Method of direction of arrival (DOA) estimation under low snapshot number based on M estimation

Abstract

The invention provides a method of direction of arrival (DOA) estimation under a low snapshot number based on M estimation, which comprises the steps of 1, setting an antenna array, and obtaining an observation data vector of the antenna array; 2, calculating a covariance matrix of the observation data vector at the snapshot number T; 3, carrying out trace regularization on the sample covariance matrix to obtain a trace-regularized matrix; 4, carrying out Toeplitz correction on the trace-regularized matrix to obtain a target matrix; 5, calculating a contraction coefficient for matrix contraction estimation according to the trace-regularized target matrix; 7, constructing a new covariance matrix according to the contracted target matrix and the contraction coefficient; 7, setting the new covariance matrix as the sample covariance matrix, repeating the step 2 to the step 6 until the final estimation is obtained; and 8, calculating the direction of arrival of the signal by adopting a subspace decomposition method according to the obtained covariance matrix.

Description

technical field [0001] The invention belongs to the technical field of wireless mobile communication, and in particular relates to a method for estimating a direction of arrival at a low number of snapshots based on M estimation. Background technique [0002] After decades of continuous development, array signal processing has been widely used in many fields such as communications, radar, sonar, and electronic countermeasures. Direction of Arrival estimation technology mainly studies how to estimate the direction of arrival (DOA) of space target signals, which is one of the important research contents in the field of array signal processing. Whether in military or civilian fields, the direction of arrival of space target signals is an extremely important estimation parameter, and it is the prerequisite for many technologies such as subsequent positioning, detection, navigation, and imaging. Therefore, it is very important to study the direction of arrival estimation technolo...

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Problems solved by technology

In addition, when the number of snapshots is insufficient, the eigenvalues ​​and eigenvectors obtained by subspace decomposition of the sample covariance matrix deviate greatly from the real values, so the DOA estimation method based on subspace decomposition cannot work well

In order to solve this problem, scholars have successively proposed the G-MUSIC algorithm, the matrix shrinkage estimation method and the matrix Toeplitzization method, but they have their own defects: the G-MUSIC algorithm is only effective for spatially adjacent signals, and the matrix shrinkage estimation is in DOA. No suitable shrinkage target in e

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