+1-th equipment.

Preferably: the ( _PINV ) _i,i+1 represents the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment in a kill chain, and represents the one-way interactive relationship in which the reconnaissance equipment i+1 performs reconnaissance on the enemy equipment i. It is the process in which our reconnaissance equipment obtains the enemy equipment information. The specific calculation method is as follows:

(1) Radar reconnaissance nodes detect ordinary targets. Radar detection uses the Neyman-Pearson criterion: the false alarm probability is constrained to a specified constant to maximize the reconnaissance effectiveness. When the square law is used for detection, the calculation method of the single reconnaissance effectiveness P _i is as follows:

Where BWA is the radar beam width; AZR is the radar scanning frequency; PRF is the pulse repetition frequency; N is the number of radar pulse accumulation; Thr is the detection threshold; Ψ is the mean signal-to-noise ratio of N samples; I(·,·) is the Pearson form of the incomplete gamma function, and the maximum radar range can be expressed as R _m ; δ ₁ is the target node anti-radar coefficient, and α is the environmental factor. The selection method is as follows:

Since a single reconnaissance cannot meet combat requirements, multiple reconnaissances are required. The corresponding reconnaissance effectiveness P(INV) calculation method is as follows:

Where N _inv is the number of multiple reconnaissances; p is the radar reconnaissance effectiveness benchmark value;

(2) When radar reconnaissance nodes detect stealth targets, the reconnaissance effectiveness model will be significantly affected when the target being reconnaissance is a stealth target. The specific calculation method of _Pi is as follows:

Where N is the number of radar pulse accumulation; Thr is the detection threshold; _SN is the signal-to-noise ratio; Θ is the radar reflection cross-sectional area of the target; ε is the stealth coefficient of the target node;

(3) When a radar reconnaissance node detects an obscured target, the maximum detection distance of the radar is affected as follows:

Where φ is the shielding coefficient of the target node; ε _k is the radar shielding angle; H _g is the target height;

(4) Radar reconnaissance nodes detect targets under interference. When the radar is interfered, taking the most commonly used interference foil in passive interference as an example, the maximum detection distance of the radar is affected as follows:

Where λ is the radar wavelength; is the interference intensity of the target node; R ₀ is the maximum detection distance of the radar when there is no interference;

(5) When a satellite-type reconnaissance node detects a target, the reconnaissance effectiveness calculation method is as follows:

Where k is the total number of target batches discovered by the reconnaissance satellite; _Nt is the total number of local incoming targets; _Di is the detection distance of the i-th batch of targets; ID is the detection range radius of the satellite to the ground; _Hi is the height of the i-th batch of target nodes; IH is the average height of the incoming targets; _p1 is the single detection probability, _p0 is the satellite reconnaissance effectiveness benchmark value; _ns is the number of detections; _δ2 is the target node anti-satellite system.

Preferably: the P(COM) represents the success probability of communication, and the specific calculation method is as follows:

Among them, n _com is the number of communications, is the c-th communication performance between two nodes, and the communication performance is represented by the communication transmission capacity p _ij .

Preferably: the specific calculation method of the communication transmission capacity p _ij is as follows:

Assuming that the two nodes in front and behind are S ₁ and S ₂ respectively, the communication interaction relationship between the two nodes can be calculated based on the coverage range d ^node , transmission rate v ^node , communication quality e ^node , communication capacity Ca ^node and information delay De ^node in the node communication modeling; the communication transmission capability P(COM) composed of five communication capability-related combat technical indicators is:

Where dis represents the relative distance between two nodes, and the communication quality between the two nodes can be calculated by the link budget P _RX . The specific algorithm is as follows:

Where P _TX is the transmit power of the transmitting antenna; G _TX is the transmit gain of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _FSPL is the signal free propagation loss model; c _T is the correction factor under different environments; R is the distance between the receiving and transmitting antennas; f is the operating frequency of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _atm is the loss of antenna power in the atmosphere; L _m is the loss of other factors. The communication capacity Ca is calculated as follows:

Where m represents the number of channels, B is the channel bandwidth; ρ _i is the signal-to-noise ratio of the i-th subchannel; λ _i is the power gain of the i-th subchannel. According to the definition of self-information, the information transmission capacity P(COM) of the edge representing the information sharing relationship is modeled as follows:

Where w _i is the weight of each communication capability; R _i (i＝1,2,3,4,5) are the membership functions of _pi respectively. Since _pi are quantitative indicators, they can be expressed by the following efficacy function:

Therefore, the information transmission capacity of the S-S edge is:

