In this paper, new attitude determination algorithms using pseudolite signal phase measurements are developed and presented with realistic simulations. Pseudolite signals are used to replace GPS signals which are often not available due to blocking by nearby large structures, for example a crew return vehicle under the International Space Station. A new observation model needs to be applied bec...

This paper deals with the problem of maneuvering target tracking in wireless tracking service. It results in a mixed linear/non-linear Models estimation problem. For maneuvering tracking systems, these problems are traditionally handled using the extended Kalman filter or Particle filter. In this paper, Marginalized Particle Filter is presented for applications in such problem. The algorithm ma...

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...

In this paper, a real-time predictive filter is derived for nonlinear systems. This provides a method of determining optimal state estimates in the presence of significant error in the assumed (nominal) model. The new real-time nonlinear filter determines (i.e., “predicts”) the optimal model error trajectory so that the measurement-minus-estimate covariance statistically matches the known measu...

This paper addresses the state-estimation problem for nonlinear systems in a context where prior knowledge, in addition to the model and the measurement data, is available in the form of a nonlinear equality constraint. Then three suboptimal algorithms based on the unscented Kalman filter (UKF) are developed, namely, the equality-constrained unscented Kalman filter (ECUKF), the projected unscen...