METHOD FOR DETECTING A DIRECTION OF ARRIVAL OF AN ACOUSTIC TARGET SIGNAL

• Main Authors: BOUCHARD, Martin, ALTAMIMI, Sa'di
• Format: Patent
• Language: English; French; German
• Published: 21.08.2024
• Subjects: ANALOGOUS ARRANGEMENTS USING OTHER WAVES; DEAF-AID SETS; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES; LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKEACOUSTIC ELECTROMECHANICAL TRANSDUCERS; MEASURING; PHYSICS; PUBLIC ADDRESS SYSTEMS; RADIO DIRECTION-FINDING; RADIO NAVIGATION; TESTING

The invention discloses a method for detecting a direction of arrival (α) of an acoustic target signal (14) by means of a plurality of microphones (ML1, ML2, MR1, MR2), said microphones (ML1, ML2, MR1, MR2) being distributed over a local device (LD) and a remote device (RD), said local device (LD) comprising at least a first local microphone (ML1) and a second local microphone (ML2), and said remote device (RD) comprising at least a first remote microphone (MR1), each of said microphones (ML1, ML2, MR1, MR2) configured to generate a corresponding microphone signal (xML1, xML2, xMR1, xMR2) from an environment sound (16), respectively, the method comprising the steps of: deriving a first local input signal (Loci ) by means of the first local microphone signal (xML1) and the second local microphone signal (xML2), deriving a second local input signal (Loc2) by means of the first local microphone signal (xML1) and/or the second local microphone signal (xML2), and deriving a first remote input signal (Rem1) by means of at least the first remote microphone signal (xMR1), said first and second local input signal (Loc1, Loc2) and first remote input signal (Rem1) forming a part of a set (18) of input signals, deriving a plurality of spatial feature quantities (Q1, Q2), said spatial feature quantities (Q1, Q2) each being derived from different respective pairs out of the set (18) of input signals, and being indicative of a spatial relation between the two corresponding input signals, using said spatial feature quantities (Q1, Q2) as an input to a neural network (20), and estimating, by means of said neural network (20), the direction of arrival (α) of said acoustic target signal (14).