US 2025/0187749 A1Published application

System integration

AssigneeBAE SYSTEMS plc

InventorMONADL ABD AL-ABBAS MANSOUR AL-AMERI

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Abstract

A feasibility display indicative of a feasibility of a weapon carried on the aircraft successfully engaging a target and/or a feasibility of a weapon carried on the target successfully engaging the aircraft is cooperatively generated by an aircraft and another device. The another device has a database describing a performance envelope of the weapon. The another device identifies a best candidate polynomial from a plurality of candidate polynomials based on respective scores using a genetic algorithm. Each score is based on a quality of fit of the candidate polynomial to a characteristic of the performance envelope of the weapon. The another device uploads, after a plurality of characteristics are evaluated, to the aircraft coefficients which are determined for the best candidate polynomial. Variables of the plurality are some or all of a weapon or aircraft firing condition parameters. The aircraft uses selected coefficients to generate the feasibility display.

Claims20

Dependent claims

A computer-implemented method of generating, in an aircraft in flight, a feasibility display indicative of a feasibility of a weapon carried on the aircraft successfully engaging a target and/or a feasibility of a weapon carried on the target successfully engaging the aircraft, the method comprising:

providing a database describing a performance envelope of the weapon;
creating coefficients characteristic of that performance envelope using a generic algorithm, wherein the generic algorithm has a form of a polynomial, the creating including:
a) generating candidate polynomials, variables of the candidate polynomials being some or all of a group of weapon or aircraft firing condition parameters;
b) for each candidate polynomial, computing coefficients for that candidate polynomial which best fit that candidate polynomial to a characteristic of the performance envelope of the weapon using a criterion of least square error;
c) for each candidate polynomial, generating a candidate score according to the quality of the fit of that candidate polynomial to the characteristic of the performance envelope of the weapon;
d) applying a genetic algorithm to the candidate polynomials and scores including selecting the best scoring candidate polynomial and discarding the other candidate polynomials, thereby identifying a best candidate polynomial and coefficients thereof;
and
e) repeating said identifying process until each of the characteristics of the performance envelope have corresponding polynomial models;
uploading, to the aircraft, the coefficients of the identified best candidate polynomial;
selecting, by a reconstructor on the aircraft containing the same generic algorithm, coefficients for the generic algorithm according to conditions of the aircraft and the target;
and
using the selected coefficients, generating, by the reconstructor, the feasibility display;
wherein step d) applying the genetic algorithm to the candidate polynomials and scores comprises:
i) defining a set of orders and/or types of the candidate polynomials and dividing the defined set of orders and/or types into a plurality of sub-sets thereof;
ii) iteratively applying the genetic algorithm concurrently over the plurality of sub-sets of the defined set of orders and/or types of the candidate polynomials, including iteratively applying the genetic algorithm over the variables of the candidate polynomials for each order and/or type of the respective sub-set thereof and saving the resulting respective coefficients and scores thereof;
and
iii) selecting the best scoring candidate polynomial using the saved coefficients and scores and discarding the other candidate polynomials, thereby identifying the best candidate polynomial and coefficients thereof.

14 more elements

A system for generating in an aircraft in flight, a feasibility display indicative of a feasibility of a weapon carried on the aircraft successfully engaging a target and/or a feasibility of a weapon carried on the target successfully engaging the aircraft, the system comprising:

a first computer comprising a memory and a processor, the first computer being remote from the aircraft;
and
a second computer comprising a memory and a processor, the second computer being onboard the aircraft;
wherein the first computer is configured to:
provide a database describing a performance envelope of the weapon;
create coefficients characteristic of that performance envelope using a generic algorithm, wherein the generic algorithm has a form of a polynomial, the creating including:
a) generating candidate polynomials, variables of the candidate polynomials being some or all of a group of weapon or aircraft firing condition parameters;
b) for each candidate polynomial, computing coefficients for that candidate polynomial which best fit that candidate polynomial to a characteristic of the performance envelope of the weapon using a criterion of least square error;
c) for each candidate polynomial, generating a candidate score according to the quality of the fit of that candidate polynomial to the characteristic of the performance envelope of the weapon;
d) applying a genetic algorithm to the candidate polynomials and scores including selecting the best scoring candidate polynomial and discarding the other candidate polynomials, thereby identifying a best candidate polynomial and coefficients thereof;
and
e) repeating said identifying process until each of the characteristics of the performance envelope have corresponding polynomial models;
upload, to the second computer, the coefficients of the identified best candidate polynomial;
wherein the second computer is configured to:
select, by a reconstructor containing the same generic algorithm, the coefficients for the generic algorithm according to conditions of the aircraft and the target;
and
using the selected coefficients, generate, by the reconstructor, the feasibility display;
wherein step d) applying the genetic algorithm to the candidate polynomials and scores comprises:
i) defining a set of orders and/or types of the candidate polynomials and dividing the defined set of orders and/or types into a plurality of sub-sets thereof;
ii) iteratively applying the genetic algorithm concurrently over the plurality of sub-sets of the defined set of orders and/or types of the candidate polynomials, including iteratively applying the genetic algorithm over the variables of the candidate polynomials for each order and/or type of the respective sub-set thereof and saving the resulting respective coefficients and scores thereof;
and
iii) selecting the best scoring candidate polynomial using the saved coefficients and scores and discarding the other candidate polynomial, thereby identifying the best candidate polynomial and coefficients thereof.

19 more elements

Dependencies are inferred from the claim text.