For reliable reception of weak signals from spacecraft, a large antenna array structure is commonly employed in deep space communication system. The signal correlation is one of the methods used to combine signals from individual antennas. However, because the signal-to-noise ratio (SNR) from individual antennas is comparatively low, the phase offsets derived from the correlation cannot be used directly to align the signals, and some special processing is necessary to take advantage of all the antenna pairs. SUMPLE and matrix-free algorithms are two main approaches that have been analyzed or implemented with the array. Based on existing SUMPLE and matrix-free algorithms, a unified model is proposed and analyzed, and a novel algorithm named MLC-SUMPLE is proposed based on the new model. Theoretical analysis and simulations proved that the new algorithm performs better than existing combining algorithms in both the speed of convergence and steady-state performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    MLC-SUMPLE Algorithm for Aligning Antenna Arrays in Deep Space Communication


    Contributors:
    Yong Shang (author) / Xiaotao Feng (author)


    Publication date :

    2013-10-01


    Size :

    1299893 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Distributed Swarm Antenna Arrays for Deep Space Applications

    Quadrelli, Marco B. / Hodges, Richard / Vilnrotter, Victor et al. | IEEE | 2019


    Large antenna apertures and arrays for deep space communications

    Ludwig, A. C. / Merrick, W. D. / Potter, P. D. | NTRS | 1965



    Antenna Arrays for High Data Return from Future Deep Space Missions

    Marti, S. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012


    Auto Aligning Laser Communication System

    Sparsh, Smit / Pendam, Adit / Govardhan, K | IEEE | 2018