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A multi-sensor multi-target joint detection, tracking and classification method

A classification method and a joint detection technology, which is applied in the directions of instruments, calculations, character and pattern recognition, etc., can solve problems such as the inability to obtain a joint optimal solution, the failure to consider decision-making and estimated correlation, and the inability to give decisions, etc.

Active Publication Date: 2022-02-08
SHANGHAI JIAOTONG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-sensor multi-target joint detection, tracking and classification method to solve the existing method because the correlation between decision-making and estimation cannot be obtained and the joint optimal solution cannot be given. Questions about explicit decisions and corresponding estimated outcomes

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  • A multi-sensor multi-target joint detection, tracking and classification method
  • A multi-sensor multi-target joint detection, tracking and classification method
  • A multi-sensor multi-target joint detection, tracking and classification method

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[0041] Next, the technical solutions in the embodiments of the present invention will be described below in conjunction with the drawings of the present invention. EXAMPLES, those of ordinary skill in the art will belong to the scope of the present invention without making creative labor.

[0042] In order to facilitate the understanding of the embodiments of the present invention, the following will be explained by the specific embodiments in conjunction with the accompanying drawings, and various embodiments do not constitute a limitation of the embodiments of the present invention.

[0043] This embodiment is provided with a multi-object multi-objective combination detection, tracking and classification method, including the following steps:

[0044] S1: Given the target category identification framework, including the category of J target, the first value of a given multi-objective state, define a new Bayesian risk, including: Setting the category decision loss for more target...

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Abstract

The invention provides a multi-sensor multi-target joint detection, tracking and classification method, which is characterized in that it includes the following steps: S1: given the initial value of the multi-target state, defining a new Bayesian risk; S2: in the Under the conditions of the category assumptions in the above category hypothesis set, predict the multi-target state to obtain the prior state distribution of multiple targets; S3: under the condition of the category decision set, calculate the multi-target posterior density at time k, and obtain the posterior Check the state distribution of multiple targets; S4: Calculate the multi-target detection loss, state estimation loss and classification loss under different decision-making conditions; S5: According to the detection loss, state estimation loss and classification loss, the multi-target Estimation and Classification Optimal Solutions of Objectives. The method is easy to implement and provides important technical support for multi-sensor network environment perception system.

Description

Technical field [0001] The present invention relates to object detection sensor technology, particularly to a multi-sensor multi-target joint detection, tracking and classification. Background technique [0002] Joint multi-sensor multi-target detection, tracking and classification is an important and complex issue battlefield environmental monitoring need to be addressed. To solve this problem is to monitor the area of ​​military targets (ships, aircraft, missiles) detection, tracking and identification. In practical applications, poly (heterogeneous) network is a common sensor means. The system generally includes a plurality of types of sensors, such as radar (the Radar), infrared (IR), Electronic Support (the ESM), Identification Friend or Foe (IFF) and the like, using the measuring and the complementary information between the sensor fusion, the target can be improved the probability of finding a comprehensive tracking accuracy, and recognition accuracy. [0003] To solve thi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06V2201/07G06F18/24155
Inventor 敬忠良李旻哲
Owner SHANGHAI JIAOTONG UNIV
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