An aspect of the invention is directed to a system of both atmospheric and underwater sensors for measuring pressure waves from a noise source. A system of pressure sensors can be formed to determine the location of an external noise source, whether in air or underwater. The system includes at least two arrays consisting of pressure sensors, including at least one atmospheric pressure sensor and at least one underwater pressure sensor, such as a hydrophone. Each sensor may be a seven-fiber intensity modulated fiber optic pressure sensor. The system includes an analog to digital converter for digitizing the pressure data received from each sensor and a processor which processes the received signals to calculate an approximate location of the noise source based upon the pressure signals received by the sensors at different times of arrival. The system can provide this capability in remote applications due to its low power requirements.

The interactive aircraft cabin environment control system employs at least one microphone array disposed within the cabin to capture spoken utterances from a passenger and is configured to provide an estimation of passenger location within the cabin based on arrival time analysis of the spoken utterances. A data source onboard the aircraft provides flight context information. Such data sources include sensors measuring real-time parameters on the aircraft, the current flight plan of the aircraft, singly and in combination. A control processor, coupled to the microphone array, is configured to ascertain passenger identity based on the spoken utterances. The control processor is programmed and configured to learn and associate passenger preference to passenger identity. The control processor is receptive of the estimation of passenger location and is coupled to provide supervisory control over at least one device forming a part of the cabin environment according to passenger location, passenger preference obtained from passenger identity and flight context information.

A directional receiver system may include a receiver, a plurality of receive antenna elements, and a circuit. The receiver may include an input port and an output. The plurality of receive antenna elements may be fixedly configured into a known geometric relationship to each other, and each of the receive antenna elements may be connected to the input port of the receiver. The circuit may be coupled to the output of the receiver, configured to determine time differences at which signals from a source are incident upon the antenna elements, and configured to determine an angular orientation of the source to the receive antenna elements based on the time differences.

Sounds arriving from outside of a mobile body are collected by a microphone disposed inside the mobile body. A sound collecting apparatus according to the present disclosure is attached to the mobile body. The sound collecting apparatus according to the present disclosure includes a microphone that is directly or indirectly in contact with an outer face member, which is a member forming an outer face of the mobile body, from an inner side of the mobile body and collects sounds propagating through the outer face member. In a case where the microphone has directivity, the microphone is disposed in a direction in which sounds propagating from the outer face of the outer face member to the inner side are collected. The outer face member is, for example, glass.

In an embodiment, a method includes: receiving ambient sound; determining if the ambient sound includes a siren; in accordance with determining that the ambient sound includes a siren, determining a first location associated with the siren; receiving a camera image; determining if the camera image includes a flashing light; in accordance with determining that the camera image includes a flashing light, determining a second location associated with the flashing light; 3D data; determining if the 3D data includes an object; in accordance with determining that the 3D data includes an object, determining a third location associated with the object; determining a presence of an emergency vehicle based on the siren, detected flashing light and detected object; determining an estimated location of the emergency vehicle based on the first, second and third locations; and initiating an action related to the vehicle based on the determined presence and location.

A method and system for generating a target map for training a neural network and obtaining a sound source map regardless of the maximum number of sound sources, having a short computation time for inference, high spatial resolution and high sound source accuracy. The method includes generating grids each having a spacing within a given range at positions where sound sources are present in order to form a sound source map, calculating a result value for each of coordinates of the grids so that the result value is a local maximum at the position of a sound source and the result value decreases depending on the distance from the sound source, arranging the result values at positions on matrices corresponding to the respective coordinates of the grids, and generating a target map having an image form by using the result values arranged in on the matrices.

A sound detector system has one or more microphone positioned with a field of regard of 360°. The system further has a processor to translate a sound into data indicative of a direction and transmit the data indicative of direction. Additionally, the system has a handheld device configured to wirelessly receive the data indicative of the direction and display data identifying the field of direction to a user.

Method of detecting and tracking an unmanned aerial vehicle, the method comprising, at a detector unit (300a) comprising a first microphone and a second microphone: monitoring for a sound associated with the presence of the unmanned aerial vehicle (505) in the vicinity of the detector unit; in response to the monitoring indicating the presence of the unmanned aerial vehicle, determining, at the detector unit, a phase delay between the sound as received at the first microphone and the sound as received at the second microphone; on the basis of the determined phase delay and a known separation of the first microphone and the second microphone, determining, at the detector unit, an azimuth angle (507a) to the unmanned aerial vehicle from the detector unit; and transmitting, to a computing node (501), the determined azimuth angle for use in determining a location of the unmanned aerial vehicle.

A device estimates direction of arrival (DOA) of sound from sound sources received by P microphones, wherein P≥>1. The device is configured to transform the output signals of the microphones into the frequency domain and compute a covariance matrix for each of N frequency bins in a range of frequencies of the sound. Further, the device is configured to calculate an adapted covariance matrix from each of the covariance matrices for wide-band merging, calculate an accumulated covariance matrix from the N adapted covariance matrices, and estimate the DOA for each of the sound sources based on the accumulated covariance matrix. In order to calculate an adapted covariance matrix from a covariance matrix, the device is configured to spectrally decompose the covariance matrix and obtain a plurality of eigenvectors, rotate each obtained eigenvector, and construct each rotated eigenvector back to the shape of the covariance matrix.

The systems, devices, and processes described herein may identify a beam of a voice-controlled device that is directed toward a reflective surface, such as a wall. The beams may be created by a beamformer. An acoustic echo canceller (AEC) may create filter coefficients for a reference sound. The filter coefficients may be analyzed to identify beams that include multiple peaks. The multiple peaks may indicate presence of one or more reflective surfaces. Using the amplitude and the time delay between the peaks, the device may determine that it is close to a reflective surface in a direction of the beam.