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1. (WO2018200045) MACHINE LEARNING ALGORITHM WITH BINARY PRUNING TECHNIQUE FOR AUTOMATIC INTRAPULSE MODULATION RECOGNITION

Pub. No.:    WO/2018/200045    International Application No.:    PCT/US2018/012891
Publication Date: Fri Nov 02 00:59:59 CET 2018 International Filing Date: Wed Jan 10 00:59:59 CET 2018
IPC: G01S 7/02
Applicants: RAYTHEON COMPANY
Inventors: HO, Phuoc T.
ANDERSON, Bruce R.
HAMMACK, Dan
Title: MACHINE LEARNING ALGORITHM WITH BINARY PRUNING TECHNIQUE FOR AUTOMATIC INTRAPULSE MODULATION RECOGNITION
Abstract:
Radio signals (101) 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 (601, 602, 611, 612, 621, 622, 631, 632, 641, 642, 651, 652, 661, 662, 671, 672) 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 (206) of discriminating vectors (603, 613, 623, 633, 643, 653, 663, 673), 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.