Signal Source Geolocation via Differential Slant Range Correlation
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Solution Overview
Problem
Existing methods for locating unknown transmitters interfering with geosynchronous satellite communications, particularly in scenarios with unstable signal frequencies or amplitudes, face challenges in achieving accurate location due to limitations in Time Difference Of Arrival (TDOA) and Frequency Difference Of Arrival (FDOA) measurements, especially when signal levels are below satellite noise levels.
Innovation Solution
A method that uses differential slant range and slant range rate calculations, combined with ephemeris error corrections, to evaluate and correct for changing positions and velocities of signal relays, allowing for efficient and scalable correlation processing on general-purpose computers, enabling precise geolocation of unknown signals without being limited by hardware delay circuits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If TDOA and FDOA measurements are used to locate unknown transmitters, then location capability is provided, but measurement precision deteriorates when signal levels are below satellite noise levels or when frequency/amplitude are unstable
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing differential slant range and slant range rate values for multiple possible transmitter locations before actual signal detection. These pre-computed values are ready for immediate comparison with measured TDOA/FDOA data, enabling rapid and accurate location determination even when signals are weak or unstable, thus improving both measurement precision and reliability
2Productivity
If hardware correlators are used for signal processing, then processing capability is provided, but device complexity and memory storage requirements increase
Solution Approach 1:
The patent replaces the mechanical hardware correlator system with a computational approach using general-purpose computers. Instead of physical delay circuits and hardware correlation, the invention uses software-based processing with pre-calculated differential slant range values stored in memory, significantly reducing hardware complexity while maintaining or improving processing speed and flexibility
Solution Approach 2:
The patent creates computational copies of the correlation function through pre-calculated differential slant range values for multiple transmitter locations. These computed values serve as digital substitutes for physical hardware delay lines, enabling the correlation process to be performed through software comparison rather than mechanical hardware operations
3Measurement precision
If satellite ephemeris data is used for location calculations, then position information is provided, but errors are introduced due to changing satellite geometry
Solution Approach 1:
The patent applies feedback by using measured TDOA and FDOA values to refine and update the differential slant range calculations. The system continuously compares pre-calculated values with actual measurements and adjusts the location determination accordingly, compensating for ephemeris errors and changing satellite geometry through iterative refinement of the position estimate
Data Source
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AI summary
A method of locating the source of an unknown signal. The method comprises the steps of:(i) calculating a differential offset for a signal for each of a plurality of positions within a region in which the transmitter must lie, for each of a series of times m with respect to first and second signal relays and respective first and second receivers, the positions of the signal relays and receivers being known; (ii) generating a cross-ambiguity function (CAF) using data corresponding to samples of the unknown signal received at the first and second receivers via the first and second signal relays respectively,(iii) estimating the level of noise on the CAF; and(iv) using data generated in steps (i), (ii) and (iii) to obtain a measure of the likelihood that the source is located within defined areas within said region, wherein the differential offsets are differential time offsets (DTOs), or differential frequency offsets (DFOs), or both DTOs and DFOs. The method further comprises the steps of (v) for each of a series of times m, sampling the unknown signal at first and second receivers via first and second signal relays respectively; (vi) generating a corresponding series of m CAF surfaces; (vii) for a given latitude α and longitude β, computing differential time and frequency offsets DTOm, DFOm, at each time m, finding the associated CAF surface value CAFm at each time m, and corresponding values SNRm of signal-to-noise ratio; and (viii) evaluating the chi-squared value χ2αβ=χmin2-2ln1-P