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Unmanned aerial vehicle robust tracking method for maneuvering target

A maneuvering target, machine robust technology, applied in the field of robust maneuvering target tracking

Active Publication Date: 2019-03-19
ZHEJIANG GONGSHANG UNIVERSITY
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  • Description
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AI Technical Summary

Problems solved by technology

[0005] The present invention discloses a robust maneuvering target tracking method aimed at the practical problems encountered by UAVs in complex environments for single target tracking

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Embodiment Construction

[0056] The present invention will be described in further detail with regard to specific implementation below, and the overall flow of the method can refer to figure 1 .

[0057] Step 1: Establishing the student's t-distribution jump Markov model when the UAV performs single maneuvering target tracking;

[0058] figure 2 Described the working scene setting of an embodiment of the present invention, the setting of concrete parameter and the hypothesis of scene are not limited to the setting described in this figure, this figure has shown UAV and moving target at two adjacent sampling moments (k-1 and the spatial position information at time k). As shown in the figure, a UAV flies in a three-dimensional space with an x-y-z coordinate system and tracks a moving target. The tracked target is a ground target. It can be considered that its vertical height does not change and its height is 0, that is, the target is only Moving on the x-y plane, at this time the UAV can also maint...

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Abstract

The invention discloses an unmanned aerial vehicle (UAV) robust tracking method for a maneuvering target. The method is suitable for UAV tracking for a target with a maneuvering behavior and suitablefor occasions, with target state sudden change, complex observation environments and the like, with high demands for target tracking robustness. According to the method, a jump Markov model is used for describing multi-model switching of the maneuvering target and modelling student t distribution with a heavy tail characteristic on the process noise, observation noise and system state, so that theinfluence of the state sudden change or abnormal observation is eliminated. Under an interaction-type multi-model frame, a model proportion density function with student t distribution is subjected to interaction processing at first, then a student t distribution function is used as a base for conducting generalized non-linear filtering design, through a filtering algorithm, each sub model can obtain a robust estimation result, and finally an updated model proportion is used for fusing the estimation results of all sub models to obtain final target state estimation.

Description

technical field [0001] The invention relates to a robust maneuvering target tracking method, which belongs to the technical field of combining recursive Bayesian estimation theory and multi-source information fusion theory to enhance the robustness of unmanned aerial vehicles for maneuvering target tracking. Background technique [0002] Unmanned Aerial Vehicle (UAV) is an aircraft that is driven by its own power system and completes specific actions and tasks autonomously or by remote control without manned driving. UAVs not only show their talents in military fields such as terrain reconnaissance, intelligence collection, and target strikes, but also widely exist in civilian fields such as geographic surveying and mapping, fire surveillance, and search and rescue. With the rapid development of material technology, manufacturing technology, computer technology, and communication technology, UAV itself is gradually becoming miniaturized, lightweight, low-cost, and low-noise....

Claims

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Application Information

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IPC IPC(8): G05B13/02G05B13/04G05D1/10
CPCG05B13/0275G05B13/042G05D1/101
Inventor 沈忱
Owner ZHEJIANG GONGSHANG UNIVERSITY
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