In high dynamic conditions, using vector tracking loops instead of scalar tracking loops in GPS receivers is proved as an efficient method to compensate the performance. The Minimum Mean Squared Error detector as a multiuser detector is applied in the vector tracking loop for more reliability and efficiency. The Kalman filter does the two tasks of tracking and extracting the navigation data aft...

This paper presents a simple model predictive control (MPC) approach to control the power injection system (PIS) for renewable energy applications. A DC voltage source and a single-phase inverter that is connected to the grid by an LCL filter form the PIS. Grid voltage is considered a disturbance for the system. For eliminating this disturbance, a modified model is proposed. It is usual to ...

This paper presents a Rao-Blackwellized mixed state particle filter for joint head tracking and pose estimation. Rao-Blackwellizing a particle filter consists of marginalizing some of the variables of the state space in order to exactly compute their posterior probability density function. Marginalizing variables reduces the dimension of the configuration space and makes the particle filter mor...

Nonlinear filter problems arise in many applications such as communications and signal processing. Commonly used numerical simulation methods include Kalman filter method, particle filter method, etc. In this paper a novel numerical algorithm is constructed based on samples of the current state obtained by solving the state equation implicitly. Numerical experiments demonstrate that our algorit...

Vehicle Dynamics Control (VDC) systems require the information about system variables, which cannot be directly measured, e.g., the wheel slip or the vehicle side-slip angle. This paper presents a new concept for the vehicle state estimation under assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilize an Unscented Kalman Filter (UKF) for estimation purp...

A receding horizon Kalman finite-impulse response (FIR) filter is suggested for continuous-time systems, combining the Kalman filter with the receding horizon strategy. In the suggested filter, the horizon initial state is assumed to be unknown. It can always be obtained irrespective of unknown information on the horizon initial state. The filter may be the first stochastic FIR form for continu...

This paper aims to reveal the relationship between the minimum L2-sensitivity of state-space digital filters and the Gramian-preserving frequency transformation. To this end, we first give a prototype low-pass state-space filter in such a manner that its structure becomes the minimum L2-sensitivity structure. Then we apply the Gramian-preserving (LP-LP) frequency transformation with a tunable p...

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Rece...

One of the most important problem in target tracking is Line Of Sight (LOS) rate estimation for using from PN (proportional navigation) guidance law. This paper deals on estimation of position and LOS rates of target with respect to the pursuer from available noisy RF seeker and tracker measurements. Due to many important for exact estimation on tracking problems must target position and Line O...