首页> 外文会议>Conference on signal and data processing of small targets >Track Segment Association for Ground Moving Targets with Evasive Move-Stop-Move Maneuvers
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Track Segment Association for Ground Moving Targets with Evasive Move-Stop-Move Maneuvers

机译:地面移动目标的轨迹段关联,采用规避的移动-停止-移动动作

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In a real tracking system, track breakages can occur due to highly maneuvering targets, low detection probability, or clutter. Previously, a track segment association approach (TSA) was developed for an airborne early warning (AEW) system to improve track continuity by "stitching" broken track segments pertaining to the same target. However, this technique cannot provide satisfactory association performance in tracking with a GMTI radar ground moving targets employing evasive move-stop-move maneuvers. To avoid detection by a GMTI radar, targets can deliberately stop for some time before moving again. Since a GMTI radar does not detect a target when the radial velocity (along the line-of-sight from the sensor) falls below a certain minimum detectable velocity (MDV), the move-stop-move maneuvers of the targets usually lead to broken tracks as a result. We present a new TSA technique which employs a dummy track to formulate a complete association. By using an IMM estimator with state-dependent mode transition probabilities (IMM-SDP) for track segment prediction (forward and backward), the proposed algorithm can effectively stitch both "regular" broken tracks and broken tracks due to targets' move-stop-move maneuvers. Comparisons are given to show the advantages of the proposed algorithm in broken tracks reduction and track continuity improvement.
机译:在真实的跟踪系统中,由于目标机动性强,检测概率低或混乱,可能会发生跟踪中断。以前,航迹段关联方法(TSA)被开发用于机载预警(AEW)系统,通过“缝合”属于同一目标的破损航迹段来改善航迹连续性。但是,此技术无法在采用GM​​TI雷达地面移动目标进行规避移动,停止-移动机动的跟踪中提供令人满意的关联性能。为了避免被GMTI雷达探测到,目标可以在再次移动之前故意停止一段时间。由于当径向速度(沿传感器的视线)低于某个最小可检测速度(MDV)时,GMTI雷达无法检测到目标,因此,目标的移动停止动作通常会导致其破裂结果跟踪。我们提出了一种新的TSA技术,该技术采用虚拟轨道来制定完整的关联。通过使用具有状态相关模式转换概率(IMM-SDP)的IMM估计器进行轨迹段预测(向前和向后),该算法可以有效地缝合“常规”断轨和由于目标的移动停止而造成的断轨移动动作。通过比较可以看出,该算法在减少断轨和改善连续性方面的优势。

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