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Derived Heading Using Lagrange Five Point Difference Method and Fusion (poster)

机译:使用拉格朗日五点差异方法和融合(海报)衍生出头

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In general, bearing measurements combined with the derived heading increases the accuracy of target state estimate in bearing only tracking (BOT). Here, Lagrange five point difference (LFPD) method is proposed for deriving the heading measurements. This method is compared with Lagrange three point difference (LTPD) and centered difference (CD) method by considering the scenario of two sensors tracking a single target. The bearing and derived heading measurements from two sensors are fused using measurement fusion (MF) technique. The nonlinear Extended Kalman filter (EKF) is implemented using fused measurement to obtain the optimized target state estimate. Performance analyses are made between LFPD compared with LTPD and CD by considering without and with fusion technique. Simulation results indicate MF-LFPD performs comparatively better.
机译:通常,与衍生头部结合的轴承测量增加了仅轴承的靶状态估计的准确性,该轴承仅轴承跟踪(Bot)。这里,提出了Lagrange五点差(LFPD)方法来导出标题测量。通过考虑跟踪单个目标的两个传感器的场景,将该方法与Lagrange三点差(LTPD)和居中差(CD)方法进行比较。使用来自两个传感器的轴承和来自两个传感器的前置测量使用测量融合(MF)技术融合。使用熔融测量来实现非线性扩展卡尔曼滤波器(EKF)以获得优化的目标状态估计。通过考虑没有融合技术,与LTPD和CD相比,在LFPD之间进行性能分析。仿真结果表明MF-LFPD相对较好地执行。

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