No abstract

Indoor tracking and navigation (ITN) mainly depend on indoor localization. An impulse radio ultra-wideband (IR-UWB) is the most advanced technology for precision indoor localization. Besides its precision, the IR-UWB also has low complex hardware, low power consumption, and a flexible data rate that makes it the ideal candidate for ITN. However, two significant challenges impede the achievement of highresolution accuracy and optimum performance: non-line-of-sight (NLOS) channel condition and multipath propagation (MPP). To enhance the performance under these conditions, the ranging error is estimated and corrected using parameters' uncertainties. The uncertainties in the channel's parameters have a relationship with the error, and these uncertainties are induced due to the NLOS and MPP propagation conditions. The parameters are collected in real-time experimental setups in two different environments. A proposed fuzzy inference model utilizes these uncertainties and the relationship to estimate ranging errors. The model is evaluated, and its performance is gauged in terms of residual ranging error cumulative distribution, root mean square error, and outage probability parameters using experimental measurements and compared with the state-of-the-art work. Moreover, the proposed fuzzy model is evaluated for computational complexity in terms of execution time and compared with the state-of-the-art work. The time is estimated on the targeted embedded system. The experimental and simulated results show that the proposed model effectively minimizes the ranging errors and computational burden. Moreover, the model does not induce a delay in estimating ranging error due to the non-statistical based solution. INDEX TERMS Fuzzy logic, indoor tracking and navigation, impulse radio ultrawide band, localization, computational complexity.

Ahstract-A modified round trip time (RTT) time of arrival (ToA ) technique is present to measure the distance between two nodes in wireless sensor network. The ultra wide band spectrum and Gaussian monopulse shaping is used on MATLAB platform for simulations. The nodes are simulated under following envi ronments of 802.1S.4a channel model for distances measurement: residential, office, industrial, outdoor and open outdoor. The measured distances are analyzed and compared with set distances using calculated absolute error versus set distance graphs for different UWB frequencies, 802.1S.4a channels and sampling fre quencies. Finally, trilateration using singular value decomposition (SVD) method calculations are done for localization by using the measured distances. The position errors with respect to set positions are calculated for different trilateration layouts.

In this paper, the proposed methodology calculates the distance between two nodes in Wireless Sensor Network for localization purpose. The methodology is a variant of Time of Arrival (TOA) methodology. The simulations are done in Matlab using Ultra wide band spectrum and Gaussian monocycle pulses. The measured distances are compared with set distances and mean square errors are calculated. Finally, the set distance and measured distances are compared for various transmission frequencies within UWB spectrum.