基于位置的增强服务是物联网应用重要内容，亦为我国导航/位置服务相关规划重要组成部分，其中无线网络室内外高效定位是关键之一。然而实际应用中无线定位易受非视距 (NLOS) 传输影响以致性能恶化。因此本课题针对NLOS/LOS传输环境中的高性能定位问题展开研究，考虑网络中有固定节点(AN)。具体包括： 1、NLOS/LOS传输环境下LOS-AN检测理论方法与算法，包含硬判决和软判决两部分，以及移动节点位置跟踪算法和可靠度辅助残差加权定位算法；2、对NLOS误差不敏感的线性结构定位理论方法与算法，首先研究有理分式变换定位算法，再将它拓展到线性结构类方法的范畴；3、运用最优化理论的定位理论方法与算法，重点研究测距加权二次规划类定位算法以及残差代价函数下的非线性优化定位算法。研究成果有望解决无线定位的NLOS误差问题，实现LOS/NLOS传输环境中定位理论方法的突破，为相关物联网研究应用提供参考。

The position-based service has been considered as an important topic in the internet of things, where one of the key issues is the accurate position estimates in diverse indoor/outdoor environments of wireless networks. However, the accuracy of wireless localization is significantly affected by the non-line-of-sight (NLOS) propagation in real-world applications. In order to tackle this problem, this project will carry out the investigation in three aspects. First, by exploiting the residual-difference idea, the theory and method to detect the line-of-sight (LOS) anchor node (AN) will be proposed to take account of the hybrid NLOS/LOS wireless environment, where the detector will be studied in terms of soft decisions or hard decisions. And then, the high-performance position tracking scheme of the mobile node, as well as the reliability-assisted residual weighting algorithm, will be incorporated into hybrid NLOS/LOS wireless environments after the LOS-AN detecting process. Second, the localization theory and method insensitive to the NLOS error is studied in hybrid NLOS/LOS wireless environments by assuming the linear least-squares (LS) structure, where it is an extension of the rational-fraction-transform based localization, and the latter also plays an important role in this project. Finally, the optimization theory will be involved into the NLOS error cancellation to yield a precise position estimation, in which there are two kinds of methods, i.e., the range-scaled quadratic programming method as well as the nonlinear optimizing method with the cost represented by the residual-difference. In summary, our study will benefit the wireless localization theory and technology, and facilitate the application of wireless localization in the internet of things.