Preferably: the P(DEC) represents the success probability of the decision-making charging node charging, and the specific calculation method is as follows:

Assume that the accusing node is D ₁ and the accused node is S ₁ . This interactive relationship is represented by the accusing capability P(DEC). The specific calculation method is as follows:

The information processing capacity of D ₁ is denoted as E ₁ , and its self-information is used to model it:

Where R _i is the membership function of the three indicators of information processing capability: response time t _com , throughput T _hr , and accuracy Acc (i = 1, 2, 3). The modeling expression of the information transmission capability E ₂ of the interactive relationship is:

in,

The expressions modeled by this type of interaction are:

Preferred: P(ATT) represents the strike effectiveness. According to the strike equipment i and target equipment j of the chain, the strike type is divided into fire strike and electronic interference. The specific calculation method is as follows:

(1) The calculation process of the firepower strike relationship is as follows: Assume that the missile guidance error obeys the circular distribution law (σ _x = σ _y = σ), and its dispersion center is not located at the location of target j, that is, the probability density of its miss distance distribution is as follows:

The target damage probability is:

but:

Its approximate expression is as follows:

Among them, r ₀ is the distance between the center of the dispersion and the target position, σ is the covariance of the guidance error, R ₀ is the weapon damage radius, and P _W is the threat level. R ₀ is the property of the weapon equipment itself, σ is a fixed value for a single weapon, and r ₀ itself is related to the distance between the red and blue sides and the speed of the blue side's equipment. The calculation method of r ₀ is now established as follows:

r ₀ = r _h · r _v · r _b (1-34)

Among them, r _h and r _v are the components of r ₀ related to distance and speed, r _b is the radius of guidance error, and the upper and lower bounds of the attack distance are given as h _min ≤ r _eff ≤ h _max . The maneuvering speed of the target node v _tar is related to the maneuvering speed of the weapon v _node of our attack node:

Where μ is the target node invulnerability coefficient, k is the adjustment parameter, and P _W in (1-33) is related to the blue threat circle. If the red attack equipment is within the threat circle of multiple blue equipment, then:

N _W is the number of blue side equipment that threatens the current deployment position of the red side's strike equipment. The threat level of the i-th blue equipment to the red equipment is calculated as follows:

Where α is the environmental factor; β∈[1,10] is the integer weight coefficient indicating the importance of the target node; w is the threat weight of the target node; R _max is the maximum threat range of the blue equipment; R is the distance between the blue equipment and the red equipment;

(2) The calculation process of the electronic jamming relationship is as follows: Consider whether the enemy target T is within the jamming range of our attack node A:

Where D _rat is the interference power of the interference attack node; μ is the invulnerability coefficient of the target node; P _received is the received power of the target node; v _wea2 is the maneuvering speed of the interference attack node; τ is the warning time of the target node; v _tar is the maneuvering speed of the target node; and D _r is the interference radius of the interference attack node.

Preferably: the kill chain closure time represents the time measurement for closing all kill chains (kill nets), and the closure time calculation method is:

T＝T ₁ +T ₂ +T ₃ (2-1)

Where _T1 is the reconnaissance time; _T2 is the decision time; _T3 is the strike time. The calculation method of reconnaissance time is:

T ₁ = t _XF + n*t _scan (2-2)

Where t _XF is the maximum reaction time of the system equipment; n is the number of radar scans; t _scan is the radar scan interval. The decision time calculation method is:

Where _tc is the time taken for command and control decision; n is the number of equipment in the kill chain; _ti is the time taken for communication between adjacent equipment in the kill chain. When calculating the decision time, it is necessary to preset the decision time required for each level of command post as _ti (i＝1,2,...,S), S is the number of command posts, and the decision time calculation method is:

When calculating the strike time, it is necessary to consider the strike equipment preparation start time t ₁ ', the strike equipment maneuvering time to the strike position t' ₂ , the strike equipment launch time t' ₃ , and the flight time t' ₄ , where r _m is the distance between the deployment position of the strike equipment and the target, and v _wea1 is the movement speed of the strike equipment when launching the weapon.

