Array antenna directional diagram fitting method based on weighted normal regression method

Abstract

The invention discloses an array antenna directional diagram fitting method based on a weighted normal regression method. Quick integration of a directional diagram is realized based on a weighted normal regression technology. The array antenna directional diagram fitting method mainly comprises the following steps: firstly, simulating an antenna array by using electromagnetic full-wave simulation software, extracting an array element active directional diagram, and building an array manifold: for an array requiring quick integration, only a middle array element is extracted, and a wave path-difference is introduced according to mutual positions of the array elements in the array to build the array manifold; building a desired directional diagram vector and a weighted matrix according to an integration demand; constructing an augmented matrix by using the weighted array manifold and the desired directional diagram vector, performing singular value decomposition, and extracting a feature vector of the minimum singular value; and finally, obtaining an exciting vector I of an array element port according to the feature vector to complete an array directional diagram integration. According to the array antenna directional diagram fitting method based on the weighted normal regression method, the problem that the conventional direct solving technology for directional diagram integration has difficulty in completing integration of irregular arrays and the problem that a bionic optimization algorithm is long in time consumption for large-size array integration are solved.

Description

technical field [0001] The invention belongs to the technical field of array antenna comprehensive design, and relates to a normal regression method for curve fitting. The software extracts the active pattern of the array element, and uses weighting technology to improve the success rate of pattern approximation. The invention is specifically a method for fitting the pattern of an array antenna based on a weighted normal regression method. Background technique [0002] With the development of multi-mission and multi-function radar technology, the scale of the array is getting larger and larger. The traditional analysis and synthesis method is difficult to complete the design of the complex array and waveform, and the complexity of the bionic optimization algorithm also increases with the increase of the array scale. , existing methods face huge time and memory consumption problems in large array synthesis problems. [0003] With the development of computer technology, the p...

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Problems solved by technology

However, most of the existing literatures directly use LSM for iteration, or combine LSM with optimization algorithm for iterative array synthesis, which fails to take full advantage of the speed advantage of the least squares method for direct solution; at the same time, the LSM algorithm ignores the However, it is difficult to establish an accurate array flow pattern for a real array. Even the array flow pattern obtained through simulation or testing also includes calculation errors or test errors. Therefore, in essence, the array synthesis should not ignore the array flow pattern. slight error

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