阅读说明：本技术 基于支持向量回归的鲁棒自适应波束合成方法 (Robust self-adaptive beam forming method based on support vector regression ) 是由 罗东琦 司宾强 朱纪洪 于 2019-10-21 设计创作，主要内容包括：基于支持向量回归的鲁棒自适应波束合成方法。将接收到的阵列信号表示成复包络列向量的形式,并依次排成数据矩阵形式。将预测误差的平均值作为最小化目标,计算阵列信号向量的协方差矩阵作为正则项的加权矩阵,将原鲁棒自适应波束合成问题转化为一个复空间上的支持向量机回归问题。利用Wirtinger导数和拉格朗日乘子法计算问题的最优解并求得其封闭形式,并提出一种递归算法用于实时处理。本发明能够适用于期望信号方向不准确以及数据量偏小的情形,能自适应地、实时地寻找最优的波束合成向量,具有很高的准确性、快速性、可信性和鲁棒性。(A robust self-adaptive beam forming method based on support vector regression. The received array signals are represented in the form of complex envelope column vectors and arranged in turn in the form of a data matrix. And taking the average value of the prediction errors as a minimization target, calculating a covariance matrix of the array signal vectors as a weighting matrix of a regular term, and converting the original robust adaptive beam forming problem into a support vector machine regression problem on a complex space. And calculating the optimal solution of the problem by utilizing a Wirtinger derivative and a Lagrange multiplier method, solving the closed form of the optimal solution, and providing a recursive algorithm for real-time processing. The invention can be suitable for the situations of inaccurate expected signal direction and small data quantity, can self-adaptively find the optimal beam forming vector in real time, and has high accuracy, rapidness, credibility and robustness.)

1. The robust self-adaptive beam forming method based on support vector regression is characterized by comprising the following steps of:

1) array signal data is collected. Taking a complex envelope of each section of array signal, regarding the complex envelope of each array element signal as a component, and arranging the complex envelopes according to a spatial sequence to obtain a section of signal complex envelope vector, which is marked as x (1), x (2), x (3), …, x (n); wherein n is valued according to actual needs

Estimating the covariance matrix of the signal by computing the outer product average of the sampled signals, i.e.

Wherein (·)^HRepresenting a conjugate transpose.

Calculating a weighted Gram matrix K and a complex Lagrange multiplier vector ζ

ζ＝-(K^T+C^-1I_K)^-1s₀

Finally, the optimal beam forming vector is obtained as

2) For the new arrival signal x (K +1), the beamforming vector is updated using a recursive algorithm. First of all, calculate

Wherein

Thereby obtaining updated Lagrange multiplier vector and beam forming vector

Technical Field

The invention relates to the field of signal processing, in particular to a beam forming method based on a support vector machine.

Background

In electronic communication systems, receivers often transmit and receive signals through phased array antennas to improve beam pointing flexibility. To achieve higher output signal-to-noise ratio, adaptive beamforming becomes an important issue in array signal processing. The traditional adaptive beam forming method has a minimum variance distortionless response method and the like, but is easily influenced by mismatching of the direction of arrival. In order to reduce the problem caused by mismatching of the direction of arrival, a linear constraint minimum variance method, a Bayesian method and the like are provided. However, in practice, these methods face many problems, such as the assumption of non-reality of signal and noise models, so that they have the disadvantages of unreliable performance, low reliability and the like when used in real environments.

Disclosure of Invention

The technical problem solved by the invention is as follows: the method overcomes the defects of the prior art, provides a robust self-adaptive beam synthesis method based on support vector regression, can well cope with the situation of mismatching of the direction of arrival, and realizes high output signal-to-noise ratio.

The technical scheme of the invention is as follows: the robust self-adaptive beam forming method based on support vector regression comprises the following steps:

1) array signal data is collected. Taking complex envelope of each array signal, regarding the complex envelope of each array element signal as a component, arranging the components according to a spatial sequence to obtain a section of signal complex envelope vector, and recording the section of signal complex envelope vector as a component

x (1), x (2), x (3), …, x (n); wherein n is valued according to actual needs

Estimating the covariance matrix of the signal by computing the outer product average of the sampled signals, i.e.

Wherein (·)^HRepresenting a conjugate transpose.

Calculating a weighted Gram matrix K and a complex Lagrange multiplier vector ζ

ζ＝-(K^T+C^-1I_K)^-1s₀

Finally, the optimal beam forming vector is obtained as

2) For the new arrival signal x (K +1), the beamforming vector is updated using a recursive algorithm. First of all, calculate

Wherein

Thereby obtaining updated Lagrange multiplier vector and beam forming vector

Compared with the prior art, the invention has the advantages that: the adaptive beam synthesis method realizes the robust adaptive beam synthesis function, allows the arrival direction to have certain mismatching compared with the traditional beam synthesis method, and has good inhibition effect on interference signals with different intensities.

Drawings

FIG. 1 is a flow chart of the method of the present invention.

Detailed Description

The flow chart of the direction of arrival estimation method of the invention is shown in the attached figure 1, and the specific steps are as follows:

1) and collecting and generating array signal data. Taking complex envelope of each array signal, regarding the complex envelope of each array element signal as a component, arranging the components according to a spatial sequence to obtain a section of signal complex envelope vector, and recording the section of signal complex envelope vector as a component

x (1), x (2), x (3), …, x (n); wherein n is valued according to actual needs

Estimating the covariance matrix of the signal by computing the outer product average of the sampled signals, i.e.

Wherein (·)^HRepresenting a conjugate transpose.

Calculating a weighted Gram matrix K and a complex Lagrange multiplier vector ζ

ζ＝-(K^T+C^-1I_K)^-1s₀

Finally, the optimal beam forming vector is obtained as

2) For the new arrival signal x (K +1), the beamforming vector is updated using a recursive algorithm. First of all, calculate

Wherein

Thereby obtaining updated Lagrange multiplier vector and beam forming vector

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.