Convex optimization algorithm-based radar array sum-difference beam directional diagram optimization method

Abstract

The invention discloses a convex optimization algorithm-based radar array sum-difference beam directional diagram optimization method. The method comprises the steps of determining that a radar circular array containing M array elements is uniformly distributed on a circumference with the radius being R, and then determining a sum beam main lobe area, a sum beam null steering area, a sum beam side lobe area, a sum beam low side lobe area, a difference beam main lobe area, a difference beam null steering area, a difference beam side lobe area and a difference beam low side lobe area; respectively obtaining a cost function for restraining the sum beam main lobe area and a cost function for restraining the difference beam main lobe area; further obtaining a sum beam directional diagram comprehensive optimization model of the radar circular array and a difference beam directional diagram comprehensive optimization model of the radar circular array, and calculating a radar circular array sum beam optimal weight vector; sequentially obtaining a slope of an angle error normalization curve of an expected target and a curve slope of an angle error curve of a radar circular array sum-difference beam directional diagram to be optimized, and calculating an optimal weight vector of a radar circular array difference beam.

Description

technical field [0001] The invention belongs to the field of radar technology, in particular to a radar array and differential beam pattern optimization method based on a convex optimization algorithm, which is suitable for radar circular array and beam and differential beam pattern optimization. Background technique [0002] With the development of radar technology, phased array radar is more and more applied to practical engineering projects. However, the current phased array radar antennas are basically linear array and traditional planar array antennas. The structure of the line array is relatively simple and easy to handle, but in practice it can only cover an azimuth angle of about 120 degrees, and its characteristics such as gain and pattern vary with the scanning angle, especially the scanning angle When the direction deviates from the normal direction of the array, the performance of the array drops sharply, so these greatly limit its application range. The tradit...

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Problems solved by technology

For the beam pattern optimization of circular arrays, the comprehensive algorithms mainly used include genetic algorithm, simulated annealing algorithm, particle swarm algorithm, and ant colony algorithm. These algorithms are essentially random-based natural algorithms, and there is a comprehensive process A large-scale search is required in this method, which leads to the slow convergence speed of this type of algorithm, and it is easy to fall into problems such as local optimal solutions.

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