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
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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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