Firepower distribution method based on aerial target threat assessment
By adopting the entropy weight method and TOPSIS method in target threat assessment and firepower allocation, the problems of strong subjectivity of target threat assessment and poor firepower allocation in the prior art are solved, and more efficient firepower resource utilization and combat effectiveness are achieved.
Patent Information
- Application Number
- CN202510304810.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-14
- Publication Date
- 2025-06-27
AI Technical Summary
In the prior art, target threat assessment relies on expert systems and is highly subjective, and the firepower distribution algorithm and target threat assessment fail to effectively combine, resulting in poor firepower distribution effect.
The entropy weight method is used to calculate the weight of the threat degree evaluation index, and the threat degree ranking of the air targets is combined with the TOPSIS method, and the matching allocation of the fire unit and the target is performed based on the threat degree ranking, firepower allocation conditions and shooting favorability.
Through effective target threat assessment and firepower allocation, the utilization efficiency of firepower resources is improved, the firepower damage effect is enhanced, and the optimal combat effectiveness is achieved.
Smart Images
Figure CN120218422A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of target threat assessment and firepower allocation, and particularly to a firepower allocation method based on air target threat assessment. Background Art
[0002] Target threat assessment and firepower allocation are information fusion technologies for battlefield situation judgment and element perception, and are important decision-making bases for the command center to make action decisions. In the current complex battlefield environment, adopting a reasonable target threat assessment and firepower allocation plan is beneficial to the effective allocation of weapon system resources, can improve the fire damage effect, and can achieve the best combat effectiveness;
[0003] In target threat assessment, most traditional sorting algorithms use expert systems, which are highly subjective and cannot fully utilize the original data to reflect the objective truth; in firepower allocation methods, most firepower allocation algorithms are not effectively combined with target threat assessment, and the best firepower allocation effect cannot be achieved. Summary of the Invention
[0004] The present disclosure aims to provide a firepower allocation method based on air target threat assessment that can effectively sort the threat levels of air targets and combine the firepower allocation algorithm with target threat assessment.
[0005] To achieve the above object, the technical solution adopted by the present disclosure is as follows:
[0006] A firepower allocation method based on air target threat assessment, comprising:
[0007] Obtaining threat degree evaluation indicators of air evaluation objects, and constructing a quantization model of the evaluation indicators based on the threat degree evaluation indicators;
[0008] Establishing a decision matrix of the quantization models of the evaluation indicators of multiple air evaluation objects;
[0009] Calculating the weights of the evaluation indicators by using the entropy weight method;
[0010] Based on the weights of the evaluation indicators, sorting the threat degrees of multiple air evaluation objects by using the TOPSIS method;
[0011] Based on the threat degree ranking of the evaluation objects, firepower allocation conditions, and the shooting advantages of firepower units, matching the selected firepower units with the selected evaluation objects, and assigning strike targets to the firepower units.
[0012] Optionally, the threat degree evaluation indicators of the air evaluation objects include flight distance, flight speed, flight altitude, course angle, time to fly over, and / or target type.
[0013] Optionally, constructing a quantization model of the evaluation index based on the threat degree evaluation index includes:
[0014] The flight distance is the projection distance of the line connecting the center of the protection area and the aerial target on the horizontal plane. The closer the flight distance, the greater the threat degree of the target;
[0015] The flight speed is obtained from the information of the aerial situation. The greater the target speed, the greater the threat degree;
[0016] The flight altitude is the difference between the altitude of the aerial target and the altitude of our defense position. The lower the target flight altitude, the greater the threat degree;
[0017] The course angle is the angle between the line connecting the projection point of the aerial target on the horizontal plane to the center of the protection area and the projection of the aerial target's course. The smaller the angle, the stronger the target's attack intention and the greater the threat degree;
[0018] The approaching time is the time when the target approaches our defense position. The smaller the approaching time, the greater the threat degree.
[0019] The target type index is a qualitative index. The index quantization model is constructed by the expert scoring method. The higher the score, the greater the threat degree.
