scholarly journals Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

Sensors ◽  
2011 ◽  
Vol 11 (9) ◽  
pp. 8569-8592 ◽  
Author(s):  
Paula Tarrío ◽  
Ana M. Bernardos ◽  
José R. Casar
Keyword(s):  
Least Squares ◽  
Weighted Least Squares ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Strength Based ◽  
Least Squares Techniques

scholarly journals Received signal strength–based target localization under spatially correlated shadowing via convex optimization relaxation

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878366 ◽  
Author(s):  
Shengming Chang ◽  
Youming Li ◽  
Hui Wang ◽  
Gang Wang
Keyword(s):  
Convex Optimization ◽  
Weighted Least Squares ◽  
Equivalent Form ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Target Localization ◽  
Correlated Shadowing ◽  
Spatially Correlated ◽  
Strength Based ◽  
Log Normal

Received signal strength–based target localization methods normally employ radio propagation path loss model, in which the log-normal shadowing noise is generally assumed to follow a zero-mean Gaussian distribution and is uncorrelated. In this article, however, we represent the simplified additive noise by the spatially correlated log-normal shadowing noise. We propose a new convex localization estimator in wireless sensor networks by using received signal strength measurements under spatially correlated shadowing environment. First, we derive a new non-convex estimator based on weighted least squares criterion. Second, by using the equivalence of norm, the derived estimator can be reformulated as its equivalent form which has no logarithm in the objective function. Then, the new estimator is relaxed by applying efficient convex relaxation that is based on second-order cone programming and semi-definite programming technique. Finally, the convex optimization problem can be efficiently solved by a standard interior-point method, thus to obtain the globally optimal solution. Simulation results show that the proposed estimator solves the localization problem efficiently and is close to Cramer–Rao lower bound compared with the state-of-the-art approach under correlated shadowing environment.

scholarly journals Visible Light Positioning with Multiple Transmitters and Multiple Receiving Sensors

2021 ◽  
Author(s):  
Muhammad Salman Bashir
Keyword(s):  
Visible Light ◽  
Least Squares ◽  
Unbiased Estimator ◽  
Communication Systems ◽  
Weighted Least Squares ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Best Linear Unbiased Estimator ◽  
Positioning Systems ◽  
Best Linear Unbiased

Visible light communications (VLC) based positioning systems will form an important part of the future generation wireless communication systems because they offer higher accuracy for indoor positioning as compared to radio frequency based systems. In this paper, we have used non Bayesian statistical signal processing techniques for the hybrid time-of-arrival/received-signal-strength and hybrid time-difference-of-arrival/received-signal-strength based positioning. These hybrid measurements are combined with the following fusion algorithms: weighted least squares and the best linear unbiased estimator. These two fusion algorithms are compared in terms of the mean Euclidean error as a function of various parameters such as signal-to-noise ratio, transmitter arrangement and synchronization error. Even though the performance of the weighted least squares algorithm is better, the best linear unbiased estimator is still an attractive algorithm for systems that require a lower complexity.

2.4 GHz RF Received Signal Strength Based Node Separation in WSN Monitoring Infrastructure for Millet and Rice Vegetation

2021 ◽  
pp. 1-1
Author(s):  
Pankaj Pal ◽  
Rashmi Priya Sharma ◽  
Sachin Tripathi ◽  
Chiranjeev Kumar ◽  
Dharavath Ramesh
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Strength Based

Context-aware, self-scaling Fuzzy ArtMap for received signal strength based location systems

2007 ◽  
Vol 12 (7) ◽  
pp. 699-713 ◽  
Author(s):  
Uzair Ahmad ◽  
Andrey V. Gavrilov ◽  
Young-Koo Lee ◽  
Sungyoung Lee
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Fuzzy Artmap ◽  
Context Aware ◽  
Strength Based ◽  
Location Systems
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