Near-Field DOA-Range and Polarization Estimation Based on Exact Propagation Model with COLD Arrays

Yin, Kejun; Dai, Yumei; Gao, Chunming

doi:10.1007/s00034-022-02029-z

Cited by 1 publication

(2 citation statements)

References 40 publications

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“…The low-rank decomposition of the matrix

yields the array manifold matrix

accordingly [ 21 , 25 ]. From matrix

we can calculate the phase difference of the k th source between the reference sensor and the m th sensor:

…”

Section: Algorithm Usedmentioning

confidence: 99%

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A Mixed-Field Circular and Non-Circular Source Localization Algorithm Based on Exact Spatial Propagation Geometry

Lin

Cui

et al. 2023

Sensors

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In passive localization techniques, as the scale of the array of the sensors used increases, the source distribution may be a coexistence of near-field (NF) and far-field (FF) sources. Most of the existing algorithms dedicated to the localization of mixed-field sources are based on a simplified model, which has model errors and cannot make good use of non-circular properties when non-circular signals are present in the sources. In this paper, we present a mixed-field circular and non-circular source localization algorithm based on exact spatial propagation geometry. First, we make an initial estimate of the source parameters using exact spatial geometry relations. The MUSIC algorithm is then used in combination with the non-circular properties of the signal to achieve an accurate estimate. The algorithm does not lose performance due to model mismatch and is able to make good use of the non-circular properties of the sources to improve the estimation accuracy. The simulation results show that the proposed algorithm can effectively distinguish between sources and that the algorithm performs satisfactorily.

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“…The low-rank decomposition of the matrix

yields the array manifold matrix

accordingly [ 21 , 25 ]. From matrix

we can calculate the phase difference of the k th source between the reference sensor and the m th sensor:

…”

Section: Algorithm Usedmentioning

confidence: 99%

“…Refs. [ 20 , 21 ] built on this model to solve the array gain–phase error problem, and the cocentered orthogonal loop and dipole (COLD) array localization problem, respectively.…”

Section: Introductionmentioning

confidence: 99%

A Mixed-Field Circular and Non-Circular Source Localization Algorithm Based on Exact Spatial Propagation Geometry

Lin

Cui

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

Near-Field DOA-Range and Polarization Estimation Based on Exact Propagation Model with COLD Arrays

Cited by 1 publication

References 40 publications

A Mixed-Field Circular and Non-Circular Source Localization Algorithm Based on Exact Spatial Propagation Geometry

A Mixed-Field Circular and Non-Circular Source Localization Algorithm Based on Exact Spatial Propagation Geometry

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