Real time RSSI error reduction in distance estimation using RLS algorithm

Recently received signal strength (RSS)-based distance estimation technique has been proposed as a low complexity, low-cost solution for mobile communication node with minimum RSSI error. After investigating the existing algorithm of location technique, it is observed that the distribution of RSSI-value at each sample point is fluctuant even in the same position due to shadow fading effect. Therefore, here present a novel method for RSSI error reduction in distance estimation using recursive least square (RLS)-algorithm to the existing deterministic algorithms. The proposed method collects RSSI-values from the mobile communication node to build the probability model. Once the probability models are estimated for different standard deviation related to path loss exponent using adaptive filtering in real time, it is possible to accurately determine the distance between the mobile communication node and fixed communication node. From simulation results it is shown, that the accuracy of RSSI-value for mobile communication node in real time distance estimation is improved in changing environments.

[1]  Zhan Xu,et al.  RSSI localization algorithm based on RBF neural network , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering.

[2]  Yu-hong Liu,et al.  A position system of multi-APs based on RSSI , 2012, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet).

[3]  Ana M. Bernardos,et al.  Real time calibration for RSS indoor positioning systems , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

[4]  W. Chung,et al.  Enhanced Rssi-Based High Accuracy Real-Time User Location Tracking System For Indoor And Outdoor Environments , 2008 .

[5]  Chunxiao Jiang,et al.  Probabilistic Neural Network for RSS-Based Collaborative Localization , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[6]  Wanhee Kim,et al.  Effects of shadow fading in indoor RSSI ranging , 2012, 2012 14th International Conference on Advanced Communication Technology (ICACT).

[7]  Santiago Mazuelas,et al.  Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks , 2009, IEEE Journal of Selected Topics in Signal Processing.

[8]  Hongyu Shi A new weighted centroid localization algorithm based on RSSI , 2012, 2012 IEEE International Conference on Information and Automation.

[9]  Raj Kumar Thenua SIMULATION AND PERFORMANCE ANALYASIS OF ADAPTIVE FILTER IN NOISE CANCELLATION , 2010 .

[10]  Ignas Niemegeers,et al.  A survey of indoor positioning systems for wireless personal networks , 2009, IEEE Communications Surveys & Tutorials.