Applying Kalman filter-based fusion algorithm to estimation problems

Chung Lain Lu, Yi Nung Chung, Chih Min Lin, Chin Chung Yu, Tsair Rong Chen

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


An algorithm denoted as Kalman filter-based fusion algorithm for estimation problems is developed in this paper. In this approach, a multiple-sensors data-fusion algorithm is applied. In order to solve the data association and target maneuvering situations, a computational logic, including 1-step conditional maximum likelihood and an adaptive estimator is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the multiple sensors can improve the tracking accuracy and the reliability of the radar surveillance. Computer simulation results indicate that this approach can successfully track multiple targets with satisfactory performance. ICIC International

Original languageEnglish
Pages (from-to)2109-2114
Number of pages6
JournalICIC Express Letters
Issue number6 A
Publication statusPublished - 2010 Dec

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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