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The reception state of a satellite is an unavailable information for Global Navigation Satellite System receivers. His knowledge or estimation can be used to evaluate the pseudorange error. This article deals with the problem using three reception states: direct reception, alternate reception and blocked situation. This parameter, estimated using a Dirichlet distribution, is included in a particle...
The estimation of a vehiclepsilas dynamic state is one of the most fundamental data fusion tasks for intelligent traffic applications. For that, motion models are applied in order to increase the accuracy and robustness of the estimation. This paper surveys numerous (especially curvilinear) models and compares their performance using a tracking tasks which includes the fusion of GPS and odometry data...
In this paper, we are introducing a GIS-based approach for forest fire growth modelling. This work has been carried out in close cooperation with a fire brigade. It is based on data obtained on the ground and on theoretical features, e.g. Drouet-Thornthwaitepsilas formula and the elliptical fire shape hypothesis, whose relevance has been proven for Mediterranean landscapes. The corresponding model...
This paper is concerned with the use of multi-platform agent-based emitter geolocation. Multiple, self-aware, agents representing different types of emitter location method, naturally form clusters, which are controlled by the network connectivity. Each cluster provides a fusion hierarchy: each agent is able to geolocate individually, a cluster of agents can refine the emitter position using fusion...
Fusion of a simulation model and observation data has been investigated extensively for the purpose of data assimilation in geophysics. The inaccuracy of the parameters, initial conditions, or boundary conditions causes a discrepancy in the simulation results and the actual phenomenon. The present paper describes the parameter identification of a pressure regulator with a nonlinear structure by sequential...
This paper studies sensor network surveillance performance at the automatic tracker output. In particular, we develop a simple analytical model for tracker performance, where the interest is in a compact representation of the impact of sensor revisit time. This model, combined with a previously developed contact fusion model, allows for an analysis of two fusion architectures: a standard centralized...
The basis for map assisted moving target tracking is a correct and up-to-date representation of the environment. In this contribution a method is proposed to model curved structures, e.g. roads or tracks, with cubic spline curves. The unknown model parameters are estimated based on corrupted measurements using a probabilistic approach. In particular, the method presented results in a linear formulation...
In recent years the discrepancy between the required knowledge and the available knowledge for obtaining the situation awareness aboard Royal Netherlands Navy ships has increased. This paper presents a methodology to automatically classify objects in the mission environment based on user defined mission information in order to close this gap. The cornerstone of this methodology is the Confidence Interval...
The objective of this research is to investigate and provide a proof-of-concept demonstration of how to approach the biosensor fusion process as a systems optimization. Recent work on biosensor fusion is disjointed and compartmentalize at each technical challenge of a very complex problem. Here we try to take a systems approach in deciding the following questions: Where to locate sensors? What sensors...
Maritime surveillance of coastal regions requires the processing of data from a large number of heterogeneous surveillance sources. The generation of effective maritime domain awareness requires that the tracks from these sources must be fused. An automated fusion process that supports maritime domain awareness requires that the tracks from heterogeneous sources be modeled in such a way as to support...
The paper presents two methods of updating the weights of a Gaussian mixture to account for the density propagation within a data assimilation setting. The evolution of the first two moments of the Gaussian components is given by the linearized model of the system. When observations are available, both the moments and the weights are updated to obtain a better approximation to the a posteriori probability...
This paper presents a method for the simultaneous state and parameter estimation of finite-dimensional models of distributed systems monitored by a sensor network. In the first step, the distributed system is spatially and temporally decomposed leading to a linear finite-dimensional model in state space form. The main challenge is that the simultaneous state and parameter estimation of such systems...
Statistical mechanics has proven to be a useful model for drawing inferences about the collective behavior of individual objects that interact according to a known force law (which for a more general usage is referred to as interacting units.). Collective behavior is determined not by computing F = ma for each interacting unit because the problem is mathematically intractable. Instead, one computes...
In this paper, we establish a link between belief functions on real numbers and the maximal coherent sets obtained in the framework of possibilistic distributions. Having proposed an original disjunctive rule of combination in the framework of continuous belief functions, we demonstrate theoretically that maximal coherent sets can be viewed as a particular case in the framework of belief functions.
Having a correct and timely classification solution for objects has become increasingly important as well as increasingly difficult to obtain in new maritime military missions; a decision support system is therefore needed. In decision support systems a challenge lies in how operator and system belief can be reconciled. This paper presents a support system for the classification process using dezert-smarandache...
In this paper, we propose in Dezert-Smarandache Theory (DSmT) framework, a new probabilistic transformation, called DSmP, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the DSmP transformation works and we compare it to main existing transformations proposed in the literature...
A computationally efficient, grid-based estimation method is presented for multiple source identification from distributed sensor data. Under the assumption that the sources are located on a grid over the region of interest, the solution to the problem of multiple source identification, that is, estimation of the number, locations, and intensities of the sources, is represented by a large sparse vector...
In this paper, a scaled unscented Kalman filter (SUKF) based on the quaternion concept is designed for integrating inertial navigation system (INS) aided by GPS measurements under large attitude error conditions. In this feedback filter, only the bias effects are considered to be independent states and are used to compensate for navigation errors. To preserve the nonlinear nature of the unit quaternion,...
The seabed characterization from sonar images is a very hard task because of the produced data and the unknown environment, even for an human expert. In this work we propose an original approach in order to combine binary classifiers arising from different kinds of strategies such as one-versus-one or one-versus-rest, usually used in the SVM-classification. The decision functions coming from these...
Wireless sensor networks are deployed for the purpose of sensing and monitoring an area of interest. Sensors in the sensor network can suffer from both random and systematic bias problems. Even when the sensors are properly calibrated at the time of their deployment, they develop drift in their readings leading to erroneous inferences being made by the network. The drift in this context is defined...
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