Few-array-element array high-resolution orientation estimation method based on two-dimensional power distribution

Abstract

The invention relates to a few-array-element array high-resolution orientation estimation method based on two-dimensional power distribution. The method comprises the following steps of: acquiring array receiving signals, and performing Kronecker product operation on the array element receiving signals; performing CBF power spectrum by taking an operation result as a new acquisition signal, selecting a space observation angle interval, and constructing a three-dimensional power spectrum matrix according to the selected observation angle; determining a two-dimensional power distribution matrix by using a compressed sensing method according to the CBF power spectrum and the three-dimensional power spectrum matrix obtained in the step; and solving a maximum value according to each column of the two-dimensional power distribution matrix, and using results as a power spectrum of a new algorithm for DOA estimation. Data in the two-dimensional matrix are mutually restricted by the two angle sets, the estimation precision is improved, meanwhile, the requirement of high resolution for the number of array elements is lowered, and the estimation precision and the resolution are effectively improved when the number of array elements is small.

Description

technical field [0001] The invention relates to the technical field of underwater acoustic direction-of-arrival estimation, and is a high-resolution orientation estimation method based on a two-dimensional power distribution with a few array elements. Background technique [0002] Direction of Arrival (DOA) estimation is a research hotspot in array signal processing. Its main research content is to obtain the exact target orientation information from the noise and interference background. It is widely used in radar, sonar, navigation, nondestructive testing and wireless communication. There are a wide range of applications. Resolution and sidelobe height are important indicators to measure the performance of the DOA estimation algorithm. It is well known that if the beam width is wide, it is difficult to detect two targets in the same beam. If the sidelobe height is high, it is difficult to detect in the presence of strong interference. Weak signal. [0003] Generally spea...

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Problems solved by technology

[0004] The beamforming algorithm is the most traditional DOA estimation method, but it is affected by the Rayleigh limit, and the azimuth resolution is low. The MVDR beamforming method has better spatial resolution and unknown strong interference suppression ability, but its estimation accuracy often decreases. Affected by various error factors such as array element amplitude and phase errors, array element position errors, etc.

[0005] Multiple signal classification method (MUSIC) is the most classic high-resolution estimation algorithm, which has higher resolution than CBF and MVDR, but when the number of snapshots decreases and the signal-to-noise ratio is low, this type of method suffers from severe estimation performance. In the worsening situation, if the number of signals is unclear or the correlation between target signals is strong, it will also cause serious damage to the signal and noise subspaces, thereby further reducing the resolution and estimation accuracy of subspace methods.

In recent years, the deconvolution method has been applied to azimuth estimation and sound source localization, which has effectively improved the disadvantage of poor resolution of the CBF method (RL-dCv), but the RL-dCv algorithm is only suitable for beam response functions with shift-invariant beam response, such as the CBF beam response of a uniform linear array, which greatly narrows the range of use of the algorithm

[0006] Most of the high-resolution algorithms, including the above algorithms, usually require a high SNR environment and a multi-element array to achieve high resolution. Strong environmental noise and a small number of array elements will affect the performance of high-resolution capabilities, but Due to the complexity of the marine environment, there are a large number of various noise sources in the ocean, including marine environmental noise, ship radiation noise, etc., and these noises usually appear randomly and are unpredictable

In addition, many practical conditions do not allow multi-element arrays. For example, small-sized unmanned platforms cannot carry large-scale arrays, or the number of array elements needs to be limited due to limited funds. The DOA algorithm with high resolution ability still needs to be paid attention to

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