Sparse array design method and device based on frequency domain broadband beam forming

Abstract

The invention provides a sparse array design method based on frequency domain broadband beam forming. The method comprises the following steps: performing J-point discrete Fourier transform on a received signal to obtain J discrete frequency points, and then replacing J frequency band adjacent narrowband signals by using J discrete frequency point signals; taking a central frequency f0 as a reference frequency to obtain a focusing matrix T(fk) of each frequency point, focusing covariance matrixes of all the frequency points on the reference frequency by using the focusing matrix T(fk), and then averaging the covariance matrixes to obtain a focused received data covariance matrix; constructing an objective function from the perspective of maximizing the signal-to-noise ratio of the array output; optimizing the objective function; obtaining a final form of the objective function according to the optimized iteration expression of the objective function; and performing iterative solution to obtain an optimal sparse array, solving the weight and performing beam forming. The sparse array design method based on frequency domain broadband beam forming reduces the complexity of data processing, reduces the radio frequency cost, increases the freedom degree of the array and obtains the sparse array with optimal array gain.

Description

technical field [0001] The invention belongs to the field of array signal processing and adaptive antenna control, in particular to a sparse array design method and device based on frequency-domain broadband beamforming. Background technique [0002] Beamforming technology has experienced nearly half a century of development, especially in the past 30 years, it has been rapidly broken through, and has been widely used in radar, sonar and communication systems. Beamforming is also called spatial filtering. The sensor array of the filter is composed of Composed of multiple array elements, they are arranged in spatial positions according to a certain method. By sampling signals from different directions in space, and then through weighting processing, the desired signal can be enhanced, sidelobe beams can be suppressed, or null traps can be formed in the interference direction. Reduce the impact of interference and noise, so that the output signal of the array can be optimized ...

AI Technical Summary

Problems solved by technology

[0005] At present, the research on sparse array design mainly focuses on the narrow band, such as designing the array structure according to the given pattern main lobe width and side lobe level level. For example, Emmanuel J. et al. proposed the minimum From the perspective of maximizing array gain, Wang Xiangrong et al. proposed a sparse array design method based on multiple expected sources. In terms of sparse array design based on broadband beamforming, Matthew B et al. proposed a sparse array design method based on broadband TDL structure. From the perspective of compressed sensing (CS), the weight and correlation coefficient of array elements are jointly minimized to obtain Sparse arrays, but this method has a huge amount of calculation and high processing complexity

And among the existing algorithms, there is no method for designing sparse arrays based on broadband frequency domain structures

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