example.bib

@article{Reference1,
	Abstract = {We have developed an enhanced Littrow configuration extended cavity diode laser (ECDL) that can be tuned without changing the direction of the output beam. The output of a conventional Littrow ECDL is reflected from a plane mirror fixed parallel to the tuning diffraction grating. Using a free-space Michelson wavemeter to measure the laser wavelength, we can tune the laser over a range greater than 10 nm without any alteration of alignment.},
	Author = {C. J. Hawthorn and K. P. Weber and R. E. Scholten},
	Journal = {Review of Scientific Instruments},
	Month = {12},
	Number = {12},
	Numpages = {3},
	Pages = {4477--4479},
	Title = {Littrow Configuration Tunable External Cavity Diode Laser with Fixed Direction Output Beam},
	Volume = {72},
	Url = {http://link.aip.org/link/?RSI/72/4477/1},
	Year = {2001}}

@article{Reference3,
	Abstract = {Operating a laser diode in an extended cavity which provides frequency-selective feedback is a very effective method of reducing the laser's linewidth and improving its tunability. We have developed an extremely simple laser of this type, built from inexpensive commercial components with only a few minor modifications. A 780~nm laser built to this design has an output power of 80~mW, a linewidth of 350~kHz, and it has been continuously locked to a Doppler-free rubidium transition for several days.},
	Author = {A. S. Arnold and J. S. Wilson and M. G. Boshier and J. Smith},
	Journal = {Review of Scientific Instruments},
	Month = {3},
	Number = {3},
	Numpages = {4},
	Pages = {1236--1239},
	Title = {A Simple Extended-Cavity Diode Laser},
	Volume = {69},
	Url = {http://link.aip.org/link/?RSI/69/1236/1},
	Year = {1998}}

@article{Reference2,
	Abstract = {We present a review of the use of diode lasers in atomic physics with an extensive list of references. We discuss the relevant characteristics of diode lasers and explain how to purchase and use them. We also review the various techniques that have been used to control and narrow the spectral outputs of diode lasers. Finally we present a number of examples illustrating the use of diode lasers in atomic physics experiments. Review of Scientific Instruments is copyrighted by The American Institute of Physics.},
	Author = {Carl E. Wieman and Leo Hollberg},
	Journal = {Review of Scientific Instruments},
	Keywords = {Diode Laser},
	Month = {1},
	Number = {1},
	Numpages = {20},
	Pages = {1--20},
	Title = {Using Diode Lasers for Atomic Physics},
	Volume = {62},
	Url = {http://link.aip.org/link/?RSI/62/1/1},
	Year = {1991}}

@INPROCEEDINGS{FineGrainedIndoorTracking,
author={Z. Li and D. B. Acuña and Z. Zhao and J. L. Carrera and T. Braun},
booktitle={2016 IEEE International Conference on Communications (ICC)},
title={Fine-grained indoor tracking by fusing inertial sensor and physical layer information in WLANs},
year={2016},
pages={1-7},
abstract={Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.},
keywords={indoor navigation;indoor radio;particle filtering (numerical methods);radio tracking;sensor fusion;wireless LAN;CSI;WLANs;anchor nodes;channel state information;cheap commercial devices;fine-grained indoor tracking method;fine-grained physical layer information;indoor environments;indoor positioning;inertial sensor fusion;location-based services;network-based system;particle filter;physical layer information;range-based methods;velocity estimation;weighting technique;Atmospheric measurements;Distance measurement;Estimation;Fuses;Mobile communication;Particle measurements;Target tracking},
doi={10.1109/ICC.2016.7511162},
month={5},
Url = {http://ieeexplore.ieee.org/document/7511162/},}

@inproceedings{kessel2012compass,
  title={Compass and wlan integration for indoor tracking on mobile phones},
  author={Kessel, Moritz and Werner, Martin and Linnhoff-Popien, Claudia},
  booktitle={The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM’12)},
  pages={1--7},
  year={2012},
  organization={Citeseer},
  Url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.457.3796&rep=rep1&type=pdf}}

@inproceedings{brouwers2014incremental,
  title={Incremental wi-fi scanning for energy-efficient localization},
  author={Brouwers, Niels and Zuniga, Marco and Langendoen, Koen},
  booktitle={Pervasive Computing and Communications (PerCom), 2014 IEEE International Conference on},
  pages={156--162},
  year={2014},
  organization={IEEE},
  Url = {http://ieeexplore.ieee.org/document/6813956/}}

@MastersThesis{JoseMaster,
title={Improve trilateration accuracy by LOS/NLOS identification and MIMO},
author={Jose L. Carerra},
year={2015}}

@inproceedings{multipathEffects,
  title={Effects of multipath propagation and measurement noise in IEEE 802.11 g WLAN beacon for indoor localization},
  author={Sapumohotti, C and Alias, MY and Tan, SW},
  booktitle={PIERS Proceedings},
  volume={447451},
  pages={27--30},
  year={2012}
}

