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为提高跟踪精度,在塔康系统距离测量中,可采用Kalman和α-β算法对距离测量值进行滤波。要确保处理精度,采用Kalman滤波器,状态变量取的会比较多,而α-β算法是一种常增益滤波器,会出现发散情况。针对两种滤波器的不足,提出了变维Kalman滤波的塔康距离跟踪算法,该算法建立距离测量的非机动模型和机动模型,通过距离滤波在机动和非机动两种模型间的自适应切换,完成塔康距离实时跟踪。应用Monte Carlo方法仿真表明:该算法可实现塔康距离的实时跟踪,而且距离测量准确度有了一定提高。
In order to improve the tracking accuracy, Kalman and α-β algorithms can be used to filter the distance measurement in the distance measurement of TACAN system. To ensure processing accuracy, the use of Kalman filter, state variables will take more, and α-β algorithm is a constant gain filter, there will be divergence. In order to overcome the shortcomings of the two kinds of filters, a Tuckah distance tracking algorithm based on variable-dimensional Kalman filter is proposed. The algorithm establishes the non-motorized model and the motorized model of distance measurement, and adaptively switches between maneuvering and non-maneuvering through distance filtering , Complete real-time tracking Tacankan distance. The application of Monte Carlo simulation shows that this algorithm can realize the real-time tracking of Taconic distance, and the accuracy of distance measurement has been improved.