Abstract

Space Surveillance and Tracking is the capacity to identify and anticipate the kinematics of space debris in orbit around the Earth. It is important for avoiding collisions with the International Space Station, operational satellites and other spacecraft. GNSS signals have been proposed as illumination sources for passive radar to track space debris. Detecting space debris by scattered GNSS signals requires extremely long integration to gather sufficient energy. Such long coherent processing is computationally expensive, and non-uniformities in the signal phase variations confound many existing processing aids, such as the Fast Fourier Transform. In this paper, we propose a novel multi-step processing strategy which is shown to be able to reduce the processing burden to an affordable level. The first step correlates the received signal with a replica of the expected signal, followed by an integrate and dump. This reduces the bandwidth of the signal to Audio frequencies, taking care that the target uncertainty volume is preserved. In the final step, the full length coherent integration is formed by summing the audio samples with the necessary phase adjustments, for example allowing the residual phase to vary a second order non-linear function over time. This processing technique is demonstrated using real data collected from GPS satellites, highlighting the ability to synthesize coherent integrations within a reasonable uncertainty volume at low cost using just the audio rate signal.

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