Adaptive RLS-Received Signal Strength Algorithm in Wireless Network Area for Multi-Mobile Nodes Location Estimation System

2013 ◽  
Vol 64 (15) ◽  
pp. 12-15
Author(s):  
Abhishek Singh ◽  
Rajesh Mehra
Keyword(s):  
Wireless Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Mobile Nodes ◽  
Network Area ◽  
Estimation System

scholarly journals A Research Cluster based Scheme for Node Positioning in Indoor Environment

2019 ◽  
Vol 8 (6S) ◽  
pp. 79-83
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Cluster Head ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Localization Error ◽  
Network Efficiency

Location estimation in Wireless Sensor Network (WSN) is mandatory to achieve high network efficiency. Identifying the positions of sensors is an uphill task as monitoring nodes are involved in estimation and localization. Clustered Positioning for Indoor Environment (CPIE) is proposed for estimating the position of the sensors using a Cluster Head (CH) based mechanism. The CH estimates the number of neighbor nodes in each floor of the indoor environment. It sends the requests to the cluster members and the positions are estimated based on the Received Signal Strength Indicators (RSSIs) from the members of the cluster. The performance of the proposed scheme is analyzed for both stable and mobile conditions by varying the number of floors. Experimental results show that the propounded scheme offers better network efficiency and reduces delay and localization error

Robustness in Fingerprinting-Based Indoor Positioning Systems

2018 ◽  
pp. 88-141 ◽  
Author(s):  
Shih-Hau Fang
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Signal Strength ◽  
Histogram Equalization ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Location Based Services ◽  
Indoor Environments ◽  
Positioning Systems

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Received signal strength (RSS), mostly utilized in Wi-Fi fingerprinting systems, is known to be unreliable due to two reasons: orientation mismatch and variations in hardware. This chapter introduces an approach based on histogram equalization to compensate for orientation mismatch in robust Wi-Fi localization. The proposed method involves converting the temporal-spatial radio signal strength into a reference function (i.e., equalizing the histogram). This chapter also introduces an enhanced positioning feature, which is called delta-fused principal strength, to enhance the robustness of Wi-Fi localization against the problem of heterogeneous hardware. This algorithm computes the pairwise delta RSS and then integrates with RSS using principal component analysis. The proposed methods effectively and efficiently improve the robustness of location estimation in the presence of mismatch orientation and hardware variations, respectively.

Self-Organizing Location Estimation Method Using Received Signal Strength

2006 ◽  
Vol E89-B (10) ◽  
pp. 2687-2695 ◽  
Author(s):  
Y. TAKIZAWA ◽  
P. DAVIS ◽  
M. KAWAI ◽  
H. IWAI ◽  
A. YAMAGUCHI ◽  
...  
Keyword(s):  
Estimation Method ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Self Organizing
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