The objective of this paper is to develop the theory for integrating magnetometer measurements with an existing inertial
navigation system (INS) aided by an acoustic wireless sensor network. The system without magnetometer measurements
provides position information reliably. However, in the absence of dynamic motion the orientation errors are not
observable using the sensor network, which only provides position information. The magnetometer provides consistent
observability of the orientation. The measurement model needed to estimate the orientation errors using the
magnetometer is derived in this paper. This measurement model is integrated with measurements from the acoustic
sensor network into a complimentary Kalman filter that is used to estimate the error states of an INS.
Indoor localization with sensing capabilities is the missing link for a Geospatial Information System and sensor web.
The sensor network is capable of environmental monitoring and geo-tagging sensor data. This paper presents a unique
algorithm which uses fusion of Radio Signal Strength Indicator and Time Difference of Arrival for centimeter level accurate
indoor localization using wireless sensor network motes. The paper also proposes the integration of various environmental
sensors with wireless sensor network. The acquired sensor data can be geo-tagged with the translated global coordinates
and additional sensory metadata. With the use of semantic sensor web, this sensor information can be utilized in various
decision making scenarios for critical situations. The main goal of the paper is to use indoor localization assisted by sensor
fusion and semantic web for first responders in emergency scenarios.
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