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Aiming at the multi-sensor multi-target assignment (MSMTA) problem under complex air defense combat environment, a new MSMTA model is proposed with the compositive combat efficiency of the identification, tracking and positioning stage. And then, the quantum particle swarm optimization (QPSQ) algorithm is imported in order to solve the MSMTA problem. Finally, the experiments show that the new MSMTA model is effective and compare the performances between the QPSO and particle swarm optimization (PSO) algorithms.

Solving Multi-Sensor Multi-Target Assignment Problem Based on Compositive Combat Efficiency and QPSO Algorithm