166 results about "Source localization" patented technology

A method of signal processing includes calculating a range based on information from a reflected ultrasonic signal. Based on the calculated range, one among a plurality of direction-of-arrival (DOA) estimation operations is selected. The method also includes performing the selected operation to calculate an estimated direction of arrival (DOA) of an audio-frequency component of a multichannel signal. Examples of DOA estimation operations include operations based on phase differences between channels of the multichannel signal and operations based on a difference in gain between signals that are based on channels of the multichannel signal.

Multiple Holocam Orbs observe a real-life environment and generate an artificial reality representation of the real-life environment. Depth image data is cleansed of error due to LED shadow by identifying the edge of a foreground object in an (near infrared light) intensity image, identifying an edge in a depth image, and taking the difference between the start of both edges. Depth data error due to parallax is identified noting when associated text data in a given pixel row that is progressing in a given row direction (left-to-right or right-to-left) reverses order. Sound sources are identified by comparing results of a blind audio source localization algorithm, with the spatial 3D model provided by the Holocam Orb. Sound sources that corresponding to identifying 3D objects are associated together. Additionally, types of data supported by a standard movie data container, such as an MPEG container, is expanding to incorporate free viewpoint data (FVD) model data. This is done by inserting FVD data of different individual 3D objects at different sample rates into a single video stream. Each 3D object is separately identified by a separately assigned ID.

Systems and methods are provided to create an acoustic map of a space containing multiple acoustic sources. Source localization and separation takes place by sampling an ultra large microphone array containing over 1020 microphones. The space is divided into a plurality of masks, wherein each masks represents a pass region and a complementary rejection region. Each mask is associated with a subset of microphones and beamforming filters that maximize a gain for signals coming from the pass region of the mask and minimizes the gain for signals from the complementary region according to an optimization criterion. The optimization criterion may be a minimization of a performance function for the beamforming filters. The performance function is preferably a convex function. A processor provides a scan applying the plurality of masks to locate a target source. Processor based systems to perform the optimization are also provided.

A method of signal processing includes calculating a range based on information from a reflected ultrasonic signal. Based on the calculated range, one among a plurality of direction-of-arrival (DOA) estimation operations is selected. The method also includes performing the selected operation to calculate an estimated direction of arrival (DOA) of an audio-frequency component of a multichannel signal. Examples of DOA estimation operations include operations based on phase differences between channels of the multichannel signal and operations based on a difference in gain between signals that are based on channels of the multichannel signal.

Systems and methods are provided for source localization and separation by sampling a large scale microphone array asynchronously to simulate a smaller size but moving microphone array. Signals that arrive from different angles at the array are shifted differently in their frequency content. The sources are separated by evaluating correlated and even equal frequency content. Compressive sampling enables the utilization of extremely large scale microphone arrays by reducing the computational effort orders of magnitude in comparison to standard synchronous sampling approaches. Processor based systems to perform the source separation methods are also provided.

Methods, systems and computer readable media for reconstruction of target locations and amplitudes from signals received from one or more real targets in a space are provided, wherein the signals are at least one of signals received from the near-field and broadband signals. The space is modeled as a region of interest, and an array manifold matrix is calculated from signals received from hypothetical targets in the region of interest. One or more signal vectors received from the one or more real targets are reshaped into a data vector. A hypothetical target configuration is identified that, when applied to a signal model comprising the array manifold matrix, matches the data vector, a reconstruction vector is calculated. The reconstruction vector is reshaped into a reconstructed representation of the real targets in the space, and at least one of outputting the reconstructed representation for viewing by a user, and storing the reconstructed representation for later use are performed.

The invention discloses a voice separation method based on binaural sound source localization. Multiple sound sources are separated through data training, multiple-sound-source localization and voice separation according to sound source directions, and a separation voice of each sound source is obtained. The voice separation method can simulate the auditory sense of human ears based on the cocktail party effect of the human ears, the number of the sound sources and the directions of the sound sources can be accurately located, and an accurate mixed matrix is obtained through the information of the located sound source directions. Thus, the voice separation process is conducted, and the separation performance of the voice separation method is effectively improved.

