Estimating and tracking multiple attributes of multiple objects from multi-sensor data
US-9500739-B2 · Nov 22, 2016 · US
US9470775B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-9470775-B1 |
| Application number | US-201314041371-A |
| Country | US |
| Kind code | B1 |
| Filing date | Sep 30, 2013 |
| Priority date | Sep 30, 2013 |
| Publication date | Oct 18, 2016 |
| Grant date | Oct 18, 2016 |
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A method for localizing signals of interest includes initializing characteristics of the signals. Signals are acquired from a sensor array having at least three acoustic sensors. After digitization and conditioning, the signals associated with each sensor are validated by comparison with initialized characteristics. The signals are correlated across sensor groups to obtain time differences of arrival (TDOA). These TDOA are validated and associated with other TDOA from different times. TDOA from different sensor pairs are associated when they share a common sensor. A hyperbola of possible locations is created for each validated TDOA. Summation of the hyperbolas gives an intensity function. The location is identified as the most intense point in the intensity function. The source can be tracked across time as a computer output.
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What is claimed is: 1. A method for localizing environmental signals of interest utilizing a computer comprising the steps of: initializing signal characteristics of signals of interest; acquiring signals from a sensor array having at least three acoustic sensors; digitizing said acquired signals; conditioning said digitized signals based on initialized signal characteristics; validating conditioned signals associated with each sensor by comparison with initialized signal characteristics; correlating the validated conditioned signal associated with one sensor with the validated conditioned signal associated with another sensor for each sensor pair in the sensor array to obtain time differences of arrival for each sensor pair, wherein the step of correlating the validated conditioned signal associated with one sensor with the validated conditioned signal associated with another sensor comprises the steps of: developing a first order click map for the validated conditioned signal associated with one sensor; developing a first order click map for the validated conditioned signal associated with another sensor; windowing the first order click map for each signal to obtain a windowed first order click map for one sensor and a windowed first order click map for another sensor; and correlating said first order click map from one sensor with a windowed first order click map from another sensor to obtain an initial time difference of arrival for the sensor pair; validating the time differences of arrival for each sensor pair; associating validated time differences of arrival from different times from the same sensor pairs; associating validated time differences of arrival from different sensor pairs when the time differences of arrival share a common sensor; creating a hyperbola of possible source locations for each validated time difference of arrival; summing hyperbolas created from associated validated time differences of arrival from different sensor pairs to obtain an intensity function; identifying location at a time as a position in the intensity function having the greatest intensity; tracking a source across time by utilizing the identified location and associated validated time differences of arrival from different times; and providing said identified location and track as computer output. 2. The method of claim 1 wherein the step of validating the time differences of arrival for each sensor pair comprises: providing a threshold time for signal repetition in said step of initializing; calculating a second order smoothed click map by multiplying the first order click map for the validated conditioned signal associated with one sensor by the first order click map for the validated conditioned signal associated with another sensor; validating the time difference of arrival when the second order smoothed click map gives a peak separation measure within the threshold time for signal repetition. 3. The method of claim 1 wherein the step of validating the time difference of arrival comprises: providing a trained model of signals of interest in said step of initializing, said trained model being capable of analyzing features comprising signal repetition rate, auto-correlation characteristics, and power spectrum characteristics; calculating a second order smoothed click map by multiplying the first order click map for the validated conditioned signal associated with one sensor by the first order click map for the validated conditioned signal associated with another sensor; calculating an autocorrelation function for the conditioned digitized signals; calculating a power spectrum for the conditioned digitized signals; and validating the time difference of arrival when the trained model of signals of interest indicates that the second order smoothed click map, autocorrelation function and power spectrum for the signals in the sensor pair are in accordance with the features of the signal of interest.
Position of source determined by a plurality of spaced direction-finders · CPC title
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