An Improved IMM Estimator Combined with Intelligent Input Estimation Technique for Tracking Maneuvering Target

Abstract:

The estimation performance of interactive multiple model (IMM) estimator for tracking a maneuvering target is influenced by the target motion models and application of filters. An improved IMM estimation algorithm combined with the intelligent input estimation technique is proposed in this study. The target motion models include the constant velocity (CV) model and the modified Singer acceleration model. The intelligent fuzzy weighted input estimation (IFWIE) is used to compute the acceleration input for the modified Singer acceleration model besides the application of standard Kalman filter (KF). The combination of KF and IFWIE can estimate the target motion state precisely and the proposed method is compared with the common IMM estimator. The simulation results prove the improved IMM estimator has superior estimation performance than the common IMM estimator, especially when the target changes the acceleration violently. The utilization of IFWIE for the improved IMM estimator can estimate the acceleration input effectively.

• Periodical: Applied Mechanics and Materials (Volumes 764-765)
• Pages: 664-670
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.764-765.664
• Online since: May 2015
• Authors: Yi Wei Chen*, Yung Lung Lee
• Keywords: Fuzzy, IMM, Input Estimation, Kalman Filter, Maneuvering Target

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