Multiple-mode Kalman filtering with node selection using bearings-only measurements

Qiang Le, L.M. Kaplan, J. McClellan
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引用次数: 14

Abstract

This work investigates multiple-mode tracking method with node selection using bearings-only measurements. We combine multiple-mode extended Kalman filter with node resource management to conserve energy while tracking a maneuvering target. Experiments using real data show that the MM adapts quicker to target maneuvers than the realizable single-mode tracker. Additional experiments show that the simplex node selection leads to better geolocation performance compared to the closest node selection when the number of active nodes is set to two.
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多模卡尔曼滤波与节点选择使用方位测量
本文研究了使用纯方位测量进行节点选择的多模跟踪方法。我们将多模扩展卡尔曼滤波与节点资源管理相结合,在跟踪机动目标时节约能量。实际数据实验表明,该跟踪器比可实现的单模跟踪器对目标机动的适应速度更快。实验表明,当活动节点数为2时,单纯形节点选择比最接近节点选择具有更好的地理定位性能。
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