Generative model processing method for cross-coupling small-aperture array

Abstract

The invention provides a generative model processing method for a cross-coupling small-aperture array, belongs to the field of array signal processing, performs signal processing on an unknown array manifold by using a depth generative model and a standard array, and is characterized by comprising the following steps: step S1, performing signal processing on an unknown array manifold; the computer randomly generates a group of directions of arrival and corresponding small aperture array sample covariance and standard aperture array sample covariance, and normalizes the sample covariance after subtracting the noise covariance from the sample covariance; s2, inputting a standard aperture covariance into the depth generative model according to the small aperture array sample covariance, and learning the depth generative model to obtain a mapping relation of probability distribution between the small aperture array sample covariance and the standard aperture array covariance; s3, inputting a small-aperture array sample covariance, and sampling to generate a plurality of standard virtual array covariances according to the mapping relation; and S4, estimating the direction of arrival through a subspace algorithm, and obtaining an average value.

Description

technical field [0001] The invention belongs to the field of array signal processing, and in particular relates to a signal processing method for improving the performance of a small-aperture array by using a depth generation model. Background technique [0002] Signal direction of arrival (Direction Of Arrival, DOA) estimation is an important content in array signal processing, and has a wide range of applications in radar, mobile communication and other fields. At present, most arrays rely on the time delay between array elements to complete DOA estimation, where the estimation performance is proportional to the array spacing (ie, array aperture size). However, in some application scenarios, the sensor array is required to have a smaller aperture, which degrades the estimation performance of the array. Not only that, the coupling between array elements cannot be ignored under the small-aperture array, and the manifold of the array no longer satisfies the preset ideal form...

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Problems solved by technology

The above method uses a discriminative model to analyze the array signal, but the discriminative model often cannot obtain ideal results when the input signal is noisy.

[0005] Therefore, the signal processing methods of small aperture arrays in many literatures can only expand the aperture of small aperture arrays or remove the coupling between array elements, without considering the mutual coupling effect of small aperture arrays, or even the distance error of array elements. problems, and in the application, these problems must be considered

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