Sparsity in array processing: methods and performances

Remy Boyer (1) , Pascal Larzabal (2)

1 L2S - Laboratoire des signaux et systèmes
2 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie

In the last few years, we witnessed to an extraordinary and still growing development of sparse signal recovery in a wide number of applicative contexts such as communications, biomedicine, radar, microwave imaging, source localization, astronomy, seismology... In many realistic array processing applications, the sparsity nature underlying various signals/arrays has to be exploit in recovery algorithms to enhance their performances. In this special session, most recent results in estimators based on sparsity-­‐promoting criteria is proposed.

Domains: Engineering Sciences [physics]; Statistics [stat]

Remy Boyer, Pascal Larzabal. Sparsity in array processing: methods and performances . IEEE Sensor Array and Multichannel signal processing workshop - SAM 2013, Nov 2013, Coruna, Spain. ⟨hal-01247024⟩