Matrix recovery from bilinear and quadratic measurements

Co-authors

Michalina Pacholska, Karen Adam and Martin Vetterli.


Downloads

Full text: arXiv.
Cite: Bibtex.


Abstract

Matrix (or operator) recovery from linear measurements is a well studied problem. However, there are situations where only bi-linear or quadratic measurements are available. A bi-linear or quadratic problem can be easily transformed to a linear one, but it raises questions when the linearized problem is solvable and what is the cost of linearization. 
In this work, we study a few

Relax and Recover: Guaranteed Range-Only Continuous Localization

Co-authors

Michalina Pacholska and Frederike Dümbgen.


Downloads

Full text: View at publisher.
Cite: Bibtex.
Code: GitHub.


Abstract

Range-only localization has applications as diverse as underwater navigation, drone tracking and indoor localization. While the theoretical foundations of lateration—range-only localization for static points—are well understood, there is a lack of understanding when it comes to localizing a moving device. As most interesting applications in robotics involve moving objects, we study the theory of trajectory recovery. This problem

Multi-Modal Probabilistic Indoor Localization on a Smartphone

Co-authors

Frederike Dümbgen, Cynthia Oeschger, Mihailo Kolundzija, Emmanuel Girardin, Johan Leuenberger and Serge Ayer.


Downloads

Full text: View at publisher.


Abstract

The satellite-based Global Positioning System (GPS) provides robust localization on smartphones outdoors. In indoor en- vironments, however, no system is close to achieving a similar level of ubiquity, with existing solutions offering different trade-offs in terms of accuracy, robustness and cost.

In this paper, we develop a multi-modal positioning system, targeted at smartphones, which

Bound and conquer: Improving triangulation by enforcing consistency

Co-authors

Alireza Ghasemi and Martin Vetterli.


Downloads

Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Code ocean.


Abstract

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction error decays quadratically as more cameras are added to the system. Furthermore, we analyse the error decay-rate of major state-of-the-art algorithms with

Combining Range and Direction for Improved Localization

Co-authors

Gilles Baechler, Frederike Dümbgen, Golnoosh Elhami, Miranda Krekovic, Robin Scheibler and Martin Vetterli.


Downloads

Full text: Infoscience.
Cite: Bibtex.
Code: GitHub.


Abstract

Self-localization of nodes in a sensor network is typically achieved using either range or direction measurements; in this paper, we show that a constructive combination of both improves the estimation. We propose two localization algorithms that make use of the differences between the sensors’

Site Footer