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Nested array direction-of-arrival estimation method based on off-grid sparse Bayesian learning

A direction-of-arrival estimation and sparse Bayesian technology, which is applied in direction-determining orientators, radio wave measurement systems, and measurement devices, can solve the problems of effective array aperture loss, seriousness, and high computational complexity, and avoid array Aperture reduction, avoiding the effect of complex matrix transformations

Active Publication Date: 2018-08-28
JIANGSU UNIV
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Problems solved by technology

However, the traditional algorithm based on subspace processing is easily affected by the signal-to-noise ratio and the number of snapshots. The main disadvantages of the existing DOA estimation method based on sparse Bayesian learning are: the loss of effective array aperture is serious, and the computational complexity is relatively high. high

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  • Nested array direction-of-arrival estimation method based on off-grid sparse Bayesian learning
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  • Nested array direction-of-arrival estimation method based on off-grid sparse Bayesian learning

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Embodiment Construction

[0017] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0018] Such as figure 1 Shown, method of the present invention comprises the steps:

[0019] (1) After the far-field narrow-band Gaussian signal received by the nested array is matched and filtered, the data vector x(t)=As(t)+n(t) containing DOA information at time t is obtained, t=1,2,. ..,T, where:

[0020] T represents the number of snapshots;

[0021] s(t)=[s 1 (t),s 2 (t),...,s K (t)] T Represents K uncorrelated narrowband signals transmitted at time t, where s k (t) satisfy the mean value is 0, the variance is k=1,2,..., K complex Gaussian distribution, ( ) T means transpose;

[0022] A=[a(θ 1 ), a(θ 2 ),...,a(θ K )] represents an M×K-dimensional array flow pattern matrix, where M=M 1 +M 2 is the number of nested array elements, M 1 and M 2 Indicates the number of array elements in the inner and outer layers of the...

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Abstract

The invention discloses a nested array direction-of-arrival estimation method based on off-grid sparse Bayesian learning. The method comprises: step one, matching filtering is carried out on a narrowband Gaussian signal received by a nested array to obtain a data vector x(t) including DOA information at a t time; step two, with the x(t), a received data covariance matrix R^x under a T snapshot number is calculated and vectorization is carried out on the R^x to obtain a one-dimensional data vector Y^; step three, K^ grid points theta^={theta^i}<K^>i=1 are divided uniformly in a range [-pai / 2,pai / 2], a counting variable I of the number of times for iteration is set to be 1, a variance vector delta and an e angle offset vector beta are initialized, and a measuring matrix phi (theta^, beta) isconstructed; step four, a variance vector theta and an angle deviation value beta in a (K^+1) dimension are updated by using an EM criterion; step five, the grid theta^ is updated by using the beta value obtained at the step four; step six, whether the counting variable I of the number of times for iteration reaches an upper limit L or the delta converges is determined; if not, the counting variable I of the number of times for iteration conforms to a formula: 1=1+1, wherein the beta is equal to 0; updating is carried out on the phi (theta^, beta) by using the updated grid theta ^, and the step four is performed; and step seven, spectral peak searching is carried out on the variance vector delta to obtain angles corresponding to K maximum points, so that a final estimation value of the target angle is obtained.

Description

technical field [0001] The invention belongs to the field of array signal processing, and relates to the estimation of direction of arrival of array signals, in particular to a method for estimation of direction of arrival of non-uniform nested array signals. Background technique [0002] Direction of Arrival (DOA) estimation of multi-narrowband signals using antenna arrays has been widely used in radar, sonar and communication fields. In the past few decades, a large number of effective DOA estimation methods have been proposed. Since the non-uniform array itself has great advantages in increasing the degree of freedom of signal processing, the target angle estimation algorithm based on the nested array has also become a research hotspot. For example, in the literature: P.Pal, P.Vaidyanathan, Nested arrays: A novel approach to array processing with enhanced degrees of freedom, IEEE Transactions on Signal Processing, 58 (8) (2010) 4167-4181, a space-based Smooth multiple s...

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Application Information

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IPC IPC(8): G01S3/00
CPCG01S3/00
Inventor 戴继生陈方方鲍煦张文策
Owner JIANGSU UNIV
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