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A Density Filtering Method Based on Potential Probability Hypotheses Aided by Swarm Movement

A technology of probability hypothesis density and hypothesis density, applied in the field of target tracking, can solve problems such as the inaccurate grasp of single target movement and the large randomness of single target

Active Publication Date: 2020-05-15
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

In traditional target tracking, the prediction of target motion is often based on a single target motion model, but the motion of a single target often has a large randomness, and the motion of a single target is often not accurately grasped.

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  • A Density Filtering Method Based on Potential Probability Hypotheses Aided by Swarm Movement
  • A Density Filtering Method Based on Potential Probability Hypotheses Aided by Swarm Movement
  • A Density Filtering Method Based on Potential Probability Hypotheses Aided by Swarm Movement

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Embodiment Construction

[0140] combine figure 1 , a kind of swarm movement tendency auxiliary aggregate potential probability hypothesis density filtering method of the present invention, comprises the following steps:

[0141] Step 1, use the measurement of each target position at time k to calculate the group state, and then use B-spline to perform trajectory fitting on the group state at time 1~k to obtain the group movement trajectory;

[0142] Step 2, calculate the group velocity through the B-spline fitting curve, and use the target position measurement and group velocity to form each target state, and obtain the potential distribution ρ at time k k (n) and probability hypothesis density D k (x), and set the single target motion model and the group motion model of each target to have the same proportion;

[0143] Step 3, let k=k+1, there is a probability hypothesis density D at the previous moment (k-1 moment) k-1 (x) and potential distribution ρ k-1 (n), predict the current moment (k momen...

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Abstract

The invention relates to the technical field of target tracking, in particular to a density filtering method of aggregate probability assumptions assisted by group movement trends, which is implemented using Gaussian mixture technology. This method uses the group motion model to assist tracking. By calculating the proportion of different motion models, different models are used to predict the target state according to the proportion in the state transition process. Compared with the traditional method, which only uses a single target motion model, the target state estimation and accuracy are more stable and accurate. Estimated number of targets. And this method solves the PHD allocation problem left by CPHD, and the tracking performance is significantly improved.

Description

technical field [0001] The present invention relates to the technical field of target tracking, in particular to a group motion assisted cardinalized probability hypothesis density (Group Motion Assisted Cardinalized Probability Hypothesis Density, GMA-CPHD) filtering method. Background technique [0002] As target tracking scenarios become more and more complex, the requirements for target tracking technology are also increasing. At present, sensors need to track more than just a single target or a small number of multiple targets. Tracking targets often appear in clusters, such as moving people in civilian scenes and traffic on the road; it is more common in military scenes, such as Tanks, armored vehicles, aircraft and other combat units and combat formations at all levels, cluster (multi-warhead) missiles, and the latest drone battle groups. In traditional target tracking, the prediction of target motion is often based on a single target motion model, but the motion of ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20G06F17/16
CPCG06F17/16G06F30/20
Inventor 卢哲俊田彪胡卫东刘永祥黎湘
Owner NAT UNIV OF DEFENSE TECH
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