CN107203493A - Multiple target battle field situation method based on complicated ratio evaluation method - Google Patents

Abstract

The invention provides a kind of multiple target battle field situation method based on complicated ratio evaluation method, objective attribute target attribute decision matrix is constructed first, then the weight of j-th of objective attribute target attribute is determined using entropy assessment, annoyance level calculating is finally carried out using complicated ratio evaluation method and sorted.Sensitivity of the present invention is high, it is adaptable to which we meets with large-scale cluster aircraft disturbed condition, and based on objective information, it is to avoid the random sex chromosome mosaicism of subjectivity of Bayesian network, analytic hierarchy process (AHP) etc., improves the reasonability and accuracy of target jamming degree sequence.

Description

Multi-objective Situation Estimation Method Based on Complex Proportional Evaluation Method

technical field

The invention belongs to the field of data fusion, and in particular relates to a multi-target situation estimation method.

Background technique

Data fusion technology refers to the information processing technology that uses a computer to automatically analyze and synthesize a number of observation information obtained in time series under certain criteria to complete the required decision-making and evaluation tasks. It is a technology in the field of information science and an important basis for a new generation of intelligent information technology, which was first used in the military field. Situation estimation is an important part of data fusion research. When our aircraft is interfered by a large number of enemy aircraft in different situations, how to make a reasonable order of interference degree is very important for our command decision-making. Therefore, situation estimation is the premise of making reasonable command and decision-making, and the research is of great significance.

At present, scholars have conducted some research on the problem of multi-objective situation estimation. Commonly used multi-objective situation estimation methods include analytic hierarchy process, intuitionistic fuzzy sets, Bayesian reasoning, expert system and so on. In the existing technology, AHP, expert system, Bayesian reasoning, etc. are mostly affected by subjective factors, and the reliability is low. The TOPSIS method ignores the distance between the alternative scheme and the ideal scheme and the distance between the negative ideal scheme, that is, It is considered that all the schemes whose distance from the positive ideal solution is less than the distance from the negative ideal solution are better than those whose distance from the positive ideal solution is equal to the distance from the negative ideal solution, so the ideal solution obtained may not be the closest to the ideal point, so the The reliability of the sorting results obtained by the TOPSIS method is not high; the multi-criteria compromise solution sorting method overcomes the limitations of the TOPSIS method, but the selection of decision factors is more difficult. When our aircraft encounters interference from the opponent's large-scale cluster aircraft, it is very important to adjust the interference order in time according to the situation changes of each opponent's aircraft. However, the above method is complex in calculation and low in sensitivity, and is not suitable for our side encountering the interference of the enemy's large-scale cluster aircraft The situation cannot reflect the impact of changes in the situation of each target in a timely manner. In addition, there are few studies on the application of complex ratio evaluation methods in situation estimation.

Contents of the invention

In order to overcome the deficiencies of the prior art, the present invention provides a multi-objective situation estimation method based on the complex ratio evaluation method. Taking advantage of the high sensitivity of the complex ratio evaluation method, the complex ratio evaluation method is introduced into the situation estimation, and combined with the entropy weight The method determines the weight, avoids subjective arbitrariness, and ensures that the obtained ideal solution is the best ideal solution.

The technical solution adopted by the present invention to solve its technical problems comprises the following steps:

Step 1: Construct the target attribute decision matrix In the formula, t _ij represents the evaluation value of the i-th target under the j-th attribute, i=1, 2, 3...m, m is the number of targets, and the target attributes j=1, 2, 3 include angle threat factors T _a ＝[|φ _k |+|θ _k |]/360°, speed threat factor and distance threat In the formula, φ _k is the lead angle of the target; θ _k is the target entry angle, v _k is the target speed, v _z is the speed of our aircraft, r _k is the distance between the target and our side, r _m is the maximum Interference distance, r _mk is the interference distance of the target, r _r is the detection distance of our machine's detection device;

Step 2, using the entropy weight method to determine the weight of the jth target attribute In the formula, k=1/Inm, H _j ≥ 0, k ≥ 0, when f _ij =0, f _ij In f _ij =0;

Step 3, using the complex ratio evaluation method to calculate the degree of interference, the specific steps are as follows:

(1) Calculate the normalized target attribute decision matrix T′=(t′ _ij ) _m×3 ,

(2) Calculate the weighted standardized decision matrix T″=(t″ _ij ) _m×3 , t″ _ij =ω _j ×t′ _ij ;

(3) Calculate the weighted standardized attribute value and and the weighted normalized attribute value under the cost attribute and Wherein, t″ _+ij is the weighted standardized attribute value under the benefit type attribute, and t″ _-ij is the weighted standardized attribute value under the cost type attribute;

(4) Calculate the relative importance of each target In the formula,

(5) Sorting according to the Q _i value, the larger the Q _i value, the greater the interference of the corresponding target to our side, the greater the threat, and the higher the ranking.

The beneficial effects of the present invention are:

The invention combines the entropy weight method and the complex ratio evaluation method to sort the target interference degree. That is, the entropy weight method is used to process objective information to obtain the weight of each target attribute, and the weight is applied to the complex proportional evaluation method to calculate the degree of multi-target interference. The invention has high sensitivity, is suitable for our side encountering large-scale cluster aircraft interference, and based on objective information, avoids subjective randomness problems such as Bayesian network and analytic hierarchy process, and improves the rationality and accuracy of the ranking of target interference levels sex.

