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A multi-target tracking device based on stochastic finite set theory

A multi-target tracking, limited set technology, applied in the field of multi-target tracking, can solve problems such as unsolvable target missed detection, unknown strength of new targets, difficult engineering application, etc., to improve calculation efficiency, reduce parameter configuration items, and improve effect. Effect

Active Publication Date: 2019-03-08
CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
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Problems solved by technology

Literature (3) focuses on solving the problem of unknown target intensity, and proposes a double threshold method, but it still cannot solve the problem of missing targets
Moreover, in practical applications, a lot of prior information is unknown, such as models of newborn targets and derived targets, information about newborn target strength, target survival rate, detection probability, etc., so these methods are basically difficult to achieve engineering applications

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  • A multi-target tracking device based on stochastic finite set theory
  • A multi-target tracking device based on stochastic finite set theory
  • A multi-target tracking device based on stochastic finite set theory

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Embodiment Construction

[0027] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0028] Such as figure 2 As shown, it is assumed that there are 6 targets moving in a straight line with a uniform speed in a two-dimensional plane (x-y plane), and the state vector is x=[x,v x ,y,v y ] T , x, y represent the positions in the x-direction and y-direction of the x-y plane respectively, v x ,v y respectively represent the speed in the x-direction and y-direction of the x-y plane, and the discrete space motion equation of each target is:

[0029]

[0030] Where F is the state transition matrix, H is the measurement matrix, ω k and υ k are process noise and measurement noise respectively, both...

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Abstract

The invention discloses a multi-target tracking device based on the random finite set theory. A measurement set generator generates a measurement set according to the received sensor measurement and sends the measurement set to a Gaussian component initialization processor. The Gaussian component initialization processor sends the initialized Gaussian component set to the Gaussian component set buffer for storage. The Gaussian component matrix generator simultaneously receives the measurement set generated by the measurement set generator and the Gaussian component set stored in the Gaussian component set buffer at the latest time, obtains the Gaussian component matrix by solving, and sends the Gaussian component matrix to the Gaussian component matrix dimension expander. The Gaussian component matrix expander simultaneously receives the measurement set generated by the measurement set generator. The device of the invention adds the threshold filtering and generation failure filteringmechanism to identify the validity of the Gaussian component, screens and filters the Gaussian component matrix, improves the calculation efficiency, protects the generation failure, and improves therobustness of the processing process.

Description

technical field [0001] The invention relates to a multi-target tracking technology, in particular to a multi-target tracking device based on random finite set theory. Background technique [0002] Multi-target tracking technology is one of the key technologies in many fields such as radar data processing, image / video processing, and robot navigation. process. Traditional target tracking algorithms are mainly methods based on data association, including track initiation, association, and track termination, among which correct association is a prerequisite for stable target tracking, so the association algorithm has become one of the most complicated processes. One, such as nearest neighbor method, joint probability data association method and multiple hypothesis tracking (MHT) algorithm. [0003] In recent years, the multi-target tracking method based on the random finite set (RFS) theory has become a research hotspot. This method processes the sensor measurement set based ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06T7/277
CPCG06T7/277G06F18/25
Inventor 武慧勇钮俊清任清安唐匀龙马志娟郭佳意王建富王文洋
Owner CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST