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The paper describes the design, implementation, and test of an autonomous vehicle navigation system using vehicle model and particle filter tracking algorithm. Typically, a vehicle navigation system comprises of real-time environment perception, vehicle localization, collision avoidance, path planning, and path following. In order to achieve the features for intelligent autonomous vehicle, a sensor...
In practice, a parameter or the state of a system is often subject to constraints. This paper considers the estimation problem for the parameter or the state constrained by a class of linear inequalities. Two sequential methods for optimal parameter estimation in the MMSE sense are obtained. They have an analytic form, which is different from most existing methods. For a dynamic system with constrained...
Due to the nonlinear relationship between Cartesian coordinates and range-direction-cosine coordinates, target tracking of state described in Cartesian coordinates with range and direction cosine measurements is a nonlinear filtering problem. Measurement conversion based Kalman filter available for this type of problem has some serious drawbacks. Depending on whether measurement of the third direction...
This paper deals with estimation fusion for a Markovian jump-linear system (MJLS) and proposes a distributed fusion scheme, in which local sensors send their transformed measurements to the fusion center and the fusion center fuses them with a multiple-model (MM) filter. A specific linear transformation for local measurements is studied and it is shown that the distributed minimum mean-squared error...
This paper considers the problem of state estimation for a hybrid system with Markovian switching parameters in a continuous space. We propose a hybrid grid multiple model (HGMM) estimator whose model set is a combination of a fixed coarse grid and an adaptive fine grid. We also present two modelset design methods by moment matching, and apply them to practical HGMM algorithms. Simulation results...
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