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针对由激光测距机与精密测角设备组成的光电跟踪系统,为了攫取跟踪系统的冗余测角信息以提升不完全量测下跟踪系统的估计性能,设计了基于验后置信度残差检测的联邦目标跟踪滤波器。依据物理结构将跟踪系统的位置探测通道分解为测距与测角2个探测通道,并对2个探测通道的量测数据分别进行基于验后置信度残差检测的目标状态估计。将估计结果送至融合中心进行信息融合。利用融合结果,并根据探测通道数据可信的验后概率,对探测通道的子滤波器进行信息分配。Monte Carlo仿真表明,在不完全量测下,所提滤波器在不增加系统硬件成本的前提下,通过攫取高采样率下的测角信息,显著改善了跟踪系统的估计性能,并且滤波器估计误差均方差(RMSE)已逼近跟踪系统统计意义下的Cramer Rao下界(CRLB).
For the electro-optical tracking system composed of laser range finder and precision angular measurement equipment, in order to capture the redundant angular measurement information of the tracking system to improve the estimation performance of the tracking system under incomplete measurement, a post-test confidence residual detection Federal target tracking filter. According to the physical structure, the position detection channel of the tracking system is decomposed into two detection channels of ranging and angle measurement, and the target state estimation based on the post-test confidence residual detection is respectively performed on the measurement data of the two detection channels. Send the estimation results to the fusion center for information fusion. The information of the sub-filters of the sounding channel is distributed by using the fusion result and based on the credible post-probabilities of the sounding channel data. The Monte Carlo simulation shows that under incomplete measurement, the proposed filter can significantly improve the estimation performance of the tracking system by capturing the angle information at high sampling rate without increasing the hardware cost of the system, and the filter estimation The mean square error of error (RMSE) approaches the Cramer Rao lower bound (CRLB) in the statistical sense of the tracking system.