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DOA tracking method based on multi-Bernoulli filtering

A multi-Bernoulli, DOA technology, applied in the field of DOA tracking, can solve problems such as the number of signal sources known in advance

Pending Publication Date: 2021-02-26
GUILIN UNIV OF ELECTRONIC TECH
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AI Technical Summary

Problems solved by technology

The classic DOA parameter estimation algorithms generally belong to the DOA estimation of static signal sources, such as the DOA estimation algorithm based on beamforming, multiple signal classification (MUSIC) and rotation invariant subspace technique (ESPRIT) and other algorithms, and one of these algorithms The main disadvantage is that the number of signal sources must be known in advance

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  • DOA tracking method based on multi-Bernoulli filtering
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  • DOA tracking method based on multi-Bernoulli filtering

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Embodiment Construction

[0063] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0064] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...

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Abstract

The invention discloses a DOA tracking method based on multi-Bernoulli filtering. The method comprises the following steps: receiving superposed measurement data through a sensor array; obtaining filtering posteriori information obtained by a multi-Bernoulli filter at the k-1 moment, wherein the filtering posteriori information comprises the existence probability of a Bernoulli component and a spatial distribution probability density function of a target; predicting the multi-Bernoulli components according to a multi-Bernoulli filter to obtain multi-Bernoulli posteriori information at the moment k; extracting a target state according to the predicted multi-Bernoulli components; and performing iteration, k is equal to k + 1 until all moments are processed. Measurement information does not need to be processed, and the calculated amount is reduced; and during tracking, the number of signal sources does not need to be known, and the signal sources are tracked in real time by directly utilizing prediction prior and current measurement information. A simulation result shows the effectiveness of the algorithm.

Description

technical field [0001] The invention belongs to the technical field of DOA tracking, and in particular relates to a DOA tracking method based on multi-Bernoulli filtering. Background technique [0002] In recent years, multi-target tracking algorithms based on random finite sets (Random Finite Sets, RFS) have opened up a new field of multi-target tracking. ), so that the single-objective Bayesian filtering can be extended to the multi-objective field, and the RFS filtering algorithm under the Bayesian framework can be obtained. The multi-target filter tracking algorithm based on RFS has been widely used in target monitoring and defense, unmanned driving and robots, remote sensing, computer vision, biomedicine, modern communications and other fields. [0003] The formulation of the RFS-based multi-object filter tracking algorithm is derived in the optimal multi-object Bayesian filtering framework, however, such an optimal RFS Bayesian filter is usually difficult to compute b...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S3/14
CPCG01S3/143Y02D30/70
Inventor 薛秋条邹宝红吴孙勇王力樊向婷孙希妍纪元法蔡如华符强严肃清王守华
Owner GUILIN UNIV OF ELECTRONIC TECH
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