원문정보
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
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
키워드
저자정보
참고문헌
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- 4Adaptive curvilinear model based target tracking algorithm for multiple passive sensors네이버 원문 이동
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- 11Bearings-Only Target Motion Analysis via Instrumental Variable Estimation네이버 원문 이동
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