Adaptive Extended Box Particle Maneuvering Target Tracking Algorithm Based on IMM-BF
To solve the problem of insufficient tracking accuracy and target loss of the box particle filter algorithm in the clutter measurement environment,an adaptive extended box particle maneuvering target tracking algorithm based on Interacting Multiple Model-Extended Box Particle-Bernoulli Filter(IMM-EBox-BF)is proposed.The algorithm uses multiple model parallel filtering.After the prediction step,the adaptive box particle expansion algorithm is introduced.After each box particle is divided into small box particles,the interval length of the small box particles is adaptively expanded,which improves the accuracy of target position estimation.In the update step,the box particle contraction algorithm is improved,the constraint on the acceleration component is increased to improve the accuracy of the target velocity estimation.The simulation and measured data processing results show that the proposed IMM-EBox-BF algorithm improves the position tracking accuracy by 16.5％compared with the traditional algorithm,and has more accurate target estimation accuracy and continuity in the case of clutter measurement and missed detection of sensor.
maneuvering targetBernoulli filterbox particle filterinteracting multiple model
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