[0020] Optionally, establishing a decision matrix of the quantization model of the evaluation index for multiple aerial evaluation objects, and calculating the weight of the evaluation index by the entropy weight method includes:
[0021] Establishing an original matrix based on the evaluation index of multiple aerial evaluation objects,
[0022] Establishing a normalized decision matrix based on the original matrix;
[0023] Based on the normalized decision matrix, obtaining the standardized index value of each evaluation index.
[0024] Optionally, the standardized index value includes benefit type index and cost type index;
[0025] For the benefit type index:
[0026]
[0027] For the cost type index:
[0028]
[0029] Where, max(a ij ) and min(a ij ) are respectively the maximum and minimum values of the j-th index in the original matrix, and a ij represents the value of the j-th evaluation index of the i-th evaluation object.
[0030] Optionally, calculating the weight of the evaluation index by using the entropy weight method includes
[0031] Determining the proportion of each evaluation object in the corresponding index;
[0032] Determining the entropy value of the evaluation index;
[0033] Determining the difference coefficient of the evaluation index;
[0034] Determining the entropy weight of the evaluation index.
[0035] Optionally, based on the weight of the evaluation index, sorting the threat levels of multiple aerial evaluation objects by using the TOPSIS method includes
[0036] Constructing a weighted normalized decision matrix based on the normalized decision matrix and the entropy weight;
[0037] Determining the ideal solution and the negative ideal solution;
[0038] Determining the closeness of the evaluation object to the optimal solution and the worst solution;
[0039] Determining the closeness of each evaluation object to the optimal solution;
[0040] Sorting the threat levels of multiple evaluation objects based on the closeness to the optimal solution.
[0041] Optionally, the steps of determining the ideal solution and the negative ideal solution include:
[0042] In the weighted normalized decision matrix, the maximum values in each column of evaluation indexes form the ideal solution, and the minimum values in each column of evaluation indexes form the negative ideal solution.
[0043] Optionally, in the steps of determining the closeness of the evaluation object to the optimal solution and the worst solution, calculate the Euclidean distances from the attribute values of each evaluation object to the ideal solution and the negative ideal solution.
[0044] Optionally, in the steps of sorting the threat levels of multiple evaluation objects based on the closeness to the optimal solution, the greater the closeness, the greater the threat level of the evaluation object.
[0045] The present disclosure first conducts threat assessment on the target, providing a reliable basis for subsequent firepower allocation. Among them, in the threat assessment, the entropy weight method is used to calculate the index weight, avoiding the subjective influence of human factors on the evaluation results, and the TOPSIS method is used to eliminate the influence of different index dimensions, making the evaluation results closer to the actual situation. In the firepower allocation, based on the threat level ranking of the targets, a reasonable and feasible firepower allocation method is formed according to the working status, killing area, ammunition reserve, allocated target situation and shooting favorability of the firepower units. BRIEF DESCRIPTION OF THE DRAWINGS
[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.
[0047] Figure 1 It is a schematic diagram of the method principle of the target threat assessment method of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0048] The following will elaborate on the preferred embodiments of the present disclosure in conjunction with the drawings, so that the advantages and features of the present disclosure can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present disclosure.
[0049] Refer to Figure 1 As shown, a firepower allocation method based on air target threat assessment includes:
[0050] S1. Obtain the threat degree evaluation index of the air evaluation object, and construct a quantization model of the evaluation index based on the threat degree evaluation index; specifically including
[0051] 1) Establish a target threat evaluation index system; in order to fully reflect the threat degree of the incoming target, the threat degree evaluation index of the air evaluation object includes flight distance, flight speed, flight altitude, course angle, approaching time, and / or target type, and establish a target threat evaluation index system;
[0052] 2) Construct a quantization model of the evaluation index;
[0053] The flight distance is the projection distance on the horizontal plane of the line connecting the center of the protection area and the air target. The closer the flight distance, the greater the threat degree of the target;
[0054] The flight speed is obtained from the information of the air situation. The greater the target speed, the greater the threat degree;
[0055] The flight altitude is the difference between the altitude of the air target and the altitude of our defense position. The lower the target flight altitude, the greater the threat degree;
[0056] The course angle is the angle between the line connecting the projection point of the air target on the horizontal plane to the center of the protection area and the projection of the air target course. The smaller the angle, the stronger the target attack intention and the greater the threat degree;
[0057] The approaching time is the time when the target approaches our defense position. The smaller the approaching time, the greater the threat degree.
