Invention Grant
- Patent Title: Machine learning algorithm with binary pruning technique for automatic intrapulse modulation recognition
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Application No.: US15499653Application Date: 2017-04-27
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Publication No.: US10915833B2Publication Date: 2021-02-09
- Inventor: Phuoc T. Ho , Bruce R. Anderson , Dan Hammack
- Applicant: Raytheon Company
- Applicant Address: US MA Waltham
- Assignee: Raytheon Company
- Current Assignee: Raytheon Company
- Current Assignee Address: US MA Waltham
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G01S7/02

Abstract:
Radio signals including modulated radar signals of an unknown modulation type selected from among a predetermined group of modulation types are received, and a plurality of features are extracted for the received radio signals. A plurality of two dimensional (2D) maps are generated for pairs of the extracted features from the received radio signals. The 2D maps of extracted feature pairs for the received radio signals are processed using a binary tree of discriminating vectors, each of the discriminating vectors corresponding to recognition of at least one of the predetermined modulation types based on 2D feature maps and each of the discriminating vectors determined by processing 2D maps for pairs of features extracted from training samples using a support vector machine learning algorithm. The binary tree is derived by pruning permutations of sequences for applying the discriminating vectors according to iterative testing of modulation type recognition accuracy.
Public/Granted literature
- US20180314974A1 MACHINE LEARNING ALGORITHM WITH BINARY PRUNING TECHNIQUE FOR AUTOMATIC INTERPULSE MODULATION RECOGNITION Public/Granted day:2018-11-01
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