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A particle swarm optimization based sensors management algorithm for armed helicopters

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.