Surface-to-air missile path planning using genetic and PSO algorithms

Zandavi, Seid Miad

doi:10.15632/jtam-pl.55.3.801

Cited by 10 publications

(2 citation statements)

References 10 publications

(9 reference statements)

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“…Modern naval battles and coordinated anti-ship missile attacks have become the most important and only longrange means of attacking the sea. Due to the coupling relationship between path planning and firepower distri-bution, in addition to the high-intensity, multi-directional, multi-wave saturation attack effect, it is necessary to avoid the problems of path crossing and range waste [1,2], which makes the anti-ship missiles coordinated attack mission planning a complex multi-objective optimization problem with multiple combinations of platforms, strong decision-making constraints, and tightly coupled links.…”

Section: Introductionmentioning

confidence: 99%

Firepower distribution method of anti-ship missile based on coupled path planning

Liu

Lao

et al. 2022

J. of Syst. Eng. Electron.

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Anti-ship missile coordinated attack mission planning is a complex multi-objective optimization problem with multiple combinations of platforms, strong decision-making constraints, and tightly coupled links. To avoid the coupling disorder between path planning and firepower distribution and improve the efficiency of coordinated attack mission planning, a firepower distribution model under the conditions of path planning is established from the perspective of decoupling optimization and the algorithm is implemented. First, we establish reference coordinate system of firepower distribution to clarify the reference direction of firepower distribution and divide the area of firepower distribution; then, we construct an index table of membership of firepower distribution to obtain alternative firepower distribution plans; finally, the fitness function of firepower distribution is established based on damage income, missile loss, ratio of efficiency and cost of firepower distribution, and the mean square deviation of the number of missiles used, and the alternatives are sorted to obtain the optimal firepower distribution plan. According to two simulation experiments, the method in this paper can effectively solve the many-to-many firepower distribution problem of coupled path planning. Under the premise of ensuring that no path crossing occurs, the optimal global solution can be obtained, and the operability and timeliness are good.

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Section: Introductionmentioning

confidence: 99%

Firepower distribution method of anti-ship missile based on coupled path planning

Liu

Lao

et al. 2022

J. of Syst. Eng. Electron.

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“…Ref. [20] used the PSO algorithm to design the trajectory, propulsion, and aerodynamic characteristics of long-range ballistic missiles quickly using the minimum take-off quality as an indicator along with the given design variables and constraint functions. Although the methods described above have improved the performance of the PSO algorithm to varying degrees, the relationship between the overall fitness value of the swarm particles and the inertia weight during the evolution process has not been considered.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Multimissile Formation Based on an Adaptive SA-PSO Algorithm

et al. 2021

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In an effort to maximize the combat effectiveness of multimissile groups, this paper proposes an adaptive simulated annealing–particle swarm optimization (SA-PSO) algorithm to enhance the design parameters of multimissile formations based on the concept of missile cooperative engagement. Firstly, considering actual battlefield circumstances, we establish an effectiveness evaluation index system for the cooperative engagement of missile formations based on the analytic hierarchy process (AHP). In doing so, we adopt a partial triangular fuzzy number method based on authoritative assessments by experts to ascertain the weight of each index. Then, considering given constraints on missile performance, by selecting the relative distances and angles of the leader and follower missiles as formation parameters, we design a fitness function corresponding to the established index system. Finally, we introduce an adaptive capability into the traditional particle swarm optimization (PSO) algorithm and propose an adaptive SA-PSO algorithm based on the simulated annealing (SA) algorithm to calculate the optimal formation parameters. A simulation example is presented for the scenario of optimizing the formation parameters of three missiles, and comparative experiments conducted with the traditional and adaptive PSO algorithms are reported. The simulation results indicate that the proposed adaptive SA-PSO algorithm converges faster than both the traditional and adaptive PSO algorithms and can quickly and effectively solve the multimissile formation optimization problem while ensuring that the optimized formation satisfies the given performance constraints.

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