The invention discloses a location information field-based radiation source localization algorithm. The location information field-based radiation source localization algorithm comprises the following steps that: first step, correlation processing is performed on time segments of acquired data so as to extract time difference of arrival (TDOA) information; second step, grid points are arranged in an area; third step, a cost function is constructed, and the values of the cost function at each grid point in the rectangular area are solved; and fourth step, and a point where the value of the cost function is maximum in the area is selected as a target location. With the location information field-based radiation source localization algorithm of the invention adopted, limitations of the performance of an existing multi-station passive detection localization system can be eliminated, and fast and accurate localization of a target can be realized under non-vision-shared and multiple-target situations.

A system and method for determining the shielding thickness of a detected radiation source. The gamma ray spectrum of a radiation detector is utilized to estimate the shielding between the detector and the radiation source. The determination of the shielding may be used to adjust the information from known source-localization techniques to provide improved performance and accuracy of locating the source of radiation.

A method of signal processing includes calculating a range based on information from a reflected ultrasonic signal. Based on the calculated range, one among a plurality of direction-of-arrival (DOA) estimation operations is selected. The method also includes performing the selected operation to calculate an estimated direction of arrival (DOA) of an audio-frequency component of a multichannel signal. Examples of DOA estimation operations include operations based on phase differences between channels of the multichannel signal and operations based on a difference in gain between signals that are based on channels of the multichannel signal.

A method for measuring pollution that includes providing a plurality of analyte sensors arranged in a grid over a sensing area, wherein the analyte sensors measure a pollutant, and positioning at least one current sensor in the sensing area. A pollution source is localized using a pollution source locator including a dispersion model and at least one hardware processor to interpolate a location of a pollution source from variations in current measured from the current sensors and measurements of pollutants from the analyte sensors.

A method for localizing the source of air pollution that includes receiving pollution data from a network in communication with at least one air pollution sensor that is connected to at least one motor vehicle in a stationary position. Each stationary motor vehicle of the network is positioned at a different air pollution measurement location. The method may further include determining from the pollution data an origin of an air pollutant using an air pollution model provided by a pollutant source localization device including at least one hardware processor.

The invention relates to a bispectrum weighted spatial correlation matrix-based speech sound source localization method. The objective of the invention is to solve problems in microphone array-based robust sound source localization in an actual complex noise environment. According to the method, the special mathematical properties of speech signals and noise signals received by a microphone array on a bispectrum domain are utilized. The method includes the following steps that: framing and bispectrum estimation are performed on signals acquired by the microphone array; on the bispectrum domain, the bispectrum phase difference of each microphone and a reference microphone is calculated; the signals of the reference microphone are adopted to estimate bispectrum unit weight; a bispectrum weighted spatial correlation matrix corresponding to a candidate direction is calculated according to the bispectrum phase difference and the bispectrum unit weight; a sound source direction cost function for a current candidate direction is calculated based on the eigenvalue of the bispectrum weighted spatial correlation matrix; and the direction of a speech sound source is estimated according to a direction corresponding to the maximum value of the sound source direction cost function.

Multiple Holocam Orbs observe a real-life environment and generate an artificial reality representation of the real-life environment. Depth image data is cleansed of error due to LED shadow by identifying the edge of a foreground object in an (near infrared light) intensity image, identifying an edge in a depth image, and taking the difference between the start of both edges. Depth data error due to parallax is identified noting when associated text data in a given pixel row that is progressing in a given row direction (left-to-right or right-to-left) reverses order. Sound sources are identified by comparing results of a blind audio source localization algorithm, with the spatial 3D model provided by the Holocam Orb. Sound sources that corresponding to identifying 3D objects are associated together. Additionally, types of data supported by a standard movie data container, such as an MPEG container, is expanding to incorporate free viewpoint data (FVD) model data. This is done by inserting FVD data of different individual 3D objects at different sample rates into a single video stream. Each 3D object is separately identified by a separately assigned ID.

A method for object tracking is presented based on the similarity of waveforms recorded at the receiving elements of the array. A rectangular array of acoustic transducers is divided into four quadrants, on the basis that each quadrant contains a receiving element in its center. Each of the four recorded waveforms are compared against each of the remaining waveforms to identify either absolute similarity of the signal characteristics, which would denote absence of the object, or identifying a waveform being the least similar from the rest, hence pointing to a part of the array above which the object is located. Further, source localization algorithms are used for ill-posed scenarios where the distance between receivers is on the same order of magnitude of the dimensions of the tracked object and of the tracking distances.

