Strong tracking SCKF based on adaptive CS model for manoeuvring aircraft tracking
| Autor: | Haowei Zhang, Junwei Xie, Jiaang Ge, Bingzhen Liu, Wenlong Lu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Computer science Recursion (computer science) Orthogonality principle 020206 networking & telecommunications 02 engineering and technology Function (mathematics) Filter (signal processing) Kalman filter Tracking (particle physics) Acceleration 020901 industrial engineering & automation Control theory 0202 electrical engineering electronic engineering information engineering Fading Electrical and Electronic Engineering |
| Zdroj: | IET Radar, Sonar & Navigation. 12:742-749 |
| ISSN: | 1751-8792 |
| DOI: | 10.1049/iet-rsn.2017.0467 |
| Popis: | A novel tracking algorithm is proposed by the integration of the adaptive current statistical (CS) model and the modified strong tracking (ST) square-root cubature Kalman filter (SCKF) for the manoeuvring aircraft tracking problem. Firstly, the acceleration recursion equation and the acceleration mean input estimation are combined in order to realise the adaptive adjustment of the CS model. Then, the introduced position of the fading factor is relocated from the orthogonality principle and a new formula is put forward. Additionally, the strong manoeuver detection function is established to adjust the manoeuvring frequency of the CS model. The simulation results show that the proposed algorithm possesses better tracking accuracy than the multiple-fading-factor SCKF based on the CS model, the SCKF-ST filter based on the modified CS model and the interacting-multiple-model (IMM)-SCKF. Moreover, the proposed algorithm decreases the runtime by 40% compared with the IMM-SCKF. |
| Databáze: | OpenAIRE |
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