Unmanned aerial vehicle flight path planning decision-making method based on fusion weighing

A technology for unmanned aerial vehicles and track planning, applied in the direction of navigation calculation tools, etc., can solve problems such as too high weighting, untimely weighting, and too subjective, etc., to achieve easy implementation, simple decision-making process, and no need for consistency checks Effect

Active Publication Date: 2017-05-17
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

The most commonly used weighting method is the expert experience assignment method. This method has the disadvantages of being too subjective and the weighting is not timely. However, the commonly used objective weighting methods such as the attribute entropy value method and the deviation maximization method have the disadvantages of internal differences in attributes. When the sex is too large, the disadvantage of giving too high a weight

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  • Unmanned aerial vehicle flight path planning decision-making method based on fusion weighing
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  • Unmanned aerial vehicle flight path planning decision-making method based on fusion weighing

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Embodiment 1

[0099] Step 1. Parameter input:

[0100] (a) The input track set to be selected is 10 track point sets to be selected;

[0101] (b) The dimension of the input attribute cost matrix is ​​10×4:

[0102]

[0103] (c) Data normalization, the dimension of the normalized attribute cost matrix is ​​10×4:

[0104]

[0105] Step 2. Objective empowerment;

[0106] (a) Normalize the columns of the attribute cost matrix, calculate the attribute entropy, and obtain the attribute entropy vector E=[0.9382,0.6699,0.580] T 4,

[0107] The weight of the first objective weighting is

[0108] (b) Calculate the difference coefficient ratio matrix, get

[0109] (c) Calculate the importance comparison matrix, get

[0110] (d) Obtained by regular decomposition, the largest eigenvalue of the importance comparison matrix λ max = 3.2263;

[0111] The adjusted weight is w * =[0.0694,0.2777,0.3467,0.3063] T .

[0112] Step 3, implicit association:

[0113] (a) The ideal trajectory sc...

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Abstract

The invention discloses an unmanned aerial vehicle flight path planning decision-making method based on fusion weighing. The unmanned aerial vehicle flight path planning decision-making method comprises the following steps: firstly inputting a to-be-selected flight path set for unmanned aerial vehicle flight path planning and a corresponding attribute cost matrix; performing objective weighting on the column-normalized attribute cost matrix through a fusion attribute entropy method based on an analytic hierarchy process; then calculating a point correlation coefficient of each of flight paths to the best flight path and a correlation metric matrix and further obtaining a correlation metric ranking; finally outputting the flight path with maximum correlation metric as a decision-making result. Compared with an existing flight path planning decision-making method, the flight path planning decision-making method disclosed by the invention has the benefits that an objective weighting result with smaller difference can be obtained according to a secondary adjusted weight; meanwhile, the subjectivity of weighing is avoided, and the defects of the single attribute decision-making result during final decision-making are overcome; the flight path planning decision-making method is simple and is strong in realizability.

Description

technical field [0001] The present invention relates to the field of unmanned aerial vehicle track planning and multi-attribute decision-making, in particular to a method for unmanned aerial vehicle track planning and decision-making based on fusion weighting, which is applied to the track decision-making stage after unmanned aerial vehicle track planning. In the mission planning stage before the high-speed flight of the unmanned aerial vehicle, for the set of candidate trajectories obtained through off-line trajectory planning, the trajectory decision-making optimization is carried out through objective weighting and implicit association. Background technique [0002] UAV track planning refers to the calculation of the position where the UAV should appear at each moment when the flight mission is performed under the premise of comprehensively considering the maneuverability of the UAV and the characteristics of the flight mission. UAV trajectory planning is not only to calc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 李景文姚锟孙兵王峰
Owner BEIHANG UNIV
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