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Soft Computing and Signal Processing pp 467–476Cite as

Improvement of Signal-to-Noise Ratio for MST Radar Using Weighted Semi-parametric Algorithm

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 900))

Abstract

The Indian mesosphere–stratosphere–troposphere (MST) radar is the prominent atmospheric radar that provides the atmospheric movements’ information. The radar data is analyzed to obtain the wind parameter that requires the power spectral estimation. At higher altitudes, the estimation of Doppler spectrum is found to be unsatisfactory using both parametric and nonparametric methods for spectral estimation. In this article, the hyperparameter-free, weighted sparse iterative covariance-based estimation (SPICE) method has been considered. Unlike existing SPICE method, a different hyperparameter–free, weighted SPICE method has been derived using a gradient approach with different step sizes. The two versions of SPICE algorithm, i.e., SPICEa and SPICEb, are applied to the practical MST radar data collected at National Atmospheric Research Laboratory, Gadanki (13.5°N, 79.2°E). The obtained results are evaluated with the existing atmospheric data processor results which use the basic periodogram method. The proposed method shows the significant enhancement in signal-to-noise ratio even at elevated heights.

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Acknowledgements

We are thankful to the National Atmospheric Research Laboratory (NARL), Gadanki, for giving the radar data, and the Centre of Excellence, Department of ECE, SVU College of Engineering, SV University, for providing resource and assistance.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, SVU College of Engineering, Tirupati, Andhra Pradesh, India

    C. Raju & T. Sreenivasulu Reddy

Authors
  1. C. Raju
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  2. T. Sreenivasulu Reddy
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Corresponding author

Correspondence to C. Raju .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ, USA

    Jiacun Wang

  2. Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangaluru, Karnataka, India

    G. Ram Mohana Reddy

  3. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad, Hyderabad, Telangana, India

    V. Kamakshi Prasad

  4. Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Secunderabad, Telangana, India

    V. Sivakumar Reddy

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Raju, C., Sreenivasulu Reddy, T. (2019). Improvement of Signal-to-Noise Ratio for MST Radar Using Weighted Semi-parametric Algorithm. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 900. Springer, Singapore. https://doi.org/10.1007/978-981-13-3600-3_44

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