Unmanned aerial vehicle safety early warning method for detecting multiple risk factors based on differential game

Abstract

The invention discloses an unmanned aerial vehicle safety early warning method for detecting multiple risk factors based on differential game. The method comprises the following steps: S1, constructing a state transition model in the flight process of an unmanned aerial vehicle; S2, establishing a differential equation of each state according to the state conversion model; S3, establishing a costfunction under the state transition model; S4, constructing a Hamiltonian equation according to the differential equation of each state and the cost function; and S5, according to the Hamiltonian equation, solving the equation set of the full-footprint cooperative state variable condition and a corresponding attack and defense strategy. The invention provides an unmanned aerial vehicle early warning system capable of detecting multi-aspect danger factors. The unmanned aerial vehicle early warning system can obtain an optimal strategy for judging whether to trigger the early warning system andexecute defense measures in a complex flight environment by utilizing a bilateral maximum principle in the attack and defense process of multi-aspect risk factors, so that the efficiency and quality of unmanned aerial vehicle risk early warning are improved.

Description

technical field [0001] The invention relates to the technical field of safe flight of unmanned aerial vehicle, in particular to a method for early warning of unmanned aerial vehicle safety based on differential game detection of multiple risk factors. Background technique [0002] At present, most drones lack autonomous conflict avoidance capabilities. The reasons behind the safety accidents of UAV flight training are complex and diverse, including subjective factors of personnel and objective factors of reality, internal contradictions and inherent defects of the system, and adverse effects of external conditions. Therefore, the causes of UAV flight safety risks are mainly concentrated in four aspects: personnel, UAV systems, meteorological conditions, airspace and venues. When organizing UAV flight activities, it is helpful to adopt corresponding risk prevention and control strategies. To prevent and defuse drone flight safety risks. [0003] Most of the existing early w...

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Problems solved by technology

From the above research, it can be found that when scholars study UAV threat early warning, most of them are based on the concept of static protection area, which is highly dependent on the detected target information.

In reality, compared with UAVs, UAVs operating in mixed airspace encounter various risk factors that are dynamic, non-cooperative, and poor in information. The danger warning during the event has brought great difficulties, which in turn affects the efficiency and quality of UAV danger warning

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