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

The present invention provides a clear and detailed basic indicator calculation model for the closure analysis of the kill chain, and analyzes the performance calculation method corresponding to the interaction relationship of multiple nodes. Compared with the prior art, the calculation of closure pays more attention to the calculation of the kill chain as a whole, and comprehensively considers the kill chain closure time and the kill chain closure probability, from each node in the kill chain to each kill chain in the kill network to the kill network in the combat network, from the bottom to the top, an overall consideration is made. From the bottom, the present invention fully considers the possible situations of each combat link, and in the reconnaissance link, the difference in the effectiveness of different enemy and friendly nodes in the reconnaissance process and the influence of multiple reconnaissance on the closure probability are analyzed in detail; in Link budget is used in the communication link to characterize the communication quality, and the loss model can be used to distinguish the impact of different battlefield environments on communication efficiency; in the strike link, calculation models for hard kill (firepower strike) and soft kill (electronic interference) are constructed respectively. During the calculation process, the impact of the enemy's deployment distribution and capability attributes on the effectiveness of our firepower strike is also analyzed, and a threat circle calculation model is proposed to consider the impact of the joint threat circle composed of multiple enemy equipment. From the top level, the impact of the battlefield environment is considered in the calculation of each interactive relationship in the kill chain, such as environmental factors in the reconnaissance link, the strike link, and the loss correction parameters of the signal loss model in the communication link under different shielding conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a diagram of a closedness analysis model of a complex network kill chain of an equipment system of the present invention;

FIG2 is a flowchart of the closedness analysis of the complex network kill chain of the equipment system of the present invention.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Example

Please refer to FIG. 1-FIG. 2, which are a preferred embodiment of the present invention, a kill chain closure evaluation method based on an equipment system model, comprising the following steps:

Step S1, calculating the kill chain closure probability based on known information requires calculating the effectiveness of the interaction relationship of each link in the chain, first calculating the reconnaissance effectiveness P(INV);

Step S2, calculating the communication performance P(COM);

Step S3, calculating the charge effectiveness P(DEC);

Step S4, calculating the attack effectiveness P (ATT);

Step S5, calculating the kill chain closing time;

Step S6, calculating all initially generated kill chains according to the above calculation results, and then designing screening rules to screen according to certain closing probability and closing time thresholds, and the obtained screening results are effective kill chains;

Step S7, after screening out effective kill chains, the set of effective kill chains constitutes the kill web of the combat network.

The kill chain consists of multiple links such as reconnaissance, communication, command and control, and strike. Each link is completed by one or more equipment to complete the combat mission of the link, but each link of the kill chain cannot guarantee 100% success. For example, if the enemy target appears within the maximum reconnaissance range of our reconnaissance equipment, the radar will discover the target with a certain probability, and multiple detections may be required to increase the probability of successful reconnaissance. This is related to the functional attributes of the reconnaissance equipment itself and the distance of the target. If each link of the kill chain successfully implements this part of the function (i.e., the reconnaissance node detects the target, the communication node successfully transmits the reconnaissance information to the command and control node, the command and control node successfully processes the reconnaissance information to determine the node that performs the strike mission, the communication node successfully transmits the command and control information to the strike node, and the strike node strikes the target), then the kill chain is closed. The kill chain closure probability index P can be established based on the ADC loop model, P = P(A)·P(D)·P(C), that is, availability, reliability, and efficiency.

Among them, the calculation method of availability P(A) is as follows:

Where _t1 is the mean time between failures and _t2 is the mean time between repairs.

Furthermore, the reliability P(D) is calculated as follows:

Where t is the platform running time.

In this embodiment, the calculation method of the effectiveness P(C) is as follows: the effectiveness between the equipment is calculated according to the combat activities (reconnaissance, communication, command and control, and attack) completed by two adjacent equipment in the kill chain, and then the effectiveness of the kill chain is obtained.

Where _Pability is the kill chain effectiveness; n is the number of equipment in the kill chain; (P _INV ) _i,i+1 is the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment; (P _COM ) _i,i+1 is the communication effectiveness between the i-th equipment and the i+1-th equipment; (P _DEC ) _i,i+1 is the command and control effectiveness between the i-th equipment and the i+1-th equipment; (P _ATT ) _i,i+1 is the strike effectiveness between the i-th equipment and the i+1-th equipment.

Furthermore, (P _INV ) _i,i+1 represents the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment in a kill chain, which indicates the one-way interactive relationship between the reconnaissance equipment i+1 and the enemy equipment i. It is the process of our reconnaissance equipment obtaining the enemy equipment information. The specific calculation method is as follows:

(1) Radar reconnaissance nodes detect ordinary targets. Radar detection uses the Neyman-Pearson criterion: the false alarm probability is constrained to a specified constant to maximize the reconnaissance effectiveness. When the square law is used for detection, the calculation method of the single reconnaissance effectiveness P _i is as follows:

Where BWA is the radar beam width; AZR is the radar scanning frequency; PRF is the pulse repetition frequency; N is the number of radar pulse accumulation; Thr is the detection threshold; Ψ is the mean signal-to-noise ratio of N samples; I(·,·) is the Pearson form of the incomplete gamma function, and the maximum radar range can be expressed as R _m ; δ ₁ is the target node anti-radar coefficient, and α is the environmental factor. The selection method is as follows:

Since a single reconnaissance cannot meet combat requirements, multiple reconnaissances are required. The corresponding reconnaissance effectiveness P(INV) calculation method is as follows:

Where N _inv is the number of reconnaissance attempts; p is the baseline value of radar reconnaissance effectiveness.

