Unified Near-Field and Far-Field Localization for AOA and Hybrid AOA-TDOA Positionings
Unified Near-Field and Far-Field Localization for AOA and Hybrid AOA-TDOA Positionings
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DOI：
10.1109/twc.2017.2777457
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发表时间：
2018-02-01
影响因子：
10.4
通讯作者：
Ho, K. C.
中科院分区：
文献类型：
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作者：
Wang, Yue;Ho, K. C.
信号源在离传感器不远的地方可以进行点定位，而到达方向（DOA）定位只有在较远的地方才适用。点定位和DOA定位采用不同的估计模型，并且通常没有关于源范围的先验知识来决定哪种模型是合适的。本文介绍了一种改进的极坐标表示方法，利用到达角（AOA）来统一定位远近源。从高斯AOA测量中，我们利用混合bhattacharya - barankin （HBB）约束来说明，当使用近场模型时，不可能获得远源的笛卡尔坐标，并且当使用远场模型时，推导出距离不太远的源的DOA偏差。其次，在改进的极坐标表示下，导出了一个单模型的迭代极大似然估计量（MLE），其中HBB界证实了估计量无论远近都具有稳定的行为。如果源很近，算法会给出位置，如果源很远，算法会给出DOA。提出了一种利用半定松弛初始化MLE的初步解决方案。将HBB界、分析和算法推广到AOA-TDOA混合定位中。
Point positioning of a signal source is feasible if it is not far from the sensors and direction of arrival (DOA) localization is only applicable if it is distant. Point positioning and DOA localization employ different estimation models and prior knowledge about the source range is often not available to decide which model is appropriate. This paper introduces the modified polar representation to unify the localization of a source using angle of arrival (AOA) regardless if it is near or far. From the Gaussian AOA measurements, we utilize the hybrid Bhattacharyya-Barankin (HBB) bound to illustrate it is not possible to obtain the Cartesian coordinates of a distant source when applying the near-field model, and derive the DOA bias of a not so distant source when using the far-field model. An iterative maximum likelihood estimator (MLE) is next derived under the modified polar representation with a single model, where the HBB bound confirms the stable behavior of the estimator regardless it is near or far. The algorithm yields a position if the source is close and a DOA if it is distant. A preliminary solution to initialize the MLE using semidefinite relaxation is also proposed. The HBB bound, the analysis and the algorithm are extended for hybrid AOA-TDOA localization.