Passive Single Satellite Geolocation of Ground EMI Sources
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Solution Overview
Problem
Current methods for geolocating ground-based electromagnetic interference (EMI) sources using a single satellite face challenges in accuracy and computational efficiency, particularly in passive geolocation methods, which are essential for mitigating satellite communication interference.
Innovation Solution
The implementation of a constrained unscented Kalman filter (cUKF) based on Doppler shifts and rates, combined with a recursive constrained posterior Cramér-Rao bound (rcPCRB), to enhance the accuracy and efficiency of passive single-satellite geolocation of ground-based EMI sources, utilizing a two-line element (TLE) file for simulation and position calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If nonlinear least squares or extended Kalman filters are used to geolocate EMI sources using Doppler information, then geolocation capability is achieved, but computational capacity requirements increase and initialization issues arise
Solution Approach 1:
The patent extracts and utilizes only the essential Doppler information from satellite signals for geolocation, separating this key parameter from other complex signal processing requirements. By focusing specifically on Doppler shift and rate measurements, the system achieves effective geolocation with reduced computational burden compared to full-signal processing approaches.
Solution Approach 2:
The patent transforms the geolocation problem by changing the measurement parameters from raw signal data to processed Doppler characteristics (Doppler shift and Doppler rate). This parameter transformation simplifies the underlying mathematical model and enables more efficient filtering algorithms while maintaining geolocation accuracy.
2Measurement precision
If particle filter techniques are applied to Doppler information for accurate geolocation, then geolocation accuracy improves, but computational efficiency decreases making it difficult to meet real-time processing requirements
Solution Approach 1:
The patent applies a constrained unscented Kalman filter that performs partial filtering actions focused specifically on the Doppler parameters rather than comprehensive signal processing. This selective approach achieves sufficient geolocation accuracy without the excessive computational burden of particle filters, meeting real-time processing requirements.
Solution Approach 2:
The patent performs preliminary processing of satellite orbit data using TLE files to pre-calculate satellite positions and velocities before the actual geolocation measurement. This preliminary action reduces the real-time computational load during Doppler-based geolocation operations, enabling faster processing while maintaining accuracy.
3Ease of operation
If DOA and DOA rate-based methods are used for geolocation, then geolocation can be achieved with simple methods, but acquisition time increases and geolocation accuracy is limited
Solution Approach 1:
The patent merges two measurement dimensions (Doppler shift and Doppler rate) into a unified geolocation estimation framework. By combining these two parameters that are naturally coupled in the satellite-Earth geometry, the system achieves faster convergence and reduced acquisition time compared to using DOA measurements alone, while maintaining methodological simplicity.
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 enables rapid and accurate 3D geolocation of EMI sources, improving convergence speed and accuracy, and meeting real-time processing requirements, even with limited satellite power and in clustered EMI environments.
Implementation Method 1
calculating Doppler shifts and Doppler rates according to the positions, the velocities and the accelerations of the satellite at the different time instants
Data Source
AI summary
The present disclosure provides a method for decentralized optimal control for passive SSG of ground-based EMI sources. The method includes simulating a scenario based on an EMI source and a satellite specified by a TLE file; and calculating positions, velocities and accelerations of the satellite at different time indexes of the simulated scenario; calculating Doppler shifts and Doppler rates according to the positions, the velocities and the accelerations of the satellite at the different time indexes; and implementing a constrained unscented Kalman filter (cUKF) based on the Doppler shifts and the Doppler rates to obtain an updated state; and calculating a recursive constrained posterior Cramér-Rao bound (rcPCRB); and fine tuning the cUKF using the calculated rcPCRB to obtain an updated cUKF.