(2) When radar reconnaissance nodes detect stealth targets, the reconnaissance effectiveness model will be significantly affected when the target being reconnaissance is a stealth target. The specific calculation method of _Pi is as follows:

Where N is the number of radar pulse accumulation; Thr is the detection threshold; _SN is the signal-to-noise ratio; Θ is the radar reflection cross-sectional area of the target; ε is the stealth coefficient of the target node.

(3) When a radar reconnaissance node detects an obscured target, the maximum detection distance of the radar is affected as follows:

Where φ is the target node shielding coefficient; ε _k is the radar shielding angle; H _g is the target height.

(4) Radar reconnaissance nodes detect targets under interference. When the radar is interfered, taking the most commonly used interference foil in passive interference as an example, the maximum detection distance of the radar is affected as follows:

Where λ is the radar wavelength; is the interference intensity of the target node; R ₀ is the maximum detection distance of the radar when there is no interference.

(5) When a satellite-type reconnaissance node detects a target, the calculation method of the reconnaissance effectiveness is as follows when the reconnaissance equipment is a satellite.

Where k is the total number of target batches discovered by the reconnaissance satellite; _Nt is the total number of local incoming targets; _Di is the detection distance of the i-th batch of targets; ID is the detection range radius of the satellite to the ground; _Hi is the height of the i-th batch of target nodes; IH is the average height of the incoming targets; _p1 is the single detection probability, _p0 is the satellite reconnaissance effectiveness benchmark; _ns is the number of detections; _δ2 is the target node anti-satellite coefficient.

In this embodiment, P(COM) represents the success probability of communication, and the specific calculation method is as follows:

Among them, n _com is the number of communications, is the c-th communication efficiency between two nodes. The communication efficiency is represented by the communication transmission capacity p _ij . The specific calculation method is as follows:

Assuming that the two nodes in front and behind are S ₁ and S ₂ respectively, the communication interaction relationship between the two nodes can be calculated based on the coverage range d ^node , transmission rate v ^node , communication quality e ^node , communication capacity Ca ^node and information delay De ^node in the node communication modeling; the communication transmission capability P(COM) composed of five communication capability-related combat technical indicators is:

Where dis represents the relative distance between two nodes, and the communication quality between the two nodes can be calculated by the link budget P _RX . The specific algorithm is as follows:

Where P _TX is the transmit power of the transmitting antenna; G _TX is the transmit gain of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _FSPL is the signal free propagation loss model; c _T is the correction factor under different environments; R is the distance between the receiving and transmitting antennas; f is the operating frequency of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _atm is the loss of antenna power in the atmosphere; L _m is the loss of other factors.

In this embodiment, the communication capacity Ca is calculated as follows:

Where m represents the number of channels, B is the channel bandwidth; ρ _i is the signal-to-noise ratio of the i-th subchannel; λ _i is the power gain of the i-th subchannel. According to the definition of self-information, the information transmission capacity P(COM) of the edge representing the information sharing relationship is modeled as follows:

Where w _i is the weight of each communication capability; R _i (i＝1,2,3,4,5) are the membership functions of _pi respectively. Since _pi are quantitative indicators, they can be expressed by the following efficacy function:

Therefore, the information transmission capacity of the S-S edge is:

In this embodiment, P(DEC) represents the success probability of the decision-making charge node charge, and the specific calculation method is as follows:

Assume that the accusing node is D ₁ and the accused node is S ₁ . This interactive relationship is represented by the accusing capability P(DEC). The specific calculation method is as follows:

The information processing capacity of D ₁ is denoted as E ₁ , and its self-information is used to model it:

Where R _i is the membership function of the three indicators of information processing capability: response time t _com , throughput T _hr , and accuracy Acc (i=1, 2, 3). Based on the above modeling of information transmission capability, the modeling expression of the information transmission capability E ₂ of the interactive relationship is:

in,

We can get expressions for modeling this type of interaction relationship:

In this embodiment, P(ATT) represents the strike effectiveness. According to the strike equipment i and the target equipment j of the chain, the strike type is divided into fire strike and electronic interference. The specific calculation method is as follows:

(1) Fire strike relationship. Fire strike relationship mainly refers to the process in which the damage nodes in our combat network attack the enemy target T to make it completely or partially lose its military or economic value. Generally speaking, the attacked enemy targets include enemy weapons such as aircraft, warships, tanks, and infrastructure such as fortifications, shelters, airports, ports, and transportation hubs. Sometimes, fire strikes are also carried out on enemy troops and personnel. This type of interactive relationship is characterized by the damage probability. The specific calculation method is as follows:

First, assume that the missile guidance error obeys the circular distribution law (σ _x =σ _y =σ).

