Multi-sensor Multi-target Data Association Algorithm Based on Swarm Intelligence

摘要

An swarm intelligence algorithm, particle swarm optimization (PSO) algorithm, is used in data association problem for multi-sensor multi-target data association. The association relation between measurements and targets is described by the likelihood function of filter innovation to establish the model of the optimal combination. Lagrange relaxation technology is used to reduce the combination to two dimensions firstly when solving the optimal combination problem, and then the improved PSO algorithm, which based on the cross and mutation rules, is used to obtain the optimal solution, and get the optimal association pairs for measurements and targets. The simulation shows the superiority of the method in accuracy and speed at last.