Kaiser Window Based Blind Beamformers for Radar Application

Abstract

Blind beamforming algorithms are the first choice for radar applications as they won’t use any training signal. But the major downside of constant modulus algorithm (CMA) is very low convergence rate. To overcome this problem and to make this algorithm more suitable for real-time applications, we firstly improved the convergence rate of CMA by making its step size adaptive. Then, we applied Kaiser window to improved CMA and conventional least-square CMA (LS-CMA) to suppress the sidelobe levels. These proposed algorithms are named Kaiser window-constant modulus algorithm and Kaiser window least square-constant modulus algorithm, respectively. Computer simulations validate the effectiveness of the proposed beamformers.

KEYWORDS:

• Blind beamforming
• CMA
• Hanning
• Kaiser
• LS-CMA
• Smart antenna

Additional information

Notes on contributors

Veerendra Dakulagi

Veerendra Dakulagi received the BE and MTech degrees from Visvesvaraya Technological University, Belagavi, India, in 2007 and 2011, respectively. He received the PhD degree in adaptive antennas from the same university in 2018. From 2007 to 2008 he was an assistant professor in Sapthagiri Engineering College, Bangalore, India. From 2009 to 2010, he was an assistant professor in BKIT, Bhalki, India. From 2010 to 2017 he was an assistant professor in Department of E&CE, Guru Nanak Dev Engineering College, Bidar, India. Since March 2017 he has been an associate professor and R&D dean of the same institute. His research interests are in the area of signal processing and communications, and include statistical and array signal processing, adaptive beamforming, spatial diversity in wireless communications, multiuser and MIMO communications. He has published over 40 technical papers (including IEEE, Elsevier, Springer and Taylor and Francis) in these areas. Dr Veerendra Dakulagi is a member of Institution of Electronics and Telecommunication Engineers (IETE) and currently serves as an editorial board member of Journal of Computational Methods in Sciences and Engineering, Journal on Communication Engineering and Systems, Journal on Electronics Engineering and International Journal of Scientific Research and Development. Currently, he is also working as a post doctoral fellow (PDF) of faculty of electronics & communication engineering, Lincoln University College, Petaling Jaya, Malaysia. Corresponding author. Email: [email protected]

Mukil Alagirisamy

Mukil Alagirisamy received her bachelor's degree in electronics and communication engineering, in 2005 and Master of Engineering degree in communication systems in 2007 and PhD in engineering in 2012. She completed her PDF in 2015. She started her career as a lecturer at Hindustan Engineering College, India. She was working as an assistant professor at B S Abdur Rahman University, India. Later she joined as a lecturer at Stamford College, Malaysia. Currently, she is working as an assistant professor and coordinator for Master of Science in electrical, electronics and telecommunication engineering programs at Lincoln University College, Malaysia. She has over 12 years of experience in teaching subjects like data communication, analog and digital communications, digital signal processing and satellite communications. Her research interests are in sink mobility patterns, clustering,modulation, data aggregation and compressive sensing techniques for wireless sensor networks. Email: [email protected]