RAM-based angle estimation with linear spatially separated polarisation sensitive array

Li, Binbin; Bai, Weixiong; He, Xingyu

doi:10.1080/00207217.2018.1477197

Cited by 2 publications

(3 citation statements)

References 30 publications

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“…Proposed method combines interference filtering approach and spectrum estimation method. As verified in [31,32] filtering based on l1 norm of STFT, which transforms the problem into a common sparse signal recovery problem. 2) 1-D or 2-D spectrum estimation of filtered data based on RAM.…”

Section: Proposed Methodsmentioning

confidence: 97%

“…[22] first proposed a compressive sensing method for radar imaging. Then the sparse recovery method was used for super-resolution [23][24][25][26][27][28], including sparse Bayesian learning [25], 2D gradient projection [26], matrix completion [27], atomic norm minimization (ANM) [29,30], reweighted atomic norm minimization (RAM) [28,31], et al Among those methods, the RAM has shown great advantage in estimation accuracy [28,31,32] because of the off-grid characteristic and high estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation

Wan

Tong

2020

IEEE Access

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This paper presents a novel framework for suppressing time-varying radio frequency interference (TRFI) in wideband dechirping radar. The TRFI challenges the wideband radar because of 1) changing in wide spectra range; 2) dynamic nature and unpredictability; 3) significant noise power in limited band. In this paper, an essential phenomenon of real measured data about TRFI in dechirping process is analyzed, where it is smashed into several segments because of the narrowband filtering. Based on that, a 2-step framework combining the interference filtering and frequency estimation is proposed. First, since the different sparsity of signal of interference, a simple yet very effective regional filtering method based on l1 norm of STFT is applied, which transforms original problem into a sparse signal recovery problem. Second, for 1-D signal, the reweighted atomic norm minimization (RAM) algorithm is applied to estimate the signal from defect filtered data; for 2-D signal block, a weighting strategy is proposed to promote the accuracy of original 2-D atomic norm minimization method. This method can be implemented as an interference suppression stage for wideband radar with dechirping processing. Experiment of real measured signal in TRFI environment and simulation of defect signal block illustrate its effectiveness. INDEX TERMS sparse recovery; reweighted atomic norm minimization (RAM); radio frequency interference (RFI); dechirping.

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Section: Proposed Methodsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation

Wan

Tong

2020

IEEE Access

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Huawei Chen. signal parameters via rotational invariance techniques (ESPRIT) algorithm [10]- [13], maximum likelihood (ML) algorithm [14], [15], polarization smoothing (PS) algorithm [16]- [19], compressed sensing technology [20]- [24], the tensor-based algorithm [25], and the quaternion-based algorithm [26] and so on. Actually, the elements of PSA are composed of electric-dipoles and magnetic-loops.…”

Section: Introductionmentioning

confidence: 99%

Vector Cross Product-Based 2D-DOA and Polarization Estimation With “Long” Electric-Dipole Quint

Liu

Feng

et al. 2019

IEEE Access

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Dipole antenna elements whose physical length L is greater than or equal to one-tenth of the wavelength λ are generally denoted as long dipoles. Such radiators are more useful in practical polarization sensitive arrays (PSAs) for electromagnetic sensing applications because their radiation efficiency is greater than that of short dipole radiators for which L < λ /10. Thus, research focused on estimating the parameters of unknown electromagnetic sources using long dipoles has attracted considerable attention from numerous researchers in recent years. However, the development of PSAs and algorithms for this purpose remains in its infancy. In this paper, we propose a PSA composed of five spatially non-collocated long dipoles in a centrosymmetric configuration and apply an algorithm based on the vector cross product for estimating the 2-D direction of arrival (2D-DOA) and polarization parameters of unknown electromagnetic sources. First, the time-domain rotational invariance of the received data facilitates the use of the ESPRIT algorithm for estimating the steering vector. Second, the relationships between the entries of the steering vector are employed to obtain highly accurate, albeit cyclically ambiguous estimates of the directional cosines of the x-and y-axes. Then, the coarse 2D-DOA parameter estimation is conducted using the vector cross product algorithm. Finally, the course 2D-DOA parameter estimations are employed as a reference to obtain a set of highly accurate and unambiguous directional cosine estimates from the previously determined set of cyclically ambiguous estimates. The effectiveness of the proposed algorithm is verified by the simulation results. INDEX TERMS ''Long'' electric-dipole quint, ESPRIT algorithm, vector cross product algorithm, 2D-DOA estimation, polarization estimation.

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RAM-based angle estimation with linear spatially separated polarisation sensitive array

Cited by 2 publications

References 30 publications

Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation

Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation

Vector Cross Product-Based 2D-DOA and Polarization Estimation With “Long” Electric-Dipole Quint

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RAM-based angle estimation with linear spatially separated polarisation sensitive array

Cited by 2 publications

References 30 publications

Time-Varying RFI Suppression of Dechirping Radar Based on l 1 Norm Filtering and RAM-Based Frequency Estimation

Time-Varying RFI Suppression of Dechirping Radar Based on l 1 Norm Filtering and RAM-Based Frequency Estimation

Vector Cross Product-Based 2D-DOA and Polarization Estimation With “Long” Electric-Dipole Quint

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Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation

Time-Varying RFI Suppression of Dechirping Radar Based on l ₁ Norm Filtering and RAM-Based Frequency Estimation