Advanced Real-Time Strategies for Direction Finding in Rapidly Changing Scenario

P. Rocca, M. Hannan, G. Oliveri
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引用次数: 0

Abstract

Recent advances on real-time direction finding strategies based on Bayesian Compressive Sensing (BCS) are discussed here. The open-circuit voltages measured at any instant of time (single snapshot data) are processed by the single-task and the multi-task Bayesian Compressive Sensing (ST-BCS and MT-BCS), combined with single frequency and multi-frequency approaches, respectively. In particular, the ST-BCS is integrated within an iterative multi-scaling strategy (IMSA-BCS) for narrowband signals and the MT-BCS is extended to the multi-frequency BCS (MF-BCS) for wideband signals. The selected results from an extensive analysis highlight that the proposed approaches estimate the DoAs with high accuracy in a fraction of second.
快速变化场景下的先进实时测向策略
本文讨论了基于贝叶斯压缩感知(BCS)的实时测向策略的最新进展。对任意时刻测量的开路电压(单快照数据)分别采用单任务贝叶斯压缩感知(ST-BCS)和多任务贝叶斯压缩感知(MT-BCS),结合单频和多频方法进行处理。特别是,ST-BCS集成在窄带信号的迭代多标度策略(IMSA-BCS)中,而MT-BCS扩展到宽带信号的多频BCS (MF-BCS)。从广泛的分析中选择的结果表明,所提出的方法在几分之一秒内就能高精度地估计出doa。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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