Mar 31, 2026

US12591786 - Intelligent ammunition co-evolution task assignment method

An intelligent ammunition co-evolution task assignment method is disclosed. The method includes the following steps. A chromosome gene encoding of genetic algorithm for ammunition assignment scheme of multi-platform interception operation is performed. A fitness of chromosome individual function in a genetic population is calculated according to a threat degree of an intercepting target in the ammunition assignment scheme and an interception probability of the intercepting target by different ammunition launching platforms. A probability ranking sequence of effective interception of the intercepting target by different ammunition launching platforms is obtained, and a genetic algorithm selection operation is performed on the chromosome individuals according to probability values of effective interception in descending order of priority. Crossover and/or mutation are performed on the selected chromosome individuals to obtain a next generation genetic population and the above steps are repeated until termination conditions are met to obtain the final ammunition assignment scheme.

ammunitionintelligentassignmentmethod

The patent describes an intelligent method for assigning ammunition tasks in multi-platform interception operations using a genetic algorithm. It involves encoding chromosome genes, calculating fitness based on threat levels and interception probabilities, ranking effective interceptions, and iterating through selection, crossover, and mutation until an optimal ammunition assignment scheme is achieved.

Claim 1

1 . An intelligent ammunition co-evolution task assignment method, comprising: S1. performing a chromosome gene encoding of genetic algorithm for ammunition assignment scheme of multi-platform interception operation; S2. calculating a fitness of chromosome individual function in a genetic population according to a threat degree of an intercepting target in the ammunition assignment scheme and an interception probability of the intercepting target by different ammunition launching platforms; S3. obtaining a probability ranking sequence of effective interception of the intercepting target by different ammunition launching platforms according to the fitness of the chromosome individual function in the contemporary genetic population, and performing a genetic algorithm selection operation on the chromosome individuals according to probability values of effective interception in descending order of priority; and S4. performing crossover and/or mutation on the chromosome individuals selected in the S3 to obtain a next generation genetic population and repeating the S2 until termination conditions are met to obtain the final ammunition assignment scheme, wherein a fitness calculation method of the chromosome individual function in the genetic population in S2 is as follows: S1. performing a chromosome gene encoding of genetic algorithm for ammunition assignment scheme of multi-platform interception operation; S2. calculating a fitness of chromosome individual function in a genetic population according to a threat degree of an intercepting target in the ammunition assignment scheme and an interception probability of the intercepting target by different ammunition launching platforms; S3. obtaining a probability ranking sequence of effective interception of the intercepting target by different ammunition launching platforms according to the fitness of the chromosome individual function in the contemporary genetic population, and performing a genetic algorithm selection operation on the chromosome individuals according to probability values of effective interception in descending order of priority; and S4. performing crossover and/or mutation on the chromosome individuals selected in the S3 to obtain a next generation genetic population and repeating the S2 until termination conditions are met to obtain the final ammunition assignment scheme, wherein a fitness calculation method of the chromosome individual function in the genetic population in S2 is as follows: f ⁡ ( X ) = ∑ j = 1 n f ⁡ ( X ji ) = ∑ j = 1 n v j · p ji wherein v j is the threat degree of the j-th target, and p ji is the interception probability of the i-th fire unit against the j-th target. wherein v j is the threat degree of the j-th target, and p ji is the interception probability of the i-th fire unit against the j-th target.

Google Patents

https://patents.google.com/patent/US12591786

USPTO PDF

https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/12591786

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