Ground target tracking and approaching based on multi-rotor drone and kernel correlation filtered visual detection

doi:10.7523/j.ucas.2020.0002

Abstract

Abstract: Currently, ground target tracking and approaching based on drone is one of the hot spots for research in the military and civilian sectors. Aiming at the problems of relative motion and guidance control in the tracking and approaching of ground targets based on UAV platform, DJI multi-rotor aircraft platform was selected to design a ground station system based on Android. The system uses an improved kernel correlation filtering visual detection algorithm to complete ground target tracking and position locking. It uses the distance between the drone and the target as a scale factor to achieve multiscale tracking, and integrates FHOG + Lab + LBP features to represent the target to increase the tracker.Robustness. Proportional guidance law is used to control the multi-rotor aircraft to complete the target tracking and approaching tasks. The experimental surface improved algorithm has improved success rate and accuracy compared with the original algorithm. At the same time, the use of proportional guidance can control the multi-rotor drone to complete the tracking and approaching tasks.

Key words: target tracking, proportional guidance, correlation filtering

CLC Number:

TP391.9

WANG He, BU Zhiyong, TAN Chong. Ground target tracking and approaching based on multi-rotor drone and kernel correlation filtered visual detection[J]. Journal of University of Chinese Academy of Sciences, 2022, 39(2): 217-223.

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