Gaussian Mixture (GM) Passive Localization using Time Difference of Arrival (TDOA)

: This paper describes the passive emitter localization using Time Difference of Arrival (TDOA) measurements. It investigates various methods for estimating the solution of this nonlinear problem: the Maximum Likelihood Estimation (ML) as a batch algorithm, the Extended Kalman Filter (EKF) as an analytical approximation, the Unscented Kalman Filter (UKF) as a deterministic sampling approach and finally the Gaussian Sum Approximation (Gaussian Mixture, GM). Different scenarios are investigated in terms of estimation accuracy, described by the Cram

• Type: Journal
• Year: 2009
• Where: GI
• Authors: Regina Kaune
• Keywords: Cram´er Rao, GI 2009, Kalman Filter, Rao Lower Bound, Theoretical Computer Science