[0058] The target type index is a qualitative index, and the index quantization model is constructed by the expert scoring method. The higher the score, the greater the threat level.
[0059] Among them, the evaluation indexes are divided into two types: benefit type indexes and cost type indexes. For benefit type indexes, the greater the attribute value, the greater the threat level. For cost type indexes, the smaller the attribute value, the greater the threat level.
[0060] S2. Establish a decision matrix for the quantization model of the evaluation indexes of multiple air evaluation objects, specifically including:
[0061] 1) Establish an original matrix based on the evaluation indexes of multiple air evaluation objects.
[0062] Form an original data matrix A with m evaluation objects and n evaluation indexes. Among them, a ij represents the value of the j-th evaluation index of the i-th evaluation object.
[0063]
[0064] 2) Establish a normalized decision matrix based on the original matrix.
[0065] Perform normalization processing on the original matrix A to establish a normalized decision matrix B=(b ij ) m×n , and b ij represents the standardized index value under the j-th evaluation index of the i-th evaluation object.
[0066] 3) Based on the normalized decision matrix, obtain the standardized index values of each evaluation index; the standardized index values include benefit type indexes and cost type indexes.
[0067] For benefit type indexes:
[0068]
[0069] For cost type indexes:
[0070]
[0071] Among them, max(a ij ), min(a ij ) are respectively the maximum and minimum values of the j-th index in the original matrix A.
[0072] S3. Calculate the weights of the evaluation indexes by the entropy weight method.
[0073] 1) Determine the proportion of each evaluation object in its corresponding index.
[0074] The proportion of the i-th evaluation object under the j-th evaluation index in this index is calculated as:
[0075]
[0076] 2) Determine the entropy value of the evaluation index;
[0077] The entropy value of the j-th evaluation index is:
[0078]
[0079] Among them,
[0080] 3) Determine the difference coefficient of the evaluation index;
[0081] The difference coefficient of the j-th evaluation index is:
[0082] g j = 1 - h j (j = 1, 2,..., n) (6)
[0083] 4) Determine the entropy weight of the evaluation index.
[0084] The entropy weight of the j-th evaluation index is:
[0085]
[0086] The weight vector V of the evaluation index is obtained j = (V1, V1,..., V n ).
[0087] S4. Based on the weights of the evaluation indexes, sort the threat levels of multiple aerial evaluation objects through the TOPSIS method; specifically,
[0088] 1) Based on the normalized decision matrix and the entropy weight, construct a weighted normalized decision matrix;
[0089] From the normalized decision matrix B = (b ij ) m×n and the weight vector V j = (V1, V1,..., V n ), a weighted normalized decision matrix C is formed. Among them, c ij = b ij V j .
[0090]
[0091] 2) Determine the ideal solution and the negative ideal solution;
[0092] In the weighted normalized decision matrix C, the maximum values in each evaluation index sequence form the ideal solution C+ The minimum values in each evaluation index sequence form the negative ideal solution C － .
[0093] C + =(C1 + , C2 + , …, C j + )=(max{c 11 , c 21 , …, c i1}, …, max{c 1j , c 2j , …, c ij ) (8)
[0095] C － =(C1 － , C2 － , …, C j － )=(min{c 11 , c 21 , …, c i1}, …, min{c 1j , c 2j , …, c ij ) (9)
[0097] 3) Determine the closeness of the evaluation objects to the optimal and worst - case scenarios;
[0098] Calculate the Euclidean distances of the attribute values of each evaluation object to the ideal solution and the negative ideal solution
[0099]
[0100] 4) Determine the closeness of each evaluation object to the optimal solution;
[0101]
[0102] 5) Rank the threat levels of multiple said evaluation objects based on the closeness to the optimal solution.