@article{surveyWirelessPersonal,
  title={A survey of indoor positioning systems for wireless personal networks},
  author={Gu, Yanying and Lo, Anthony and Niemegeers, Ignas},
  journal={IEEE Communications surveys \& tutorials},
  volume={11},
  number={1},
  pages={13--32},
  year={2009},
  publisher={IEEE}
}

@article{surveyIndoorTechniques,
  title={Survey of wireless indoor positioning techniques and systems},
  author={Liu, Hui and Darabi, Houshang and Banerjee, Pat and Liu, Jing},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)},
  volume={37},
  number={6},
  pages={1067--1080},
  year={2007},
  publisher={IEEE}
}

@book{sauter2010gsm,
  title={From GSM to LTE: An Introduction to Mobile Networks and Mobile Broadband},
  author={Sauter, M.},
  isbn={9780470978221},
  lccn={2010038166},
  series={Wiley Online Library: Books},
  url={https://books.google.ch/books?id=uso-6LN2YjsC},
  year={2010},
  publisher={Wiley}
}

@article{haverinen2009global,
  title={Global indoor self-localization based on the ambient magnetic field},
  author={Haverinen, Janne and Kemppainen, Anssi},
  journal={Robotics and Autonomous Systems},
  volume={57},
  number={10},
  pages={1028--1035},
  year={2009},
  publisher={Elsevier}
}

@article{afzal2010assessment,
  title={Assessment of indoor magnetic field anomalies using multiple magnetometers},
  author={Afzal, Muhammad Haris and Renaudin, Val{\'e}rie and Lachapelle, G{\'e}rard},
  journal={Proceedings of ION GNSS10},
  pages={1--9},
  year={2010}
}

@INPROCEEDINGS{Li2012feasableMagnetic,
author={B. Li and T. Gallagher and A. G. Dempster and C. Rizos},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on},
title={How feasible is the use of magnetic field alone for indoor positioning?},
year={2012},
pages={1-9},
abstract={The use of magnetic field variations for positioning and navigation has been suggested by several researchers. In most of the applications, the magnetic field is used to determine the azimuth or heading. However, for indoor applications, accurate heading determination is difficult due to the presence of magnetic field anomalies. Here location fingerprinting methodology can take advantage of these anomalies. In fact, the more significant the local anomalies, the more unique the magnetic “fingerprint”. In general, the more elements in each fingerprint, the better for positioning. Unfortunately, magnetic field intensity data only consists of three components. Since true north (or magnetic north) is generally unknown, even with help of the accelerometer to detect the direction of the gravity, only two components can be extracted, i.e. the horizontal intensity and the vertical intensity (or total intensity and inclination). Furthermore, moving objects containing ferromagnetic materials and electronic devices may affect the magnetic field. Tests were carried out to investigate the feasibility of using magnetic field alone for indoor positioning. Possible solutions are discussed.},
keywords={accelerometers;ferromagnetic materials;fingerprint identification;indoor communication;magnetic fields;navigation;accelerometer;electronic devices;ferromagnetic materials;heading determination;horizontal intensity;indoor positioning;location fingerprinting methodology;magnetic field anomaly;magnetic field intensity data;magnetic field variations;magnetic fingerprint;magnetic north;navigation;true north;vertical intensity;Fingerprint recognition;Indexes;Interference;Fingerprinting;Magnetic field},
doi={10.1109/IPIN.2012.6418880},
month={11},}

@INPROCEEDINGS{angermann2012CharacterizationMagnetic,
author={M. Angermann and M. Frassl and M. Doniec and B. J. Julian and P. Robertson},
booktitle={Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on},
title={Characterization of the indoor magnetic field for applications in Localization and Mapping},
year={2012},
pages={1-9},
abstract={To improve our understanding of the indoor properties of the perturbed Earth's magnetic field, we have developed a methodology to obtain dense and spatially referenced samples of the magnetic vector field on the ground's surface and in the free space above. This methodology draws on the use of various tracking techniques (photometric, odometric, and motion capture) to accurately determine the pose of the magnetic sensor, which can be positioned manually by humans or autonomously by robots to acquire densely gridded sample datasets. We show that the indoor magnetic field exhibits a fine-grained and persistent micro-structure of perturbations in terms of its direction and intensity. Instead of being a hindrance to indoor navigation, we believe that the variations of the three vector components are sufficiently expressive to form re-recognizable features based on which accurate localization is possible. We provide experimental results using our methodology to map the magnetic field on the ground's surface in our indoor research facilities. With the use of a magnetometer and very little computation, these resulting maps can serve to compensate the perturbations and subsequently determine pose of a human or robot in dead reckoning applications.},
keywords={SLAM (robots);compensation;indoor environment;magnetic fields;magnetic sensors;magnetometers;mobile robots;perturbation techniques;accurate localization;dead reckoning application;fine-grained microstructure;ground surface;indoor magnetic vector field;indoor navigation;indoor properties;localization and mapping;magnetic sensor pose;magnetometer;motion capture;odometric capture;perturbation compensation;perturbed Earth magnetic field;photometric capture;tracking technique;vector component},
doi={10.1109/IPIN.2012.6418864},
month={11},}

