Single-shot direction finding method in shock noise environment

Abstract

The invention relates to a single-snapshot direction finding method in an impact noise environment, which includes establishing a uniform line array single-snapshot sampling signal model; constructing an infinite norm covariance matrix based on a Gaussian kernel, and obtaining an infinite norm single-shot method based on a Gaussian kernel. Snapshot the maximum likelihood equation; initialize the African buffalo population; calculate the position fitness of each buffalo, record the local optimal position of each buffalo and the global optimal position of the entire African buffalo herd; update the buffalo position and buffalo communication position, and generate Fibonacci Nacci weight; use Fibonacci search strategy to update the local optimal position of each buffalo; calculate the fitness of the new position of each buffalo, determine the local optimal position of each buffalo and the global optimal position of the African buffalo herd; The output global optimal position of the African buffalo herd is the estimated value of the direction of arrival. The present invention only processes a single snapshot data in a complex environment such as strong impact noise, reduces the amount of DOA estimation calculations, and realizes effective estimation of the direction of arrival of received signals.

Description

technical field [0001] The invention relates to a single snapshot direction finding method in an impact noise environment, in particular to a single snapshot direction finding method based on a Fibonacci African buffalo search mechanism in an impact noise environment, and belongs to the field of array signal processing. Background technique [0002] Direction finding, also known as Direction of Arrival (DOA) estimation, has always been a hot topic in array signal processing, and has been widely used in systems such as communications, radar, and sonar. Although the traditional multiple signal classification method (MUSIC) and the rotation-invariant subspace technique for signal parameter estimation (ESPRIT) already have high estimation performance, these algorithms are all based on eigenvalue decomposition operations, and often In order to obtain good estimation performance, a large number of snapshots are required, which not only has low real-time performance, but also requi...

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Problems solved by technology

[0004] According to the existing technical literature, Wei Yinsheng et al published in "System Engineering and Electronic Technology" (2013, Vol. "Sub-snapshot super-resolution algorithm" uses a dimensionality reduction method to estimate the covariance matrix in the frequency domain, which improves the resolution and resolution accuracy to a certain extent, but the second matrix decomposition of this method increases the amount of calculation and loses the array aperture. Effective direction finding in impulsive noise environments

Xie Xin et al. proposed a lossless The single-snapshot direct data domain algorithm of the array aperture has a low amount of computation, but this method is too demanding for the real receiving environment and cannot fail in the direction finding under the background of impact noise

[0005] Existing literature shows that single-snapshot DOA estimation can improve the real-time performance of the system and reduce the amount of computation, but the reduction in the number of snapshots will lead to inaccurate or even invalid estimation performance, and so far there is no effective method for single-snapshot DOA estimation under the background of impact noise. shot direction finding, so it is necessary to design a high-performance single-shot direction finding method suitable for impact noise background

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