Hybrid Mechanism for Multiple User Indoor Localization Using Smart Antenna

Abstract

GPS is commonly used for navigation. But Location estimation in indoor environments is not possible using GPS, as GPS signals cannot work in indoor environment. In indoor localization there is a huge impact of multipath parameters like shadowing, reflection, refraction, diffraction phenomena which have an impact on the position estimation which leads to inaccurate localization. Large number of Access Points (APs) equipped with single antenna could receive enough Receive Signal Strength (RSS) information that gives information about signal characteristics of the target area. But this results in a large cost of deployment. Various localization methods available are: TDOA, TOA, AOA, Location Finger Printing, GPS and RSSI.However in all these approaches the localization depends either on distance or on angle or on time only. In this paper the hybrid mechanism of range and angle measurements is considered. This proposed mechanism will provide an indoor positioning solution using the smart antenna architecture to increase the location estimation accuracy using mode of RSSI values followed by adaptive filtering.

Location and sensing network for industrial automation

“…There are several methodologies utilized to triangulate a mobile tag. The most common techniques are localization based on received signal strength (RSSI), Time of Arrival (ToA), Angle of Arrival (AoA), and Time Difference of Arrival (TDoA) [12]. Despite various methodologies utilized to estimate the distance of a mobile tag from a fixed node many indoor tracking systems utilize triangulation to pin-point the location of a mobile tag.…”

“…To realize a reliable localization accuracy it was experimented that at least 5 samples are required. Therefore, as shown in Formula ( 11) latency of MT to be 250 ms and since each AN takes sensory data of MTs and add its ID, and RSSI values to it, it is expected that each AN require 750 ms of delay in the system as calculated in Formula (12). Therefore, assuming 10 ms is required for synchronization of system it takes 2510 ms or 2.51 seconds for system to go through a full cycle.…”

Location and sensing network for industrial automation

“…There are several methodologies utilized to triangulate a mobile tag. The most common techniques are localization based on received signal strength (RSSI), Time of Arrival (ToA), Angle of Arrival (AoA), and Time Difference of Arrival (TDoA) [12]. Despite various methodologies utilized to estimate the distance of a mobile tag from a fixed node many indoor tracking systems utilize triangulation to pin-point the location of a mobile tag.…”

“…To realize a reliable localization accuracy it was experimented that at least 5 samples are required. Therefore, as shown in Formula ( 11) latency of MT to be 250 ms and since each AN takes sensory data of MTs and add its ID, and RSSI values to it, it is expected that each AN require 750 ms of delay in the system as calculated in Formula (12). Therefore, assuming 10 ms is required for synchronization of system it takes 2510 ms or 2.51 seconds for system to go through a full cycle.…”

An improved hybrid indoor positioning system based on surface tessellation artificial neural network

“…Another hybrid approach is carried out in Sharma and Gulhane. 14 The proposed system combines a mechanism of range-based technique with multiple angle measurements (AOA). However, the experimental analysis was not discussed and incomplete.…”