A Sequential ESPRIT Algorithm Based on a Novel UCSA Configuration for Parametric Estimation of Two-dimensional Incoherently Distributed Source

In the field of array signal processing, distributed sources can be regarded as an assembly of point sources within a spatial distribution. In this study, a two-dimensional (2D) non-symmetric incoherently distributed (ID) source model is proposed; we explore the estimation of a 2D non-symmetric ID source using L-shape arrays. The 2D non-symmetric ID source is established by modeling the angular power density function (APDF) as a Gaussian mixture model. Estimation of the non-symmetric distributed source is proposed based on the expectation maximization (EM) framework. The proposed EM iterative framework contains three steps in the process of each circle. Firstly, the nominal azimuth and nominal elevation of each Gaussian component are obtained from the phase parts of elements in sample covariance matrices. Then the angular spreads can be solved through a one-dimensional (1D) search by the original generalized Capon estimator. Finally, weights of each Gaussian component are obtained by solving the least-squares estimator. Simulations are conducted to verify the effectiveness of the estimation technique.

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Multiple RFI Sources Location Method Combining Two-Dimensional ESPRIT DOA Estimation and Particle Swarm Optimization for Spaceborne SAR

Remote Sensing ◽

10.3390/rs13061207 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1207

Author(s):

Junfei Yu ◽

Jingwen Li ◽

Bing Sun ◽

Yuming Jiang ◽

Liying Xu

Keyword(s):

Particle Swarm Optimization ◽

Particle Swarm ◽

Geographic Location ◽

Doa Estimation ◽

Pso Algorithm ◽

Two Dimensional ◽

Swarm Optimization ◽

Location Method ◽

Esprit Algorithm ◽

To Receive

Synthetic aperture radar (SAR) systems are susceptible to radio frequency interference (RFI). The existence of RFI will cause serious degradation of SAR image quality and a huge risk of target misjudgment, which makes the research on RFI suppression methods receive widespread attention. Since the location of the RFI source is one of the most vital information for achieving RFI spatial filtering, this paper presents a novel location method of multiple independent RFI sources based on direction-of-arrival (DOA) estimation and the non-convex optimization algorithm. It deploys an L-shaped multi-channel array on the SAR system to receive echo signals, and utilizes the two-dimensional estimating signal parameter via rotational invariance techniques (2D-ESPRIT) algorithm to estimate the positional relationship between the RFI source and the SAR system, ultimately combines the DOA estimation results of multiple azimuth time to calculate the geographic location of RFI sources through the particle swarm optimization (PSO) algorithm. Results on simulation experiments prove the effectiveness of the proposed method.

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Distributed source localization using ESPRIT algorithm

IEEE Transactions on Signal Processing ◽

10.1109/78.950773 ◽

2001 ◽

Vol 49 (10) ◽

pp. 2169-2178 ◽

Cited By ~ 138

Author(s):

S. Shahbazpanahi ◽

S. Valaee ◽

M.H. Bastani

Keyword(s):

Source Localization ◽

Distributed Source ◽

Esprit Algorithm

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Estimation for Two-Dimensional Nonsymmetric Coherently Distributed Source in L-Shaped Arrays

International Journal of Antennas and Propagation ◽

10.1155/2018/5247919 ◽

2018 ◽

Vol 2018 ◽

pp. 1-16

Author(s):

Tao Wu ◽

Zhenghong Deng ◽

Qingyue Gu ◽

Jiwei Xu

Keyword(s):

Expectation Maximization ◽

Two Dimensional ◽

Signal Distribution ◽

Distributed Source ◽

One Dimensional ◽

Least Squares Estimators ◽

Iterative Calculation ◽

Symmetric Source ◽

Relationship Of ◽

The Relationship

We explore the estimation of a two-dimensional (2D) nonsymmetric coherently distributed (CD) source using L-shaped arrays. Compared with a symmetric source, the modeling and estimation of a nonsymmetric source are more practical. A nonsymmetric CD source is established through modeling the deterministic angular signal distribution function as a summation of Gaussian probability density functions. Parameter estimation of the nonsymmetric distributed source is proposed under an expectation maximization (EM) framework. The proposed EM iterative calculation contains three steps in each cycle. Firstly, the nominal azimuth angles and nominal elevation angles of Gaussian components in the nonsymmetric source are obtained from the relationship of rotational invariance matrices. Then, angular spreads can be solved through one-dimensional (1D) searching based on nominal angles. Finally, the powers of Gaussian components are obtained by solving least-squares estimators. Simulations are conducted to verify the effectiveness of the nonsymmetric CD model and estimation technique.

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