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Multi-target tracking method based on measure-driven target birth intensity PHD (MDTBI-PHD)

A multi-target tracking and target strength technology, which is applied in the PHD multi-target tracking field based on measurement-driven new target strength estimation, can solve the problems such as the recursive formula form of new target strength is not given, so as to reduce the calculation complexity and ensure Effect of Tracking Accuracy

Inactive Publication Date: 2016-08-10
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Summary
  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

However, it simply distinguishes new goals from existing goals, and does not give a recursive formula for the strength of new goals

Method used

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  • Multi-target tracking method based on measure-driven target birth intensity PHD (MDTBI-PHD)
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  • Multi-target tracking method based on measure-driven target birth intensity PHD (MDTBI-PHD)

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Embodiment Construction

[0024] According to the accompanying drawings, the technical solution of the present invention is described in detail.

[0025] In the present invention, the target state and target measurement information at time k are respectively expressed as a random state set X k with random measurement set Z k :

[0026] x k ={x k，1 , x k，2 ,...,x k，i ,...,x k，M(k)}=S k|k-1 (X k-1 )∪B k|k-1 (X k-1 )∪Γ k (1)

[0027] Z k = { z k , 1 , z k , 2 , ... , z k , j , ... , z k , N ( k ) ...

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Abstract

The invention discloses a multi-target tracking method based on measure-driven target birth intensity PHD (MDTBI-PHD), mainly solves the problems in estimating the multi-target motion state and the number of targets when the target birth intensity is unknown. The method comprises the steps of estimating the target state and the clutter state respectively by using an augmented state-space method, thereby avoiding the interference of unknown clutter to the target intensity estimation; constructing a target birth measure set, and estimating the target birth intensity by using a measure-driven method, thereby avoiding dependence on the priori knowledge of the target birth intensity; and implementing the above method using Gaussian mixture probability hypothesis density filter. The method has the advantage of being sensitive to the change in the number of targets, and meanwhile can reduce the computational complexity and significantly improve the tracking accuracy.

Description

technical field [0001] The invention belongs to the field of target tracking, in particular to a PHD multi-target tracking method based on measurement-driven new target intensity estimation. Background technique [0002] Multi-target tracking is a method of estimating the position and velocity of multiple targets using sensor measurement information. This estimation process is a typical filtering problem. Due to complex problems such as clutter interference, target disappearance, and target appearance in the process of multi-target tracking, how to judge the actual number of targets and the corresponding motion status of each target through sensor measurement information is the difficulty of multi-target tracking. [0003] Existing multi-target tracking algorithms mainly include multi-target tracking algorithms based on data association and probability hypothesis density (Probability Hypothesis Density, PHD) filtering algorithms. Among them, the PHD filtering algorithm redu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/20
Inventor 丁勇张祺琛柏茂羽胡忠旺
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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