Abstract This paper considers the detection and tracking of dim targets for multiple pulse repetition frequency (PRF) pulsed Doppler radar systems through the use of multi-frame track-before-detect (TBD) methods. The main challenge is that each measurement frame is a mixture with measurements recorded, periodically, at different PRF settings, thus with different range and Doppler ambiguities. To achieve this goal, we propose variable step size multi-PRF and multi-frame (or scan) TBD (MP-MF-TBD) algorithm. Specifically, by incorporating the ambiguity factors related to both the range and velocity ambiguities, MP-MF-TBD first accomplishes the target SNR integration directly using multiple ambiguous measurement frames. After analyzing the properties of the over-threshold tracks, we further propose an efficient detection procedure, which can effectively eliminate the false tracks caused by the measurement ambiguities and accomplish the target kinematic state estimation and multi-PRF ambiguity resolution simultaneously. The proposed MP-MF-TBD does not require certain limitations on the PRF type (i.e., low, medium and high PRF) or the number of PRFs in pulsed Doppler radar systems, and appears to be robust to the target loss when target fall into a blind frequency band of certain PRFs. Extensive numerical simulations demonstrated the efficacy of the proposed MP-MF-TBD by comparing with classical techniques.

中文翻译：

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多PRF雷达系统中的多PRF和多帧Track-Before-Detect算法

摘要 本文考虑了通过使用多帧跟踪前检测（TBD）方法对多脉冲重复频率（PRF）脉冲多普勒雷达系统的弱目标进行检测和跟踪。主要挑战是每个测量帧都是在不同 PRF 设置下定期记录的测量值的混合，因此具有不同的距离和多普勒模糊度。为了实现这一目标，我们提出了可变步长多 PRF 和多帧（或扫描）TBD（MP-MF-TBD）算法。具体而言，通过结合与距离和速度模糊度相关的模糊度因素，MP-MF-TBD 首先使用多个模糊测量帧直接完成目标 SNR 集成。在分析过阈值轨迹的特性后，我们进一步提出了一种有效的检测程序，可有效消除测量模糊度引起的虚假轨迹，同时完成目标运动状态估计和多PRF模糊度解析。提出的 MP-MF-TBD 对脉冲多普勒雷达系统中的 PRF 类型（即低、中和高 PRF）或 PRF 的数量没有某些限制，并且当目标落入时似乎对目标损失具有鲁棒性。某些 PRF 的盲频带。通过与经典技术进行比较，广泛的数值模拟证明了所提出的 MP-MF-TBD 的功效。中和高 PRF）或脉冲多普勒雷达系统中 PRF 的数量，当目标落入某些 PRF 的盲频带时，它似乎对目标损失具有鲁棒性。通过与经典技术进行比较，广泛的数值模拟证明了所提出的 MP-MF-TBD 的功效。中和高 PRF）或脉冲多普勒雷达系统中 PRF 的数量，当目标落入某些 PRF 的盲频带时，它似乎对目标损失具有鲁棒性。通过与经典技术进行比较，广泛的数值模拟证明了所提出的 MP-MF-TBD 的功效。