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Multi-constraint rectangular array thin cloth optimization method based on area normalization strategy

A technology of rectangular array and optimization method, applied in the field of array synthesis, to achieve the effect of reducing the peak side lobe level, reducing the computational complexity, and improving the optimization ability

Active Publication Date: 2020-11-10
HARBIN ENG UNIV
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Problems solved by technology

[0004] The invention of this application aims at the sidelobe level suppression problem of rectangular planar arrays under multi-constraint conditions, and proposes a multi-constraint rectangular array sparse distribution optimization method based on the area normalization strategy

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  • Multi-constraint rectangular array thin cloth optimization method based on area normalization strategy
  • Multi-constraint rectangular array thin cloth optimization method based on area normalization strategy
  • Multi-constraint rectangular array thin cloth optimization method based on area normalization strategy

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Embodiment Construction

[0043] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0044] A multi-constraint rectangular array sparse distribution optimization method based on an area normalization strategy of the present invention specifically includes:

[0045] (1.1) Taking the lowest peak side lobe level as the optimization goal, an area normalization strategy is proposed to simplify the rectangular array structure and reduce the computational complexity;

[0046] (1.2) The gray wolf optimization algorithm based on the dynamic weight strategy is used to realize the multi-constrained rectangular array sparse optimization, speed up the algorithm convergence speed, and improve the optimization ability.

[0047] The method features (1.1) include:

[0048] (2.1) Assuming that there is a rectangular planar array with an array aperture of 2L×2H on the xoy plane, the number of array elements is 4N, the array elements ar...

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Abstract

The invention provides a multi-constraint rectangular array thin cloth optimization method based on an area normalization strategy. A rectangular planar array sidelobe level suppression problem underthe multi-constraint condition is mainly studied. The method comprises the steps of initializing parameters through a good point set method; optimizing an array structure by calculating a normalized area coefficient; and updating the grey wolf position by using a dynamic weighting strategy, and completing sparse rectangular planar array optimization by using a grey wolf optimization algorithm. Therectangular array structure can be simplified, the operation complexity is reduced, the algorithm optimization capability is improved, and the peak sidelobe level is reduced.

Description

technical field [0001] The present invention relates to a multi-constraint rectangular array sparsely distributed optimization method based on an area normalization strategy, which is a sidelobe level suppression problem of a rectangular sparsely distributed array constrained by the array aperture, the minimum array element spacing and the number of array elements on the ring. It belongs to the field of array synthesis. Background technique [0002] Array antennas are widely used in civil and military fields such as radar, broadcasting, and navigation because they can easily obtain high-gain, low-sidelobe, and narrow-beam patterns. In the initial research stage of array antenna, uniform array has been widely researched and applied due to its simple mathematical treatment, easy design and implementation. Compared with a uniform array, a sparse array has a higher degree of design freedom, and can achieve the same effect with fewer array elements, which can effectively reduce ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06F17/16G06N3/00
CPCG06F30/20G06F17/16G06N3/006
Inventor 国强王亚妮戚连刚袁鼎李佳莹于添铎
Owner HARBIN ENG UNIV
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