title: Generating nonstationary multisensor signals under a spatial coherence constraint.
abstract: Noise fields encountered in real-life scenarios can often be approximated as spherical or cylindrical noise fields. The characteristics of the noise field can be described by a spatial coherence function. For simulation purposes, researchers in the signal processing community often require sensor signals that exhibit a specific spatial coherence function. In addition, they often require a specific type of noise such as temporally correlated noise, babble speech that comprises a mixture of mutually independent speech fragments, or factory noise. Existing algorithms are unable to generate sensor signals such as babble speech and factory noise observed in an arbitrary noise field. In this paper an efficient algorithm is developed that generates multisensor signals under a predefined spatial coherence constraint. The benefit of the developed algorithm is twofold. Firstly, there are no restrictions on the spatial coherence function. Secondly, to generate M sensor signals the algorithm requires only M mutually independent noise signals. The performance evaluation shows that the developed algorithm is able to generate a more accurate spatial coherence between the generated sensor signals compared to the so-called image method that is frequently used in the signal processing community.
authors.affiliation: School of Engineering, Bar-Ilan University, Ramat-Gan 52900, Israel. e.habets@ieee.org
authors.forename: Emanuël A P
authors.initials: EA
authors.lastname: Habets
authors.forename: Israel
authors.initials: I
authors.lastname: Cohen
authors.forename: Sharon
authors.initials: S
authors.lastname: Gannot
mesh_terms: D000162:Acoustics; D000465:Algorithms; D006801:Humans; D009622:Noise; D009623:Noise, Occupational; D012815:Signal Processing, Computer-Assisted; D015398:Signal Transduction; D013028:Space Perception; D013060:Speech