Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks

Young Min Ki, Jeong Woo Kim, Sang Rok Kim, Dong Ku Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Time of arrival (TOA) based geolocation schemes for indoor multi-hop environment are investigated and compared to some of conventional geolocation schemes such as least squares (LS) or residual weighting (RWGH). The multi-hop ranging involves positive multi-hop noise as well as non-line of sight (NLOS) and Gaussian measurement noise, so that it is more prone to ranging error than one-hop range. In this paper, RWGH algorithm is modified by adapting weighted residual normalization considering the number of hops taken to measure each ranging. The iterative positive noise mitigation schemes are further developed by using distance enlargement test (DET) to mitigate the multi-hop ranging noise. Simulation results show that the proposed modified RWGH algorithms show 5 to 25% smaller average estimation error compared to LS and RWGH for both positive noise mitigation and no mitigation cases, and the positive noise mitigation schemes provide 28 to 42% error mitigation compared to no mitigation schemes.

Original languageEnglish
Title of host publicationPersonal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings
EditorsPedro Cuenca, Luiz Orozco-Barbosa
PublisherSpringer Verlag
Pages471-482
Number of pages12
ISBN (Electronic)9783540451747
ISBN (Print)3540451749, 9783540451747
Publication statusPublished - 2006 Jan 1
EventIFIP TC6 11th International Conference on Personal Wireless Communications, PWC 2006 - Albacete, Spain
Duration: 2006 Sep 202006 Sep 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4217 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherIFIP TC6 11th International Conference on Personal Wireless Communications, PWC 2006
CountrySpain
CityAlbacete
Period06/9/2006/9/22

Fingerprint

Multi-hop Wireless Networks
Time of Arrival
Weighting
Multi-hop
Wireless networks
Least Squares
Error analysis
Enlargement
Estimation Error
Normalization
Time of arrival
Range of data
Simulation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ki, Y. M., Kim, J. W., Kim, S. R., & Kim, D. K. (2006). Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks. In P. Cuenca, & L. Orozco-Barbosa (Eds.), Personal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings (pp. 471-482). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4217 LNCS). Springer Verlag.
Ki, Young Min ; Kim, Jeong Woo ; Kim, Sang Rok ; Kim, Dong Ku. / Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks. Personal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings. editor / Pedro Cuenca ; Luiz Orozco-Barbosa. Springer Verlag, 2006. pp. 471-482 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "Time of arrival (TOA) based geolocation schemes for indoor multi-hop environment are investigated and compared to some of conventional geolocation schemes such as least squares (LS) or residual weighting (RWGH). The multi-hop ranging involves positive multi-hop noise as well as non-line of sight (NLOS) and Gaussian measurement noise, so that it is more prone to ranging error than one-hop range. In this paper, RWGH algorithm is modified by adapting weighted residual normalization considering the number of hops taken to measure each ranging. The iterative positive noise mitigation schemes are further developed by using distance enlargement test (DET) to mitigate the multi-hop ranging noise. Simulation results show that the proposed modified RWGH algorithms show 5 to 25{\%} smaller average estimation error compared to LS and RWGH for both positive noise mitigation and no mitigation cases, and the positive noise mitigation schemes provide 28 to 42{\%} error mitigation compared to no mitigation schemes.",
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Ki, YM, Kim, JW, Kim, SR & Kim, DK 2006, Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks. in P Cuenca & L Orozco-Barbosa (eds), Personal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4217 LNCS, Springer Verlag, pp. 471-482, IFIP TC6 11th International Conference on Personal Wireless Communications, PWC 2006, Albacete, Spain, 06/9/20.

Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks. / Ki, Young Min; Kim, Jeong Woo; Kim, Sang Rok; Kim, Dong Ku.

Personal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings. ed. / Pedro Cuenca; Luiz Orozco-Barbosa. Springer Verlag, 2006. p. 471-482 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4217 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Time of arrival (TOA) based geolocation schemes for indoor multi-hop environment are investigated and compared to some of conventional geolocation schemes such as least squares (LS) or residual weighting (RWGH). The multi-hop ranging involves positive multi-hop noise as well as non-line of sight (NLOS) and Gaussian measurement noise, so that it is more prone to ranging error than one-hop range. In this paper, RWGH algorithm is modified by adapting weighted residual normalization considering the number of hops taken to measure each ranging. The iterative positive noise mitigation schemes are further developed by using distance enlargement test (DET) to mitigate the multi-hop ranging noise. Simulation results show that the proposed modified RWGH algorithms show 5 to 25% smaller average estimation error compared to LS and RWGH for both positive noise mitigation and no mitigation cases, and the positive noise mitigation schemes provide 28 to 42% error mitigation compared to no mitigation schemes.

AB - Time of arrival (TOA) based geolocation schemes for indoor multi-hop environment are investigated and compared to some of conventional geolocation schemes such as least squares (LS) or residual weighting (RWGH). The multi-hop ranging involves positive multi-hop noise as well as non-line of sight (NLOS) and Gaussian measurement noise, so that it is more prone to ranging error than one-hop range. In this paper, RWGH algorithm is modified by adapting weighted residual normalization considering the number of hops taken to measure each ranging. The iterative positive noise mitigation schemes are further developed by using distance enlargement test (DET) to mitigate the multi-hop ranging noise. Simulation results show that the proposed modified RWGH algorithms show 5 to 25% smaller average estimation error compared to LS and RWGH for both positive noise mitigation and no mitigation cases, and the positive noise mitigation schemes provide 28 to 42% error mitigation compared to no mitigation schemes.

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M3 - Conference contribution

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Ki YM, Kim JW, Kim SR, Kim DK. Modified RWGH and positive noise mitigation schemes for TOA geolocation in indoor multi-hop wireless networks. In Cuenca P, Orozco-Barbosa L, editors, Personal Wireless Communications - IFIP TC6 11th International Conference, PWC 2006, Proceedings. Springer Verlag. 2006. p. 471-482. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).