Hexagonal array-based coherent signal two-dimensional DOA (Direction of Arrival) estimation method

Abstract

The invention belongs to the array signal processing field and relates to a hexagonal array-based coherent signal two-dimensional DOA (Direction of Arrival) estimation method, in particular to a high-precision, de-coherence, two-dimensional signal DOA subspace estimation method. According to the estimation method of the invention, an array is virtualized and extended through performing conjugate matrix solution on array receiving data, so that a hexagonal array including three sub arrays are obtained, and then, a correlation matrix of a subspace algorithm is extended and reconstructed according to an autocorrelation matrix and a cross correlation matrix of the three sub arrays, and therefore, de-coherence can be realized; and singular value decomposition is performed on the new correlation matrix, so that a signal subspace and a noise subspace can be obtained, and then, DOA estimation is performed on coherent receiving signals through utilizing a two-dimensional MUSIC (Multiple Signal Classification) estimation method. With the estimation method of the invention adopted, coherence between source signals can be eliminated, and the estimation accuracy of two-dimensional DOA can be further improved. The estimation method is mainly applied to two-dimensional high-precision DOA estimation of coherent signals.

Description

technical field [0001] The invention belongs to the field of antenna array signal processing, and particularly relates to a high-precision, decoherent, two-dimensional signal direction-of-arrival (DOA) subspace estimation method. Background technique [0002] Super-resolution Direction of Arrival (DOA) technology is an important research point of spatial spectrum estimation and is widely used in high-resolution array signal processing. Its high precision of angle estimation and its application prospect have aroused people's great attention. Multiple signal classification algorithm (MUSIC, multiple signal classification) and signal parameter estimation algorithm based on rotation invariant technique (ESPRIT, estimation of signal parameter via rotational inviance techniques) are two classic super-resolution subspace algorithms. Among them, the MUSIC algorithm can be applied to arrays of arbitrary shapes, and can estimate source signals of multiple parameters. However, in pra...

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Problems solved by technology

The improved MUSIC decoherence algorithm based on spatial smoothing technology has good performance, but it needs to divide the array into multiple sub-arrays, which not only reduces the number of array elements and array aperture, but also has certain requirements on the array structure, which cannot be achieved in practical applications. Get good decorrelation performance, for arbitrary shape arrays, such as hexagonal arrays, there is no better decorrelation algorithm

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