Its scatter center is not located at the location of target j, that is, the probability density of its miss amount distribution is as follows:

The target damage probability is:

but:

Through certain mathematical derivation, the approximate expression is as follows:

Where _r0 is the distance between the center of the scatter and the target position, σ is the covariance of the guidance error, _R0 is the weapon damage radius, _PW is the threat level, _R0 is the attribute of the weapon equipment itself, σ is a fixed value for a single weapon, _r0 itself is related to the distance between the red and blue sides and the speed of the blue side's equipment. The calculation method of _r0 is now established as follows:

r ₀ = r _h · r _v · r _b (1-34)

r _h , r _v are the components of r ₀ related to distance and speed, and r _b is the radius of guidance error. Given the upper and lower bounds of the strike distance h _min ≤ _{r eff} ≤ h _max , the maneuvering speed of the target node v _tar and the maneuvering speed of our weapon attacking node v _node are:

Where μ is the target node invulnerability coefficient, k is the adjustment parameter, and P _W in (1-33) is related to the blue threat circle. If the red attack equipment is within the threat circle of multiple blue equipment, then:

N _W is the number of blue side equipment that threatens the current deployment position of the red side's strike equipment. The threat level of the i-th blue equipment to the red equipment is calculated as follows:

Where α is the environmental factor; β∈[1,10] is the integer weight coefficient indicating the importance of the target node; w is the threat weight of the target node; R _max is the maximum threat range of the blue equipment; and R is the distance between the blue equipment and the red equipment.

(2) Electronic interference relationship. Electronic interference relationship mainly refers to our ability to use electronic equipment to effectively reduce or destroy the enemy target T's ability to use various electronic equipment to conduct battlefield reconnaissance, combat command, communication and liaison and other combat activities. Electronic interference can be divided into two types: radar interference and communication interference. The indicators related to radar interference mainly include: suppression of enemy radar (interference rate), effective suppression (interference) time, enemy early warning reconnaissance distance reduction ratio, etc. Technical indicators include antenna gain and interference power, etc. The main indicator related to communication interference is the false positive rate. The main influencing factor P(ATT) in calculating the false positive rate is the signal-to-noise ratio (inside the communication receiver input terminal and outside the communication receiver input terminal). The suppression rate (suppression coefficient) can also be used to measure the communication interference capability. The modeling of the electronic interference capability of the strike node abstracted by the electronic interference relationship takes into account the suppression rate on the one hand, and whether the enemy target T is within the interference range of our strike node A on the other hand:

Where D _rat is the interference power of the interference attack node; μ is the invulnerability coefficient of the target node; P _received is the received power of the target node; v _wea2 is the maneuvering speed of the interference attack node; τ is the warning time of the target node; v _tar is the maneuvering speed of the target node; and D _r is the interference radius of the interference attack node.

In this embodiment, the kill chain closure time represents the time measurement for closing all kill chains (kill nets). Closing time calculation method:

T＝T ₁ +T ₂ +T ₃ (2-1)

Where _T1 is the reconnaissance time; _T2 is the decision time; _T3 is the strike time.

Among them, the calculation method of reconnaissance time is: T ₁ = t _XF + n*t _scan (2-2)

Where t _XF is the maximum reaction time of the system equipment; n is the number of radar scans; t _scan is the radar scan interval. Generally speaking, the reconnaissance time is mainly the information processing and fusion time. In practical applications, the reconnaissance time is directly given.

Further, the decision time calculation method is:

Where _tc is the time taken for command and control decision; n is the number of equipment in the kill chain; _ti is the time taken for communication between adjacent equipment in the kill chain. When calculating the decision time, it is necessary to preset the decision time required for each level of command post as _ti (i＝1,2,...,S), and S is the number of command posts. So the decision time calculation method is:

When calculating the strike time, it is necessary to consider the strike equipment preparation start time t ₁ ', the strike equipment maneuvering time to the strike position t' ₂ , the strike equipment launch time t' ₃ , and the flight time t' ₄ , where r _m is the distance between the deployment position of the strike equipment and the target, and v _wea1 is the movement speed of the strike equipment when launching the weapon.

