Space Debris Tracking Via Generalized Labeled Multi-Bernoulli Random Finite Sets
Quan Sun, Ding Ding, Zhaodong Niu · 2019
In this paper we present an algorithm for detection and tracking space debris under complex space background via (δ-generalized labeled multi-Bernoulli (δ-GLMB) random finite sets (RFS). It includes two parts, position extractor for suspected targets and tracking filter. The core strategy of this position extractor is morphological method. The filter is implemented by Sequential Monte Carlo (SMC) method and each iteration of (δ-GLMB multi-target tracking filter includes two operations: update and prediction. The processing results of measured data show that the algorithm has strong detection and tracking ability for dim and small targets under complex space background. To the best of our knowledge, this is the first time that the (δ-GLMB multitarget tracking filter has been successfully applied in the field of space debris target detection and tracking.