Indoor Positioning Using Ultrawideband and Inertial Measurements

Abstract

Abstract-In this work we present an approach to combine measurements from inertial sensors (accelerometers and gyroscopes) with time of arrival measurements from an ultrawideband system for indoor positioning. Our algorithm uses a tightlycoupled sensor fusion approach, where we formulate the problem as a maximum a posteriori problem that is solved using an optimization approach. It is shown to lead to accurate 6D position and orientation estimates when compared to reference data from an independent optical tracking system. To be able to obtain position information from the ultrawideband measurements, it is imperative that accurate estimates of the ultrawideband receivers' positions and their clock offsets are available. Hence, we also present an easy-to-use algorithm to calibrate the ultrawideband system using a maximum likelihood formulation. Throughout this work, the ultrawideband measurements are modeled by a tailored heavy-tailed asymmetric distribution to account for measurement outliers. The heavy-tailed asymmetric distribution works well on experimental data, as shown by analyzing the position estimates obtained using the ultrawideband measurements via a novel multilateration approach.

Multidevice Map-Constrained Fingerprint-Based Indoor Positioning Using 3-D Ray Tracing

“…Obviously, works have reported in literature which achieve fingerprinting accuracy in the sub-meter-range (e.g. UWB [4]- [6], MFI [7], [8]) however they require nonoff-the-shelf and usually expensive equipment.…”

“…Such techniques include Ultra-Wideband (UWB) [4]- [6] or Magnetic Field Intensity (MFI) [7], [8] technologies etc. Because of this, fingerprint-based positioning [9]- [11] which became a popular topic of research over the last decades, still remains an active area of research mainly because of its simplicity and its potential to be applicable using off-the-shelf technologies.…”

Graph-Optimization-Based ZUPT/UWB Fusion Algorithm

“…As a result, multi-sensor data fusion methods have been brought to the fore [1]. Algorithms of this type include the IMU (Inertial Measurement Unit) and wireless positioning techniques such as UWB (Ultra-wideband) [2,3], WiFi [4,5], and Bluetooth [6]. An accurate location can be obtained in the short term through integrating the IMU measurements, but this approach belongs to an incremental positioning system that produces cumulative error.…”

Ultra-Wideband Time of Flight Based Localization System and Odometry Fusion for a Scanning 3 DoF Magnetic Field Autonomous Robot

“…It is considered one of the most promising indoor positioning technologies currently available, especially due to its fine time resolution [8]. UWB time of flight has already captured the researchers attention that combines it with inertial sensors [10]. Unfortunately, the orientation cannot be determined with this approach.…”