Essays about: "unscented Kalman filtering"

Showing result 1 - 5 of 12 essays containing the words unscented Kalman filtering.

1. 1. Implementing Kalman Filtering Algorithms for Estimating Clamp Force on a Test Rig : Testing the Power and Limitations of Unscented Kalman Filter-based Estimations

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Tim Naser; [2023]
   Keywords : Clamping Froce; Kalman Filtering; Unscented Kalman Filtering; Tightening; Consequence of User Errors During Tightening; Velocity Profiles; Klämkraft; Kalman Filtrering; Unscented Kalman Filtrering; Åtdragning; Konsekvens av Användarfel Under Åtdragning; Hastightersprofiler.;

   Abstract : his study explores clamp force estimation using Unscented Kalman Filtering (UKF) in torque-controlled tightening scenarios with various velocity profiles. Previous research has explored the impact of velocity levels on target torque and clamping force, but only using hand-held tools. READ MORE

3. 2. Localization For AutonomousDriving using Statistical Filtering : A GPS aided navigation approach with EKF and UKF

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Devrat Singh; [2022]
   Keywords : Land Vehicle Localization; Sensor Fusion; GNSS-INS Fusion; UKF; EKF;

   Abstract : A critical requirement for safe autonomous driving is to have an accurate state estimate of thevehicle. One of the most ubiquitous yet reliable ways for this task is through the integrationof the onboard Inertial Navigation System (INS) and the Global Navigation Satellite System(GNSS). READ MORE

4. 3. The Effect of Simulink Block Kalman Filters in a CubeSat ADCS

   University essay from KTH/Rymdteknik

   Author : Jesper Larsson; [2020]
   Keywords : ADCS; Kalman Filter; Simulink; Simulation; Block; EKF; UKF; ADCS; Kalmanfilter; Simulink; Simulering; Block; EKF; UKF;

   Abstract : The purpose of this paper was to implement Kalman filtering in the form of pre-existing Simulink blocks into a CubeSat attitude determination and control system simulation and to evaluate their performance. In recent versions of Simulink, the block library has been expanded, providing a new level of abstraction for simulation engineers. READ MORE

5. 4. Filtering techniques for asset allocation using a Discrete Time Micro-structure model: a comparative study

   University essay from Lunds universitet/Nationalekonomiska institutionen

   Author : Henning Zakrisson; [2017]
   Keywords : portfolio management; kalman filter; asset allocation; hidden variable; state space; discrete time micro-structure model; Business and Economics;

   Abstract : This paper is a comparative study of different approaches to using a Discrete Time Micro-structure model. By using the three filtering techniques Extended Kalman, Unscented Kalman and Bootstrap Particle, the hidden variables; excess demand and market liquidity, were estimated and used in an asset allocation strategy that invested in the asset when the excess demand as estimated as positive, due to the assumption that positive excess demand would make the price go up. READ MORE

6. 5. Attitude Navigation using a Sigma-Point Kalman Filter in an Error State Formulation

   University essay from KTH/Rymd- och plasmafysik

   Author : Periklis-Konstantinos Diamantidis; [2017]
   Keywords : unscented Kalman filtering; information ltering; quaternions; attitude navigation; gyroscope modelling; error state formulation; sensor fusion;

   Abstract : Kalman filtering is a well-established method for fusing sensor data in order to accuratelyestimate unknown variables. Recently, the unscented Kalman filter (UKF) has beenused due to its ability to propagate the first and second moments of the probability distribution of an estimated state through a non-linear transformation. READ MORE