Abstract:
Range of applications for Wireless Sensor Networks (WSNs) is increasing rapidly. One class of such applications is Energy-Aware Wireless Positioning Systems for
situation awareness. Localization deals with determining a
target node?s position in WSN by analyzing signals exchanged
between nodes. Received Signal Strength Indicator (RSSI)
represents the ratio between received signal power and a
reference power, and is typically used to estimate distances
between nodes. RSSI distance estimations are affected by
many factors. This paper aims to enhance the accuracy of
RSSI-based localization techniques in ZigBee Networks
through studying the communication channel status between
two nodes. As the network nodes are exposed to high noise
levels, position estimation accuracy deteriorates. A novel
adaptive localization scheme is proposed; Two-State Markov
model with moving average is employed to detect unpredictable RSSI readings that may reflect badly on the estimation.
The proposed scheme achieves better estimation accuracy,
for example, the estimation error was reduced from 11.7 m
to just 3 m using the proposed scheme.