OPTIMIZED DIFFERENTIAL EVOLUTION FOR RADIO FREQUENCY TRILATERATION IN COMPLEX ENVIRONMENTS
First Claim
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1. A device localization method comprising:
- obtaining by a plurality of sensor distances between a wireless device and a vehicle;
generating by trilateration of the distances a first population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device;
computing fitness levels of each of the plurality of the coordinate sets by employing a fitness function based on ranging results obtained from a plurality of anchors having known positions;
saving coordinates sets from the first population having a fitness level above a threshold fitness level;
computing a vector offset to the saved coordinate sets based on updated ranging results from the plurality of anchors;
applying the vector offset based on historical data to the saved coordinate sets to obtain a shifted population;
generating a second population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device;
combining the shifted population with the second population to form a combined population; and
computing fitness levels of the coordinate sets in the combined population by employing the fitness function.
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Abstract
A system, device and method for wireless device localization using a differential evolution algorithm in a continuous trilateration process.
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Citations
14 Claims
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1. A device localization method comprising:
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obtaining by a plurality of sensor distances between a wireless device and a vehicle; generating by trilateration of the distances a first population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device; computing fitness levels of each of the plurality of the coordinate sets by employing a fitness function based on ranging results obtained from a plurality of anchors having known positions; saving coordinates sets from the first population having a fitness level above a threshold fitness level; computing a vector offset to the saved coordinate sets based on updated ranging results from the plurality of anchors; applying the vector offset based on historical data to the saved coordinate sets to obtain a shifted population; generating a second population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device; combining the shifted population with the second population to form a combined population; and computing fitness levels of the coordinate sets in the combined population by employing the fitness function. - View Dependent Claims (2, 4)
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3. The device localization method 1 further comprising:
locating the plurality of anchors to minimize region of interest size. - View Dependent Claims (5, 6, 7)
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8. A system for localization of a wireless device comprising:
one or more processors operatively coupled to one or more non-transitory storage devices on which is stored executable computer code, which when executed by the one or more processors causes the system to perform the method of; obtaining by a plurality of sensors distances between a wireless device and a vehicle; generating by trilateration of the distances a first population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device; computing fitness levels of each of the plurality of the coordinate sets by employing a fitness function based on ranging results obtained from a plurality of anchors having known positions; saving coordinates sets from the first population having a fitness level above a threshold fitness level; computing a vector offset to the saved coordinate sets based on updated ranging results from the plurality of anchors; applying the vector offset based on historical data to the saved coordinate sets to obtain a shifted population; generating a second population of a plurality of coordinate sets, each set describing a possible location in 3-D space of the device; combining the shifted population with the second population to form a combined population; and computing fitness levels of the coordinate sets in the combined population by employing the fitness function. - View Dependent Claims (9, 10, 11, 12, 13, 14)
Specification