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Particle filtering method and device based on TSK fuzzy model and storage medium

A particle filter and fuzzy model technology, applied in the field of target tracking, can solve the problems of poor particle filter performance and reduced target tracking performance, and achieve the effect of improving robustness and diversity, and enhancing target tracking performance

Active Publication Date: 2019-10-18
SHENZHEN UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the embodiments of the present invention is to provide a particle filter method, device and storage medium based on the TSK fuzzy model, which can at least solve the problem of target tracking caused by the poor particle filter performance in nonlinear and non-Gaussian scenarios in related technologies. slow performance issues

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  • Particle filtering method and device based on TSK fuzzy model and storage medium
  • Particle filtering method and device based on TSK fuzzy model and storage medium
  • Particle filtering method and device based on TSK fuzzy model and storage medium

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no. 1 example

[0029] In order to solve the technical problem of poor target tracking performance caused by poor particle filter performance in nonlinear non-Gaussian scenes in related technologies, this embodiment proposes a particle filter method based on the TSK fuzzy model, such as figure 1 Shown as a schematic diagram of the basic flow of the particle filter method provided in this embodiment, the particle filter method proposed in this embodiment includes the following steps:

[0030] Step 101: Construct an importance density function of the particle filter based on the TSK fuzzy model.

[0031] Specifically, in this embodiment, the TSK fuzzy model is introduced to model the dynamic system of the target and construct an effective importance density function. Aiming at the uncertainty modeling problem of the target dynamic model, this embodiment adopts a spatially constrained TSK fuzzy model, in which the spatial feature information is represented by multiple semantic fuzzy sets, and a genera...

no. 2 example

[0129] In order to solve the technical problem of poor target tracking performance caused by poor particle filter performance in nonlinear non-Gaussian scenes in related technologies, this embodiment provides a particle filter device based on the TSK fuzzy model. For details, please refer to image 3 The particle filter device shown, the particle filter device of this embodiment includes:

[0130] The construction module 301 is used to construct the importance density function of the particle filter based on the TSK fuzzy model;

[0131] The extraction module 302 is used to extract N particles from the importance density function to form a particle state set of the target;

[0132] The first calculation module 303 is used to calculate the weights of the particles in the particle state set, and to normalize the weights;

[0133] The second calculation module 304 is configured to calculate the state and covariance of the target at time k based on the normalized weight value and the parti...

no. 3 example

[0169] This embodiment provides an electronic device, see Figure 5 As shown, it includes a processor 501, a memory 502, and a communication bus 503. The communication bus 503 is used to realize the connection and communication between the processor 501 and the memory 502; the processor 501 is used to execute one or more of the storage in the memory 502. A computer program to implement at least one step of the method in the first embodiment.

[0170] This embodiment also provides a computer-readable storage medium, which is included in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules, or other data). Volatile or non-volatile, removable or non-removable media. Computer-readable storage media include but are not limited to RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory) ), flash memory or other storage technology, CD-ROM (Compact Disc ...

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Abstract

The embodiment of the invention discloses a particle filtering method and device based on a TSK fuzzy model and a storage medium. The method includes: constructing an importance density function of particle filtering based on the TSK fuzzy model; extracting N particles from the importance density function to form a particle state set of the target; calculating weights of particles in the particlestate set, and normalizing the weights; and calculating the state and covariance of the target at the moment k based on the normalized weight and the particle state set. Through the implementation ofthe invention, the TSK fuzzy model is introduced to model the dynamic system of the target, an effective importance density function is constructed, the robustness and diversity of particle sampling are effectively improved, and the target tracking performance in a non-linear non-Gaussian environment is enhanced.

Description

Technical field [0001] The present invention relates to the technical field of target tracking, in particular to a particle filtering method, device and storage medium based on a TSK fuzzy model. Background technique [0002] As an effective method to optimally deal with nonlinear and non-Gaussian problems, particle filtering has been considered by the academia to be one of the most promising state estimation methods. It is widely used in various nonlinear filtering fields, such as image monitoring and target Location and tracking, environmental monitoring and other fields. [0003] However, at present, when the target motion model and observation model are uncertain, the filtering performance of the particle filter is reduced, and when the target is maneuvering, the prediction error increases more obviously, which leads to the increase of the variance of the prior distribution of the target state and the decrease of the target. Track performance. It can be seen that there is an ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/15G06F17/16G06T7/277G06N7/02
CPCG06F17/15G06F17/16G06T7/277G06N7/02G06T2207/20024
Inventor 李良群李小香谢维信刘宗香
Owner SHENZHEN UNIV
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