Abstract
Due to the ease of development and inexpensiveness, indoor localization systems are getting a significant attention but, with recent advancement in context and location aware technologies, the solutions for indoor tracking and localization had become more critical. Ranging methods play a basic role in the localization system, in which received signal strength indicator- (RSSI-) based ranging technique gets the most attraction. To predict the position of an unknown node, RSSI measurement is an easy and reliable method for distance estimation. In indoor environments, the accuracy of the RSSI-based localization method is affected by strong variation, specially often containing substantial amounts of metal and other such reflective materials that affect the propagation of radio-frequency signals in nontrivial ways, causing multipath effects, dead spots, noise, and interference. This paper proposes an adaptive smoother based location and tracking algorithm for indoor positioning by making fusion of RSSI and link quality indicator (LQI), which is particularly well suited to support context aware computing. The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms.
Highlights
Due to the ease in deployment, inexpensiveness and potential applications in the smart building, security, and healthcare, indoor localization system gets significant attentions in these recent years
In our second filtering process, we proposed a fusion filter which is the fusion of Received Signal Strength Indicator (RSSI) and link quality indicator (LQI) where we decided to use LQI as a reference aid when the RSSI or LQI is below RSSI and LQI threshold
For our second experiment we used a fusion of LQI and RSSI values based on the filtering conditions to smooth the measured RSSI
Summary
Due to the ease in deployment, inexpensiveness and potential applications in the smart building, security, and healthcare, indoor localization system gets significant attentions in these recent years. The localization systems presented in this paper are based on the RSSI as a strength indicator and LQI as a quality indicator of a received packet. The indoor localization systems presented in this report are based on the RSSI as a strength indicator and LQI as a quality indicator of received packets. The effect of distance on received signal strength (RSS) can be measured by RSSI and LQI provided by the radio. This scheme performs with respect to the signal analysis which is to filter the original signals in order to remove the noise.
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