Title :
A hybrid Fuzzy dynamic model for maneuvering targets
Author :
Tafti, Abdolreza Dehghani ; Sadati, Nasser
Author_Institution :
Sci. & Res. Branch, Islamic Azad Univ., Tehran
Abstract :
Accuracy and precision of estimated state of target depends on the used motion model in tracking algorithm. Motion model of maneuvering targets is changed uncertainly, in each instant for their varying acceleration. In this paper, to minimize the estimation error produced from using mismatch motion model, an adaptive motion model is proposed. It is obtained based on adjusting the maneuvering time constant of the Singer model according to the output of a fuzzy ARTMAP which classifies motion into constant velocity and constant acceleration in each step time. The improved tracking performance of using the proposed motion model over using popular models such as the interacting multiple model and the Singer model, is illustrated by simulation in tracking of an anti-ship missile.
Keywords :
ART neural nets; fuzzy neural nets; military computing; target tracking; adaptive motion model; antiship missile tracking; constant acceleration; constant velocity; estimation error; fuzzy ARTMAP; hybrid fuzzy dynamic model; maneuvering targets; maneuvering time constant; tracking algorithm; Acceleration; Adaptive filters; Computational efficiency; Data mining; Fuzzy neural networks; Motion estimation; Neural networks; Noise measurement; State estimation; Target tracking;
Conference_Titel :
Aerospace conference, 2009 IEEE
Conference_Location :
Big Sky, MT
Print_ISBN :
978-1-4244-2621-8
Electronic_ISBN :
978-1-4244-2622-5
DOI :
10.1109/AERO.2009.4839485