In this paper, we present a new method for terrain and gravity aided navigation. Gravity
aided navigation and terrain aided navigation are map aided navigation methods for …

The Kalman filter is popularly known to be an optimal recursive implementation of the
Bayesian prediction and correction in the sense that it minimises the estimated error …

In this paper, we study the collaborative state fusion problem in a multi-agent environment,
where mobile agents collaborate to track movable targets. Due to the limited sensing range …

Process of finding the “best estimate” from noisy signals amounts to “filtering out” the noise.
Many methods exist to filter the unwanted noise. A tried and tested method is to use a …

A new robust time scale algorithm, Autonomous Time scale using the Student's T-distribution
(ATST), has been proposed and validated using simulated clock data. Designed for use in a …

We address object tracking by radar and the robustness of the current state-of-the-art
methods to process outliers. The standard tracking algorithms extract detections from radar …

Nesta tese, exploramos dois domínios interconectados: a estabilidade de estados
sincronizados em redes de neurônios Izhikevich eo desafio da inferência de redes em …

The fields of deep learning and Bayesian estimation offer signal processing methods that
exhibit unique and contrasting capabilities. The main advantage of Bayesian estimation …

This project aimed to study different torque control techniques for a multi-phase PMSM with
an emphasis on minimising the torque ripple. Where torque ripple refers to noise in the …

Den normale tilnærmingen til sporing av bevegelige objekter antar at posisjonen og
orienteringen til sporingssensoren er kjent. Dette er ikke tilfellet når sensoren er montert på …