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Joint Detection and Tracking of Unresolved Targets with a Joint-Bin Processing Monopulse Radar

机译:联合处理单脉冲雷达对未解决目标的联合检测和跟踪

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摘要

Detection and estimation of multiple unresolved targets with a monopulse radar is limited by the availability of information in monopulse signals. The maximum possible number of targets that can be extracted from the monopulse signals of a single bin is two. Recently two approaches have been proposed in the literature to overcome this limitation. The first is joint-bin processing that exploits target spill-over among adjacent cells by modeling the target returns in the adjacent cells. In addition to making use of the additional information available in target spill-over, it handles a more practical problem where the usual assumption of ideal sampling is relaxed. The second approach is to make use of tracking information in detection through joint detection and tracking with the help of Monte Carlo integration of a particle filter. It was shown that the extraction of even more targets is possible with tracking information. In this paper, a new approach is proposed to combine make the best of these two approaches — a new joint detection and tracking algorithm with multibin processing. The proposed method increases the detection ability as well as tracking accuracy. Simulation studies are carried out with amplitude comparison monopulse radar for an unresolved target scenario. The relative performances of various methods are also provided.
机译:单脉冲雷达对多个未解决目标的检测和估计受到单脉冲信号中信息可用性的限制。可以从一个单元的单脉冲信号中提取的最大目标数目为2。最近,文献中提出了两种方法来克服这一限制。第一种是联合仓处理,它通过对相邻单元中的目标收益建模来利用相邻单元之间的目标溢出。除了利用目标溢出中可用的附加信息外,它还处理了一个更实际的问题,即通常理想采样的假设被放宽了。第二种方法是在粒子滤波器的蒙特卡洛积分的帮助下,通过联合检测和跟踪在检测中利用跟踪信息。结果表明,利用跟踪信息可以提取更多目标。在本文中,提出了一种结合这两种方法的优点的新方法-一种具有多仓处理的新型联合检测和跟踪算法。所提出的方法提高了检测能力以及跟踪精度。针对未解决的目标场景,使用幅度比较单脉冲雷达进行了仿真研究。还提供了各种方法的相对性能。

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