An adaptive update-rate control of a phased array radar for efficient usage of tracking tasks

Sang Hoon Baek, Hyunchul Seok, Kyu Ho Park, J. Chun
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引用次数: 7

Abstract

In multi-functional radar, task scheduling algorithm should be designed such that timing resource is efficiently utilized by functions such as surveillance and tracking, and its performance is maximized. In the target tracking, the tasks are required to be executed to consider the maneuvering motion, measurement condition and required tracking performance. Frequent execution of tracking tasks results in not only precise tracking, but also waste of timing resource which is shared with other functions. Therefore, to reduce the number of unnecessary observations, the tracking task is required to be executed only when the update is needed. In this paper, the innovation, position residual, in Kalman filter is used as reference value for adjusting update rate of tracking tasks. Using feedback controller, the update rate is allocated so that predicted observation is expected to be within specified error range. In addition, targets are classified into 7 priorities according to tactical characteristics, and target's priority is also used as reference value for calculating update rate. The simulation results show that the proposed method reduces the tracking error of the target on maneuvering movement compared to fixed update rate case.
相控阵雷达的自适应更新速率控制,以有效地利用跟踪任务
在多功能雷达中,要设计任务调度算法,使监视、跟踪等功能有效利用时间资源,使其性能最大化。在目标跟踪中,要求执行的任务要考虑机动运动、测量条件和所要求的跟踪性能。频繁地执行跟踪任务不仅导致跟踪不精确,而且浪费了与其他功能共享的时间资源。因此,为了减少不必要的观察次数,只需在需要更新时执行跟踪任务。本文将卡尔曼滤波的创新点——位置残差作为调整跟踪任务更新速率的参考值。利用反馈控制器分配更新速率,使预测观测值期望在指定误差范围内。此外,根据战术特点将目标划分为7个优先级,目标优先级也作为计算更新率的参考值。仿真结果表明,与固定更新率情况相比,该方法减小了目标在机动运动时的跟踪误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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