  Indoor positioning is one of the core technologies of Internet of Things
(IoT) and artificial intelligence (AI), and is expected to play a significant
role in the upcoming era of AI. However, affected by the complexity of indoor
environments, it is still highly challenging to achieve continuous and reliable
indoor positioning. Currently, 5G cellular networks are being deployed
worldwide, the new technologies of which have brought the approaches for
improving the performance of wireless indoor positioning. In this paper, we
investigate the indoor positioning under the 5G new radio (NR), which has been
standardized and being commercially operated in massive markets. Specifically,
a solution is proposed and a software defined receiver (SDR) is developed for
indoor positioning. With our SDR indoor positioning system, the 5G NR signals
are firstly sampled by universal software radio peripheral (USRP), and then,
coarse synchronization is achieved via detecting the start of the
synchronization signal block (SSB). Then, with the assistance of the pilots
transmitted on the physical broadcasting channel (PBCH), multipath acquisition
and delay tracking are sequentially carried out to estimate the time of arrival
(ToA) of received signals. Furthermore, to improve the ToA ranging accuracy,
the carrier phase of the first arrived path is estimated. Finally, to quantify
the accuracy of our ToA estimation method, indoor field tests are carried out
in an office environment, where a 5G NR base station (known as gNB) is
installed for commercial use. Our test results show that, in the static test
scenarios, the ToA accuracy measured by the 1-{\sigma} error interval is about
0.5 m, while in the pedestrian mobile environment, the probability of range
accuracy within 0.8 m is 95%.
