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A particle swarm optimization based sensors management algorithm for armed helicopters
Author(s): Shaojie Zhang; Hongbin Zhang; Yanqiu Ju; Chi Qi; Huichao Lv
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Paper Abstract

This paper proposes a particle swarm optimization (PSO) based sensors management algorithm for armed helicopters. With the objective of solving the efficient pairing between multiple sensors and multiple targets, the proposal defines the sensor-target pairing matrix as a particle and defines the aggregated performance using the pairing matrix as the fitness function. Further, the iterative updates of the key parameters, including the velocity, the local optimum and the global optimum, are designed. The optimal aggregated performance is achieved through multiple iterations. Simulation results demonstrate that the proposed algorithm outperforms the existing non-linear optimization algorithms in terms of the computational complexity. While, the proposal can adapt to the variation of both sensors and targets, which makes it more suitable to the dynamic battle environment.

Paper Details

Date Published: 29 October 2018
PDF: 6 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083622 (29 October 2018); doi: 10.1117/12.2514022
Show Author Affiliations
Shaojie Zhang, Army Aviation Institute (China)
Hongbin Zhang, Army Aviation Institute (China)
Yanqiu Ju, Army Aviation Institute (China)
Chi Qi, Army Aviation Institute (China)
Huichao Lv, Army Aviation Institute (China)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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