[0103] Sort the values of the closeness E i in descending order. The evaluation objects closer to the front have a greater threat level. Through the target threat assessment method, select the targets with a greater threat level as the priority targets for attack.
[0104] S5. Based on the threat - level ranking of the above - mentioned evaluation objects, according to the fire - power allocation conditions and the shooting advantages of the fire - power units, match the selected fire - power units with the selected evaluation objects and assign strike targets to the fire - power units.
[0105] The specific method is as follows:
[0106] 1) Select fire units that meet the allocation conditions
[0107] Fire units must all meet the following allocation conditions to participate in firepower allocation:
[0108] a) The working state is the combat operation state;
[0109] b) The incoming target enters the kill zone of the fire unit;
[0110] c) The remaining ammunition is not zero;
[0111] d) No other targets have been assigned.
[0112] Only fire units that meet the above conditions can be allocated firepower.
[0113] 2) Calculate the firing advantage
[0114] Calculate the firing strength for fire units that meet the conditions. The firing advantage of a fire unit is mainly determined by the range shortcut of the incoming target relative to the fire unit. The smaller the range shortcut, the more favorable the firing.
[0115] 3) Assign strike targets to fire units
[0116] Based on the current air situation, and based on the target threat degree ranking, firepower allocation conditions, and the firing advantage of fire units, match the selected fire units with the selected targets, and assign strike targets to fire units, so as to implement the firepower allocation plan.
[0117] In a specific embodiment of the present disclosure, this embodiment exemplarily provides evaluation indicators and data for some evaluation objects, and the threat assessment method processes for other evaluation indicators are the same;
[0118] I. Target threat assessment
[0119] 1) Extract the index attribute values of the incoming target
[0120] In an air situation obtained through reconnaissance on a certain occasion, there are 8 batches of incoming targets with batch numbers 1 to 8, etc. These 8 batches of targets are used as evaluation objects, and 6 evaluation indicators such as target type, distance, speed, altitude, course angle, and flying time are selected as threat degree evaluation indicators. The quantitative index attribute values of the incoming targets are shown in Table 1 below.
[0121] Table 1 Statistical table of quantitative attribute values of incoming targets
[0122]
[0123] For the target type indicators, the expert scoring method is used for qualitative quantification as follows:
[0124]
[0125] 2) Establish the original matrix
[0126] Establish the original matrix A from the attribute value data quantified by the incoming targets.
[0127]
[0128] 3. Establish the normalized decision matrix
[0129] Perform normalization processing on the original matrix A to establish the normalized decision matrix B. Among them, two evaluation indicators, such as target type and speed, are benefit type indicators and are calculated according to formula (1). Four indicators, such as the distance, altitude, course angle, and approaching time of the target, are cost type indicators and are calculated according to formula (2) to establish the normalized decision matrix B.
[0130]
[0131] 4) Calculate the weights corresponding to each evaluation indicator using the entropy weight method
[0132] Obtain the weight vector V of the evaluation indicators from formulas (3), (4), (5), (6), and (7).
[0133] V = (0.1630, 0.1626, 0.1673, 0.1788, 0.1656, 0.1627).
[0134] 5) Construct the weighted normalized decision matrix
[0135] The product of the normalized decision matrix B and the weight vector V constitutes the weighted normalized decision matrix C.
[0136]
[0137] 6) Determine the ideal solution and the negative ideal solution
[0138] Obtain the ideal solution C + and the negative ideal solution C － .
[0139] C + = (0.1630, 0.1626, 0.1673, 0.1788, 0.1656, 0.1627);
[0140] C － = (0, 0,..., 0).