In this embodiment, the kill chain closure probability is first calculated based on the above known information. It is necessary to calculate the efficiency of the interaction relationship of each link in the chain. The reconnaissance efficiency P(INV) is first calculated, and the types of target nodes and reconnaissance nodes are first determined. For example, the reconnaissance equipment is an active radar, the target is an ordinary target without obstruction and stealth, and the reconnaissance node is not interfered with in the battlefield environment. Then, the equipment capability attribute parameters mounted on the reconnaissance equipment (such as BWA radar beam width, AZR radar scanning frequency, PRF pulse repetition frequency, etc.) are substituted into formula (1-4) to calculate the single reconnaissance efficiency. According to the calculation result and the actual situation, formula (1-5) is considered to calculate the corresponding probability of multiple reconnaissance. When the reconnaissance node and the target node are in different situations, they are substituted into formulas (1-6) to (1-9) respectively. After the calculation is completed, the number of multiple reconnaissances of each chain is recorded to facilitate the calculation of the kill chain closure time.

Furthermore, the communication efficiency P(COM) is calculated, and the basic communication capacity of the node is calculated according to formulas (1-11) to (1-15). If the known data cannot provide communication quality and communication capacity, the communication quality and communication capacity must be calculated according to formulas (1-16) and (1-17), and then the calculated basic communication capacity is aggregated according to formulas (1-18) to (1-20) to obtain the communication efficiency.

Going further, the command and control effectiveness P(DEC) can be calculated according to equations (1-21) to (1-29). The prerequisite for this step is to consider the battlefield environment as a multi-level command and control environment, that is, there are multiple command and control nodes, and the command and control nodes are divided into multiple levels, and each level is connected according to the command and control relationship. If the multi-level command and control structure is not considered in the modeling process, the probability can be set as appropriate.

Furthermore, to calculate the strike effectiveness P(ATT), first determine the type of the strike node. If it is an electronic interference type, directly calculate it according to formulas (1-39) to (1-41); if it is a firepower strike type node, first traverse the enemy nodes according to formulas (1-37) and (1-38), calculate the threat level of the strike node, and substitute the results into formulas (1-30) to (1-36) to calculate the strike effectiveness. Finally, combine the above calculation results and substitute them into formulas (1-1) to (1-3) to obtain the kill chain closure probability, and then calculate the kill chain closure time, considering the calculation of multiple reconnaissance times. , and the basic capability information of each node on the kill chain are substituted into formulas (2-1) to (2-5) to obtain the result. Then, all the initially generated kill chains are calculated according to the above calculation steps, and then the screening rules are designed. Screening is performed according to a certain closure probability and closure time threshold. The screening result is the effective kill chain. If no kill chain meets the requirements after screening, it means that the battlefield deployment is poor, and it is impossible to form effective combat effectiveness against enemy targets and the closure cannot be calculated. It is necessary to consider optimizing the deployment. After screening and obtaining effective kill chains, the collection of effective kill chains constitutes the kill network of the combat network.

The above content is a further detailed description of the present invention in combination with specific implementation methods. It cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, some simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as belonging to the scope of protection determined by the claims submitted for the present invention.

Claims (2)

