Data Association in Multi-Target Localization Using Bearing-Only Sensor Networks

Multi-target bearing-only localization on sensor network suffers from unknown association between measurements and targets,making it difficult to achieve real-time localization,especially with the existence of bearing measurement errors.A data association method is designed for multi-target localization to deal with the unknown target initial states and complex measuring phenomena.Theoretical deduction of sensing probability and gate threshold selection is given on the basis of measurement error analysis.A data association method based on scalable gate threshold is proposed to estimate target when the measurement is importing to the data fusion center,ensuring the probability that intersection of bearing measurement is real target localization.Simulation results show that the proposed method works well under different settings and the required acceptable computation load.