TY - JOUR
T1 - Three-dimensional Localization of Mixed Near-Field and Far-Field Sources Based on a Unified Exact Propagation Model
AU - Fang, Jiaxiong
AU - Chen, Hua
AU - Liu, Wei
AU - Yang, Songjie
AU - Yuen, Chau
AU - So, Hing Cheung
PY - 2025
Y1 - 2025
N2 - In applications like speaker localization using a microphone array, the collected signals are typically a mixture of far-field (FF) and near-field (NF) sources. To find the positions of both NF and FF sources, a three-dimensional spatial-temporal localization algorithm based on a unified exact propagation geometry is developed in this paper, which avoids approximating the spatial phase difference with the first-order and second-order Taylor expansions applied to FF and NF sources, respectively. Our scheme utilizes cross-correlation to produce virtual observations for establishing a third-order parallel factor data model with the use of spatial and temporal information. The array's steering vectors can be extracted by trilinear decomposition. The amplitude and phase information of the whole array elements is jointly exploited to classify the source types and obtain the location estimates via a least squares method. Moreover, the proposed algorithm is computationally efficient since no spectral searches, high-order statistics calculations or parameter pairing procedures are required. The deterministic Cramér-Rao bound is also derived as a performance benchmark, and numerical results are provided to demonstrate the effectiveness of the developed method. © 1991-2012 IEEE.
AB - In applications like speaker localization using a microphone array, the collected signals are typically a mixture of far-field (FF) and near-field (NF) sources. To find the positions of both NF and FF sources, a three-dimensional spatial-temporal localization algorithm based on a unified exact propagation geometry is developed in this paper, which avoids approximating the spatial phase difference with the first-order and second-order Taylor expansions applied to FF and NF sources, respectively. Our scheme utilizes cross-correlation to produce virtual observations for establishing a third-order parallel factor data model with the use of spatial and temporal information. The array's steering vectors can be extracted by trilinear decomposition. The amplitude and phase information of the whole array elements is jointly exploited to classify the source types and obtain the location estimates via a least squares method. Moreover, the proposed algorithm is computationally efficient since no spectral searches, high-order statistics calculations or parameter pairing procedures are required. The deterministic Cramér-Rao bound is also derived as a performance benchmark, and numerical results are provided to demonstrate the effectiveness of the developed method. © 1991-2012 IEEE.
KW - Array signal processing
KW - far-field
KW - near-field
KW - source localization
KW - spatial-temporal
UR - http://www.scopus.com/inward/record.url?scp=85213057608&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85213057608&origin=recordpage
U2 - 10.1109/TSP.2024.3520551
DO - 10.1109/TSP.2024.3520551
M3 - RGC 21 - Publication in refereed journal
SN - 1053-587X
VL - 73
SP - 245
EP - 258
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
ER -