Sensor fusion: Particle filter discrete PF

1. Introduction

2. GPS Jammer geolocation – ideal case

2.1. Model Assumptions and Methodology

2.2. Extended Kalman Filter (EKF)

2.3. Unscented Kalman Filter (UKF)

2.4. Particle filter discrete PF

3. Analysis of the designed filters for isotropic case

3.1. Choosing of the appropriate number of particles in the Particle Filter case

3.2. Selection of appropriate Pini, Q and R matrices for the EKF, UKF and PF

3.2.1. Initial state covariance matrix P and its influence on the filters

3.2.2. Process uncertainty covariance Q and its influence on the filters

3.2.3. Measurement noise covariance R and its influence on the filters

3.3. Performance comparison of the filters for the given