A method of separating and localizing sources of traveling waves, by obtaining linearly independent time-differentiated instantaneous observations of the sources, from spatial derivatives of the traveling wave acquired using a distributed sensor or a sensor array. The sources are blindly separated by direct application of (static) independent component analysis on the time-differentiated observations, yielding both the sources and their direction cosines relative to the sensor geometry. The method is suited for arrays of small aperture, with dimensions shorter than the coherence length of the waves. In one preferred embodiment, three sources are separated and localized from differential observations on four coplanar sensors positioned on the corners of a square. Applications include miniature microphone arrays for intelligent hearing aids with adaptive suppression of interfering signals and nonstationary noise, and integrated RF arrays for resolving or localizing multiple users or channels from a base station or mobile unit.

A system and method for determining a probability of the location of an illicit radiation source within an environment based on directional detectors. An embodiment includes a plurality of directional radiation detectors distributed about the environment and integrated with a processing unit adapted to determine the probability of the source location based on the radiation count data received from the plurality of detectors. The processing unit is further adapted to output information indicative of the location of the radiation source within the environment.

The invention relates to a radar signal feature extraction method based on residual depth learning. With a designed residual depth learning network, deep-level feature extraction is carried out on a radar radiation source signal in a complex electromagnetic environment. The method is implemented as follows: parameters of the residual depth network are trained by using the existing radar data in adatabase; the intercepted data are sent to the input terminal of the residual depth network and results are outputted after mapping of multiple hidden layers, wherein the outputted results are used asthe depth features of the pulse string; with a clustering method, the obtained depth features are clustered, and the correlation degree of each two radiation sources after clustering is calculated and processed according to a correlation criterion; and then the parameter of each radiation source after fusion is calculated and sorting is completed. Therefore, the depth features among data can be dug; the sorting precision is high; and the radar signal feature extraction method can be applied to fields of target reconnaissance and interference source localization.

The invention relates to a fluctuation source localization method of multi-loop oscillation of a novel process industry. According to the method, a frequency domain independent component analysis (ICA) is employed to carry out independent component decomposition on industry historical process data; a variable quantity that plays a leading role in fluctuation oscillation and a dominant frequency can be screened; a local directed coherence analysis is carried out on the screened data; and a cause-and-effect relationship graph is used to visually express a cause-and-effect relationship between loop variables, so that a propagation path of a fluctuation interference can be characterized; process priori knowledge is used to simplify the cause-and-effect relationship graph as well as a threshold automatic searching mode is utilized to filter a secondary cause-and-effect relationship branch, so that a main propagation path of fluctuation is obtained and thus a fluctuation source is localized and identified. Compared with the prior art, the technology employed in the invention enables the method to have the following beneficial effects: a signal analysis on a frequency domain is utilized to reveal an essential attribute of oscillation of a multi-loop control system, so that a fluctuation source of the oscillation is determined; and thus, it is beneficial for a factory engineer to carry out follow-up maintenance and repairing work of a fault circuit.

A method for object tracking is presented based on the similarity of waveforms recorded at the receiving elements of the array. A rectangular array of acoustic transducers is divided into four quadrants, on the basis that each quadrant contains a receiving element in its center. Each of the four recorded waveforms are compared against each of the remaining waveforms to identify either absolute similarity of the signal characteristics, which would denote absence of the object, or identifying a waveform being the least similar from the rest, hence pointing to a part of the array above which the object is located. Further, source localization algorithms are used for ill-posed scenarios where the distance between receivers is on the same order of magnitude of the dimensions of the tracked object and of the tracking distances.

The invention discloses a microseismic / acoustic emission source localization method in a complex structure with an empty space. The method comprises the following steps of: the step 1, installing sensors at different positions on a two-dimensional location area; the step 2, recording difference of actual time of receiving P-wave signals generated by an unknown microseismic / acoustic emission sourceby different sensors; the step 3, selecting nodes on the location area, and calculating the difference of theoretical travel time of the P-wave signals generated by the microseismic / acoustic emissionsource and excited at the nodes from the nodes to different sensors; and the step 4, determining the degree of deviation between each node and the unknown microseismic / acoustic emission source according to the actual time difference and the difference of theoretical travel time to determine a node having the smallest deviation from the microseismic / acoustic emission source, and taking the node coordinates as the location coordinates of the microseismic / acoustic emission source.

