Transceiver SoC for Wireless Indoor Sensing Data-fusion

Abstract

Wireless indoor navigation/position system aims to navigate and localize a large number of people or objects inside buildings/places where GPS signals are unavailable. It requires both indoor position information and indoor environmental information. The indoor position information extraction can be performed by Ultra-wideband (UWB) sensors with high-precision positioning capability [1], [2], [3]. The indoor complex and diverse environment information can be obtained by using FMCW radar sensors. In addition, communication between devices/nodes is required to obtain environment information of various positions and enhance indoor navigation/position accuracy under NLOS environments through multi-source data-fusion. In order to support the wireless indoor sensing data-fusion, this paper introduces a digital-intensive 1T2R joint-radar-communication transceiver SoC. The transceiver consists of a UWB mode and an FMCW radar mode. The UWB mode of the transceiver is compatible with IEEE 802.15.4/4z, which can provide accurate ranging, position information, and communication capability. The FMCW radar mode can actively detect and model the indoor environment. It covers a wide frequency range from 6-to-11 GHz, which can support Channels 5 to 10 & Channels 11 to 14 according to the UWB protocol. The 1T2R structure supports a variety of UWB positioning/ranging algorithms, including two-way ranging, time-difference-of-arrival (TDoA), phase-difference-of arrival (PDoA), and angle-of-arrival. The UWB mode implements HRP PHY/MAC standards as described in IEEE 802.15.4/4z and supports data-rates of 0.85/6.81/27.24 Mb/s. In addition, in the FMCW mode, the transceiver can be configured as 1T1R or 1T2R, giving it the ability to provide accurate range results and a degree of angle results in a large range. As shown in the right part of the Fig. 1, the FMCW radar mode of the transceiver can cooperate between devices in the UWB mode to perform multi-device joint detection and modeling of the environment for multi-source data-fusion.