Method for optimizing linear array antenna radiation pattern
A technology of antenna pattern and optimization method, applied in antennas, instruments, calculation models, etc., can solve problems such as limited adjustment of variable parameters, and achieve the effect of improving probability and speed
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Embodiment 1
[0042] Step 1, set parameters
[0043] According to the requirements of the system, the number of array elements N=10, the operating frequency 1880MHz≤F≤2025MHz, the height of the array element H=30mm, the length of the array element arm L=30mm and the downtilt angle θ max =0°, the level value of the pattern requires that both the upper side lobe and the lower side lobe are suppressed below -20dB.
[0044] Step 2, generate the corresponding level suppression fitness function fitness according to the given level value requirements 1 , level filling fitness function fitness 2 and downtilt angle fitness function fitness 3 .
[0045] The fitness function prototype is:
[0046] fitness 1 =∑(max(f(θ), f 0 (θ))-f 0 (θ)) m +∑abs(max(f(θ), f 0 (θ))-f 0 (θ))
[0047] fitness 2 =∑(min(f(θ), f 0 (θ))-f 0 (θ)) m +∑abs(min(f(θ), f 0 (θ))-f 0 (θ))
[0048] fitness 3 =(f(θ max )-f 0 (θ max )) m +|f(θ max )-f 0 (θ max )|;
[0049] Since the level value given by the s...
Embodiment 2
[0084] Step 1, set parameters.
[0085] According to the requirements of the system, the number of array elements N=10; the working frequency is 1880MHz≤F≤2025MHz; the height of the array element is H=30mm; max =6°; the unit spacing is specified as d(i)=115mm; the excitation amplitudes of 10 units are respectively given as: 1, 1, 1, 1, 1.414, 1.414, 1.414, 1.414, 1.414, 1.414; the pattern level The value requires that the upper side lobe be suppressed to below -20dB, and the first zero value of the lower side lobe is filled to above -15dB.
[0086] Step 2, generate the corresponding level suppression fitness function fitness according to the given level value requirements 1 , level filling fitness function fitness 2 and downtilt angle fitness function fitness 3 .
[0087] The fitness function prototype is
[0088] fitness 1 =∑(max(f(θ), f 0 (θ))-f 0 (θ)) m +∑abs(max(f(θ), f 0 (θ))-f 0 (θ))
[0089] fitness 2 =∑(min(f(θ), f 0 (θ))-f 0 (θ)) m +∑abs(min(f(θ), f 0...
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