A Null Sink Widening Method Based on Sparse Constraint Controlling Sidelobes

Abstract

The invention relates to a null-sag widening method based on sparse constraints to control side lobes, mainly aiming at expected signal mismatch and interference disturbance, including: obtaining the covariance matrix of the data received by the antenna array, and using the Capon spectrum to expand and re-expand the interference interval known in advance The interference plus noise covariance matrix is ​​constructed; the interference covariance matrix is ​​obtained by guiding the vector integration of the interference expansion interval, and the eigenvector corresponding to the large eigenvalue is obtained by the eigenspace method to construct a linear constraint condition; the weight vector solution formula is constructed, and the weight vector is obtained by solving . The method of the present invention has good robustness to expected signal mismatch and realizes null widening, better null depth and lower side lobe.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a zero trap widening method for controlling side lobes based on sparse constraints. Background technique [0002] Array signal processing technology has been widely used in many fields such as radar and communication. Its biggest advantage is that it can perform beamforming in the direction of interest to increase the energy of the signal, and form a gain null in the interference direction. Traditional adaptive beamforming algorithms are mostly proposed for ideal conditions. However, the actual environment is very complex and there are various errors, especially when the interference direction shakes and the beam pointing deviates from the desired signal direction. The forming algorithm not only cannot effectively suppress the interference, but also produces nulls in the direction of the desired signal, which seriously reduces the output SINR. [0003] Aiming at the pr...

AI Technical Summary

Problems solved by technology

Among them, the diagonal loading algorithm will make the zero-sink of the pattern shallower and the loading amount is difficult to control, the linear constraint method will consume too many degrees of freedom of the array, the beamforming method based on the feature space is sensitive to the dimension of the signal subspace, and the covariance-based Robust beamforming algorithms for matrix reconstruction and steering vector estimation have good robustness to steering vector mismatches, but shallow null-trap depth

For the fluctuation of the interference direction caused by the vibration of the antenna platform or the fast movement of the interference, there is currently a CMT (covariance matrix weighted) algorithm, but the CMT algorithm will lead to a shallower null depth while widening the null.

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