A recursive fusion filter for angular data

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 of a circular recursive filter for the estimation and fusion of the carrier phase delay. The contribution of this work is the definition of a recursive change point estimate that fuse the discriminator values and integrate prior information for the detection. The proposed architecture that uses a circular filter enables to fuse the phase delays and to extract the message of navigation. The method is assessed on synthetic data in the experimentation.

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“…Then we show [8] that the recursive estimate of the mean phase delay and of the parameter of concentration is given by:X…”

Section: Recursive Estimate Of the Carrier Phase Delaymentioning

confidence: 99%

Information fusion applied to the tracking of GPS pilot and data channels

Azmani

Reboul

Choquel

et al. 2010

2010 13th International Conference on Information Fusion

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“…Since WN distributions are not closed under multiplication, an intermediate representation of VM distributions is used. Multiplication of two VM distributions and normalization of the resulting density is performed as described in [9].…”

Section: F Measurement Updatementioning

confidence: 99%

“…Azmani et. al have recently proposed a circular filter based on the von Mises distribution [9]. This filter allows the estimation of a single angle for a system whose system and measurement function are the identity disturbed by additive noise.…”

Section: Introductionmentioning

confidence: 99%

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Recursive nonlinear filtering for angular data based on circular distributions

Kurz

Gilitschenski

Hanebeck

2013

2013 American Control Conference

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Estimation of circular quantities is a widespread problem that occurs in many tracking and control applications. Commonly used approaches such as the Kalman filter, the extended Kalman filter (EKF), and the unscented Kalman filter (UKF) do not take periodicity explicitly into account, which can result in low estimation accuracy. We present a filtering algorithm for angular quantities in nonlinear systems that is based on circular statistics. The new filter switches between three different representations of probability distributions on the circle, the wrapped normal, the von Mises, and a Dirac mixture density. It can be seen as a systematic generalization of the UKF to circular statistics. We evaluate the proposed filter in simulations and show its superiority to conventional approaches.

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“…In Figure 7, the left figure shows the trajectory and the observed positions provided by the GNSS receiver. In Figure 7, the top right figure presents the measurements of direction provided by the magnetometer and the filtered directions obtained with a circular filter [20]. The bottom right figure presents the measurements of speed, V x and V y, along the x-and y-axis.…”

Section: Multi-sensor Estimationmentioning

confidence: 99%

Non-Linear Fusion of Observations Provided by Two Sensors

Azmani

Reboul

Benjelloun

2013

Entropy

Self Cite

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When we try to make the best estimate of some quantity, the problem of combining results from different experiments is encountered. In multi-sensor data fusion, the problem is seen as combining observations provided by different sensors. Sensors provide observations and information on an unknown quantity, which can differ in precision. We propose a combined estimate that uses prior information. We consider the simpler aspects of the problem, so that two sensors provide an observation of the same quantity. The standard error of the observations is supposed to be known. The prior information is an interval that bounds the parameter of the estimate. We derive the proposed combined estimate methodology, and we show its efficiency in the minimum mean square sense. The proposed combined estimate is assessed using synthetic data, and an application is presented.

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A recursive fusion filter for angular data

Cited by 36 publications

References 12 publications

Information fusion applied to the tracking of GPS pilot and data channels

Information fusion applied to the tracking of GPS pilot and data channels

Recursive nonlinear filtering for angular data based on circular distributions

Non-Linear Fusion of Observations Provided by Two Sensors

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