1. A kill chain closure evaluation method based on an equipment system model, characterized in that it comprises the following steps: Step S1, calculating the kill chain closure probability based on known information requires calculating the effectiveness of the interaction relationship of each link in the chain, first calculating the reconnaissance effectiveness P(INV); Step S2, calculating the communication performance P(COM); Step S3, calculating the charge effectiveness P(DEC); Step S4, calculating the attack effectiveness P (ATT); Step S5, calculating the kill chain closing time; Step S6, calculating all initially generated kill chains according to the above calculation results, and then designing screening rules to screen according to certain closing probability and closing time thresholds, and the obtained screening results are effective kill chains; Step S7, after screening out effective kill chains, the set of effective kill chains constitutes a kill net of the combat network; When all links of the kill chain successfully achieve this part of the function, the kill chain is called closed. Based on the ADC loop model, the kill chain closure probability index P is established, P = P(A)·P(D)·P(C); The calculation method of availability P(A) is as follows: Where _t1 is the mean time between failures and _t2 is the mean time between repairs. The reliability P(D) is calculated as follows: Where t is the platform operation time. The calculation method of effectiveness P(C) is as follows: the effectiveness between the equipment is calculated according to the combat activities completed by two adjacent equipment in the kill chain, and then the effectiveness of the kill chain is obtained. Where n is the number of equipment in the kill chain; (P _INV ) _i,i+1 is the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment; (P _COM ) _i,i+1 is the communication effectiveness between the i-th equipment and the i+1-th equipment; (P _DEC ) _i,i+1 is the command and control effectiveness between the i-th equipment and the i+1-th equipment; (P _ATT ) _i,i+1 is the strike effectiveness between the i-th equipment and the i+1-th equipment; The ( _PINV ) _i,i+1 represents the reconnaissance effectiveness between the i-th equipment and the i+1-th equipment in a kill chain, indicating the one-way interactive relationship between the reconnaissance equipment i+1 and the enemy equipment i. It is the process of our reconnaissance equipment obtaining the enemy equipment information. The specific calculation method is as follows: (1) Radar reconnaissance nodes detect ordinary targets. Radar detection uses the Neyman-Pearson criterion: the false alarm probability is constrained to a specified constant to maximize the reconnaissance effectiveness. When the square law is used for detection, the calculation method of the single reconnaissance effectiveness P _i is as follows: Where BWA is the radar beam width; AZR is the radar scanning frequency; PRF is the pulse repetition frequency; N is the number of radar pulse accumulation; Thr is the detection threshold; Ψ is the mean signal-to-noise ratio of N samples; I(·,·) is the Pearson form of the incomplete gamma function, and the maximum range of the radar can be expressed as R _max ; δ ₁ is the target node anti-radar coefficient, and α is the environmental factor. The selection method is as follows: Since a single reconnaissance cannot meet combat requirements, multiple reconnaissances are required. The corresponding reconnaissance effectiveness P(INV) calculation method is as follows: Where N _inv is the number of multiple reconnaissances; p is the radar reconnaissance effectiveness benchmark value; (2) When radar reconnaissance nodes detect stealth targets, the reconnaissance effectiveness model will be significantly affected when the target being reconnaissance is a stealth target. The specific calculation method of _Pi is as follows: Where N is the number of radar pulse accumulation; Thr is the detection threshold; _SN is the signal-to-noise ratio; Θ is the radar reflection cross-sectional area of the target; ε is the stealth coefficient of the target node; (3) When a radar reconnaissance node detects an obscured target, the maximum detection distance of the radar is affected as follows: Where φ is the shielding coefficient of the target node; ε _k is the radar shielding angle; H _g is the target height; (4) Radar reconnaissance nodes detect targets under interference. When the radar is interfered, taking the most commonly used interference foil in passive interference as an example, the maximum detection distance of the radar is affected as follows: Where λ is the radar wavelength; is the interference intensity of the target node; R ₀ is the maximum detection distance of the radar when there is no interference; (5) When a satellite-type reconnaissance node detects a target, the reconnaissance effectiveness calculation method is as follows: Where k is the total number of target batches discovered by the reconnaissance satellite; _Nt is the total number of local incoming targets; _Di is the detection distance of the i-th batch of targets; ID is the detection range radius of the satellite to the ground; _Hi is the height of the i-th batch of target nodes; IH is the average height of the incoming targets; _p1 is the single detection probability, _p0 is the satellite reconnaissance efficiency benchmark; _ns is the number of detections; _δ2 is the target node anti-satellite system; The P(COM) represents the success probability of communication, and the specific calculation method is as follows: Among them, n _com is the number of communications, is the c-th communication efficiency between two nodes, and the communication efficiency is represented by the communication transmission capacity p _ij ; The specific calculation method of the communication transmission capacity p _ij is as follows: Assuming that the two nodes in front and behind are S ₁ and S ₂ respectively, the communication interaction relationship between the two ^nodes can be calculated based on the communication transmission capability P(COM) composed of five communication capability-related combat technical indicators, namely, coverage range d ^node , transmission rate v _c ^node , communication quality e _c ^node , communication capacity _{Ca c} ^node , and information delay Dec node in the node communication modeling: Where dis