An Improved Interacting Multiple Model Algorithm for Target Tracking Based on ANFIS

다국어 초록 (Multilingual Abstract)

IMM (Interacting Multiple Model) algorithm is widely used in target tracking, and its basic principle is described in detail at first. However, the IMM algorithm fails to obtain the prior probability of model conversion quickly and accurately when tracking for target. In this paper, an improved IMM algorithm based on ANFIS (the adaptive neural fuzzy inference system) is proposed. The improved algorithm can update the value of system noise covariance in real-time by ANFIS module through observing the coefficient of system noise covariance. Consequently, the probability of model conversion can be obtained more quickly and accurately. Then, the comparison and analysis of the experiment results between the original IMM algorithm and the improved one have been carried out. The experiment results show that the reaction rate for maneuvering target tracking is significantly boosted and tracking error is obviously reduced because the improved algorithm can update the value of system noise covariance in real-time and improve the system adaptability.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Principle and Defect of the Original IMM Algorithm
• 2.1. Principle of the IMM Algorithm
• 2.2 Limitation of the Original IMM Algorithm
• 3. The improved IMM Algorithm
• 3.1 Principle of the Improved Algorithm
• 3.2 Design of ANFIS System
• 4. Experiment Results Comparison between the Original Algorithm and the Improved One
• 5. Parameter Optimization in the ANFIS Module
• 6. Conclusions
• Acknowledgements
• References