A Direction of Arrival Estimation Method Based on Fitting Model Under Array Model Error

Abstract

The invention discloses a method for estimating the direction of arrival based on a fitting model under an array model error, comprising the following steps: S1: building a steering vector model including an array error; S2: generating a training set sample and a test set by setting different proportional coefficients Sample; S3: Carry out autocorrelation operation on the training set sample and the test set sample, obtain the feature data vector as the input data of the neural network, and generate the label corresponding to the angle; S4: Build the fitting neural network model, and initialize the parameters; S5 : Input the feature data vector and the label corresponding to the coming angle into the fitting neural network model for training; S6: Input the test set samples into the saved fitting neural network model for testing, and obtain the estimated angle. The invention adopts the fully connected layer to realize the neural network of the fitting model, and can be better applicable to the rapid and high-precision direction finding of the interference signal received by the array in actual engineering.

Description

technical field [0001] The invention belongs to the technical field of direction of arrival, and in particular relates to a method for estimating direction of arrival based on a fitted model under the error of an array model. Background technique [0002] A fundamental problem in array signal processing is the direction of arrival of signals in space, which is also one of the important tasks in the fields of radar, sonar and medicine. Traditional DOA estimation algorithms are based on ideal mathematical models for estimation. However, in practical engineering applications, there are various model errors in the received signal of the array, which affect the received data and thus the estimation results. The existing machine learning-based DOA estimation algorithms require too large number of training parameters in training the network model, the network is more complex, and the training time is too long. SUMMARY OF THE INVENTION [0003] The purpose of the present inventio...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that the existing direction of arrival estimation algorithm needs too many training parameters, the network is relatively complex and the training time is too long, and a method of direction of arrival estimation based on the fitting model under the error of the array model is proposed

Images