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Experimental study of satellite signal processing with software defined radios

Chatzigeorgiou Roza

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Summary

This work studies the decoder of a low Earth orbit (LEO) micro-satellite (CubeSat) that transmits a GFSK telemetry in the UHF frequency band and specifically at 437.2 MHz. The first stage of the decoding process is FM demodulation, which converts the GFSK signal to a PAM waveform. The PAM symbols are time-synchronized by the Mueller and Müller algorithm, which exploits the structure of a Phase Locked Loop and estimates the time delay of the receiver sampling clock and the optimal sampling time. Next, the symbol samples are convolutionally decoded and frame detection is performed. Finally, descrambling and Reed-Solomon decoding follows. Frame synchronization and bit detection of this decoder are sub-optimal, so a different decoding scheme is proposed. We suggest performing preamble-based frame synchronization first, using correlators. The bits of the detected frame are decoded using a non-coherent FSK detector, a convolutional decoder, a descrambler and a Reed-Solomon decoder. The simulation results showed that for uncoded and unscrambled signals, the suggested decoder achieved approximately a 2 dB gain. Finally, the process of capturing and decoding the satellite’s GFSK signal is thoroughly explained. The signal is captured using a low-cost software-defined radio (SDR) receiver and a Yagi antenna. The decrypted telemetry bits in the GFSK signal give indications about the status of the satellite’s electronics, such as the current and voltage of the its transmitter and receiver, the PLL status and the temperature of the CubeSat microcontroller.

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