The complex ratio evaluation method proposed by the present invention is simple to calculate, based on the original objective attribute value of each target, can quickly reflect the impact of the situation change of each target, and is more sensitive than the multi-criteria compromise solution sorting method and the TOPSIS method. It is suitable for the situation where our side is interfered by the enemy's large-scale cluster aircraft.

Description of drawings

Fig. 1 is the schematic diagram of target situation of the present invention;

In the figure, T is the target, O is our side, φ _k is the target lead angle; θ _k is the target entry angle, v _k is the target speed, r _k is the distance between the target and our side, and the arrow points to the positive direction.

detailed description

The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the present invention includes but not limited to the following embodiments.

The present invention proposes a situation estimation method based on a complex proportional evaluation method, uses an entropy weight method to determine target attribute weights, and applies the obtained target attribute weights to the complex proportional evaluation method for sorting and calculation.

Concrete steps involved in the present invention are as follows:

Step 1: Construct the target attribute decision matrix

In the formula, t _ij represents the evaluation value of the i-th (i=1,2,3...m) target under the j-th (j=1,2,3) attribute, and m is the number of targets. Target properties include the following:

(1) Angle threat factor T _a

T _a ＝[|φ _k |+|θ _k |]/360°

In the formula, φ _k is the target lead angle; θ _k is the target entry angle.

(2) Speed threat factor T _v

In the formula, v _k is the target speed; v _z is the speed of the aircraft

(3) Distance threat factor T _d

In the formula, r _k is the distance between the target and our side; r _m is the maximum interference distance of our machine's jamming device; r _mk is the target's jamming distance; r _r is the detection distance of our machine's detection device.

Step 2: Use the entropy weight method to determine the weight of the target attribute.

Let the weight of the target attribute be ω, then the weight ω _j of the jth target attribute is as follows:

In the formula, k=1/In m, H _j ≥ 0, k ≥ 0. And define that when f _ij =0, f _ij Inf _ij =0. n is the number of attributes, which is 3 in the present invention.

Step 3: Calculate the degree of interference by using the complex ratio evaluation method. Specific steps are as follows:

(1) Normalize the target attribute decision matrix to obtain the normalized decision matrix T′=(t′ _ij ) _m×3

(2) Weighting the normalized decision matrix T′=(t′ _ij ) _m×3 to obtain a weighted standardized decision matrix T″=(t″ _ij ) _m×3 .

t″ _ij =ω _j ×t′ _ij

(3) Calculate the sum of the weighted standardized attribute values under the benefit attribute and the cost attribute respectively

t″ _+ij is the weighted standardized attribute value under the benefit attribute, and t″ _-ij is the weighted standardized attribute value under the cost attribute. Under the benefit attribute, the larger the attribute value, the greater the enemy's interference with our side, the greater the threat, and the higher the ranking; under the cost type attribute, the larger the attribute value, it indicates that the enemy has a greater impact on our side. The smaller the interference, the smaller the threat and the lower the ranking.

(4) Calculate the relative importance Q _i of each target

Further simplifying the above formula, the following formula can be obtained:

In the formula, It can be seen from the above formula that Q _i is directly proportional to S _+i and inversely proportional to S _-i .

(5) Optimal target adjustment.

The targets are sorted according to the Q _i value. The larger the Q _i value, the greater the interference of the corresponding target to our side, and the higher the ranking.

The present invention aims at the deficiencies of existing technologies such as TOPSIS method, Bayesian network, and AHP, combines the entropy weight method, and applies the weight of each target attribute obtained by it to the complex ratio evaluation method, which overcomes the disadvantages of the traditional method. Limit and avoid the problem of subjective arbitrariness. Using the method of the invention to estimate the target situation is more accurate than other methods, has high sensitivity, and is easy to implement, and is suitable for the situation that our side encounters interference from large-scale cluster aircraft.

Claims (1)

1. A multi-objective situation estimation method based on complex ratio evaluation method, is characterized in that comprising the steps: Step 1: Construct the target attribute decision matrix In the formula, t _ij represents the evaluation value of the i-th target under the j-th attribute, i=1, 2, 3...m, m is the number of targets, and the target attributes j=1, 2, 3 include angle threat factors T _a ＝[|φ _k |+|θ _k |]/360°, speed threat factor and distance threat In the formula, φ _k is the lead angle of the target; θ _k is the target entry angle, v _k is the target speed, v _z is the speed of our aircraft, r _k is the distance between the target and our side, r _m is the maximum Interference distance, r _mk is the interference distance of the target, r _r is the detection distance of our machine's detection device; Step 2, using the entropy weight method to determine the weight of the jth target attribute In the formula, k=1/Inm, H _j ≥0, k≥0, when f _ij =0, f _ij Inf _ij =0; Step 3, using the complex ratio evaluation method to calculate the degree of interference, the specific steps are as follows: (1) Calculate the normalized target attribute decision matrix T′=(t′ _ij ) _m×3 , (2) Calculate the weighted standardized decision matrix T″=(t″ _ij ) _m×3 , t″ _ij =ω _j ×t′ _ij ; (3) Calculate the weighted standardized attribute value and and the weighted normalized attribute value under the cost attribute and Wherein, t″ _+ij is the weighted standardized attribute value under the benefit type attribute, and t″ _-ij is the weighted standardized attribute value under the cost type attribute; (4) Calculate the relative importance of each target In the formula, (5) Sorting according to the Q _i value, the larger the Q _i value, the greater the interference of the corresponding target to our side, the greater the threat, and the higher the ranking.