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논문검색

A New Tracking Algorithm for Strong-Maneuvering Target with Two-Layer Nested Model of CS and CL

초록

영어

A new tracking algorithm is proposed for strong-maneuvering target, which is based on a two-layer nested model with Improved Current Statistical (ICS) model and Curvilinear (CL) model as the inner and outer layer respectively. The inner layer use ICS model to construct statistics with filtering residuals to detect target’s maneuver and thus correcting the parameters of CS model in real time in order to adapt to target’s real motion. The outer layer uses the estimate of acceleration obtained from the inner layer as its input and in this way conduct better performance of target tracking by taking advantage of CL model, which can better correspond to the curvilinear motion of target. Simulation results show the practicability of the algorithm proposed in this article and demonstrate good tracking performance.

목차

Abstract
 1. Introduction
 2. System Configuration of the Two-Layer Models
 3. Improved CS Model
  3.1. Maneuver Detecting Algorithm of Target
  3.2. Adaptive Parameters Algorithm
 4. Filtering Algorithm of CL Model
  4.1. CL Model of Target Motion
  4.2. Filtering Algorithm of CL Model
 5. Simulation Results
  5.1. The Simulation Results of Acceleration Estimate in ICS Model
  5.2. The Two-Layer Nested Model Simulation Results
 6. Conclusions
 Acknowledgments
 References

저자정보

  • Jinshuan Peng Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China
  • Lei Xu Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China
  • Liping Wang School of Computer Science, Engineering and Mathematics, Flinders University, South Australia 5042, Australia
  • Xiaoxiang Zhou Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China

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