Sökning: "partikelfiltret"

Visar resultat 1 - 5 av 13 uppsatser innehållade ordet partikelfiltret.

1. 1. Traffic State Estimation on Swedish Highways : Model Comparison using Multisource Data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jiaqi Xu; [2023]
   Nyckelord :Traffic State Estimation; Macroscopic Traffic Model; Extended Kalman Filter; Particle Filter; Data Fusion; Trafiklägesuppskattning; Makroskopisk trafikmodell; Utökad Kalman-filter; Partikelfilter; Datafusion;

   Sammanfattning : Due to the escalating demand for traffic information and management, the significance of traffic state estimation, which involves the assessment of traffic conditions on road segments with limited measurement data, is increasing. Two primary estimation methods are model-driven and data-driven. LÄS MER

3. 2. Robust Non-Linear State Estimation for Underwater Acoustic Localization : Expanding on Gaussian Mixture Methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Diogo Antunes; [2023]
   Nyckelord :Robust state estimation; Underwater localization; Target tracking; Gaussian mixture; AUV; Estimação robusta de estado; Localização subaquática; Rastreamento de alvos; Mistura Gaussiana; AUV; Robust tillståndsuppskattning; Undervattenslokalisering; Målspårning; Gaussisk blandning; AUV;

   Sammanfattning : Robust state estimation solutions must deal with faulty measurements, called outliers, and unknown data associations, which lead to multiple feasible hypotheses. Take, for instance, the scenario of tracking two indistinguishable targets based on position measurements, where each measurement could refer to either of the targets or even be a faulty reading. LÄS MER

4. 3. The Implementation and Evaluation of Learning Approaches to State Filtering

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Anna Wilhelmsson; [2022]
   Nyckelord :;

   Sammanfattning : State estimation uses measurements of a system’s output to estimate the state. A particular method within state estimation is filtering, which estimates the state using measurements up to and including the current time. LÄS MER

5. 4. Indoor 5G Positioning using Multipath Measurements

   Master-uppsats, Linköpings universitet/Institutionen för systemteknik

   Författare :Andreas Lidström; Martin Andersson; [2022]
   Nyckelord :Multipath Propagation; 5G Networks; Target Tracking; Sensor Fusion; Positioning; Particle Filter; Kalman Filter;

   Sammanfattning : Positioning with high precision and reliability is considered as an important feature of new wireless radio networks such as 5G. In areas where satellite positioning is not available or is not reliable enough, 5G can work as an alternative. An example is inside factories where autonomous vehicles might need to be positioned in complex environments. LÄS MER

7. 5. Map-aided localization for autonomous driving using a particle filter

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Simon Eriksson; [2020]
   Nyckelord :Particle filter; Monte Carlo filter; Gaussian noise; Bayesian estimation; probabilistic localization; autonomous vehicles; Scania; OpenStreetMap; Partikelfilter; Monte Carlo-filter; Gaussiskt brus; Bayesisk uppskattning; sannolikhetsbaserad lokalisering; autonoma fordon; Scania; OpenStreetMap;

   Sammanfattning : Vehicles losing their GPS signal is a considerable issue for autonomous vehicles and can be a danger to people in their vicinity. To circumvent this issue, a particle filter localization technique using pre-generated offline Open Street Map (OSM) maps was investigated in a software simulation of Scania’s heavy-duty trucks. LÄS MER