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Non-Cooperative Target Localisation Using Rank Based EDM Approach

机译:基于秩的EDM方法的非合作目标本地化

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An analysis of the effect of the number of sensors on the non-cooperative target node localisation is presented. This work examines the target localisation using a centralised range based approach. In doing this, the work leverages an algorithm based on a class of matrix structure called Euclidean distance matrices (EDMs) for the specific purpose of improving localisation performance when the fusion centre (FC) cannot receive certain sensors' information due to fading or shadowing, etc. While this interesting approach to the problem of localisation has been found to be successful, it is also shown at high delay values the proposed alternating rank-based EDM algorithm outperforms the conventional linear least squares (LLS) based algorithm for the minimum number of sensors. The localisation error decreases when the conditioning of EDM is better, i.e., when the sensors are further apart from each other and closer to the target.
机译:介绍了对非协作目标节点定位的传感器数量的影响。这项工作使用基于集中式范围的方法来检查目标本地化。在这样做的情况下,该工作利用了一种基于一类矩阵结构的算法,称为欧几里德距离矩阵(EDMS),以提高本地化性能的特定目的,当融合中心(FC)由于衰落或阴影而导致某些传感器的信息时,虽然已经找到了本地化问题的这种有趣方法是成功的,但在高延迟值中也显示了所提出的基于秩的EDM算法优于基于传统的线性最小二乘(LLS)的最小数量的算法传感器。当EDM的调节更好时,本地化误差会降低,即,当传感器彼此彼此交换并且更靠近目标时。

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