基于分布式有限感知网络的多伯努利目标跟踪

In order to solve the problem of multi-target tracking in distributed sensor networks with limited sensing range (LSR), a distributed arithmetic average (AA) fusion multi-Bernoulli filter is proposed based on field of view complementation and multi-Bernoulli association. First, the sensor＇s sensing range is expanded by complementing the field of view, in which the local common areas are complemented only once to reduce the calculation cost. Secondly, each sensor separately operates a local multi-Bernoulli filter and conducts flood communication between neighbor sensors over the filter posteriors, so that each sensor can obtain posterior information of multiple sensors. Then, multi-Bernoulli correlation is performed by distance division to associate Bernoulli components corresponding to the same target to the same subset, and the AA fusion is performed for each associated subset to complete fusion state estimation. Simulation results show that the proposed method can effectively track multiple targets in distributed sensor networks with LSR.