UWB for Robust Indoor Tracking: Weighting of Multipath Components for Efficient Estimation

Meißner, Paul; Leitinger, Erik; Witrisal, Klaus

doi:10.1109/lwc.2014.2341636

Cited by 75 publications

(111 citation statements)

References 8 publications

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“…Because the measurement scenario considers only one time reflections, VT-Knowledge-Algo reflects algorithms of [24,53] which consider reflected signals as signals emitted from VTs, where the VT positions are precalculated based on the knowledge of the reflecting surface and physical transmitter positions. VT-KnowledgeAlgo can be seen as a lower bound for Channel-SLAM.…”

Section: Evaluations Based On Measurementsmentioning

confidence: 99%

“…The authors of [21,22] exploit multipath propagation for positioning of mobile terminals using multipath fingerprinting algorithms. Other algorithms, for example, [23,24], interpret reflected signals as signals emitted from virtual transmitters (VTs), where the VT positions are precalculated based on the knowledge of the reflecting surface and physical transmitter positions. Furthermore, the authors of [25] estimate and track the phase information of MPCs using an extended Kalman filter (EKF) and estimate the user position using a time difference of arrival (TDOA) positioning approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Positioning Using Terrestrial Multipath Signals and Inertial Sensors

Gentner¹,

Pöhlmann²,

Ulmschneider³

et al. 2017

Mobile Information Systems

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This paper extends an algorithm that exploits multipath propagation for position estimation of mobile receivers named Channel-SLAM. Channel-SLAM treats multipath components (MPCs) as signals from virtual transmitters (VTs) and estimates the positions of the VTs simultaneously with the mobile receiver positions. For Channel-SLAM it is essential to obtain angle of arrival (AoA) measurements for each MPC in order to estimate the VT positions. In this paper, we propose a novel Channel-SLAM implementation based on particle filtering which fuses heading information of an inertial measurement unit (IMU) to omit AoA measurements and to improve the position accuracy. Interpreting all MPCs as signals originated from VTs, Channel-SLAM enables positioning also in non-line-of-sight situations. Furthermore, we propose a method to dynamically adapt the number of particles which significantly reduces the computational complexity. A posterior Cramér-Rao lower bound for Channel-SLAM is derived which incorporates the heading information of the inertial measurement unit (IMU). We evaluate the proposed algorithm based on measurements with a single fixed transmitter and a moving pedestrian carrying the receiver and the IMU. The evaluations show that accurate position estimation is possible without the knowledge of the physical transmitter position by exploiting MPCs and the heading information of an IMU.

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Section: Evaluations Based On Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Positioning Using Terrestrial Multipath Signals and Inertial Sensors

Gentner¹,

Pöhlmann²,

Ulmschneider³

et al. 2017

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…There are also some research activities focused on realizing futuristic personal and body area networks for various applications such as medical body area networks [49], bespoke learning environments [50], etc. A further key trend in UWB is the focus on implementing radar sensor network technologies such as indoor localization and personnel tracking [51,52], intruder movement [53], through-wall and under-rubble radar [54,55], and mobile robot navigation [56], to name a few. UWB excels in these applications due to its large bandwidth and high accuracy at low signal-to-noise ratios.…”

Section: Current Commercial Position and Research Trendsmentioning

confidence: 99%

Ultrawideband Communications—An Idea Whose Time has Still Yet to Come? [Wireless Corner]

Catherwood

Scanlon

2015

IEEE Antennas Propag. Mag.

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This paper presents a critical analysis of ultrawideband (UWB) and considers the turbulent journey it has had from the Federal Communications Commission's bandwidth allocation in 2002 to today. It analyzes the standards, the standoffs, and the stalemate in standardization activities and investigates the past and present research and commercial activities in realizing the UWB dream. In this paper, statistical evidence is presented to depict UWB's changing fortunes and is utilized as an indicator of future prominence. This paper reviews some of the opinions and remarks from commentators and analyzes predictions that were made. Finally, it presents possible ways forward to reignite the high-data-rate UWB standardization pursuit.

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“…While some of the above approaches provide quite accurate identification, but a full channel impulse response is required in almost all of the methods which is inconvenient for real-time positioning based on simple mobile devices. Attempts of improving UWB indoor ranging and positioning performance is made by a proposed ranging likelihood and the analysis of indoor multipath situations (Lu, Mazuelas, and Win 2013;Meissner, Leitinger, and Witrisal 2014) which still requires the waveform features and indoor map information. On the other hand, detecting the ranging accuracy is more important that knowing whether it is LOS or NLOS for positioning purposes.…”

Section: Uwb Signal Ranging Errorsmentioning

confidence: 99%

Detection of UWB ranging measurement quality for collaborative indoor positioning

Jing

Bonenberg

Pinchin

et al. 2015

Journal of Location Based Services

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Wireless communication signals have become popular alternatives for indoor positioning and navigation due to lack of navigation satellite signals in such environments. The signal characteristics determines the method used for positioning as well as the positioning accuracy. Ultra-wideband (UWB) signals, with a typical bandwidth of over 1 GHz, overcome multipath problems in complicated environments. Hence potentially achieves centimetre level ranging accuracy in open areas. However, signals can be disrupted when placed in environments with obstructions and cause large ranging errors. This paper proposes a ranging measurement quality indicator (RQI) which detects the UWB measurement quality based on the received signal strength pattern. With a detection validity of more than 83%, the RQI is then implemented in a ranging based collaborative positioning system. The relative constraint of the collaborative network is adjusted adaptively according to the detected RQI. The proposed detection and positioning algorithm improves positioning accuracy by 80% compared to non-adaptive collaborative positioning.

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UWB for Robust Indoor Tracking: Weighting of Multipath Components for Efficient Estimation

Cited by 75 publications

References 8 publications

Positioning Using Terrestrial Multipath Signals and Inertial Sensors

Positioning Using Terrestrial Multipath Signals and Inertial Sensors

Ultrawideband Communications—An Idea Whose Time has Still Yet to Come? [Wireless Corner]

Detection of UWB ranging measurement quality for collaborative indoor positioning

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