Measurement Uncertainty Assessment in Remote Object Geolocation

Kuščer, Lovro; Diaci, Janez

doi:10.5545/sv-jme.2012.642

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…MCMC simulations are an increasingly popular method in a wide range of engineering problems [3], [6], [13] and [14]. In inverse modelling, Bayesian frameworks proved their ability to effectively estimate the posterior pdf of parameters.…”

Section: Dream (Zs) Algorithmmentioning

confidence: 99%

Investigating Prior Parameter Distributions in the Inverse Modelling of Water Distribution Hydraulic Models

Kozelj

Kapelan

Novak

et al. 2014

SV-JME

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Inverse modelling concentrates on estimating water distribution system (WDS) model parameters that are not directly measurable, e.g. pipe roughness coefficients, which can, therefore, only be estimated by indirect approaches, i.e. inverse modelling. Estimation of the parameter and predictive uncertainty of WDS models is an essential part of the inverse modelling process. Recently, Markov Chain Monte Carlo (MCMC) simulations have gained in popularity in uncertainty analyses due to their effective and efficient exploration of posterior parameter probability density functions (pdf). A Bayesian framework is used to infer prior parameter information via a likelihood function to plausible ranges of posterior parameter pdf. Improved parameter and predictive uncertainty are achieved through the incorporation of prior pdf of parameter values and the use of a generalized likelihood function. We used three prior information sampling schemes to infer the pipe roughness coefficients of WDS models. A hypothetical case study and a real-world WDS case study were used to illustrate the strengths and weaknesses of a particular selection of a prior information pdf. The results obtained show that the level of parameter identifiability (i.e. sensitivity) is an important property for prior pdf selection.

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Section: Dream (Zs) Algorithmmentioning

confidence: 99%

Investigating Prior Parameter Distributions in the Inverse Modelling of Water Distribution Hydraulic Models

Kozelj

Kapelan

Novak

et al. 2014

SV-JME

View full text Add to dashboard Cite

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Assessment of the Kinematic Parameters of Distant Noncooperative Objects

Kuščer

Diaci

2013

Advances in Mechanical Engineering

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The paper presents a method and a system for assessing the kinematic parameters of distant noncooperative objects. An experimental measuring system was developed using a long distance laser rangefinder, a GPS receiver, an electronic inclinometer, and a CCD camera mounted on a motorized pan-tilt unit. During the measurement process, the system first establishes its position and orientation in a global coordinate system. Particle filtering approach based on adaptive template matching is used to track a moving object of interest in the acquired digital image sequence. The tracking and rangefinder data is employed to determine in real time the relative position of the object, thus obtaining its 3D trajectory and velocity. To enable repetitive range measurements, the tracking data is also used to actuate the pan-tilt unit directing the rangefinder towards the object. Experiments are presented which demonstrate the performance of the system for characterization of movement of vehicles and people at kilometer-range distances.

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Measurement Uncertainty Assessment in Remote Object Geolocation

Cited by 2 publications

References 9 publications

Investigating Prior Parameter Distributions in the Inverse Modelling of Water Distribution Hydraulic Models

Investigating Prior Parameter Distributions in the Inverse Modelling of Water Distribution Hydraulic Models

Assessment of the Kinematic Parameters of Distant Noncooperative Objects

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