# Heading Estimation Using Ultra-Wideband Received Signal Strength and Gaussian Processes

arXiv: https://arxiv.org/abs/2109.04868 · HTML: https://mlsanity.com/paper/2109.04868/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 18 references that are in the map.
- First posted on arXiv 10 Sep 2021.

## Builds on (most cited first, 4 of 4)

- [A micro Lie theory for state estimation in robotics](https://mlsanity.com/paper/1812.01537/) (2018)
- [The invariant extended Kalman filter as a stable observer](https://mlsanity.com/paper/1410.1465/) (2014)
- [Kernel Methods for Accurate UWB-Based Ranging with Reduced Complexity](https://mlsanity.com/paper/1511.04045/) (2015)
- [Impact of 3D UWB Antenna Radiation Pattern on Air-to-Ground Drone Connectivity](https://mlsanity.com/paper/1810.01442/) (2018)

## Abstract (arXiv)

It is essential that a robot has the ability to determine its position and orientation to execute tasks autonomously. Heading estimation is especially challenging in indoor environments where magnetic distortions make magnetometer-based heading estimation difficult. Ultra-wideband (UWB) transceivers are common in indoor localization problems. This letter experimentally demonstrates how to use UWB range and received signal strength (RSS) measurements to estimate robot heading. The RSS of a UWB antenna varies with its orientation. As such, a Gaussian process (GP) is used to learn a data-driven relationship from UWB range and RSS inputs to orientation outputs. Combined with a gyroscope in an invariant extended Kalman filter, this realizes a heading estimation method that uses only UWB and gyroscope measurements.