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In many multi-sensor applications, noisy angular data are modeled as random variables which are commonly defined on the linear domain while the “classical fusion and filtering” are used to process their realizations. Weighted sum and Kalman filter are indeed the common approaches used to fuse and filter the data in most cases. These approaches are limited by the periodic nature of the angular data...
In this article we propose to process the code and phase delay of a dataless GNSS signal in open and semi-open loops. The aims of this processing are to get an accurate estimate of the phase and code delays by integration of the GNSS signal. We show that in an open loop the code delay evolution is a piecewise stationary process and we propose to model the phase delay as a circular random variable...
Soil moisture can be processed with the difference of power between a direct and a nadir GNSS signal reflected by the soil. The estimate carrier to noise ratio C/N0 is a classical measure of power for the GNSS signals. We show in this paper that the classical estimate of C/N0 processed for one satellite depends on the carriers, code and phase delay of the visible satellites. This dependence decreases...
New GNSS signals broadcast at different carrier frequencies include, most of them, a pilot and data channels. In this article we propose to fuse the information of code and phase delay provided by the two channels in order to improve the position accuracy and to extract the message of navigation. The proposed system is composed of a change point estimate of the slope of discriminator variations and...
Many practical application in the field of robotic and perception are using angular data. In this work we present a multi-sensor multi-temporal data fusion filter for angular data. Most of the time, statistic filters, are designed on linear domain. In this work we propose a recursive filter defined on the circular domain with a von Mises distribution. In our application we consider a set of measurement...
Mean wind speeds and mean wind directions are important input parameters for environmental models and applications. In many practical cases, anemometer sensor provides measurements of direction and wind speed, supposed to be Gaussian and piecewise stationary. In this work we use a von Mises distribution and a Log-normal distribution in order to model sensor data with distributions having a physical...
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