An Efficient Synthesis Method for Large Sparse Array Antennas Based on Adaptive Probabilistic Learning

Abstract

The invention discloses a large-scale sparse array antenna high-efficiency synthesis method based on adaptive probability learning, which solves the problem of poor radiation characteristics due to poor gradient density distribution of antenna elements within the array aperture and high sidelobes of the direction diagram in the large-scale array antenna sparse array synthesis. , The problem of low efficiency. The present invention combines the layout of the sparse array with the selection probability estimation of the antenna elements, and combines the array synthesis problem with the optimization of the adaptive probability learning model to realize the implementation steps as follows: randomly initialize the distribution of the antenna array elements and construct the initial probability estimation model; use the fast Fu The far-field pattern is quickly calculated by the Liye transform from the excitation coefficient; based on the strategy of probability learning, a new solution is generated according to the probability model to participate in the competition; the far-field pattern is adjusted; the element excitation is obtained by the fast Fourier transform, and the probability is updated Model. When the requirements of the objective function are met or the maximum number of iterations is reached, the optimal sparse array arrangement scheme is output to solve the large sparse array antenna synthesis problem.

Description

technical field [0001] The invention relates to the technical field of array antennas, and relates to a sparse array method for antennas, in particular to the sparse design of large-scale array antennas, and in particular to an efficient synthesis method for large-scale sparse array antennas based on adaptive probability learning. Background technique [0002] Large-scale array antennas have the characteristics of high gain and narrow beam. In the fields of long-distance detection and identification, large-scale arrays have an irreplaceable role. However, with the increase of the aperture of the array antenna, the number of units increases sharply, and the system complexity and manufacturing cost also increase accordingly. Therefore, in applications that mainly require narrow beams and do not pursue maximum gain, a sparse array can be formed by removing part of the antenna elements in the full array without significantly broadening the beam. Sparse arrays contribute to the ...

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Problems solved by technology

[0004] The technical problems to be solved by the present invention are: for the comprehensive existence of a large sparse array antenna, the response time is long, the efficiency is not high, the gradient density distribution of the antenna elements in the array aperture is not good, and then the side lobes of the array antenna pattern are high, and the anti-interference The problem of weak ability and poor radiation effect

Most of the existing technologies regard the excitation of the array unit as an unknown quantity, regard the sparseness of the array as a parameter optimization problem, and realize the selection of the unit by optimizing the unit excitation coefficient, but the optimization method currently used cannot efficiently adapt to the array antenna. The large-scale expansion of large-scale, the comprehensive time-consuming is too long, the convergence quality is poor, and it is easy to fall into the local optimum

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