Maximum Averaged Likelihood Estimation Tree for Anchor-Less Localization Exploiting IR-UWB Multipaths

Tosa, V. La; Denis, Benoît; Uguen, Bernard

doi:10.1109/vetecs.2010.5494101

Cited by 4 publications

(13 citation statements)

References 15 publications

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“…In theory, (11) and (12) give access to the full posterior PDF of the state vector. In practice, both equations can be solved analytically only for special cases, e.g.…”

Section: State Space Estimatorsmentioning

confidence: 99%

“…Single-bounce paths are also used in [11], where in addition to the angular parameters, also the Doppler shift is estimated. For an UWB link with single antennas on both link ends, [12] proposes an algorithm for anchor-less localization, but with an assumed LOS situation and a fixed number of multipaths. The concept of virtual anchors is also used in [13], where the reflections result in new nodes at unknown locations that contribute in the location estimation through cooperation.…”

Section: Introductionmentioning

confidence: 99%

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UWB sequential Monte Carlo positioning using virtual anchors

Meißner

Gigl

Witrisal

2010

2010 International Conference on Indoor Positioning and Indoor Navigation

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We present a novel UWB indoor localization concept that performs the position estimation with a set of virtual anchor nodes, generated from a single physical anchor and floor plan information. Using range estimates to the virtual anchors, we perform multilateration to estimate the position of an agent. Previous work has shown the general applicability of this concept. In this contribution, we use a moving agent to exploit the correlation in successive positions using state-space concepts. A motion model for the agent and the measurement likelihood function allow for the use of the powerful framework of Bayesian state estimation. With this concept, we can propagate prior information on the agent position from one time step to the next. The statistical model for the ranging to the virtual anchors accounts for several imperfections, which lead to multimodal and heavy-tailed measurement distributions. We show how modified versions of the Kalman filter as well as a particle filter can account for these imperfections and yield accurate and robust position estimates. In a typical indoor pedestrian motion scenario, we can achieve an accuracy of about 45 cm for 90% of the estimates.

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“…In theory, (11) and (12) give access to the full posterior PDF of the state vector. In practice, both equations can be solved analytically only for special cases, e.g.…”

Section: State Space Estimatorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

UWB sequential Monte Carlo positioning using virtual anchors

Meißner

Gigl

Witrisal

2010

2010 International Conference on Indoor Positioning and Indoor Navigation

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show abstract

“…As in [8], a Normal measurement error model will be assumed in the following for AoI θ n and ToAs τ n , with standard deviations σ θ and σ τ respectively. Therefore, according to the independence assumption of measurements for each n (e.g.…”

Section: Path Parameters Modelmentioning

confidence: 99%

“…Therefore, according to the independence assumption of measurements for each n (e.g. as in [8]), the joint truncated Probability Density Function (PDF) f Θ1,Θ2,Θ3,Θ4 of θ 1 , θ 2 , θ 3 and θ 4 is the product of four independent truncated Normal densities, as follows:…”

Section: Path Parameters Modelmentioning

confidence: 99%

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Impact of antennas on the anchor-less indoor localization of a static IR-UWB pair

Tosa

Denis

Bories

et al. 2010

21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

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This paper investigates the impact of realistic antennas on joint anchor-less localization and indoor characterization based on Impulse Radio (IR) Ultra Wideband (UWB) communications. In this frame, the Maximum Averaged Likelihood (MAL) algorithm and its extended version are considered, both relying on a tree approach consisting in two stages. The first part of the process exploits the cross-correlation between received and locally predicted paths and it is the same for both algorithms. The second stage calculates the averaged likelihood of measured path parameters obtained in the previous step, but different measurements are used for MAL and extended MAL (eMAL), as in the first case only the Angle of Incidence (AoI) and the Time of Arrival (ToA) are considered. Additionally, the eMAL tree algorithm also accounts for two couples of Angles of Departure (AoDs) and Angles of Arrival (AoAs). The estimation errors of both nodes coordinates and room dimension obtained with the two algorithms are compared for three realistic UWB antennas. Finally, the remaining algorithm-independent ambiguities (i.e. resulting from scenario and geometry) are discussed.

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Effect of varying the step-size of least mean squares filter in the accuracy of extraction of passive RFID root-music direction-of-arrival estimates

Penas

Cruz

2014

2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and M

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Maximum Averaged Likelihood Estimation Tree for Anchor-Less Localization Exploiting IR-UWB Multipaths

Cited by 4 publications

References 15 publications

UWB sequential Monte Carlo positioning using virtual anchors

UWB sequential Monte Carlo positioning using virtual anchors

Impact of antennas on the anchor-less indoor localization of a static IR-UWB pair

Effect of varying the step-size of least mean squares filter in the accuracy of extraction of passive RFID root-music direction-of-arrival estimates

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