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A Judgment Method of Target Extinction Applied to rbmcda Tracking Algorithm

A tracking algorithm and target technology, applied in the field of multi-target tracking, can solve problems such as unintuitive adjustment of target extinction model parameters, mismatch of model parameters, and error in target extinction judgment.

Active Publication Date: 2022-04-22
HARBIN ENG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that in the RBMCDA algorithm, the parameter adjustment of the target extinction model is not intuitive, and the model parameters do not match the actual situation, which leads to the problem that the judgment of the target extinction is wrong, and a tracking algorithm applied to RBMCDA is proposed. The target demise judgment method of

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  • A Judgment Method of Target Extinction Applied to rbmcda Tracking Algorithm

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[0045] The target orientation is used as the state quantity and quantity measurement to carry out simulation verification. The existing RBMCDA algorithm is based on the target extinction mode of continuous unrelated duration, and 25 groups of parameters are selected. The method of the present invention is based on the target extinction model of the predicted target state value variance. 30 groups of parameters. Taking multi-target tracking accuracy (MOTA) as the evaluation standard, the missing rate of multi-target tracking p miss , misjudgment rate p fp and the mismatch rate p mme For statistics, MOTA can be expressed as

[0046] MOTA=1-(p miss +p fp +p mme )

[0047] The closer the MOTA value is to 1, the better the multi-target tracking performance is. The MOTA value is 1 only when the missing rate, false positive rate, and false match rate are all zero.

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Abstract

The present invention proposes a kind of target demise judging method that is applied to RBMCDA tracking algorithm, and described method comprises step one: predict the target state value variance of next moment at k-1 moment; Step two: by the target state value variance of prediction, Calculate the target extinction probability according to the uniform distribution probability termination model; Step 3: According to the target extinction probability, the particles perform Monte Carlo sampling to determine the target state. Because the present invention uses the variance of the predicted target state value as the judgment basis, the parameters of the target extinction probability model are connected with the measurement noise and the state transition noise, and there is no need to adjust the parameters of the target extinction model, so that the system has more Good robustness.

Description

technical field [0001] The invention belongs to the technical field of multi-target tracking, and in particular relates to a target demise judgment method applied to an RBMCDA tracking algorithm. Background technique [0002] R-B Monte Carlo data association tracking algorithm (RBMCDA, Rao-Blackwellized Monte Carlo DataAssociation) is an improved multi-target tracking algorithm based on multi-hypothesis tracking, which achieves the goal by combining Rao-Blackwellized particle filter (RBPF) and multi-hypothesis data association Tracking and trajectory generation, this method uses a mixture of particle filter and Kalman filter methods, and uses the posterior distribution of data association as the optimal importance density function for particle sampling, which has good robustness and high Tracking accuracy is one of the most effective ways to solve the multi-sensor MTT problem in the complex environment of the real world. [0003] The target disappearance problem refers to w...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/18G06F30/20G06F111/08
CPCG06F17/18
Inventor 齐滨付进王燕梁国龙卢鹏博樊姜华王逸林张光普孙思博邹男王晋晋
Owner HARBIN ENG UNIV