An orbit determination Kalman filter has been developed that uses two types of measurements of time division multiple access (TDMA) L-Band signals from satellites in low Earth orbit, a carrier phase measurement and a biased pseudorange measurement. This algorithm will enable precise orbit determination of satellites broadcasting TDMA signals not originally intended for navigation. The TDMA stru...

Finding particle trajectories is usually the most time consuming part of modern experiments in high energy physics. In many present experiments with high track densities and complicated event topologies a Kalman filter based track fit is used already at this combinatorial part of the event reconstruction. Therefore speed of the track fitting algorithm becomes very important for the total proces...

Nowadays with increasing use of numerous nonlinear loads, voltage and current harmonics in power systems are one of the most important problems power engineers encounter. Many of these nonlinear loads, because of their dynamic natures, inject time-varying harmonics into power system. Common techniques applied for harmonics measurement and assessment such as FFT have significant errors in presen...

Kalman filter technniques are widely used in the areas of attitude and orbit determination, prediction and calibration. These techniques work well if the system dynamics are well-defined. Problems arise, however, when the system parameters are unknown ahead of time or changing over time. This paper discusses an adaptive Kalman filter design that utilizes recursive maximum likelihood parameter i...

In this paper the problems of state estimation, tracking control and shape control in a micro-cantilever beam with nonlinear electrostatic actuation are investigated. The system’s partial differential equation of motion is converted into a set of ordinary differential equations by projection method. Observabillity of the system is proven and a state estimation system is designed using extended ...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

Control of a class of uncertain nonlinear systems, which estimates unavailable state variables, is considered. A new approach for robust tracking control problem of satellite for large rotational maneuvers is presented in this paper. The features of this approach include a strong algorithm to estimate attitude, based on discrete extended Kalman filter combined with a continuous extended Kalman ...

in this paper, we deal with the problem of adaptive coherent signal detection in gaussian interference (clutter plus noise) for surveillance pulse radars. some of the adaptive radar detectors exploit the ar model for clutter. most of these detectors have been obtained using the glr test. this test relies on the maximum likelihood estimation whose accuracy depends on the number of data. whereas,...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...