Independent satellite detection and monitoring is vital for Space Domain Awareness given increasing concerns of cross-tagging and conjunction risks. Passive radio frequency (RF) data can be collected regardless of illumination and material makeup when compared to optical sensors, and beyond the range of typical radar. Signals from these data can be exploited by identifying periodic signatures, even if the structure of such signals is not known a priori. However, many signal detection algorithms suffer from ambiguities in resulting pseudo-ranges due to the periodic nature of the signals. Traditional tracking and initial orbit determination (IOD) techniques require external data for disambiguation, obstructing independent estimation. We propose an IOD algorithm to exploit ambiguous measurements from arbitrary signals, even with a complete lack of prior information about the transmitter. State estimation is performed on time and frequency difference of arrival (TDOA and FDOA) data from simultaneous pseudo-range and Doppler measurements. Initial estimates are solved using basin-hopping optimization, leveraging known receiver positions to drive convergence. Subsequently restricting the search space around these estimates using visibility constraints facilitates tractable optimization with the ambiguous TDOA data. The resulting estimates can be used to disambiguate measurements and initialize precision tracking algorithms. Performance is demonstrated using measurements from random International Global Navigation Satellite System (GNSS) Service (IGS) stations, using both a diverse simulated orbit set and real GNSS data. Our results support leveraging ambiguous measurements of passive RF signals for the independent detection, tracking, and characterization of active spacecraft, addressing significant challenges in the use of such data.


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    Title :

    Initial Orbit Determination from Ambiguous TDOA and FDOA Measurements of Passive Radio Frequency Signals


    Additional title:

    J Astronaut Sci


    Contributors:


    Publication date :

    2025-07-23




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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