Radar and video fusion traffic target tracking method and system, equipment and terminal

Abstract

The invention belongs to the technical field of traffic target tracking, and discloses a radar and video fusion traffic target tracking method and system, equipment and a terminal. The method comprises the steps of: determining a single-sensor target tracking problem, namely selecting a platform bridge test scene to carry out radar and video data collection and analysis; performing space-time matching, namely selecting an open site with a high test position, and controlling the number of targets; performing coordinate system matching debugging by adopting single-target test scene data; and constructing a radar and video fusion algorithm based on a fuzzy set theory, namely carrying out target classification and fuzzy evaluation problem classification, and determining a target judgment criterion. According to the radar and video fusion traffic target tracking method and system, two common traffic information acquisition sensor millimeter wave radars and cameras are selected, a radar and video fusion traffic target tracking algorithm based on a fuzzy set is provided, and high-precision and high-accuracy target tracking is realized by using a multi-sensor fusion algorithm under the condition of reducing the complexity of a single-sensor tracking algorithm.

Description

technical field [0001] The invention belongs to the technical field of traffic target tracking, and in particular relates to a radar and video fusion traffic target tracking method, system, equipment and terminal. Background technique [0002] At present, the intelligent transportation system collects various road traffic information in a complex environment and integrates multiple information to achieve the purpose of all-round detection, perception and decision-making. Among them, traffic information collection is the first step of the intelligent transportation system and the basis for subsequent data analysis. One of the key issues that need to be solved in the process of acquiring traffic information is multi-target tracking in complex environments, and the accuracy of target tracking directly affects the analysis, judgment and processing of traffic status by the subsequent intelligent traffic system. [0003] In actual traffic scenarios, each sensor has some advantage...

AI Technical Summary

Problems solved by technology

[0007] (2) The form of information collected by millimeter-wave radar is not intuitive. If you want to obtain more detailed information such as the shape of the detected target, you often need more complex signal processing algorithms, and the visibility is not strong

[0008] (3) The camera is greatly affected by weather and light when collecting data, and its ability to acquire depth information such as the speed of the target is weak, and the amount of calculated data is also large, and its processing speed and efficiency will be relatively slow

[0009] (4) The data volume of a single sensor is too thin to realize the construction of an intelligent transportation system, and due to its own structure and monitoring range limitations, there will always be false detection and missed tracking

[0010] The difficulty in solving the above problems and defects is: the current radar and video fusion algorithm is mainly set through specific scenarios, which is not universal, and in the field of traffic management, the relevant research on multi-target tracking based on radar and video fusion Fewer, still in its infancy; for the data collected by two sensors in different dimensions, it is difficult to accurately match time and space; it is difficult to design a decision-making scheme to accurately judge the target during fusion

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