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An Assignment Based Algorithm for Multiple Target Localization Problems Using Widely-separated MIMO Radars

机译:广泛分离的MIMO雷达基于目标的多目标定位算法

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Multiple-Input Multiple-Output (MIMO) radars with widely-separated antennas have attracted much attention in recent literature. The highly efficient performance of widely-separated MIMO radars in target detection compared to multistatic radars have been widely studied by researchers. However, multiple target localization by the enlightened structure has not been sufficiently explored. While Multiple Hypothesis Tracking (MHT) based methods have been previously applied for target localization, in this paper, the well-known 2-D assignment method is used instead in order to handle the computational cost of MHT. The assignment based algorithm works in a signal-level mode. That is, signals in receivers are first matched to different transmitters and, then, outputs of matched niters are used to find the cost of each combination in the 2-D assignment method. The main benefit of 2-D assignment is to easily incorporate new targets that are suitable for targets with multiple scatters where a target may be otherwise unobservable in some pairs. Simulation results justify the capability of 2-D assignment method in tackling multiple target localization problems, even in relatively low SNRs.
机译:具有广泛分开的天线的多输入多输出(MIMO)雷达在最近的文献中引起了很多关注。研究人员已经广泛研究了与多基地雷达相比,广泛分离的MIMO雷达在目标检测中的高效能。但是,尚未充分探索通过开明结构进行的多目标定位。尽管基于多重假设跟踪(MHT)的方法先前已应用于目标定位,但在本文中,为了处理MHT的计算成本,使用了众所周知的2-D分配方法。基于分配的算法在信号级模式下工作。即,首先将接收器中的信号匹配到不同的发射器,然后使用匹配的niters的输出来查找2-D分配方法中每种组合的成本。二维分配的主要好处是可以轻松地合并适用于具有多个散点的目标的新目标,在这种情况下,可能无法成对观察到目标。仿真结果证明了二维分配方法能够解决多个目标定位问题,即使在相对较低的SNR中也是如此。

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