Joint MWC and Linear Array for Mixed Near-Field and Far-Field Source Localization

Source localization is a crucial research component of array signal processing in radar, communication, sonar, seismic surveys, and other fields. Aiming at the problem that the traditional Nyquist sampling theorem used in array signal processing needs too much data and too high a sampling rate, this...

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Bibliographic Details
Published in:IEEE sensors journal 2023-11, Vol.23 (22), p.27458-27467
Main Authors: He, Jiai, Qiu, Lili, Wang, Chanfei, Li, Zhixin, Zhu, Weijia
Format: Article
Language:English
Subjects:
Algorithms
Array signal processing
Classification algorithms
Estimation
Far fields
Linear arrays
Localization
Location awareness
mixed field source localization
modulated wideband converter (MWC)
Near fields
Parameter estimation
Radar arrays
Sampling
Seismic surveys
Sensor arrays
Sensors
Signal processing
Signal processing algorithms
Theorems
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Summary:Source localization is a crucial research component of array signal processing in radar, communication, sonar, seismic surveys, and other fields. Aiming at the problem that the traditional Nyquist sampling theorem used in array signal processing needs too much data and too high a sampling rate, this article proposes that the modulated wideband converter-mixed localization using the exact model (MWC-MILE) joint method. This method is based on the sub-Nyquist theorem, which can effectively reduce the sampling rate, decrease data volume, and save cost. In this article, we combine the linear array structure and MWC sampling and use the MILE algorithm to estimate the signal source step by step. First, the range parameters are roughly estimated, and the boundary is drawn to classify far and near fields (NFs). Then, the angle and range parameters are accurately estimated using sensors with array element spacing greater than half a wavelength. It can achieve precise positioning of the signal source in the mixed field. The MWC-MILE joint method is not limited by the array element spacing. It can be applied to mixed and pure fields. The experimental simulation proves that the proposed method has higher feasibility and accuracy than traditional methods in source classification and parameter estimation.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3319364