改进的3D角度目标跟踪平滑

Qian Zhang, Seung-Hyo Park, T. Song
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引用次数: 2

摘要

本文提出了两种平滑滤波器来解决三维纯角度目标跟踪问题。一种是平滑扩展卡尔曼滤波器(sEKF),另一种是平滑修正增益扩展卡尔曼滤波器(sMGEKF)。这两种方法都基于Rauch-Tung-Striebel (RTS)平滑。与传统的无源定位方法(如EKF和MGEKF)相比,本文提出的滤波器在跟踪精度方面具有潜在的优势。将这两种滤波器应用于三维纯角度滤波问题,仿真结果表明了这两种方法的优越性。
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Improved 3D angle-only target tracking with smoothing
In this paper, two smoothing filters are proposed to address the 3D angle-only target tracking. One is smoothing extended Kalman filter (sEKF) and the other one is smoothing modified gain extended Kalman filter (sMGEKF). Both of them are based on Rauch-Tung-Striebel (RTS) smoothing. Compared to the traditional approaches (e.g., the EKF and the MGEKF) used in passive localization, the proposed filters have potential advantages in tracking accuracy. Both new filters are applied in 3D angle-only filtering problems and simulation results demonstrate the advantages of these two approaches.
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