A Multiple Maneuvering Target Tracking Method Based on Random Set Theory

A mobile target tracking and multi-target technology, which is applied in the research field of multi-maneuvering target tracking technology under the random set theory, can solve the problems of multi-target mobility, inconsistency, and difficult to apply to complex scenes with high mobility

Active Publication Date: 2019-07-19
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] The purpose of the present invention is to aim at the defect of background technology, research and design a kind of multi-maneuvering target tracking method based on random set theory, realize the multi-maneuvering target tracking based on generalized label multi-target Bernoulli filter, solve existing generalized label multi-target The Bernoulli filter is difficult to apply to the problem of complex scenes with high mobility of the target
This method has the characteristics of strong robustness, wide adaptability, and high estimation accuracy. It can effectively solve the problem of strong and inconsistent multi-target maneuverability that often occurs in practical applications, and realizes maneuvering multi-target tracking in complex scenes. Estimated target motion model

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  • A Multiple Maneuvering Target Tracking Method Based on Random Set Theory
  • A Multiple Maneuvering Target Tracking Method Based on Random Set Theory
  • A Multiple Maneuvering Target Tracking Method Based on Random Set Theory

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Embodiment Construction

[0058] The present invention mainly adopts the method of computer simulation to verify, and all steps and conclusions are verified correctly on MATLAB-R2010b. The specific implementation steps are as follows:

[0059] Step 1. Parametrically characterize the generalized labeled multi-objective Bernoulli distribution:

[0060]

[0061] Among them, π(X) represents the generalized label multi-objective Bernoulli posterior probability distribution, X represents the target state set, and Ξ is the discrete space; represents the set of target tracks, means all A collection of subsets, I is a collection of any number of targets; w (I,ξ) Represents the weight, non-negative and satisfies p (ξ) (·,l) is a probability density function that satisfies ∫p (ξ) (x,l)dx=1. Through this step, with the parameter w (I,ξ) and p (ξ) (·,l) fully characterizes the generalized labeled multi-objective Bernoulli distribution.

[0062] Step 2, multi-objective state space is carried out aug...

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Abstract

The invention discloses a multi-maneuvering target tracking method based on random set theory, which is characterized in that firstly, the multi-target state space is augmented, and the model dimension is increased on the basis of the original dynamic information, so as to realize the target model Then, based on the jumping Markov system, the state transition function and the likelihood function are augmented to contain model information; finally, the prediction of the augmented multi-model generalized label multi-objective Bernoulli filter is realized And update process, and extract the target state and estimate the target motion model, so as to solve the tracking problem of maneuvering multiple targets. This method has the characteristics of strong robustness, wide adaptability, and high estimation accuracy. It can effectively solve the problem of strong and inconsistent multi-target maneuverability that often occurs in practical applications, and realizes maneuvering multi-target tracking in complex scenes. Estimate the target motion model.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to the research on multi-maneuvering target tracking technology under random set theory. Background technique [0002] Multi-target tracking is one of the research hotspots in the field of radar. Its difficulties mainly focus on: 1) The measurement values ​​received by the radar are not all from the target, but also include clutter, false alarm, interference, etc.; 2) Due to the new Targets appear, old targets disappear, and the number of targets changes over time. [0003] In the past few decades, multi-target tracking mainly uses the traditional tracking method based on data association. The basic idea is to decompose the multi-target tracking problem into several sub-problems, and filter each single target. The measured values ​​are correctly correlated. However, in engineering applications, data association is not an easy task, and it is computationally intensive and error-prone. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/66
CPCG01S13/66
Inventor 易伟姜萌陈方园谌振华王佰录李溯琪孔令讲
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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