Narrowband Radio Frequency Inference: Physical Modeling and Measurement Processing

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2018-06-28
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Author
Date
2018
Department
Tietoliikenne- ja tietoverkkotekniikan laitos
Department of Communications and Networking
Major/Subject
Mcode
Degree programme
Language
en
Pages
164 + app. 92
Series
Aalto University publication series DOCTORAL DISSERTATIONS, 100/2018
Abstract
Narrowband RF inference is an emerging field that aims at estimating the location and actions of a person using commercial off-the-shelf narrowband wireless communication devices. In the research field, the location and actions of a person are estimated using the received signal strength measurements of the receivers. In this thesis, both statistical and deterministic measurement models are derived that can be used for processing the data to achieve the goals set by the applications. In particular, device-free localization and respiration rate monitoring are considered, and the models are used and extended for various scenarios. The results suggest that the models allow optimized deployments and low-complexity systems that can reach the performance of state-of-the-art systems. The research in the thesis shows that the impact of a person on the measurements of a link can be represented using mutually exclusive three temporal states. This temporal characterization extends the widely used two-state model by adding a state to explicitly describe the reflection dominated the effect. The reflection model enables different possibilities, which are significant in a number practical aspects. First, the measurement of the links can be related to a large area around the link-line. This relation can be used for developing localization systems using as few as two receivers and can be used for detecting the occupancy of a region using a single receiver. Second, the impact of reflection can be parametrized using a single parameter known as excess path length. This parameter allows one to determine the effective area of the links and relate them to the measurements, which in turn enables development of a localization system that is detector based and has a low complexity. Third, the excess path length parametrization also enables one to investigate the impact of small amplitude movements, such as inhaling and exhaling induced chest movements. These implications are elaborated in depth and their validity is evaluated through experimentation.  The models presented in the thesis are elaborated numerically and validated using empirical measurement data. For the purpose, two different test subjects are used: a mobile robot equipped with a container that is simulating human torso, and a human. The former can navigate while accurately localizing itself in indoor environments, and has a repeatable set of physical parameters affecting the measurement. The latter allows one to observe the performance under realistic operating conditions. The effect of the test subjects on the received signal strength is measured using an experimental setup that is designed to acquire high-quality measurements. The acquired data are used for making conclusive statements about the validity of the models and assess the generality of the underlying assumptions. Therefore, the thesis is composed of both mathematical modeling and the development of the validation system. 
Description
Supervising professor
Jäntti, Riku, Asst. Prof., Aalto University, Department of Communications and Networking, Finland
Keywords
RF inference, device-free localization, radio tomographic imaging, received signal strength, physical model
Other note
Parts
  • [Publication 1]: Hüseyin Yigitler, Ossi Kaltiokallio, Riku Jäntti. A Management Framework for Device-free Localization. In The International Joint Conference on Neural Networks (IJCNN), pp. 1–8, Dallas, Texas, August 2013.
    DOI: 10.1109/IJCNN.2013.6707131 View at publisher
  • [Publication 2]: Hüseyin Yigitler, Riku Jäntti, Neal Patwari. On Log-Normality of RSSI in Narrowband Receivers Under Static Conditions. IEEE Signal Processing Letters, vol. 24, no. 4, pp. 367-371, April 2017.
    DOI: 10.1109/LSP.2017.2657332 View at publisher
  • [Publication 3]: Ossi Kaltiokallio, Hüseyin Yigitler, Riku Jäntti. A Three-State Received Signal Strength Model for Device-free Localization. IEEE Transactions on Vehicular Technology, vol. 66, no. 10, pp. 9226-9240, October 2017.
    DOI: 10.1109/TVT.2017.2701399 View at publisher
  • [Publication 4]: Hüseyin Yigitler, Riku Jäntti. Experimental accuracy assessment of radio tomographic imaging methods. In IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), pp. 1–6, Sydney, March 2016.
    DOI: 10.1109/PERCOMW.2016.7457117 View at publisher
  • [Publication 5]: Hüseyin Yigitler, Ossi Kaltiokallio, Riku Jäntti, Neal Patwari. Detector Based Radio Tomographic Imaging. IEEE Transactions on Mobile Computing, vol. 17, no.1, pp. 58-71, January 2018.
    DOI: 10.1109/TMC.2017.2699634 View at publisher
  • [Publication 6]: Ossi Kaltiokallio, Hüseyin Yigitler, Riku Jäntti, Neal Patwari. Noninvasive Respiration Rate Monitoring Using a Single COTS TX-RX Pair. In Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, IPSN, pp. 59–69, Berlin, April 2014.
    DOI: 10.1109/IPSN.2014.6846741 View at publisher
  • [Publication 7]: Hüseyin Yigitler, Ossi Kaltiokallio, Roland Hostettler, Riku Jäntti, Neal Patwari, Simo Särkkä. RSS Models for Respiration Rate Monitoring. Submitted to submitted to IEEE Transactions on Signal Processing, November 2017
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Permanent link to this item
https://urn.fi/URN:ISBN:978-952-60-8009-3
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[diss] Sähkötekniikan korkeakoulu / ELEC