Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array

Su, Xiaolong; Liu, Tianpeng; Peng, Bo; Chen, Xin; Li, Xiang

doi:10.1007/s00034-020-01413-x

Cited by 5 publications

(3 citation statements)

References 34 publications

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“…DOAs correspond to maximums of F(φ). As shown in (8), parameter h affects the performance of INPS. e suitable value has been experimentally obtained and can be written as [20][21][22] h � tr(R) M .…”

Section: Signal Modelmentioning

confidence: 99%

“…On the basis of electromagnetic (EM) wave radiated by hostile radiator and propagated by troposcatter, passive surveillance can realize b-LOS location [3,4]. Direction of arrival (DOA) estimation with high performance is the prerequisite of a passive surveillance system [5][6][7][8][9][10][11][12]. Intricate scattering procedure can generate multipath propagation, and scattered signals can be treated as closely spaced sources and own respective power; some signals with low signal to noise ratio (SNR) may be flooded by noises.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Liu

Chen

et al. 2021

Mathematical Problems in Engineering

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Direction of arrival (DOA) estimation plays an important role in the passive surveillance system based on troposcatter. Rank deficiency and subspace leakage resulting from multipath propagation can deteriorate the performance of the DOA estimator. In this paper, characteristics of signals propagated by troposcatter are analyzed, and an efficient DOA estimation method is proposed. According to our new method, the invariance property of noise subspace (IPNS) is introduced as the main method. To provide precise noise subspace for INPS, forward and backward spatial smoothing (FBSS) is carried out to overcome rank deficiency. Subspace leakage is eliminated by a two-step scheme, and this process can also largely reduce the computational load of INPS. Numerical simulation results validate that our method has not only good resolution in condition of closely spaced signals but also superior performance in case of power difference.

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Section: Signal Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Liu

Chen

et al. 2021

Mathematical Problems in Engineering

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show abstract

“…In the initial stage of source location research, the direction of incoming wave is mainly estimated for radiation far-field (RFF) sources and a large number of related algorithms are proposed [4][5][6][7][8]. With the rapid development of 5G and MIMO technologies [8,9], the space electromagnetic field environment becomes more complex, and the distances between some sources and arrays are less than the Rayleigh distance. The location of such sources also needs to consider the estimation of source range parameters.…”

Section: Introductionmentioning

confidence: 99%

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

Zhang,

Li,

et al. 2024

Journal of Sensors

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The limitation of the number of estimable sources in the localization of radiation near-field sources with gain–phase error is examined in this paper. When only the reference element has no gain–phase error, a new method based on an accurate model is proposed to enhance the maximum number of estimable sources. Based on the location parameter details of the auxiliary source, the method first derives the gain–phase error estimate matrix. Second, the source steering vector including errors is estimated using the total least square estimating signal parameter via rotational invariance techniques (TLS-ESPRIT), and the time-shifted data matrix is built utilizing the space–time combination idea, thus increasing the degree of freedom of the array. Then, the source steering vector containing the error is modified by the error compensation matrix constructed according to the moment of gain–phase error estimation. Finally, the estimated values of the source position parameters are obtained by using the closed formula of the gain phase of the modified source steering vector and the source position parameters. The experimental results show that the maximum estimable source number of the proposed algorithm is significantly improved compared with the previous results when only the reference array element has no gain–phase error. When the array number is 5 and 9, the maximum estimable source number of the algorithm is 9 and 17, respectively.

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Mixed-field source localization based on robust matrix propagator and reduced-degree polynomial rooting

Cheng

Liu

et al. 2023

Signal Processing

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Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array

Cited by 5 publications

References 34 publications

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

Mixed-field source localization based on robust matrix propagator and reduced-degree polynomial rooting

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