[0141] 7) Calculate the closeness degree of each evaluation object to the optimal solution
[0142] Calculate the distances between each evaluation object and the ideal solution and the negative ideal solution according to Equations (10) and (11), obtain the closeness degree of each evaluation object to the optimal solution according to Equation (12), and sort them according to the numerical values of the closeness degree. The closeness degree of each evaluation object to the optimal solution is shown in Table 2.
[0143] Table 2 Closeness degree of each evaluation object to the optimal solution
[0144]
[0145]
[0146] 8) Threat degree ranking and selection of the priority strike object
[0147] According to the ranking from large to small of the closeness degree values, the target batch ranking of the incoming threat degree from large to small is obtained as follows:
[0148] Lot No. 3 > Lot No. 1 > Lot No. 5 > Lot No. 4 > Lot No. 2 > Lot No. 6 > Lot No. 7 > Lot No. 8.
[0149] According to the threat degree ranking of the incoming targets, select the incoming target with Lot No. 3, which has the greatest threat degree, as the priority strike object.
[0150] II. Firepower allocation plan
[0151] 1) Select the firepower units that meet the allocation conditions
[0152] Select the firepower units that meet the allocation conditions according to the working status of the firepower units, whether the incoming targets enter the killing area of the firepower units, the remaining ammunition, and whether other targets have been allocated, etc. The situation of the firepower units meeting the allocation conditions is shown in Table 3.
[0153] Table 3 Statistical table of the situation of firepower units meeting the allocation conditions
[0154]
[0155] After polling, Firepower Unit 1, Firepower Unit 2, Firepower Unit 5, and Firepower Unit 6 meet the allocation conditions and can be allocated firepower.
[0156] 2) Calculate the shooting advantage
[0157] The shooting advantage of each firepower unit is mainly determined by the lateral offset of the incoming target with Lot No. 3 relative to each firepower unit. The smaller the lateral offset, the more favorable the shooting. The lateral offset of the incoming target with Lot No. 3 relative to each firepower unit is shown in Table 4.
[0158] Statistical Table of the Route Shortcuts of Targets Relative to Firepower Units
[0159] Firepower unit number Range shortcut of the target relative to the firepower unit (km) Sorting 1 7 3 2 9 4 5 6 2 6 4 1
[0160] Sorted in ascending order of the route shortcut values, the descending order of the shooting advantages of the firepower units is as follows:
[0161] Firepower Unit 6 > Firepower Unit 5 > Firepower Unit 1 > Firepower Unit 2.
[0162] 3) Assign Strike Targets to Firepower Units
[0163] Based on the current air situation, considering the target threat degree ranking, firepower allocation conditions, and the shooting advantages of the firepower units, the incoming targets with batch number 3 are assigned to Firepower Unit 6 for fire strikes.
[0164] The technical solution of the present disclosure first conducts a threat assessment on the targets, providing a reliable basis for subsequent firepower allocation. Among them, the entropy weight method is used to calculate the index weights in the threat assessment, avoiding the subjective influence of human factors on the evaluation results, and the TOPSIS method is used to eliminate the influence of different index dimensions, making the evaluation results closer to the actual situation. In firepower allocation, based on the target threat degree ranking, a reasonable and feasible firepower allocation method is formed according to the working status, kill area, ammunition remaining, assigned target situation, and shooting advantages of the firepower units.
[0165] Although the embodiments of the present disclosure are described in conjunction with the accompanying drawings, the patent owner can make various deformations or modifications within the scope of the appended claims. As long as it does not exceed the protection scope described by the claims of the present disclosure, it should be within the protection scope of the present disclosure.
Claims
1. A firepower allocation method based on aerial target threat assessment, characterized in that: include: Acquire a threat level evaluation index of an aerial evaluation object, and construct a quantitative model of the evaluation index based on the threat level evaluation index; Establishing a decision matrix of a quantitative model of the evaluation indexes of a plurality of aerial evaluation objects; The entropy weight method is used to calculate the weight of the evaluation index; Based on the weights of the evaluation indicators, the threat levels of multiple air evaluation objects are ranked by the TOPSIS method; Based on the threat ranking of the evaluation object, the firepower allocation conditions and the shooting advantage of the firepower unit, the selected firepower unit is matched with the selected evaluation object, and a strike target is allocated to the firepower unit.
