Future Research and Trends in Ultra-Wideband Indoor Tag Localization

Abstract

Indoor tag localization technology is one area of research applied to positioning, tracking, and navigation. UWB is a signal that is widely used for indoor tag localization with the consideration of having higher accuracy, wide bandwidth, and low power consumption. The diversity and breadth of research in the field of indoor tag localization can be confusing for new researchers to find out how this research has progressed until this day. The use of other sensors besides UWB in indoor tag localization is an alternative solution offered, thus obscuring the trend of UWB research on indoor tag localization. The way to find out whether indoor tag localization research using UWB still has a good trend and has research opportunities is to read paper reviews from previous researchers. However, until now no one has reviewed the previous paper review using the SMS and SLR methods. The SMS method is quantitative which directs the paper collection to the intended research area so it can be mapped properly. SMS is the process of identifying, categorizing, and analyzing existing literature that is relevant to a certain research topic. Meanwhile, the SLR method is qualitative which makes paper discussions sharper and more focused. SLR is the process of collecting and critically analyzing multiple research studies or papers through a systematic process. It aims to synthesize the findings of the studies and conclude the state of the art on the topic. This paper describes the literacy results of the paper using the SMS and SLR methods to thoroughly discuss research developments on UWB indoor tag localization. The discussion includes research developments and topic areas of indoor tag localization from 2017-2022, trends in the use of UWB in indoor tag localization research, issues and metrics that are carried out in indoor tag localization research, and opportunities for future research. Literacy results show that machine learning, filtering, and sensor fusion are topic areas that are currently being researched on UWB indoor tag localization. In general, every research optimizes performance metrics, namely accuracy, scalability, energy efficiency, latency, cost, and complexity. Each optimized metric related to different issues will be represented in the form of a taxonomy for easy understanding and explained in detail in this paper. Several future promising research opportunities are described in this paper to provide insight to other researchers to dig deeper into this research field.