represents the relative distance between two nodes, and the communication quality between the two nodes can be calculated by the link budget P _RX . The specific algorithm is as follows: Where P _TX is the transmit power of the transmitting antenna; G _TX is the transmit gain of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _FSPL is the signal free propagation loss model; c _T is the correction factor under different environments; R is the distance between the receiving and transmitting antennas; f is the operating frequency of the transmitting antenna; G _RX is the receive gain of the receiving antenna; L _atm is the loss of antenna power in the atmosphere; L _m is the loss of other factors. The communication capacity Ca _c is calculated as follows: Where m represents the number of channels, B is the channel bandwidth; ρ _i is the signal-to-noise ratio of the i-th subchannel; λ _i is the power gain of the i-th subchannel. According to the definition of self-information, the information transmission capacity P(COM) of the edge representing the information sharing relationship is modeled as follows: Where w _i is the weight of each communication capability; R _i (i＝1,2,3,4,5) are the membership functions of _pi respectively. Since _pi are quantitative indicators, they can be expressed by the following efficacy function: Therefore, the information transmission capacity of the S-S edge is: The P(DEC) represents the success probability of the decision-making charge node charge, and the specific calculation method is as follows: Assume that the accusing node is D ₁ and the accused node is S ₁ . This interactive relationship is represented by the accusing capability P(DEC). The specific calculation method is as follows: The information processing capacity of D ₁ is denoted as E ₁ , and its self-information is used to model it: Where R _i is the membership function of the three indicators of information processing capability: response time t _com , throughput T _hr , and accuracy Acc (i = 1, 2, 3). The modeling expression of the information transmission capability E ₂ of the interactive relationship is: in, The expressions modeled by this type of interaction are: P(ATT) represents the strike effectiveness. According to the strike equipment i and target equipment j of the chain, the strike type is divided into fire strike and electronic interference. The specific calculation method is as follows: (1) The calculation process of the firepower strike relationship is as follows: Assume that the missile guidance error obeys the circular distribution law (σ _x = σ _y = σ), and its dispersion center is not located at the location of target j, that is, the probability density of its miss distance distribution is as follows: The target damage probability is: but: Its approximate expression is as follows: Where _r0 is the distance between the center of the scatter and the target position, σ is the covariance of the guidance error, _R0 is the weapon damage radius, _PW is the threat level, _R0 is the attribute of the weapon equipment, σ is a fixed value for a single weapon, _r0 itself is related to the distance between the red and blue sides and the speed of the blue side's equipment. The calculation method of _r0 is now established as follows: r ₀ = r _h · r _v · r _b (1-34) Among them, r _h and r _v are the components of r ₀ related to distance and speed, r _b is the radius of guidance error, giving the upper and lower bounds of the attack distance h _min ≤ r _eff ≤ h _max , and the maneuvering speed of the target node v _tar and the maneuvering speed of the weapon of our attack node v _node , Where μ is the target node invulnerability coefficient, k is the adjustment parameter, and P _W in (1-33) is related to the blue threat circle. If the red attack equipment is within the threat circle of multiple blue equipment, then: N _W is the number of blue side equipment that threatens the current deployment position of the red side's strike equipment. The threat level of the i-th blue equipment to the red equipment is calculated as follows: Where α is the environmental factor; β∈[1,10] is the integer weight coefficient indicating the importance of the target node; w is the threat weight of the target node; R′ _max is the maximum threat range of the blue equipment; R' is the distance between the blue equipment and the red equipment; (2) The calculation process of the electronic jamming relationship is as follows: Consider whether the enemy target T is within the jamming range of our attack node A: Where D _rat is the interference power of the interference attack node; μ is the invulnerability coefficient of the target node; P _received is the received power of the target node; v _wea2 is the maneuvering speed of the interference attack node; τ is the warning time of the target node; v _tar is the maneuvering speed of the target node; and D _r is the interference radius of the interference attack node. 2. According to claim 1, a kill chain closure evaluation method based on an equipment system model is characterized in that: the kill chain closure time represents the time measurement of all kill chain closures, and the closure time calculation method is: T＝T ₁ +T ₂ +T ₃ (2-1) Where _T1 is the reconnaissance time; _T2 is the decision time; _T3 is the strike time. The calculation method of reconnaissance time is: T ₁ ＝t _XF +n _p *t _scan (2-2) Where _tXF is the maximum reaction time of the system equipment; _np is the number of radar scans; _tscan is the radar scan interval. The decision time calculation method is: Where _tc is the time taken for command and control decision; n is the number of equipment in the kill chain; _ti is the time taken for communication between adjacent equipment in the kill chain. When calculating the decision time, it is necessary to preset the decision time required for each level of command post as _ti (i＝1,2,...,S), S is the number of command posts, and the decision time calculation method is: When calculating the strike time, it is necessary to consider the strike equipment preparation start time t′ ₁ , the strike equipment maneuvering time to the strike position t′ ₂ , the strike equipment launch time t′ ₃ , and the flight time t′ ₄ , where r _m is the distance between the deployment position of the strike equipment and the target, and v _wea 1 is the movement speed of the strike equipment when launching the weapon.