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Proceedings Paper

Robust 2D fringe search algorithm for radio interferometry of very weak downlink signals of deep space probes
Author(s): Fengchun Shu; Xiuzhong Zhang
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Paper Abstract

The function of fringe search is to find the maximum amplitude of complex cross-correlation function and determine the residual delay and delay rate with respective to correlator model. When the signals transmitted by deep space probes have high SNR, the fringe search algorithm based on weighted least square estimation is very effective by tracking the fringe phase without 2π ambiguities in the frequency and time domain respectively, but it is not suitable for very weak signals when fringe phases include relatively large noises. According to VLBI data processing method for extra-galactic radio sources, a robust 2D fringe search algorithm is proposed for radio interferometry of very weak downlink signals of deep space probes. Compared with phase tracking fringe search algorithm, the proposed iterative process for searching the maximum correlation amplitude is performed in the two dimensional delay and delay rate plane, which is insensitive to large phase fluctuation in time and frequency domain, phase cycle ambiguities and phase outliers, so it is an optimal algorithm and much more robust for very weak signals. It can be proved theoretically that the proposed algorithm is equivalent to weighted least square estimation. Finally, fringe search for the VLBI observation of Mars Express is presented by using a software program implementing the iterative algorithm.

Paper Details

Date Published: 10 November 2007
PDF: 6 pages
Proc. SPIE 6795, Second International Conference on Space Information Technology, 67954Q (10 November 2007); doi: 10.1117/12.774886
Show Author Affiliations
Fengchun Shu, Shanghai Astronomical Observatory (China)
Xiuzhong Zhang, Shanghai Astronomical Observatory (China)

Published in SPIE Proceedings Vol. 6795:
Second International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Jiaolong Wei, Editor(s)

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