Missile guidance algorithm against high-g barrel roll maneuvers

1994 ◽  
Vol 17 (1) ◽  
pp. 123-128 ◽  
Author(s):  
Fumiaki Imado ◽  
Susumu Miwa
Keyword(s):  
Missile Guidance ◽  
Guidance Algorithm

Missile Guidance Algorithm Design Using Particle Swarm Optimization

2013 ◽  
Vol 284-287 ◽  
pp. 2411-2415
Author(s):  
Chien Chun Kung ◽  
Kuei Yi Chen
Keyword(s):  
Objective Function ◽  
Fitness Function ◽  
Equations Of Motion ◽  
Algorithm Design ◽  
Solution Space ◽  
Pso Algorithm ◽  
Local Optimum ◽  
Missile Guidance ◽  
Pursuit Evasion ◽  
Guidance Algorithm

This paper presents a technique to design a PSO guidance algorithm for the nonlinear and dynamic pursuit-evasion optimization problem. In the PSO guidance algorithm, the particle positions of the swarm are initialized randomly within the guidance command solution space. With the particle positions to be guidance commands, we predict and record missiles’ behavior by solving point-mass equations of motion during a defined short-range period. Taking relative distance to be the objective function, the fitness function is then evaluated according to the objective function. As the PSO algorithm proceeds, these guidance commands will migrate to a local optimum until the global optimum is reached. This paper implements the PSO guidance algorithm in two pursuit-evasion scenarios and the simulation results show that the proposed design technique is able to generate a missile guidance law which has satisfied performance in execution time, terminal miss distance, time of interception and robust pursuit capability.

MISSILE GUIDANCE ALGORITHM DESIGN USING PARTICLE SWARM OPTIMIZATION

2013 ◽  
Vol 37 (3) ◽  
pp. 971-979 ◽  
Author(s):  
Chien-Chun Kung ◽  
Kuei-Yi Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problem ◽  
Algorithm Design ◽  
Solution Space ◽  
Global Optimum ◽  
Missile Guidance ◽  
Swarm Optimization ◽  
Pursuit Evasion ◽  
Guidance Algorithm ◽  
Miss Distance

This paper presents a PSO guidance (PSOG) algorithm design for the pursuit-evasion optimization problem. The initialized particles are randomly set within the guidance command solution space and the relative distance is taken as the objective function. As the PSOG algorithm proceeds, the iteration will execute until the global optimum is reached. Two pursuit-evasion scenarios show that the PSOG algorithm has satisfied performance in execution time, terminal miss distance, time of interception, final stage turning rate and robust pursuit capability.

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