Abstract:
In order to estimate the trajectory of a moving wave source, this trajectory estimation device (10) comprises: an acquisition unit (11) that acquires wave motion data based on wave motion detected by a plurality of sensors (100); a generation unit (12) that generates a spectrogram using the wave motion data; an extraction unit (13) that extracts a Doppler shift from the spectrogram; a selection unit (14) that selects, as a sensor pair, two sensors that satisfy a preset selection condition pertaining to the Doppler shift; and an estimation unit (15) that estimates the trajectory of a wave source, which is the source generating the wave motion, on the basis of the positional relationship between the sensors constituting the sensor pair and the relationship of the Doppler shift between the two sensors constituting the sensor pair.
Abstract:
A trajectory estimation device that includes a waveform generation unit that generates, by using signals based on waves detected by at least three sensors, peak waveforms consisting of time series data of peak frequencies of the signals, a parameter estimation unit that estimates, from the peak waveforms relating to the waves detected by the at least three sensors, a trajectory parameter relating to a trajectory of a moving body having a wave source of the waves, and a trajectory estimation unit that estimates, for all combinations of two of the peak waveforms selected from among combinations of at least three of the peak waveforms, a wave source direction candidate for each of the waves by using the trajectory parameter, and estimate, as a trajectory of the moving body, overlapping trajectory candidates from among trajectory candidates estimated based on the wave source direction candidates.
Abstract:
A wave-source-direction estimation device includes: a plurality of input units that acquires, as input signals, electrical signals based on waves detected by a plurality of sensors; a signal selection unit that selects a plurality of pairs that are each a combination of two input signals from among a plurality of the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves at the sensors that are supply sources of the two input signals composing each of the pairs, for each wave source direction; and an integrated-estimated-direction-information calculation unit that generates per-frequency estimated direction information for each of the pairs using the input signals composing each of the pairs and the relative delay times of each of the pairs and generates integrated estimated direction information by assigning a weight to and integrating the estimated direction information on all the pairs.
Abstract:
A noise suppression apparatus according to the present disclosure includes at least one memory configured to store instructions, and at least one processor configured, by executing the instructions, to input a plurality of noise superimposed signals that are acquired by distributed acoustic sensing (DAS) using an optical fiber cable and on which noise is superimposed, extract a common feature of the plurality of input noise superimposed signals as a noise suppression signal in which noise is suppressed, and output the extracted noise suppression signal.
Abstract:
A wave source direction estimation device includes a signal extraction unit that sequentially extracts, one at a time, signals of signal segments according to a set time length from at least two input signals based on a wave detected at different detection positions, a function generation unit that generates a function associating at least two signals extracted by the signal extraction unit, a sharpness calculation unit that calculates sharpness of a peak of the function generated by the function generation unit, and a time length calculation unit that calculates the time length based on the sharpness and set the calculated time length.
Abstract:
A wave motion signal processing device that includes a spectrum generation unit that generates a first spectrum with high resolution and a second spectrum with low resolution based on an input signal derived from a wave motion detected by at least one sensor, an extraction unit that extracts, from the second spectrum, a first peak satisfying an extraction condition in a target time window, a tracking unit that tracks, in the first spectrum, a second peak satisfying the extraction condition with regard to a time frame following the target time frame from which the first peak is extracted, and a waveform generation unit that generates a peak waveform, which is time-series data of a frequency including a plurality of second peaks, having the first peak as a starting end.
Abstract:
A wave-source-direction estimation device includes: input units that acquire, as input signals, electrical signals that have been converted from waves acquired by sensors; a signal selection unit that selects at least two pairs that are each a combination of at least two input signals from among the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves for each wave source searching direction between the at least two input signals composing one of the pairs of the input signals; at least one per-frequency estimated-direction-information generation unit that uses the pairs of the input signals and the relative delay times to generate estimated direction information on a wave source of the waves for each frequency; and an integration unit that integrates the estimated direction information generated for each frequency by the per-frequency estimated-direction-information generation unit.
Abstract:
A vibration source estimation device, method and computer-readable medium are provided. The vibration source estimation device comprises a processor configured to execute instructions to receive data samples of a plurality of vibration signals generated at a vibration position, the data samples being associated with a plurality of frames. The processor is also configured to execute instructions to calculate a cross correlation function for each frame based on the data samples, calculate a weight for each frame based on a signal-to-noise ratio calculated from the cross correlation function, multiply the cross correlation function for each frame by the weight, calculate a sum of weighted cross correlation functions for respective frames as a weighted-cross-correlation function, and estimate the vibration position based on the weighted-cross-correlation function.