Search for dissertations about: "multiple-model filtering"

Found 3 swedish dissertations containing the words multiple-model filtering.

  2. 1. Multiple Model Filtering and Data Association with Application to Ground Target Tracking

    Author : Daniel Svensson; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Multiple model filtering; semi-Markov processes; multi-target tracking; FISST; state estimation; IMM; performance evaluation; OSPA; PHD; ground target tracking; Kalman filtering; target tracking; CPHD; MHT; random finite sets;

    Abstract : This thesis is concerned with two central parts of a tracking system, namely multiple-model filtering and data association. Multiple models are introduced to provide accurate filtering, whereas data association deals with the unknown origin of the received measurements. READ MORE

  4. 2. Target Tracking in Complex Scenarios

    Author : Daniel Svensson; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; ran- dom finite sets; multiple-model filtering; radar.; state estimation; Target tracking; performance evaluation; sensor models;

    Abstract : This thesis is concerned with three important components in target track- ing, namely multiple-model filtering, data association and sensor resolution modeling. For multiple-model filtering, the preferred method has long been the Interacting Multiple Model (IMM) filter, which relies on the assumption that immediate model shifts have the highest probability. READ MORE

  5. 3. Nonlinear Filtering Methods in Road Geometry Estimation

    Author : Maryam Fatemi; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Abstract : Advanced driver assistance systems require information about the traffic scene of which the road geometry is an important part. In this thesis we use nonlinear filtering methods to estimate the shape of the road ahead of a host vehicle by fusing measurements of lane markings obtained from a camera and measurements of moving vehicles and barriers obtained from a radar-camera fusion system. READ MORE