中南大学学报（英文版）
中南大學學報（英文版）
중남대학학보（영문판）
Journal of Central South University
2015年
10期
3935-3945
,共11页
占荣辉%刘盛启%胡杰民%张军
佔榮輝%劉盛啟%鬍傑民%張軍
점영휘%류성계%호걸민%장군
Bernoulli filter%multiple model%target maneuver%track-before-detect (TBD)%sequential Monte Carlo (SMC) technique
Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target’s maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo (particle) technique. Target detection was accomplished through the estimation of target’s existence probability, and the estimate of target state was obtained by combining the outputs of model- dependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.
