Threshold Selection Based on the SNR in Time of Arrival Localization System Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/8336h5627

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  • Threshold-based time of arrival (TOA) estimation is a technique for high-precision indoor localization. Existing threshold selection methods, such as xed thresh- old and normalized threshold methods, do not consider the signal-to-noise radio (SNR) value at the receiver. This is not desired for high-precision positioning. A proper threshold value depends on the statistics of the received signal. The dominating parameter that a ects the statistics of the receiver is the SNR. In this thesis, we propose an adaptive threshold selection method which takes the SNR value at the receiver into consideration, resulting in an increased precision of the timing detection ( rst peak detection). The performance of the proposed method is evaluated in simulation. The simulation uses ultra wideband transmitted signal, and adopts the IEEE 802.15.3a channel model. Performance of the normalized threshold method and the proposed selection threshold method are compared.
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  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2016-03-22T19:15:04Z (GMT) No. of bitstreams: 2 license_rdf: 1527 bytes, checksum: d4743a92da3ca4b8c256fdf0d7f7680f (MD5) LyuTao2016.pdf: 1759179 bytes, checksum: 186c3258377862273ff16ede088bff34 (MD5)
  • description.provenance : Submitted by Tao Lyu (lyut@oregonstate.edu) on 2016-03-19T00:00:17Z No. of bitstreams: 2 license_rdf: 1527 bytes, checksum: d4743a92da3ca4b8c256fdf0d7f7680f (MD5) LyuTao2016.pdf: 1759179 bytes, checksum: 186c3258377862273ff16ede088bff34 (MD5)
  • description.provenance : Made available in DSpace on 2016-03-24T18:54:57Z (GMT). No. of bitstreams: 2 license_rdf: 1527 bytes, checksum: d4743a92da3ca4b8c256fdf0d7f7680f (MD5) LyuTao2016.pdf: 1759179 bytes, checksum: 186c3258377862273ff16ede088bff34 (MD5) Previous issue date: 2016-03-11
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2016-03-24T18:54:57Z (GMT) No. of bitstreams: 2 license_rdf: 1527 bytes, checksum: d4743a92da3ca4b8c256fdf0d7f7680f (MD5) LyuTao2016.pdf: 1759179 bytes, checksum: 186c3258377862273ff16ede088bff34 (MD5)

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