# Analysis of Dual-Band Direction of Arrival Estimation in Multipath Scenarios
## 1 Introduction  
Indoor localization represents an enabling technology for a wide range of applications where it is necessary to contextualize the position of people, objects and/or vehicles such as Unmanned Ground Vehicles (UGV), in real complex indoor environments. With special reference to logistic scenarios including UGVs, the interaction between the latter and the indoor positioning system may be related to supply UGV requirements in terms of operating environment awareness or support for high-precision autonomous driving [1].  
Moreover, it is a matter of fact that Internet of Things (IoT) paradigm can benefit from localization in many applications [2]. Indoor localization will be a key focus also in 5 th generation mobile (5G) [3], which will take advantage of the inherently use of massive Multiple Input Multiple Output (MIMO) technology.  
In recent years, several studies have been carried out on localization techniques and methodologies, with the common aim of achieving improvements in positional accuracy as well as infrastructure simplifications. It is well known that these objectives are extremely difficult to achieve at the same time. Nevertheless, recent works have proposed solutions to overcome this issue. Specifically, some approaches compensate the lower complexity of the implemented infrastructure with solutions characterized by a higher computational cost enabling accuracy enhancements such as in [4], where likelihood functions are implemented in machine learning (ML) algorithms. Localization methods based on ML are discussed also in [5, 6, 7], where in the latter such algorithm is applied to a WiFi dual-band-basedposition system. In this context, processing solutions that can extract the location estimate in the case of limited data availability have also been investigated, as described in [8]. In such approach the localization is computed according to statistical methods based on Gibbs sampling of a mobility model. On the contrary, in [9; 10], the authors discuss the use of Switched Beam Antennas to achieve lower infrastructural complexity and more compact nodes.  
There is no doubt that all these approaches have contributed to a progressive improvement in terms of localization accuracy. However, in many real-world application scenarios, the presence of very severe multi-path phenomena may limit these enhancements. To mitigate these effects, specific multi-path-oriented techniques have been proposed. Some of these methods involve multi-path modeling in the localization algorithm with the disadvantage of increased computational overhead. In this regard, some ML techniques including multi-path models are described in [11; 12], while [13] proposes a localization system based on Angle of Arrival technique assisted by an algorithm used to elaborate multi-path information relying on the image method. With the aim of preferring a simplified infrastructure, also [14] discusses about the exploitation of multi-path signals estimated using JADE algorithm to improve the positioning accuracy using a single receiver. Conversely, other methods prefer to implement a more robust hardware infrastructure against multi-path phenomena, but with the disadvantage of a more complex positioning system. In such context, ref [15] describes a multi-path mitigation method using MIMO beamforming scheme.  
Mitigation of adverse effects caused by multi-path is a very challenging problem in all the localization techniques. All the papers cited in this section suggest approaches to attenuate the problem related to this important issue affecting the application in real scenarios. In the present paper, the authors propose an analysis method aimed at fully exploiting the capability of dual-band DoA approach as suggested by [16].