Prabha G. received M. Tech. in Computational Engineering and Networking from Amrita Vishwa Vidyapeetham in 2008, where she is currently pursuing the Ph. D. degree in Electronics and Communication Engineering in Antenna Array Signal Processing. She is currently an Assistant Professor with the School of Engineering, Amrita Vishwa Vidyapeetham, Tamilnadu, India. She has been teaching undergraduate courses since 2008 in Electronics and Communication Engineering. Her current research interests include Antenna Array Processing, Direction of Arrival Estimation and Optimization Techniques.
Year | Affiliation |
2013 to till date | Assistant Professor (Sr. G), Amrita Vishwa Vidyapeetham Domain : Teaching |
2010-2013 | Assistant Professor, Amrita Vishwa Vidyapeetham Domain : Teaching |
2008-2010 | Lecturer, Amrita Vishwa Vidyapeetham Domain : Teaching |
Position | Class / Batch | Responsibility |
Class Adviser | 2009- 13,2016-20 | administrative |
SNo | Title | Organization | Period | Outcome |
1. | Workshop on Introduction to Non linear dynamics and chaos, Theory and computation | Amrita, Coimbatore | January 27 - 28, 2017 | Research |
2. | Workshop on Fundamentals of Electronics | Amrita,Coimbatore | June 7 - 10, 2016 | Teaching |
3. | Author Workshop on scholarly writing and publishing | Amrita,coimbatore | April 11, 2018 | Research |
4. | Two week ISTE workshop on Analog Electronics | Amrita ,Coimbatore | June 4 - 14, 2013 | teaching |
5. | Two week ISTE workshop on Signals and Systems | Amrita,Coimbatore, IIT Kharagpur | January 2 - 12, 2014 | Teaching |
SNo | Name of the Scholar | Programme | Specialization | Duration | Status |
1. | Vignesh R | Communication& Signal processing | Signal processing | 2015-16 | Completed |
2. | Leishangthem R Singh | Communication& Signal processing | Signal processing | 2016-17 | Completed |
3. | K S Anjali | Communication& Signal processing | Signal processing | 2017-18 | Completed |
Year of Publication | Title |
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2016 |
Prabha G and Sundaram, G. A. S., “Estimation of DOA using a Cumulant Based Quadricovariance Matrix”, 2016 10th European Conference on Antennas and Propagation (EuCAP). pp. 1-5, 2016.[Abstract] This paper discusses the estimation of direction of arrival of narrowband signals received by a linear array. The algorithm uses fourth order cumulants of the array input data to construct a matrix whose dimension is increased by a power of two compared to the classical Multiple Signal Classification (MUSIC) and Estimation of Signal parameters using Rotational Invariance Technique (ESPRIT) algorithm. This extended matrix along with extended array steering vectors uses the steps followed by MUSIC algorithm for the calculation of direction of arrival. The proposed method is able to detect more number of sources than the elements of the array and hence helps in increasing the effective aperture size. Preprocessing using forward backward averaging is used to improve the accuracy of estimation. More »» |
Year of Publication | Title |
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2016 |
V. Ranganathan, Prabha G, and Narayanankutty Karuppath, “Constant modulus hybrid recursive and least mean squared algorithm performance comparable to unscented Kalman filter for blind beamforming”, in 2016 IEEE Annual India Conference, INDICON 2016, 2016.[Abstract] In this paper, we propose an adaptive filtering algorithm, Hybrid Recursive and Least Mean Square-based Constant Modulus Algorithm (RLS-LMS-CMA) for optimized blind beamforming for a Uniform Linear Array (ULA). We consider that Recursive Least Square-based Constant Modulus Algorithm (RLS-CMA) and Least Mean Square-based Constant Modulus Algorithm (LMS-CMA) algorithms are time tested. Therefore, we investigated a combination of RLS-LMS-CMA algorithm. We achieve similar tracking performance when compared to Unscented Kalman Filter-based Constant Modulus Algorithm (UKF-CMA) with minimal computational complexity. Simulations are carried out to compare the performance of RLS-LMS-CMA with other state-of-the-art algorithms. Results obtained indicate that proposed algorithm leads to an equivalent tracking ability and convergence rate of UKF-CMA algorithm. © 2016 IEEE. More »» |