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US Patent 12013456 Multi-target detection using convex sparsity prior

Patent 12013456 was granted and assigned to Numerica Corporation on June, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Numerica Corporation
Numerica Corporation
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Current Assignee
Numerica Corporation
Numerica Corporation
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
120134560
Patent Inventor Names
Shawn Michael Herman0
Jason Kyle Johnson0
Dylan Scott Eustice0
Evan Jackson Everett0
Date of Patent
June 18, 2024
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Patent Application Number
183560420
Date Filed
July 20, 2023
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Patent Citations
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US Patent 8907841 Method for detecting targets using space-time adaptive processing
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US Patent 9048942 Method and system for reducing interference and noise in speech signals
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US Patent 9630318 Feature detection apparatus and methods for training of robotic navigation
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US Patent 9875428 Ensemble sparse models for image analysis and restoration
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US Patent 10032285 Multi-hypothesis moving object detection system
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US Patent 10310074 System and method for denoising synthetic aperture radar (SAR) images via sparse and low-rank (SLR) decomposition and using SAR images to image a complex scene
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US Patent 10445862 Efficient track-before detect algorithm with minimal prior knowledge
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US Patent 10531806 Brain state advisory system using calibrated metrics and optimal time-series decomposition
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Patent Primary Examiner
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Nuzhat Pervin
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CPC Code
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G01S 13/726
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G01S 7/292
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G01S 13/581
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Patent abstract

Provided is a method for detecting the trajectories of one or more targets in the field of view of one or more sensors, the method comprising: receiving one or more sensor frames corresponding to the one or more sensors; defining a space of allowable target states for the one or more sensor frames; specifying a set of potential target trajectories, each comprising one allowable target state for each of the one or more sensor frames; specifying target signal parameters for each of the allowable target states, such that the target signal parameters predict the expected target signal contribution corresponding to the one or more sensor frames; specifying a data fidelity objective to quantify how well the target signal parameters match the one or more sensor frames; specifying a sequence of one or more sparsity objectives to penalize a number of detected targets; determine the trajectories of one or more targets as follows: obtain values for all the target signal parameters in all the sensor frames, the obtained values being initialized values or previously optimized values, for each sparsity objective of the sequence, starting with the obtained target signal parameters, determine new target signal parameters to optimize the sum of the data fidelity objective and the sparsity objective; and storing the final trajectories in memory.

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