Apparatuses and methods are described herein for identifying an Unmanned Aerial Vehicle (UAV) by a central server connected to a first detection device and a plurality of detection devices, including, but not limited to, receiving, by the central server, information related to the UAV from the first detection device, selecting, by the central server, a second detection device from a plurality of detection devices connected to the central server, and sending, by the central server, the information to the second detection device.

Apparatuses and methods are described herein for identifying an Unmanned Aerial Vehicle (UAV) by a central server connected to a first detection device and a plurality of detection devices, including, but not limited to, receiving, by the central server, information related to the UAV from the first detection device, selecting, by the central server, a second detection device from a plurality of detection devices connected to the central server, and sending, by the central server, the information to the second detection device.

An image processing apparatus includes a first reception section, a second reception section, an association processing section, an object detection section, and a process execution section. The first reception section receives image information acquired by an image sensor. The second reception section receives sound information that is acquired by one or plural directional microphones and that is generated for at least a partial region in a field of the image sensor. The association processing section associates the sound information with a pixel address of the image information indicating a position in the field. The object detection section detects, from the image information, at least a part of an object that is present in the field. The process execution section executes a predetermined process on the object on the basis of a result of the association performed by the association processing section.

Techniques, systems, architectures, and methods for estimating the time difference of arrival (TDOA) based on a joint-optimization formulation, the method comprising providing at least two noisy signals, y1 and y2, where the signals are measured across different antenna elements and where one signal is a delayed amplitude, scaled version of the other signal; and estimating the TDOA using an optimization formulation.

Techniques, systems, architectures, and methods for estimating the time difference of arrival (TDOA) based on a joint-optimization formulation, the method comprising providing at least two noisy signals, y1 and y2, where the signals are measured across different antenna elements and where one signal is a delayed amplitude, scaled version of the other signal; and estimating the TDOA using an optimization formulation.

Apparatuses and methods are described for determining displacement and/or rotation of a Unmanned Aerial Vehicle (UAV), including, but not limited to, determining a first Time of Flight (ToF) for audio signals transmitted by an audio transmitter of the UAV and received by a first audio receiver of the UAV while the UAV is in motion, determining a second ToF for the audio signals transmitted by the audio transmitter and received by a second audio receiver of the UAV while the UAV is in motion, and determining the displacement or the rotation of the UAV based, at least in part, on the first ToF and the second ToF.

Apparatuses and methods are described for determining displacement and/or rotation of a Unmanned Aerial Vehicle (UAV), including, but not limited to, determining a first Time of Flight (ToF) for audio signals transmitted by an audio transmitter of the UAV and received by a first audio receiver of the UAV while the UAV is in motion, determining a second ToF for the audio signals transmitted by the audio transmitter and received by a second audio receiver of the UAV while the UAV is in motion, and determining the displacement or the rotation of the UAV based, at least in part, on the first ToF and the second ToF.

A system is described that comprises a plurality of sensor nodes and at least one remote server, wherein each sensor node of the plurality of sensor nodes and the at least one remote server are communicatively coupled, wherein the plurality of sensor nodes receive at least one acoustic signal, process the at least one acoustic signal to detect one or more transient events, classify the one or more transient events as an event type, and determine geometry information and timing information of the one or more transient events. The system comprises at least one of the plurality of sensor nodes and the at least one remote server identifying the source of the one or more transient events.

A system is described that comprises a plurality of sensor nodes and at least one remote server, wherein each sensor node of the plurality of sensor nodes and the at least one remote server are communicatively coupled, wherein the plurality of sensor nodes receive at least one acoustic signal, process the at least one acoustic signal to detect one or more transient events, classify the one or more transient events as an event type, and determine geometry information and timing information of the one or more transient events. The system comprises at least one of the plurality of sensor nodes and the at least one remote server identifying the source of the one or more transient events.

A method for locating a mobile device is disclosed. Initially, a set of modulated ultrasound signals and a set of radio signals are separately broadcast from a group of transmitters. The ultrasound signals include at least one symbol configured for pulse compression. After the receipt of a demodulated ultrasound signal from a mobile device, wherein the demodulated ultrasound signal is derived from the modulated ultrasound signals, transmitter identifier and timing information are extracted from the demodulated ultrasound signal. Timing information include, for example, the arrival time of the demodulated ultrasound signal in relation to the start time of its transmission. After the locations of the transmitters have been ascertained from the transmitter identifier information, the location of the mobile device can be determined based on the timing information and the locations of the transmitters.