@INPROCEEDINGS{chapre2013RSSI,
author={Y. Chapre and P. Mohapatra and S. Jha and A. Seneviratne},
booktitle={Local Computer Networks (LCN), 2013 IEEE 38th Conference on},
title={Received signal strength indicator and its analysis in a typical WLAN system (short paper)},
year={2013},
pages={304-307},
abstract={Received signal strength based fingerprinting approaches have been widely exploited for localization. The received signal strength (RSS) plays a very crucial role in determining the nature and characteristics of location fingerprints stored in a radio-map. The received signal strength is a function of distance between the transmitter and receiving device, which varies due to various in-path interferences. A detailed analysis of factors affecting the received signal for indoor localization is presented in this paper. The paper discusses the effect of factors such as spatial, temporal, environmental, hardware and human presence on the received signal strength through extensive measurements in a typical IEEE 802.11b/g/n network. It also presents the statistical analysis of the measured data that defines the reliability of RSS-based location fingerprints for indoor localization.},
keywords={computer network reliability;indoor radio;radio direction-finding;radio receivers;radio transmitters;radiofrequency interference;radiotelemetry;statistical analysis;wireless LAN;IEEE 802.11b-g-n network;RSS;WLAN system;fingerprint location;in-path interference;indoor localization;radio-map characteristics;received signal strength indicator;receiving device;reliability;statistical analysis;transmitter device;Conferences;Hardware;Interference;Portable computers;Standards;Time measurement;Wireless LAN},
doi={10.1109/LCN.2013.6761255},
ISSN={0742-1303},
month={10},}

@article{chang2011libsvm,
  title={LIBSVM: a library for support vector machines},
  author={Chang, Chih-Chung and Lin, Chih-Jen},
  journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
  volume={2},
  number={3},
  pages={27},
  year={2011},
  publisher={ACM}
}

@misc{RSSIwikipedia,
  title = {{Wikipedia} Received signal strength indication},
  howpublished = {\url{https://en.wikipedia.org/wiki/Received_signal_strength_indication}},
  note = {Accessed: 2017-03-18}
}

@misc{GaussNewtonwikipedia,
  title = {{Wikipedia} Gauss–Newton algorithm},
  howpublished = {\url{https://en.wikipedia.org/wiki/Gauss-Newton_algorithm}},
  note = {Accessed: 2017-03-18}
}

@misc{LevenbergMarquardtwikipedia,
  title = {{Wikipedia} Levenberg–Marquardt algorithm},
  howpublished = {\url{https://en.wikipedia.org/wiki/Levenberg-Marquardt_algorithm}},
  note = {Accessed: 2017-05-19}
}

@misc{EarthMagnetwikipedia,
  title = {{Wikipedia} Earth's magnetic field},
  howpublished = {\url{https://en.wikipedia.org/wiki/Earth's_magnetic_field}},
  note = {Accessed: 2017-03-19}
}

@misc{crossValidatedSVMC,
  title = {{Cross Validated} What is the influence of C in SVMs with linear kernel?},
  howpublished = {\url{http://stats.stackexchange.com/questions/31066/what-is-the-influence-of-c-in-svms-with-linear-kernel}},
  note = {Accessed: 2016-09-23}
}

@misc{trilaterationTool,
  title = {{GitHub} leastSquaresTriangulation},
  howpublished = {\url{https://github.com/fischchopf/leastSquaresTriangulation}}
}

@misc{ErikKimKernelTrick,
  title = {{Eric Kim} the Kernel Trick},
  howpublished = {\url{http://www.eric-kim.net/eric-kim-net/posts/1/kernel_trick.html}},
  note = {Accessed: 2016-09-23}
}

@misc{crossvalidation,
  title = {{Wikipedia} Cross-validation},
  howpublished = {\url{https://en.wikipedia.org/wiki/Cross-validation_(statistics)}},
  note = {Accessed: 2017-05-23}
}

@inproceedings{li2015passiveWIFIsource,
  title={A passive wifi source localization system based on fine-grained power-based trilateration},
  author={Li, Zan and Braun, Torsten and Dimitrova, Desislava C},
  booktitle={World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2015 IEEE 16th International Symposium on a},
  pages={1--9},
  year={2015},
  organization={IEEE}
}

@inproceedings{josePaper,
  title={A Real-time Indoor Tracking System in Smartphones},
  author={Carrera, Jose and Li, Zan and Zhao, Zhongliang and Braun, Torsten and Neto, Augusto},
  booktitle={The 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (ACM MSWiM)},
  year={2016},
}