2022, Volume 23, Issue 12
Frontiers of Information Technology & Electronic Engineering >> 2022, Volume 23, Issue 12 doi: 10.1631/FITEE.2200286
Generalized labeled multi-Bernoulli filter with signal features of unknown emitters
Affiliation(s): College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China; China National Aeronautical Radio Electronics Research Institute, Shanghai 200233, China; less
Next Previous
Abstract
A novel algorithm that combines the (GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features (EFs) are often unknown and time-varying. Aiming at the unknown feature problem, we propose a method for identifying EFs based on of data fields. Because EFs are time-varying and the probability distribution is unknown, an improved algorithm is proposed to calculate the correlation coefficients between the target and measurements, to approximate the EF likelihood function. On this basis, the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations. Simulation results show that the proposed method can improve the tracking performance of multiple targets, especially in heavy clutter environments.
京公网安备 11010502051620号
