# Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation +
## 2 Related Work  
Numerous works have focused on the use of UWB and GNSS for pedestrian positioning and navigation. In particular, with regard to UWB, most of the efforts in recent years have focused on characterizing their performance both indoors and outdoors and also in complex environments [17; 18]. These analyzes have shown that, despite the excellent performance of these systems for indoor positioning, there are however numerous difficulties mainly related to measurement errors related to non-line of sight (NLOS) and multipath conditions. For this reason, many papers have focused on the characterization of measurement errors and on the search for filtering techniques and outlier rejection [19; 20; 21] As for the use of UWBs in conjunction with other technologies, little has been done. [PERSON] et al. [22] describe in their paper an IPS that fuses an UWB positioning system with an IMU sensor-based solution through an ad-hoc extended Kalman filter (EKF) design which coupled tightly the inertial sensors with the measured ranged from the UWB system. Although mainly tested in a simulation environment and designed for 2-dimensional positioning, their proposal demonstrates a significant increase in positioning performances of the hybrid solution with respect to the stand-alone counterpart. [PERSON] et al. [23] present an experimental system which fuse two RF-based solution, an UWB system for accurate 3D positioning and a wireless sensor network (WSN) system that enlarge the coverage areas of the UWB. In this case, the UWB positioning is performed with the time difference of arrival technique (TDOA) while the WSN rely on the weighted centroid localization algorithm in the received signal straight indication (RSSI) value. In this case the 2D accuracy move from 4 m, when the receiver is outside the UWB network, to 10 cm when entered in the UWB subsystem range. [PERSON] and [PERSON] [24] formulate an integration between GNSS and UWB in a particular condition, where both ranges from UWB and from satellites are partially visible, as in the case of an indoor space with windows. Even in this case the aims is to verify the improvement in position estimation accuracy of the integrated solution. [PERSON] et al. [25] combine UWB measurements with inertial measurements to estimate the 6-D pose of a sensor again with a tightly coupled sensor fusion. In this work the major effort was in modelling the UWB measurement errors as a heavy-tailed Cauchy distribution in order to consider NLOS conditions and multipaths. The proposed algorithm reaches centimeter level of accuracy also with data containing a fairly large amount of outliers. [PERSON] et al. [26] analyze the use of UWB-based distance measurements and INS, and provide a hybrid GNSS/UWB/INS sensor fusion strategy for robust seamless indoor/outdoor unmanned aerial vehicle (UAV) navigation while [PERSON] et al. [27] propose a low-cost multi-sensor fusion positioning prototype which integrates GNSS, INS and UWB measurements to test real-time positioning and communication capabilities in assisted driving applications. In these works, several approaches has been applied for data fusion and sensor integration. For example, in the AGAVE (AGV nAvigation system based on flexible and innovatiVE UWB positioning) project [28] statistical error correction and data fusion technique based on Monte Carlo particle filter has been developed in order to integrate different input (odometry, Differential GPS, UWB, gyroscope for bearing and attitude determination) and provide an accurate position estimation of automatic guided vehicles (AGC). Most of the previous works were done in indoor controlled environment. According to our best knowledge, few studies were done applying designed estimation algorithms in seamless conditions, with data acquired continuously during the motion of a pedestrian user from an outdoor space to an indoor environment.