scholarly journals Hybrid RSS/AOA Localization using Approximated Weighted Least Square in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1159 ◽  
Author(s):  
SeYoung Kang ◽  
TaeHyun Kim ◽  
WonZoo Chung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Least Squares ◽  
Covariance Matrix ◽  
Weighted Least Squares ◽  
Target Position ◽  
Superior Performance ◽  
Wireless Sensor ◽  
Error Covariance Matrix ◽  
Error Covariance

We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.

scholarly journals A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

2018 ◽  
Vol 11 (6) ◽  
pp. 3263-3280 ◽  
Author(s):  
Swadhin Nanda ◽  
J. Pepijn Veefkind ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Measurement Error ◽  
Least Squares ◽  
Covariance Matrix ◽  
Weighted Least Squares ◽  
Dynamic Scaling ◽  
Aerosol Layer ◽  
Error Covariance Matrix ◽  
Layer Height ◽  
Error Covariance ◽  
Least Squares Approach

Abstract. This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758–770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe.

scholarly journals A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

2018 ◽  
Author(s):  
Swadhin Nanda ◽  
J. Pepijn Veefkind ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Measurement Error ◽  
Least Squares ◽  
Covariance Matrix ◽  
Weighted Least Squares ◽  
Dynamic Scaling ◽  
Aerosol Layer ◽  
Error Covariance Matrix ◽  
Layer Height ◽  
Error Covariance ◽  
Least Squares Approach

Abstract. This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758 nm–770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons traveling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires, and the October 2017 Portugal wildfire plume over Western Europe.

scholarly journals Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Phet Aimtongkham ◽  
Tri Gia Nguyen ◽  
Chakchai So-In
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Packet Loss ◽  
Superior Performance ◽  
Wireless Sensor ◽  
Volume Data ◽  
Energy Aware ◽  
Fuzzy Logic Systems ◽  
Hop Count

Network congestion is a key challenge in resource-constrained networks, particularly those with limited bandwidth to accommodate high-volume data transmission, which causes unfavorable quality of service, including effects such as packet loss and low throughput. This challenge is crucial in wireless sensor networks (WSNs) with restrictions and constraints, including limited computing power, memory, and transmission due to self-contained batteries, which limit sensor node lifetime. Determining a path to avoid congested routes can prolong the network. Thus, we present a path determination architecture for WSNs that takes congestion into account. The architecture is divided into 3 stages, excluding the final criteria for path determination: (1) initial path construction in a top-down hierarchical structure, (2) path derivation with energy-aware assisted routing, and (3) congestion prediction using exponential smoothing. With several factors, such as hop count, remaining energy, buffer occupancy, and forwarding rate, we apply fuzzy logic systems to determine proper weights among those factors in addition to optimizing the weight over the membership functions using a bat algorithm. The simulation results indicate the superior performance of the proposed method in terms of high throughput, low packet loss, balancing the overall energy consumption, and prolonging the network lifetime compared to state-of-the-art protocols.

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