DOA estimation method of weak sources for an array antenna under strong interference conditions

Gong, Jian Chun; Lou, Shun-Tian; Guo, Yiduo

doi:10.1080/00207217.2018.1494324

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…Expanded Noise Subspace DOA Estimation. Taking the MUISC algorithm as an example, the spatial spectrum value of a certain angle is the reciprocal of the projection modulus of the steering vector in direction to the projection space, that is, the noise subspace [21][22][23]. e peak value represents that the steering vector at this angle projected in the noise subspace is smaller than its surrounding angle.…”

Section: Doa Estimation Based On Foc Vectormentioning

confidence: 99%

DOA Estimation Method of Weak Signal under the Compound Background of Strong Interference and Colored Noise

Lin

Zhou

et al. 2022

International Journal of Antennas and Propagation

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The traditional algorithm performing direction of arrival (DOA) estimation under the background of strong interference and colored noise has the problems of low estimation accuracy and small measurement targets. Based on the construction of a fourth-order cumulant (FOC) matrix to suppress colored noise, this paper adopts the extended noise subspace (ENS) algorithm and the fixed projection blocking (FPB) algorithm to estimate the DOA of weak targets. Firstly, a FOC matrix of the received signal vector is established to curb the noise component, and the eigenvalue decomposition is performed. Then, two approaches of weak signal DOA estimation are proposed. One approach is to merge the space where the strong interference steering vector lies into the noise subspace to construct an extended noise subspace, and then, the multisignal classification (MUSIC) algorithm is used to obtain the DOA estimation of the weak signal on the basis of the extended noise subspace. Another approach is to build the orthogonal projection matrix of the interference subspace as the interference blocking matrix, and the receiving array signal is preprocessed, and on the basis of it, the eigen decomposition is performed again to obtain the DOA information of the weak signal. Both algorithms make breakthroughs in the aperture limitation of the traditional algorithm, effectively expand the aperture, and promote the accuracy of estimation. The simulation tests the effectiveness of the proposed method.

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Section: Doa Estimation Based On Foc Vectormentioning

confidence: 99%

DOA Estimation Method of Weak Signal under the Compound Background of Strong Interference and Colored Noise

Lin

Zhou

et al. 2022

International Journal of Antennas and Propagation

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“…The authors of [22] use the angular information of the signal matrix to construct an interference blocking matrix to suppress strong interference signals, but this method requires precisely known interference directions, and different blocking matrices need to be constructed for different array structures. Gong et al [23] analyzed in detail the direction-preserving orthogonality in array signal data under the background of strong interference and performed simulations for a variety of scenarios, verifying that the algorithm was suitable for situations with low signal-to-noise ratios (SNR) and small angular spacing. The authors of [24] propose a broadband signal localization method based on sparse spectral fitting and a zero-value matrix filter with a high localization accuracy in a strong interference environment.…”

Section: Introductionmentioning

confidence: 99%

Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise

Lin

Zhou

2022

Sensors

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To address the problems of low accuracy and low robustness of the conventional algorithm in estimating the direction of arrival (DOA) of coherent signals against a composite background of strong interference and non-uniform noise, in this paper, a coherent signal DOA estimation algorithm based on fixed projection blocking is proposed in conjunction with a multi-input multi-output (MIMO) radar. The covariance matrix of the received signal is first decomposed by eigenvalues, and a fixed projection matrix orthogonal to the interference guidance vector is constructed as the interference blocking matrix. Then, the received array signal is pre-processed to re-form the covariance matrix, and this matrix is rendered decoherent through a Toeplitz reconstruction. Finally, the reconstructed covariance matrix is estimated by DOA using the propagation operator algorithm to reduce the complexity. The simulation verifies that the proposed algorithm has a better robustness and higher accuracy than conventional algorithms for the DOA estimation of coherent signals in composite backgrounds.

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“…An improved ENS for weak signal DOA estimation under strong interference and colored noise is presented in [13]. Jian et al proposed a DOA estimation algorithm based on the elimination of the eigenvectors of interference (EEOI) [14]. The eigenvectors of the weak signals are determined according to the ratio of the eigenvalues to eliminate interference, and the noise subspace is reconstructed, and then the DOA of weak signal is estimated by MUSIC algorithm.…”

Section: Introductionmentioning

confidence: 99%

A novel DOA estimation method of antenna array under strong interference

Zuo,

Xie

2022

Preprint

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This paper investigates the weak signal direction of arrival (DOA) estimation for an antenna array under strong interference signals, and a novel DOA estimation method is proposed for strong interference source suppression and weighted l1-norm sparse representation. The parallel adaptive beamforming algorithm based on power inversion is used to suppress strong interference and form a new array data, and the weighted matrix is determined according to the optimized subspace algorithm of the subspace projection. Then, the DOA estimation, which is calculated by weighted l1-norm sparse representation, is formed by the weighted matrix and new array data. In this paper, the superiority of proposed algorithm is illustrated by an example of unmanned aerial vehicle (UAV) video signal DOA estimation under strong interference signals. The simulated results of orthogonal frequency division multiplexing (OFDM) signal indicate that the proposed algorithm shows merits of less snapshots, sharper main lobe, lower average noise spectrum value, higher DOA estimation accuracy and success rate. For validation, an outdoor experiment was conducted, demonstrating that the proposed algorithm is superior to other algorithms and can be used for DOA estimation of UAV video signal under strong WiFi interferences. Both the simulations and experiments have verified the proposed algorithm can effectively suppress the strong interference and achieve better DOA estimation performance of weak signal.

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DOA estimation method of weak sources for an array antenna under strong interference conditions

Cited by 6 publications

References 5 publications

DOA Estimation Method of Weak Signal under the Compound Background of Strong Interference and Colored Noise

DOA Estimation Method of Weak Signal under the Compound Background of Strong Interference and Colored Noise

Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise

A novel DOA estimation method of antenna array under strong interference

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