Information Fusion for Radar/Infrared Compound Seeker based on Federated Filter
| Autor: | Yanke Xu, Xiaogeng Liang |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Computer Networks and Communications
Infrared business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Stability (learning theory) Kalman filter Tracking (particle physics) Field (computer science) law.invention Extended Kalman filter Filter (video) law Computer vision Artificial intelligence Radar business Software |
| Zdroj: | International Journal of Digital Content Technology and its Applications. 5:218-229 |
| ISSN: | 2233-9310 1975-9339 |
| DOI: | 10.4156/jdcta.vol5.issue4.27 |
| Popis: | Active radar/infrared (IR) compound guidance technology has become a hot research content of compound guidance field. According to the characteristics and the engineering application of active radar/IR composite seeker system, in this paper, a distributed flow of information fusion for Radar/IR composite seeker was established. First the observation data of the two seekers were pretreated, including time and space registration and outlier elimination of the observation data. After that, the Federated Filter (FF) was used to setup an information fusion algorithm of radar/IR composite seeker. According to the different characteristics of radar and IR system, the Extended Kalman Filter (EKF) algorithm and the Pseudo-linear Kalman Filter (PLKF) algorithm were used to design radar and IR local filter respectively. The simulation results show that this information fusion algorithm provides significant improvement in the tracking precision of the radar/IR composite seeker system, and it has good real-time performance and stability. |
| Databáze: | OpenAIRE |
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