The described method and system utilize continuous and / or periodic measurement of the fuel pipes to detect leakage of fuel. In general, the piping is enclosed in an air-tight containment cover so that a passage is formed between the piping and containment cover. Measurements can be conducted, using known hydrocarbon and other combustible gases industrial analyzers, and leak detectors. Pressure drop within the passage can be compensated by controlling of air inlet flow into the passage, coordinated with the analyzer pumping rate. Temperature and motion of a gas sample can be controlled by heating the inlet air. The system can includes the controlling valves for the leak source localization. The described method and system can be used to analyze and control fuel leak for late lean injection system for combustor of a turbine.

An electroencephalogram source localization method based on granger causality includes the steps: recording scalp electroencephalogram signals of a plurality of leads by an electroencephalogram acquisition device and performing elementary pretreatment; respectively analyzing the granger causality among each lead and the other leads by taking each lead as an observation lead, and performing source localization among the leads according to causality indexes; counting the number of the leads capable of becoming sources, and calculating the possibility index of taking each lead capable of becoming a source as a whole brain source area to realize whole brain source localization. The electroencephalogram source localization method solves the problems of poor electroencephalogram source localization stability and uniqueness, and the possibility of taking each lead as the whole brain source area can be obtained, so that whole brain source localization is realized. Instability and non-uniqueness of solutions of electroencephalogram inverse problems can be improved to a certain extent. The electroencephalogram source localization method can be used for determining a cranial nerve system disease focus portion, localizing a neurosurgery operation and performing electroencephalogram source localization and tracking in recognition tasks, and has an important significance in scientific research and clinical practice.

Methods, systems and computer readable media for reconstruction of target locations and amplitudes from signals received from one or more real targets in a space are provided, wherein the signals are at least one of signals received from the near-field and broadband signals. The space is modeled as a region of interest, and an array manifold matrix is calculated from signals received from hypothetical targets in the region of interest. One or more signal vectors received from the one or more real targets are reshaped into a data vector. A hypothetical target configuration is identified that, when applied to a signal model comprising the array manifold matrix, matches the data vector, a reconstruction vector is calculated. The reconstruction vector is reshaped into a reconstructed representation of the real targets in the space, and at least one of outputting the reconstructed representation for viewing by a user, and storing the reconstructed representation for later use are performed.

Systems and methods are provided for source localization and separation by sampling a large scale microphone array asynchronously to simulate a smaller size but moving microphone array. Signals that arrive from different angles at the array are shifted differently in their frequency content. The sources are separated by evaluating correlated and even equal frequency content. Compressive sampling enables the utilization of extremely large scale microphone arrays by reducing the computational effort orders of magnitude in comparison to standard synchronous sampling approaches. Processor based systems to perform the source separation methods are also provided.

The present invention is a two-stage distributed cooperative source positioning method based on pseudo-code spread spectrum, which involves radar detection technology, absorbs the advantages of distributed systems and computer network systems, and realizes the system's positioning search capture and positioning tracking functions separately, reducing the Difficulty in technical implementation. A method and technology for long-distance and high-precision detection of air, ground and sea targets is proposed by using cooperative pseudo-code spread spectrum signals to construct a distributed detection system. The present invention is not only different from the systems and methods of air target detection using the non-cooperative signals of terrestrial TV stations, radio stations and mobile communication base stations that have been developed at home and abroad, but also different from the passive positioning that uses the radiation source carried by the target to achieve detection. system. It can realize reliable detection of unconventional and conventional targets such as stealth aircraft, cruise missiles, and ultra-low-altitude aircraft in a large area, which is of great military value.

In one aspect, a method for performing signal source localization is provided. The method comprises the steps of obtaining compressive measurements of an acoustic signal or other type of signal from respective ones of a plurality of sensors, processing the compressive measurements to determine time delays between arrivals of the signal at different ones of the sensors, and determining a location of a source of the signal based on differences between the time delays. The method may be implemented in a processing device that is configured to communicate with the plurality of sensors. In an illustrative embodiment, the compressive measurements are obtained from respective ones of only a designated subset of the sensors, and a non-compressive measurement is obtained from at least a given one of the sensors not in the designated subset, with the time delays between the arrivals of the signal at different ones of the sensors being determined based on the compressive measurements and the non-compressive measurement.