Interpolation transformation and beam forming-based far-field coherent signal DOA estimation method

Abstract

The invention relates to an interpolation transformation and beam forming-based far-field coherent signal DOA estimation method. According to the method, firstly, an interpolation matrix is adopted to convert a non-uniform linear array covariance matrix into a covariance matrix of a virtual uniform linear array. Data on the covariance matrix of the virtual array are subjected to noise pre-whitening to obtain img file = 'DDA 00013602494400000000000011.T'wi = '67 'he = '71 '. After that, img file = 'DDA 00013602494400000000000011.T'wi = '43 'he = '70 ' is subjected to spatial smoothing treatment to resolve the phase coherence, so that a coherence-resolved data covariance matrix is obtained. The coherence-resolved data covariance matrix is processed through constructing a cost function, and then the estimated value of the DOA of a far-field coherent signal is obtained. According to the invention, on the premise that the precision is guaranteed, the operations of feature decomposition, frequency spectrum searching and the like which are complicated in operation, can be avoided. The method is low in calculation complexity, simple and effective. Meanwhile, based on the method, the application range is popularized from a uniform linear array to any linear array, and from a non-coherent signal source to a coherent signal source. Therefore, the method is wider in application range.

Description

technical field [0001] The invention belongs to the technical field of array signal processing, and in particular relates to a far-field coherent signal DOA estimation method based on interpolation transformation and beamforming. Background technique [0002] Source location has important applications in the fields of radar, sonar, wireless communication, etc. In practical applications, due to multi-path propagation of signals or intelligent interference in military affairs, the received signals are often coherent. At the same time, the geometric structure of the receiving array is usually determined by physical facilities, and it is difficult to achieve an ideal uniform array. At present, there are many methods for solving the problem of coherent signal source localization, such as estimation method based on subspace and beamforming technology. But none of these algorithms can be directly used for non-uniform arrays, and there are some other defects and deficiencies. Subs...

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Problems solved by technology

However, none of these algorithms can be directly used for non-uniform arrays, and there are some other defects and deficiencies

Subspace-based algorithms represented by multiple signal classification (MUSIC) use computationally complex eigendecomposition operations; while beamforming techniques represented by Capon beamformers have limited estimation accuracy and are limited by signal-to-noise ratio (SNR) and snapshots. The number has a great influence, and the performance of the algorithm declines sharply when the signal-to-noise ratio or the number of snapshots is small

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