Search ETDs:
Application of Kalman Filter to estimate position of a mobile node in Indoor environments
Gudipati, Mounika

2016, Master of Science in Engineering, University of Akron, Computer Engineering.
Estimating the position of mobile agents in indoor environments is a challenging problem especially when the estimates must be obtained using commercial, low cost devices. The work in this thesis presents experimental results that demonstrate the effectiveness of our approach, that integrates the signal strength data with sensed values of acceleration and angular velocity. A well-known framework called the Kalman Filter is used. To cope with the noise in the measured values, different versions of the Kalman Filter had to be used such as the Extended Kalman Filter and the Unscented Kalman Filter. This framework allowed us to systematically fuse the data from multiple sources to improve the accuracy of the position estimates. Our results demonstrate that positional accuracy of 0.8m within an 30m x 10m area is achieved.
In the future, this work can be extended to further reduce the error in the location estimates by inclusion of encoders.
Shiva Sastry, Dr (Advisor)
Nghi Tran, Dr (Committee Member)
Jin Kocsis, Dr (Committee Member)
55 p.

Recommended Citations

Hide/Show APA Citation

Gudipati, M. (2016). Application of Kalman Filter to estimate position of a mobile node in Indoor environments. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

Hide/Show MLA Citation

Gudipati, Mounika. "Application of Kalman Filter to estimate position of a mobile node in Indoor environments." Electronic Thesis or Dissertation. University of Akron, 2016. OhioLINK Electronic Theses and Dissertations Center. 22 Jun 2018.

Hide/Show Chicago Citation

Gudipati, Mounika "Application of Kalman Filter to estimate position of a mobile node in Indoor environments." Electronic Thesis or Dissertation. University of Akron, 2016. https://etd.ohiolink.edu/

Files

GudipatiM.t (final).pdf (663.03 KB) View|Download