A Novel Track-Before-Detect Algorithm for Weak Target
نویسندگان
چکیده
In this paper, a novel track-before-detect algorithm is proposed for weak target with low signal to noise ratio. Multi-sensor information combining with trackbefore-detect technology is used to improve the signal to noise ratio. According to frame sequences of each sensor, Rao-Blackwellized particle filter, which is a clever combination of the Kalman filter and the standard particle filter, is employed to obtain state estimation and likelihood ratio of the target. In the detection process, the proposed cusum joint detection is adopted to realize detection of target appearance and disappearance. Calculation of the disappearance statistic is started the moment a target is detected, which ensures the continuous detection of target appearance and shorter delay for the detection of target disappearance. Simulation results show the efficiency of the proposed algorithm.
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