Journal of Systems Engineering and Electronics ›› 2006, Vol. 17 ›› Issue (2): 343-349.doi: 10.1016/S1004-4132(06)60060-1

• SYSTEMS ENGINEERING • Previous Articles     Next Articles

Tracking maneuvering target based on neural fuzzy network with incremental neural leaning*

Liu Mei , Quan Taifan & Yao Tianbin   

  1. Dept of Electronic and Communication Engineering, Harbin Inst. of Technology, Harbin 150001, P. R. China
  • Online:2006-06-26 Published:2019-12-20

Abstract:

The scheme for tracking maneuvering target based on neural fuzzy network with incremental neural learning is proposed. When tracked target maneuver occurs, the scheme can detect maneuver immediately and estimate the maneuver value accurately , then the tracking filter can be compensated correctly and duly by the estimated maneuver value. When environment changes, neural fuzzy network with incremental neural learning (INL-SONFIN) can find its optimal structure and parameters automatically to adopt to changed environment. So, it always produce estimated output very close to the true maneuver value that leads to good tracking performance and avoids misstracking. Simulation results show that the performance is superior to the traditional schemes and the scheme can fit changed dynamic environment to track maneuvering target accurately and duly.

Key words: neural fuzzy network, incremental neural learning, maneuvering target tracking