Localization and Mapping in Wireless Networks: Models and Algorithms

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Journal ISSN
Volume Title
School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2018-04-13
Date
2018
Major/Subject
Mcode
Degree programme
Language
en
Pages
134 + app. 80
Series
Aalto University publication series DOCTORAL DISSERTATIONS, 55/2018
Abstract
In recent years, location-based services (LBS) have become a key component of wireless technology. A large variety of radio-based localization systems, such as the Global Positioning System (GPS), have been developed during last decades. However, satellite-based or cellular systems may have limited availability and reduced accuracy in indoor and dense urban environments. This is partly due to propagation effects such as multipath reflections and scattering of radio signals in such environments. Indoor localization has many important applications such as first responders, tracking and navigation in airports and shopping malls, surveillance, and robotics. The performance of wireless localization, especially in indoor environments, can be improved by cooperation among the network nodes, combining different sensing modalities, and exploiting multipath propagation of radio signals. In this thesis, the problem of cooperative network localization with different sensing approaches is studied. The employed sensing methods are pairwise distance estimation, hybrid distance and direction estimation, and multipath distance estimation. Novel problem formulations for cooperative localization are introduced and optimal algorithms are derived. Algorithms for high resolution distance and direction estimation, and network clock synchronization are also developed in order to support the proposed localization methods. High accuracy is facilitated by the broad bandwidth of wireless signals as well as the use of multiantenna transceivers in most current and emerging wireless systems. The proposed algorithms provide improved reliability and accuracy in comparison to the state-of-the art techniques. A geometrical model or map of the environment is necessary information for multipath-aided localization. Indoor maps are also vital to many other applications such as robot navigation and emergency response. Specular reflections of radio (or acoustic) signals form the walls and other objects in the environment contain rich geometric information, which can be exploited to create indoor maps. Two algorithms for indoor mapping with different sensing modalities are presented in this thesis. Multipath delay estimation, and hybrid multipath delay and direction estimation are employed. Typically mapping algorithms require exact information about sensor positions. Therefore, a radio-based cooperative simultaneous localization and mapping (SLAM) algorithm is also developed in this research work. The proposed algorithm exploits the multipath propagation of radio signals in order to jointly estimate the locations of the nodes and a map of the indoor environment. The proposed algorithms produce indoor maps with higher precision and enhanced geometric information compared to the state of the art.
Description
Supervising professor
Koivunen, Visa, Prof., Aalto University, Department of Signal Processing and Acoustics, Finland
Thesis advisor
Koivunen, Visa, Prof., Aalto University, Department of Signal Processing and Acoustics, Finland
Keywords
localization, indoor mapping, cooperation, synchronization, SLAM
Other note
Parts
  • [Publication 1]: Hassan Naseri, Mario Costa, Visa koivunen, A generalized formulation for harmonic retrieval in correlated noise, 2014 48th Annual Conference in Information Sciences and Systems, (CISS 2014), Princeton, USA.
    DOI: 10.1109/CISS.2014.6814179 View at publisher
  • [Publication 2]: Hassan Naseri, Jussi Salmi, Visa Koivunen, Synchronization and ranging by scheduled broadcasting, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013
    DOI: 10.1109/ICASSP.2013.6638588 View at publisher
  • [Publication 3]: Hassan Naseri, Visa koivunen, Cooperative joint synchronization and localization using time delay measurements, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Sanghai, China 2013,
    DOI: 10.1109/ICASSP.2016.7472257 View at publisher
  • [Publication 4]: Hassan Naseri, Visa Koivunen, A Bayesian algorithm for distributed network localization using distance and direction data, submitted to the IEEE Transactions on Signal and Information Processing over Networks, 2018
  • [Publication 5]: Hassan Naseri, Mário Costa, Visa Koivunen, Multipath-aided cooperative network localization using convex optimization, in 2014 48th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA,
    DOI: 10.1109/ACSSC.2014.7094716 View at publisher
  • [Publication 6]: Hassan Naseri, Visa Koivunen, Indoor mapping based on time delay estimation in wireless networks, in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia,
    DOI: 10.1109/ICASSP.2015.7178406 View at publisher
  • [Publication 7]: Hassan Naseri, Jussi Salmi, Visa Koivunen, Indoor Mappinmg Using MIMO Radio Channel Measurements, International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017) New Orleans, USA,
    DOI: 10.1109/ICASSP.2017.7952771 View at publisher
  • [Publication 8]: Hassan Naseri, Visa Koivunen, Cooperative Simultaneous Localization and Mapping by Exploiting Multipath Propagation, IEEE Transactions on Signal Processing, 2017, 65, 1, pp. 200-211,
    DOI: 10.1109/TSP.2016.2616324 View at publisher
  • [Errata file]: Errata publ. 3, p.3; publ. 5, p.9; publ. 6, p.3
Citation