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中文摘要：
为了解决非线性系统中杂波环境下的多传感器多目标跟踪问题,提出了一种集中式顺序多传感器不敏多假设滤波算法。在算法中,首先根据顺序结构多传感器系统实现方法将研究问题转化为顺序处理多个非线性单传感器多目标跟踪问题,然后结合多假设跟踪的思想将单传感器中量测点迹与多个航迹互联,在此基础上采用不敏卡尔曼滤波完成非线性条件下目标状态估计与协方差的递推。仿真结果表明,与MSJPDA/EKF算法相比,本算法具有更高的跟踪精度和稳定性。
英文摘要：
In order to solve the problem of multi-sensor multi-target tracking in nonlinear system in the presence of clutter,a Centralized Multi-Sensor Unscented Multiple Hypothesis Tracking Algorithm（CMSUMHT） is proposed.In the new algorithm,the problem of interest is first converted into multiple nonlinear single-sensor multi-target tracking problems,which can be dealt with sequentially.Then the association of measurements to tracks is implemented according to the principle of multiple hypothesis tracking.Based on this,Unscented Kalman Filter（UKF） is used for the propagation of state distribution in nonlinear system.Simulation results indicate that the accuracy and robustness of proposed algorithm are improved compared with the MSJPDA/EKF algorithm.
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