TRAMP：基于实时的立体声的粒子滤波跟踪
TRAMP: Tracking by a Real-time AMbisonic-based Particle filter
摘要：
本文介绍了一种由Eigenmike阵列馈电的多声源定位与跟踪系统。一阶高保真度立体声（FOA）格式被用来建立一个伪强度为基础的球形直方图，从源位置估计推导。这些瞬时估计值由依赖于一组粒子滤波器的众所周知的跟踪系统处理。本文首次提出了基于这些算法的全功能、完整的、实时的【形】运行系统。因此，它可以作为LOCATA挑战的额外基线方法。
英文摘要：
This article presents a multiple sound source localization and tracking system, fed by the Eigenmike array. The First Order Ambisonics (FOA) format is used to build a pseudointensity-based spherical histogram, from which the source position estimates are deduced. These instantaneous estimates are processed by a wellknown tracking system relying on a set of particle filters. While the novelty within localization and tracking is incremental, the fully-functional, complete and real-time running system based on these algorithms is proposed for the first time. As such, it could serve as an additional baseline method of the LOCATA challenge.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
