scholarly journals Efficient estimators in closed-form for source localization and sensor network self-localization

2011 ◽  
Author(s):  
Ming Sun
Keyword(s):  
Closed Form ◽  
Sensor Network ◽  
Source Localization

scholarly journals Conditional and Unconditional Deterministic Bounds on the MSE of the Non-Uniform Linear Co-centered Orthogonal Loop and Dipole Array

2021 ◽  
Vol 1 (1) ◽  
pp. 13-20
Author(s):  
Tao Bao ◽  
Mohammed Nabil EL KORSO
Keyword(s):  
Theoretical Analysis ◽  
Closed Form ◽  
Mean Square Error ◽  
Source Localization ◽  
Threshold Region ◽  
Observation Model ◽  
Mean Square ◽  
Numerical Examples ◽  
Cramer Rao Bound ◽  
Deterministic Bounds

The co-centered orthogonal loop and dipole (COLD) array exhibits some interesting properties, which makes it ubiquitous in the context of polarized source localization. In the literature, one can find a plethora of estimation schemes adapted to the COLD array. Nevertheless, their ultimate performance in terms the so-called threshold region of mean square error (MSE), have not been fully investigated. In order to fill this lack, we focus, in this paper, on conditional and unconditional bounds that are tighter than the well known Cramér-Rao Bound (CRB). More precisely, we give some closed form expressions of the McAulay-Hofstetter, the Hammersley-Chapman-Robbins, the McAulaySeidman bounds and the recent Todros-Tabrikian bound, for both the conditional and unconditional observation model. Finally, numerical examples are provided to corroborate the theoretical analysis and to reveal a number of insightful properties.

scholarly journals Mean Shift-Based Multisource Localization Method in Wireless Binary Sensor Network

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaosheng Yu ◽  
Jianning Chi ◽  
Ying Wang ◽  
Hao Chu
Keyword(s):  
Sensor Network ◽  
Source Localization ◽  
Mean Shift ◽  
High Energy ◽  
False Alarms ◽  
Localization Accuracy ◽  
Pearson Criterion ◽  
Binary Sensor ◽  
Sensing Model ◽  
Novel Method

Source localization is one of the major research contents in the localization research of wireless sensor networks, which has attracted considerable attention for a long period. In recent years, the wireless binary sensor network (WBSN) has been widely used for source localization due to its high energy efficiency. A novel method which is based on WBSN for multiple source localization is presented in this paper. Firstly, the Neyman-Pearson criterion-based sensing model which takes into account the false alarms is utilized to identify the alarmed nodes. Secondly, the mean shift and hierarchical clustering method are performed on the alarmed nodes to obtain the cluster centers as the initial locations of signal sources. Finally, some voting matrices which can improve the localization accuracy are constructed to decide the location of each acoustic source. The simulation results demonstrate that the proposed method can provide a desirable performance superior to some traditional methods in accuracy and efficiency.

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