2. The firepower allocation method based on the aerial target threat assessment according to claim 1 is characterized in that: The threat level evaluation index of the aerial evaluation object includes flight distance, flight speed, flight altitude, heading angle, flight time and / or target type.
3. The firepower allocation method based on the aerial target threat assessment according to claim 2 is characterized in that: The step of constructing a quantitative model of the evaluation index based on the threat level evaluation index includes: The flight distance is the projection distance of the line connecting the center of the protection zone and the aerial target on the horizontal plane. The shorter the flight distance, the greater the threat of the target. The flight speed is obtained from the information of the air situation. The faster the target speed, the greater the threat. The flight altitude is the difference between the altitude of the aerial target and the altitude of our defensive position. The lower the target's flight altitude, the greater the threat. The heading angle is the angle between the line from the projection point of the aerial target in the horizontal plane to the center of the protection zone and the heading projection of the aerial target. The smaller the angle, the stronger the target's attack intention and the greater the threat. The arrival time refers to the time it takes for the target to fly over our defense position. The shorter the arrival time, the greater the threat. The target type indicator is a qualitative indicator, and the expert scoring method is used to construct the indicator quantitative model. The higher the score, the greater the threat.
4. The firepower allocation method based on the aerial target threat assessment according to claim 1 is characterized in that: The step of establishing a decision matrix of a quantitative model of the evaluation indexes of the plurality of aerial evaluation objects and using an entropy weight method to calculate the weights of the evaluation indexes comprises: An original matrix is established based on the evaluation indicators of multiple aerial evaluation objects. Establishing a normalized decision matrix based on the original matrix; Based on the normalized decision matrix, a standardized index value of each evaluation index is obtained.
5. The method for firepower allocation based on the aerial target threat assessment according to claim 4 is characterized in that: The standardized index values include benefit-based indexes and cost-based indexes; For benefit indicators: For cost indicators: Among them, max(a ij )、min(a ij ) are the maximum and minimum values of the jth index in the original matrix, respectively. ij Indicates the value of the jth evaluation indicator of the i-th evaluation object.
6. The method for firepower allocation based on aerial target threat assessment according to claim 4 is characterized in that: The entropy weight method is used to calculate the weight of the evaluation index, including Determine the proportion of each evaluation object in its indicator; Determine the entropy value of the evaluation index; Determine the coefficient of variation of the evaluation indicators; Determine the entropy weight of the evaluation index.
7. The method for firepower allocation based on aerial target threat assessment according to claim 6 is characterized in that: Based on the weight of the evaluation index, the threat levels of multiple air evaluation objects are ranked by the TOPSIS method. include, Based on the normalized decision matrix and the entropy weight, constructing a weighted normalized decision matrix; Determine ideal solutions and negative ideal solutions; Determine the degree of proximity between the evaluation object and the optimal solution and the worst solution; Determine the degree of closeness of each evaluation object to the optimal solution; The threat levels of the plurality of evaluation objects are ranked based on the degree of closeness to the optimal solution.
8. The method for firepower allocation based on aerial target threat assessment according to claim 7 is characterized in that: The step of determining the ideal solution and the negative ideal solution comprises: In the weighted normalized decision matrix, the maximum values in each evaluation index series constitute the ideal solution, and the minimum values in each evaluation index series constitute the negative ideal solution.
9. The method for firepower allocation based on the aerial target threat assessment according to claim 7 is characterized in that: In the step of determining the degree of proximity between the evaluation object and the optimal solution and the worst solution, the Euclidean distance from the attribute value of each evaluation object to the ideal solution and the negative ideal solution is calculated.
10. The method for firepower allocation based on aerial target threat assessment according to claim 7 is characterized in that: In the step of ranking the threat levels of the plurality of evaluation objects based on the degree of proximity of the optimal solution, the greater the degree of proximity, the greater the threat level of the evaluation object.