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The accuracy and confidence level of the unmanned aerial vehicle(UAV) landing range are of great significance for objectively assessing the UAV’s ground risk. The uncertain wind field and complex electromagnetic environment are the main causes of uncertainty regarding UAV failure and landing range. Given the particle assumption in the case of complete failure of the UAV, firstly, a dynamic model of the UAV trajectory descent with the initial position and velocity as the boundary value and the wind speed vector and the initial position as random variables was constructed, and the failure and landing range of the UAV were determined by Monte Carlo simulation. Secondly, a geometric method for determining the envelope of the UAV ground risk buffer was proposed, and the quantitative determination of the ground risk buffer of the entire UAV track was realized. Finally, the method proposed was verified by taking an aerial inspection route as example and compared with the buffer protection area of the UAV in different wind fields and under various operating conditions, the effect of uncertain wind field and its operating conditions on the ground crash range of the UAV was studied, and the ground risk buffer zone under different operating conditions was established. The results show that falling at higher speed and higher altitudes under stronger winds yields a wider impacting area and a larger ground risk buffer.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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