Roland Hostettler

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This paper is concerned with sigma-point methods for filtering in nonlinear systems, where the process and measurement noise are heavy tailed and enter the system non-additively. The problem is approached within the framework of assumed density filtering and the necessary statistics are approximated using sigma-point methods developed for Student's(More)
We present an approach for computing the heading direction of a vehicle by processing measurements from a 2-axis magnetometer rapidly. The proposed method relies on a non-linear transformation of the measurement data comprising only two inner products. Deterministic analysis of the signal model shows how the heading direction is contained in the signal and(More)
Traffic monitoring using low-cost two-axis magnetometers is considered. Although detection of metallic vehicles is rather easy, detecting the driving direction is more challenging. We propose a simple algorithm based on a nonlinear transformation of the measurements, which is simple to implement in embedded hardware. A theoretical justification is provided,(More)
This paper addresses a novel method for vehicle tracking using an extended Kalman filter and measurements of road surface vibrations from a single accelerometer. First, a measurement model for vibrations caused by vehicular road traffic is developed. Then the identifiability of the involved parameters is analyzed. Finally, the measurement model is combined(More)
This article shows how a particle smoother based system identification method can be applied for estimating the trajectory of road vehicles. As sensors, a combination of an accelerometer measuring the road surface vibrations and a magnetometer measuring magnetic disturbances mounted on the side of the road are considered. First, sensor models describing the(More)
The main contribution of this paper is a comparison of different machine learning algorithms for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard using measurements of road surface vibrations and magnetic field disturbances caused by vehicles. The algorithms considered are logistic regression,(More)
In this paper, we propose a method for respiratory rate estimation based on the received signal strength of narrowband radio frequency transceivers. We employ a state-space formulation of periodic Gaussian processes to model the observed variations in the signal strength. This is then used in a Rao-Blackwellized unscented Kalman filter which exploits the(More)