Cooperative Localisation: Distributed Optimisation with Hypothesis Testing

关键位置信息长期以来一直用于各种军事环境。在许多这些设置中，如果可以传达关于特定实体和/或事件的空间位置的信息，则将是有利的。本地化要求也变得更加普遍，并在地面部队中得到了许多战略应用。例如，部队的安全可以直接与部队及其敌人在战场上的位置意识程度相关联。对于非军事应用，从1996年美国联邦通信委员会（FCC）发布的命令开始，跟踪移动的用户的第一个需求就作为基本的公共安全特征出现，该命令要求所有无线服务提供商向公共安全应答点提供紧急911（E-911）呼叫者的准确位置。从那时起，市场上出现了各种基于位置的服务（LBS），从识别朋友或员工的下落到个性化的LBS，例如发现最近的取款机。据估计，LBS将在全球范围内每年产生100亿美元的收入。在某些情况下，提供有用的定位将需要在空中实现米级完美的分辨率。然而，基本的物理挑战，如信道衰落，低信噪比（SNR），多用户干扰，和多径条件下，提出了障碍，以满足这一目标。我们对下一代（xG）本地化系统的愿景将是提供动态、分布式、强大和高分辨率的LBS。这些xG LBS的实现将需要节点处的高级信号处理和智能，以解决干扰问题，并检测直接视线（LoS）的存在，以实现可靠的测距和定位。先进的多天线技术，如多输入多输出（MIMO），预计将在移动的terminals.To实现所需的LBS，以提供增强的位置信息，以及减轻多径和多用户interference. This项目建议调查使用的移动的用户合作定位。用户或节点协作的新奇在于，节点可以通过适当的中继来协作地工作，以减轻多径干扰，这可以帮助在存在延迟路径的情况下识别用于测距的LoS。更重要的是，这种合作可以将位置信息从一个节点交换到另一个节点，以便消除由于缺乏LoS信号路径而导致的位置模糊性，并且还可以实现更高的分辨率。该提案的另一个新奇是使用基于假设检验的机器学习来检测LoS，这将与无线定位的合作信号处理相结合。这一极具挑战性的目标也有可能重新定义无线网络的体系结构，提供一种新的系统解决方案，用于组织用户对这种合作和自我调节体系结构中的系统资源的访问，并彻底改变21世纪世纪ICT的关键领域。（2）检测-使用协作信号处理在多用户和多径干扰信道中增强接收;（3）高分辨率定位-确定无线环境中移动的用户的位置;（4）多路径缓解-利用合作信号处理抑制多径干扰。这个项目的最终成果不仅将阐明利用移动的节点合作的无线定位问题的好处，还提供了分布式算法，用于实现高分辨率定位以及解决通信系统中的一些关键问题。

Critical locational information has long been used in a variety of military settings. In many of these settings, it would be advantageous if information concerning the spatial locations of particular entities and/or events could be conveyed. Localisation requirement has also become more pervasive and has found many strategic applications to the ground forces. For instance, the troops' safety can be directly linked to the degree of location-awareness of the troops and their enemies in a battlefield. For non-military applications, the first need to track a mobile user appeared as an essential public safety feature from the order issued by the Federal Communications Commission (FCC) in the US in 1996, which mandated all wireless service providers to deliver accurate location of an emergency 911 (E-911) caller to public safety answering points. Since then, various location-based services (LBSs) have emerged in the market, from identifying the whereabouts of a friend or employee to personalised LBS such as discovering the nearest cash machine. It is estimated that LBSs will generate annual revenues of the order of 10 billions worldwide.Providing a useful localisation will require, in some cases, metre-perfect resolution to be achieved over air. Yet, the fundamental physical challenges such as channel fading, low signal-to-noise ratios (SNRs), multiuser interference, and multipath conditions have put obstacles on meeting the objective. Our vision of next-generation (xG) localisation systems will be the provision of dynamic, distributed, robust and high-resolution LBSs. The realisation of these xG LBSs will require advanced signal processing and intelligence at the nodes to resolve the problem of interference and to detect the presence of a direct line-of-sight (LoS) for reliable ranging and localisation. Advanced multi-antenna technologies such as multiple-input multiple-output (MIMO) are expected to be adopted at mobile terminals for providing enhanced locational information as well as mitigating the multipath and multiuser interference.To achieve the needed LBSs, this project proposes to investigate the use of mobile user cooperation for localisation. The novelty of user or node cooperation lies in that nodes can work collaboratively by proper relaying to mitigate the multipath interference that can help identify the LoS for ranging in the presence of delay paths. The cooperation can, more importantly, exchange locational information from one node to another so that location ambiguity due to the lack of LoS signal paths could be removed and higher resolution can also be achieved. Another novelty of this proposal is the use of hypothesis testing based machine learning for the detection of LoS, which will be integrated with the cooperative signal processing for wireless localisation. This exceptionally challenging objective also has the potential to redefine the architecture of wireless networks, provide a novel system solution for organising the access of users to the system resources in this cooperative and self-regulating architecture, and revolutionise key areas of the 21st century ICT.Of particular relevance to the interests of DSTL, the areas that this project covers include:(1) Broadband signal separation - classification of LoS and non-LoS signals;(2) Detection - enhanced reception in multiuser and multipath interference channels using cooperative signal processing;(3) High-resolution localisation - determining the locations of mobile users in wireless environments;(4) Multipath mitigation - suppressing multipath interference using cooperative signal processing.The final outcomes of this project will not only elucidate the benefits of a wireless positioning problem using mobile node cooperation but also offer distributed algorithms for realising high-resolution localisation as well as address some key problems in communications systems.