Abstract :
The path loss exponent is very important parameter for localization using receive signal strength (RSS). In actual environments, path loss exponent for each link (target to each receive node) differs. However, the conventional localization methods use the same path loss exponent for all links. Hence, there are some mismatches between the real path loss exponent and the one used to estimate. We proposed the localization method that considers all the combinations of path loss exponents for each link and estimates the target location by averaging the target locations derived with all the combinations. However, the amount of calculation is huge. In this paper we propose RSS-based localization in environments with different path loss exponent for each link. The proposed method is a grid-based centralized localization using RSS. First the proposed method sets the minimum distance di,min and maximum distance di,max for each node i by using the RSS of each receive node i and the minimum and maximum path loss exponents set before estimation. Next, it calculates the distance di,(k,l) between the candidate target position (k, I) and each receive node i. If di,min les di,(k,l) les di,max, vote the grid (k,l). These processes are performed for all the receive nodes over the search area. Finally, the grid point with most voting is estimated to be the target location. According to the simulation results, we show that the proposed method achieves the higher localization accuracy than the conventional localization method using the same path loss exponent for all the links when the distribution of the path loss exponents over the field is uniform distribution.
Keywords :
array signal processing; distributed sensors; RSS-based localization; grid-based centralized localization; path loss exponent; receive signal strength; Bandwidth; Collaboration; Computer science; Energy consumption; Monitoring; Reflection; Signal processing algorithms; Target tracking; Time difference of arrival; Voting;