Maneuvering target tracking via dynamic-programming based Track-Before-Detect algorithm

Ziqian Wang, Jun Sun
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引用次数: 5

Abstract

Owing to a high detection possibility and a simple kinetic model, track-before-detect (TBD) processorsare capable to detect low signal-to-noise ratio (SNR) targets uniformly moving with constant velocities. However, when a target with weak echo is accelerating, redirecting or decelerating, conventional TBD method might be ineffective for two reasons: heavier computational cost and higher possibility of forming false trajectories. In order to solve the problem of poor capability in tracking with the maneuvering targets, we propose a dynamic programming based TBD algorithm. In this TBD procedure, higher threshold is selected in order to reduce the possibility of forming false tracks during multi-frame processing. Additionally, resulted lower detection probability can be tolerated. The performance of tracking maneuvering objects based on this TBD processor is also exhibited.
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基于动态规划的机动目标检测前跟踪算法
由于检测前跟踪(track-before-detect, TBD)处理器具有较高的检测可能性和简单的动力学模型,因此能够检测出均匀匀速运动的低信噪比目标。然而,当弱回波目标加速、重定向或减速时,传统的TBD方法可能会失效,原因有二:计算成本更大,形成错误轨迹的可能性更大。为了解决机动目标跟踪能力差的问题,提出了一种基于动态规划的TBD算法。在TBD过程中,为了减少在多帧处理过程中形成假轨迹的可能性,选择了较高的阈值。此外,可以容忍导致较低的检测概率。并展示了基于该处理器的机动目标跟踪性能。
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