Radar Emitter Identification Using UMOP and Unsupervised Clustering

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Solution Overview

Problem

Existing emitter identification systems are ineffective in rapidly identifying and classifying agile radar emitters due to their rapidly changing waveform characteristics, leading to challenges in distinguishing between similar emitters and long cycle times for identification, especially in dense radar environments.

Innovation Solution

The implementation of Unintentional Modulation on Pulses (UMOP) systems that exploit unique physical features of each emitter's hardware structure, using automatic recognition algorithms to estimate and cluster signal characteristics, and applying unsupervised learning functions for real-time specific emitter identification.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional IMOP detection techniques are used with PDW parameters, then emitter identification can be performed, but the estimated parameters are difficult to distinguish and de-interleave due to inseparable distribution

Engineering Contradiction:

Improveemitter identification accuracyVSAvoidparameter distinction difficulty

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The patent extracts unintentional modulation features from the radar waveform that are independent of intentional modulation parameters. By focusing on hardware-induced characteristics rather than intentional signal parameters, the system separates the identification features from the confusing PDW parameters, enabling clear distinction between different emitters even when their intentional parameters overlap.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of analyzing intentional modulation parameters as traditional systems do, the patent inverts the approach by analyzing unintentional modulation characteristics caused by hardware imperfections. This inversion allows the system to identify emitters based on their unique physical fingerprints rather than their intentionally variable parameters.

Inventive Principle:

Principle #13The other way round (Inversion)

2Productivity

If existing NGJ systems process rapidly changing radar waveforms, then emitter detection can be performed, but the processing speed is insufficient to attack rapidly changing threats

Engineering Contradiction:

Improveprocessing speedVSAvoidemitter classification accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent performs preliminary extraction of unintentional modulation features during the signal reception phase, before full waveform processing is required. By pre-identifying unique hardware characteristics early in the processing chain, the system enables rapid emitter identification without requiring complete analysis of rapidly changing waveform parameters, thus maintaining both speed and accuracy.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If traditional waveform features are used for emitter identification, then classification can be attempted, but agile radar systems create separate clusters that belong to the same radar emitter making classification almost impossible

Engineering Contradiction:

Improveagile radar waveform variationVSAvoidemitter classification accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent focuses on local, invariant hardware characteristics within the emitter system that remain consistent regardless of waveform variations. By analyzing specific local features of the hardware-induced modulation rather than global waveform characteristics, the system maintains consistent emitter identification across different agile radar modes and waveform configurations.

Inventive Principle:

Principle #3Local quality

4Quantity of substance

If adhoc methods of grouping features are used, then emitter classification can be performed, but when the density of radar systems are closely spaced, this approach becomes ineffective

Engineering Contradiction:

Improvenumber of detectable emittersVSAvoidemitter distinction capability

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent introduces a new dimensional space for emitter identification by analyzing unintentional modulation characteristics in the time-frequency domain. This additional dimensional approach provides enhanced separation between closely spaced emitters, allowing the system to distinguish and classify multiple dense radar systems that would be indistinguishable using traditional feature grouping methods.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS11063563B1Systems and methods for specific emitter identification

Publication Date: 2021.07.13 RAYTHEON CO

AI summary

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.