Bearings-only tracking using data fusion and instrumental variables
Bearings-only tracking using data fusion and instrumental variables
复制标题
使用数据融合和工具变量进行仅方位跟踪
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
T. Rea
中科院分区：
文献类型：
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作者：
Y. Chan;T. Rea
本文提出了一种递推测量辅助变量纯方位跟踪方法。平滑操作直接融合多传感器方位测量值，通过交换测量值作为伪线性估计器中的仪器。MIV-BOT公式产生平滑的速度估计，参数化到沿目标轨迹的任何位置沿着，这是从一个单一的激光测距仪测量。目标距离的预测，来自平滑的两个状态的速度估计，然后用作两个并行卡尔曼滤波器的距离测量。其结果是一个递归的，被动的和无偏的融合方案。在短跟踪的情况下，通过蒙特卡罗模拟的理论发展进行了研究。实验结果表明，融合方案产生可靠的估计非机动目标。
This paper presents a recursive Measurement Instrumental Variables Bearings-Only Tracking (MIV-BOT) method for a stationary observer. A smoothing operation directly fuses multi-sensor bearing measurements by exchanging the measurements as the instruments in a pseudo linear estimator. The MIV-BOT formulation produces a smoothed velocity estimate parameterized to any position along the target trajectory, which is found from a single laser range finder measurement. Target range predictions, derived from the smoothed two-state velocity estimate, are then used as range measurements in two parallel Kalman filters. The result is a recursive, passive and unbiased fusion scheme. The theoretical development is investigated by Monte Carlo simulation in short tracking scenarios. Experimental results show that the fusion scheme produces reliable estimates for non-manoeuvring targets.