文章基本信息

标题：Lateral Cross Localization Algorithm Using Orientation Angle for Improved Target Estimation in Near-Field Environments
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作者：Penghao Xu ; Bing Yan
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2016
卷号：7
期号：3
页码：40-53
DOI：10.3390/info7030040
出版社：MDPI Publishing
摘要：Passive positioning systems with a small aperture array exhibit poor accuracy of target estimation under strong interference in near-field environments. To improve this accuracy, we propose a novel cross localization algorithm for direction-finding using the orientation angle. Improved geometric and numerical target-positioning models are constructed after analyzing the mechanism of the conventional positioning algorithm. The target prediction equation is then derived using the constructed models, and the equation for nonlinear estimation is linearized using the Taylor series. An unbiased estimation of the target is obtained by optimizing the control of the iteration process, thus achieving an accurate positioning of the target. The performance of the proposed algorithm was evaluated in terms of its effectiveness and positioning accuracy under varying signal-to-noise conditions and orientation angle-measurement errors. Simulation results show that the proposed algorithm is capable of positioning the target effectively, and offers better positioning accuracy than traditional algorithms under the conditions of large orientation angle measurement errors or high-level background noise.
关键词：lateral cross localization; orientation angle; Gauss-Newton iteration; error characteristics lateral cross localization ; orientation angle ; Gauss-Newton iteration ; error characteristics