Cluster Track Identification for Radar Warning Emitter Separation
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Solution Overview
Problem
In dense Radio Frequency (RF) environments, existing geolocation algorithms face challenges in accurately determining whether multiple emitters with similar identification and angle-of-arrival are grouped together in the same Radar Warning (RW) track, leading to incorrect convergence and location predictions due to combined Long Base Interferometer (LBI) pulses from multiple emitters.
Innovation Solution
The Cluster Track Identification (CTI) algorithm uses a Direction Finding (DF) conic bearing and one sigma DF accuracy of a Short Baseline Interferometer (SBI) array to determine if LBI detections represent one emitter or multiple emitters, laying down a grid on the Earth and updating at each new detection to invoke the geolocation method appropriately, thereby distinguishing between single and multiple emitters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple emitters with similar ID and AoA are correlated into the same RW track, then the system can operate in dense RF environments, but geolocation accuracy deteriorates due to combined LBI pulses from multiple emitters
Solution Approach 1:
The patent segments the RW track by dividing it into multiple sub-tracks, each potentially containing a single emitter. The system processes LBI detections and determines whether they represent one emitter or multiple emitters, then splits the track accordingly. This segmentation allows the system to maintain operation in dense RF environments while restoring geolocation accuracy by ensuring each geolocation algorithm invocation processes data from a single emitter.
2Productivity
If LBI detections from multiple emitters are combined, then the system can detect signals in dense RF environments, but convergence and location predictions deteriorate
Solution Approach 1:
The patent extracts individual emitter signals from the combined LBI detections by analyzing the detections over time and determining whether they represent one emitter or multiple emitters. The system separates the mixed signals into distinct emitter tracks, allowing reliable convergence and location predictions for each emitter while maintaining the ability to detect signals in dense RF environments.
3Ease of manufacture
If residual LBI phase errors are present, then the system can function with practical hardware limitations, but geolocation accuracy deteriorates especially for frequency agile emitters
Solution Approach 1:
The patent applies preliminary phase error correction to LBI detections before processing them through the geolocation algorithm. By correcting residual phase errors in advance, particularly accounting for frequency agility effects, the system maintains hardware implementation feasibility while significantly improving geolocation accuracy. This preliminary action removes a key source of error that would otherwise degrade performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves geolocation accuracy by correctly identifying the number of emitters in a RW track, reducing errors from combined LBI pulses and enhancing the precision of emitter location predictions, especially in frequency agile scenarios.
Implementation Method 1
Direction Finding (DF) conic bearing and one sigma DF accuracy of a Short Baseline Interferometer (SBI) array
Implementation Method 2
A LBI delta phase measurement is the combination of the theoretical delta phase between a pair of LBI antennas and the residual phase produced by the overall receiver system
Data Source
AI summary
A correlation and track system identifies whether a Radar warning (RW) Track contains one or more emitters by receiving a set of initial Short and Long Baseline Interferometer (SBI) (LBI) detections; receiving inertial navigational data; receiving subsequent LBI detections; determining whether the LBI detections represent one or multiple emitter(s) by designating an initial SBI conic with a multiple of its one sigma conic Direction Finding (DF) accuracy window as containing the emitter; laying down a set of grid points within the SBI conic window as possible emitters' locations; summing real and imaginary values of a residual phase in the form of a unit vector at each grid point for each LBI update; identifying whether there are one or more emitters in RW track based on whether the magnitude of a peak vector is above or below a defined threshold; and invoking geolocation algorithms based on the vector's magnitude.