High-resolution direct position determination based on eigenspace using a single moving ULA

Wu, Guizhou; Zhang, Min; Guo, Fei

doi:10.1007/s11760-019-01425-4

Cited by 15 publications

(1 citation statement)

References 19 publications

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“…In Ma et al, 23 multiple moving arrays are used to intercept static emitter signals, ignoring TDOA, and a moving multi-station direct positioning method based only on AOA and frequency difference of arrival (FDOA) is proposed. In Wu et al’s study, 24 a direct positioning method is proposed, which fully combines the noise subspace and signal subspace; therefore, the positioning accuracy of the algorithm is better than that of minimum variance distortion-less response (MVDR) or multiple signal classification (MUSIC) spectrum. In Li et al’s study, 25 the SDF direct positioning method is improved, and two weighted DPD methods are proposed to improve the positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

A reduced dimension multiple signal classification–based direct location algorithm with dense arrays

Zhao

et al. 2022

International Journal of Distributed Sensor Networks

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Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. Based on the idea of dimension reduction, the algorithm avoids multi-dimensional search in spatial domain and attenuation coefficient domain and reduces the search complexity. Simulation results show that the performance of the algorithm is better than the traditional angle of arrival two-step localization algorithm and subspace data fusion direct localization algorithm.

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Section: Introductionmentioning

confidence: 99%