Vice-Chancellor gets Sustained Impact Award

Mats Viberg

BTH’s Vice-Chancellor Mats Viberg is rewarded the International Association of IEEE for his article “Two Decades of Array Signal Processing Research: The Parametric Approach”. The prize is awarded for the impact the article has had on developments in the research area.

At a prize ceremony that was broadcast last week, and thus could be followed by the whole world, Vice-Chancellor Mats Viberg received an award for his article with the motivation “Sustained Impact Award”, that is, the article has had a major impact on the development in the specific research area. It is the international association IEEE, the Institute of Electrical and Electronics Engineers, that is behind the award..

The article, published in 1996, is an overview article in the field of array signal processing. An “array” here is a number of sensors that collect data on some phenomenon in the environment, and the signal processing is about extracting information from this data.

Mats Viberg has worked extensively with applications in radar and mobile communication, where the sensors are electromagnetic antennas.

“Within radar, it can be about separating very close targets – closer than the so-called Fourier resolution allows, and in mobile communication a receiver antenna equipped with antenna arrays can distinguish and simultaneously decode signals from several users on the same channel. In this way, the capacity of the communication system can be significantly increased”, explains Mats Viberg.

The article has often been used to introduce new researchers to the subject and it has become a standard reference. According to Google Scholar, it has so far collected over 4400 citations.

In new mobile systems, so-called MIMO (Multiple Input Multiple Output) technology has become a standard and in the coming 5G it is a key component. In addition to a number of direct applications (including SONAR, microphone arrays, seismic sensors, etc.), array signal processing addresses a generic statistical estimation problem in signal processing, which emerges in many applications that do not directly deal with sensor arrays.

One such area of ​​application that has received extremely high attention over the last 10+ years is “Compressive Sensing”, which is about collecting data in a compressed manner, with a data rate and thus cost that is far lower than previously thought possible.

Link to the article

14 May 2020