Sökning: "Radar"

Visar resultat 36 - 40 av 691 uppsatser innehållade ordet Radar.

  1. 36. Contribution to the Understanding of the Effects of Propagation through the Ionosphere of P-band SAR Data

    Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Johannes Samuel Erland Rönner; [2023]
    Nyckelord :Synthetic aperture radar; Ionosphere;

    Sammanfattning : The BIOMASS mission from the European Space Agency (ESA) is designed to measurebiomass and carbon content in Earth’s forests. To account for phase changes caused byionospheric variations, a map-drift autofocus algorithm is developed, which utilises a phasescreen of the ionosphere to eliminate phase errors in the signal. LÄS MER

  3. 37. Domain Adaptation Of Front View Synthetic Point Clouds Using GANs For Autonomous Driving

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Friedemann Kleinsteuber; [2023]
    Nyckelord :LiDAR; Domain Adaptation; GAN; CycleGAN; Simulation; LiDAR; Domänadaption; GAN; CycleGAN; Simulation;

    Sammanfattning : The perception of the environment is one of the main enablers of Autonomous Driving and is driven by Cameras, RADAR, and LiDAR sensors. Deep Learning algorithms used in perception need a vast amount of labeled, high-quality data which is costly to obtain for LiDAR sensors. LÄS MER

  4. 38. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

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

    Författare :Viktor Kårefjärd; [2023]
    Nyckelord :Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

    Sammanfattning : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. LÄS MER

  5. 39. MmWave Radar-based Deep Learning Collision Prediction

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

    Författare :Taylor Lauren V'dovec; [2023]
    Nyckelord :collision prediction; mmWave radar; deep learning; variational autoencoder VAE ; drone; autonomous navigation; kollisionsprognos; mmWave radar; djupinlärning; variational autoencoder VAE ; drönare; autonom navigation;

    Sammanfattning : Autonomous drone navigation in classical approaches typically involves constructing a map representation and employing path planning and collision checking algorithms within that map. Recently, novel deep learning techniques combined with depth camera observations have emerged as alternative approaches capable of achieving comparable collision-free performance. LÄS MER

  7. 40. Map Based Sensor Fusion for Lane Boundary Estimation on ADAS

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

    Författare :Puya Faghi; [2023]
    Nyckelord :Lane estimation; Lane detection; Map-matching; Sensor fusion; Smart camera; Vehicle Radar; Intelligent vehicle systems; Körfältsestimering; Körfältsdetektering; Kartmatchning; Sensorfusion; Smart Kamera; Radar system; Fordonsradar; Intelligenta fordonssystem;

    Sammanfattning : A vehicles ability to detect and estimate its surroundings is important for ensuring the safety of the vehicle and passengers regardless of the level of vehicle autonomy. With an improved road and lane estimation, advanced driver-assistance systems will be able to provide earlier and more accurate warnings and actions to prevent a possible accident. LÄS MER