Raytheon Company

Phuoc T Ho

David Brent Wilson

Stanley I Tsunoda

Edward Marsh Jackson

Bruce R Anderson

Dan Hammack

Albert Yoon

An emitter identification system arranged to: receive a detected signal including one or more emitter signals from one or more emitters respectively where each of the emitter signals includes a unique signal characteristic related to a unique physical feature of a hardware structure associated with each of the emitters; apply a modulation signal to the detected signal to generate pulse in-phase and quadrature (IQ) data associated with the one or more emitter signals; extract one or more amplitude envelopes associated with the one or more emitter signals, where each amplitude envelope is related to the unique signal characteristic associated with each of the one or more emitters; estimate the unique signal characteristic of each of the one or more emitter signals; estimate a number of clusters related to a number of emitter signals; and identify each of the emitters by applying an unsupervised learning function.

Systems and methods for specific emitter identification

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.

Machine learning algorithm with binary pruning technique for automatic intrapulse modulation recognition

A geolocation system on a platform, for example, an airplane, to identify a location of a signal emitting site includes an inertial navigation system and an array of signal detectors. A first subset of the detectors is on a flexing portion of the platform and a second subset of detectors is on a rigid portion of the platform. An inertial measurement unit is disposed adjacent to each of the detectors on the flexing portion. A locator module is configured to: calculate a respective velocity and a respective position of each one of the detectors positioned on the flexing portion as a function of respective inertial measurement data; and determine a position of the emitter as a function of the calculated velocity, calculated position, inertial navigation data, the detected signal data and data defining a flexure relationship between the flexing and rigid portions of the platform.

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El Segundo, CA, United States of America

Phuoc T Ho