彭会萍, 曹晓军. 异类传感器集中观测融合UKF滤波算法[J]. 微电子学与计算机, 2013, 30(1): 123-125,130.
引用本文: 彭会萍, 曹晓军. 异类传感器集中观测融合UKF滤波算法[J]. 微电子学与计算机, 2013, 30(1): 123-125,130.
PENG Hui-ping, CAO Xiao-jun. The UKF Filter Algorithm of Heterogeneous Sensors Combination[J]. Microelectronics & Computer, 2013, 30(1): 123-125,130.
Citation: PENG Hui-ping, CAO Xiao-jun. The UKF Filter Algorithm of Heterogeneous Sensors Combination[J]. Microelectronics & Computer, 2013, 30(1): 123-125,130.

异类传感器集中观测融合UKF滤波算法

The UKF Filter Algorithm of Heterogeneous Sensors Combination

  • 摘要: 由于雷达具有较好的测距性能,红外传感器具有高精度的测角性能.雷达和红外传感器是异类传感器系统的一个典型组合,但是异类传感器信息融合因没有现成的数学工具和方法而面临诸多困难.本文首次将UKF (un-scented Kalman filter)引入到异类传感器的信息融合,并且利用集中式观测融合UKF,解决同步配置、同步采样的异类传感器的信息融合问题.仿真结果表明,本算法的SMSE要小得多.

     

    Abstract: Radars have sound performance in orientation and infrared sensors have excellent performance in angle measure.Radar and infrared sensor is exceptional sensor system of a typical heterogeneous sensors combination,but heterogeneous sensors information fusion for no mathematical tools and methods and are facing many difficulties.This paper first introduced UKF(unscented Kalman filter) to heterogeneous sensors combination.And it used the centralized measurement fusion UKF to solve the information fusion of heterogeneous sensors combination of synchronization configuration and synchronous sampling.The simulation results show that This algorithm of SMSE are much smaller.

     

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