The limits of extended Kalman filtering for pulse train deinterleaving

The limits of extended Kalman filtering for pulse train deinterleaving

Some signals, such as in radar systems, communication systems, and neural systems, are transmitted as periodic pulse trains. If more than one pulse train is transmitted over the same communication channel, a challenge is to separate them for source identification at the receiver. This is known as pulse train deinterleaving and is clearly a fundamental problem in the study of discrete-event syst...

Pulse train deinterleaving via the Hough transform

The nonlinear problem of pulse train deinterleaving is mapped into that of line detection in a plane. The image processing technique known as the Hough transform is then applied. The problem is now one of peak detection and the selection of a threshold is examined.

Pulse train deinterleaving: algorithms and cost criteria

Consider the problem where pulse trains transmitted from a known number of sources are received on a single communications channel. These pulses are corrupted with noise. The deinterleaving problem is to determine which source contributed which pulse and the periods and phases of each source. This paper explores the performance of a number of deinterleaving algorithms. We propose an alternative...

Extended Kalman Filtering by

Synchronization through Extended Kalman Filtering

We study the synchronization problem in discrete-time via an extended Kalman filter (EKF). That is, synchronization is obtained of transmitter and receiver dynamics in case the receiver is given via an extended Kalman filter that is driven by a noisy drive signal from the transmitter. Extensive computer simulations show that the filter is indeed suitable for synchronization of (noisy) chaotic t...