Performance Comparison of Reconstruction Algorithms in Compressive Sensing Based Single Snapshot DOA Estimation

Abstract

Direction of arrival (DOA) estimation from sparse signal representation has gained much attention in recent years. In this, the spatial signal is reconstructed by using a Compressive sensing (CS) framework. CS is a new paradigm by which the signal acquisition and reconstruction are carried out at sub-Nyquist rates. The limitation of the Nyquist sampling theorem is overcome by sparse sampling and reconstruction. This paper uses the CS framework in DOA estimation to reduce the underlying computational cost in the reconstruction process. Many reconstruction algorithms have been described in the past years. However, the comparative study on the reconstruction performances for CS-based DOA estimation is lacking. This work primarily concentrates on different reconstruction algorithms that are utilized in CS. The performance of various reconstruction algorithms for single snapshot DOA estimation is compared in this paper. Different parameters, like finding the target failure rate, Root Mean Square Error (RMSE), execution time are considered to evaluate the performance of the techniques.

Keywords:

• Array signal processing
• Compressive sensing
• DOA estimation

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Science and Engineering Research Board (SERB), Government of India, under the Early Career Research Award scheme with reference number (ECR/2016/001563).

Notes on contributors

Kankanala Srinivas

Kankanala Srinivas received the BTech and MTech degrees in electronics and communication engineering from Jawaharlal Nehru Technological University, Hyderabad, India. He is currently pursuing the PhD degree in electronics engineering with the National Institute of Technology Patna, India. His research interests include compressive sensing, radar signal processing, array signal processing, image enhancement and image segmentation.

Saurav Ganguly

Saurav Ganguly graduated with physics (Hons) from University of Calcutta. Obtained AMIETE (B.Tech) degree in ETCE from the IETE, New Delhi and MTech degree in ECE (Communication) from West Bengal University of Technology, Kolkata. After a brief stint in the IT sector, he worked as assistant professor at various engineering colleges in Kolkata for more than twelve years. At present he is pursuing PhD as a full-time research scholar at National Institute of Technology, Patna. His field of interest in research is in the domain of optimum array processing, compressive sensing, smart antennas, etc. Email: [email protected]

Puli Kishore Kumar

Puli Kishore Kumar received his MTech degree in communication and radar systems from ACHARYA Nagarjuna University in 2008, and PhD degree from NIT Warangal, in 2013. He is currently working as assistant professor in the Department of Electronics and Communication Engineering at NIT Andhra Pradesh, India. His current research area interests are radar signal processing and VLSI signal processing. Email: [email protected]