Direct localization systems can outperform two-step localization ones by jointly processing all the measurements observed at base stations. However, such systems encounter large communication and computational load when the signal dimension is high, e.g., with large-scale antenna arrays. In this paper, we establish a general framework for beamspace direct localization, which consists of beamspace design and position determination. By deriving the performance bound of beamspace direct localization, we first prove that the high-dimensional array signal can be represented in a low-dimensional beamspace without information loss, and then cast the beamspace design as an optimization problem under dimension constraints. In the presence of parameter uncertainty, we propose a robust beamspace scheme to guarantee the performance in the worst case. Using the low-dimensional signals, we develop an efficient direct localization algorithm with the computational complexity and communication overhead orders of magnitude smaller than the conventional methods. Simulation results show that the proposed approach attains near-optimal localization performance.

中文翻译：

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大规模天线阵列系统的波束空间直接定位

通过联合处理在基站观察到的所有测量结果，直接定位系统可以胜过两步定位系统。然而，当信号维度很高时，例如使用大规模天线阵列，此类系统会遇到大量通信和计算负载。在本文中，我们建立了波束空间直接定位的通用框架，包括波束空间设计和位置确定。通过推导波束空间直接定位的性能界限，我们首先证明高维阵列信号可以在低维波束空间中表示而不会丢失信息，然后将波束空间设计转化为维度约束下的优化问题。在存在参数不确定性的情况下，我们提出了一种鲁棒的波束空间方案来保证最坏情况下的性能。使用低维信号，我们开发了一种有效的直接定位算法，其计算复杂度和通信开销比传统方法小几个数量级。仿真结果表明，所提出的方法获得了接近最优的定位性能。