Praneet Raj Jeripotula,C. Anil Kumar,Mudavath Raju,B. Rajendra Naik,




Least Mean Square (LMS) algorithm,Variable Step Size LMS algorithm,Leaky LMS algorithm,Null depth,Rate of Convergence,


Adaptive antenna systems use advanced adaptive signal processing algorithms to generate main beams in the direction of interest and steer the nulls in the desired direction to reduce interferences from incoming signals. These algorithms are implemented in various applications such as channel equalization, object tracking, system identification and also in Radar systems which uses phased array antenna setup. In phased array radar systems, the noise and interference mitigation is a challenging task. The optimization of these algorithms to generate signals at a faster rate, steering nulls in the unwanted directions thereby improving the signal qualityis  very crucial. Few major factors which effect the Adaptive beam forming are complexity, rate of convergence, placing deeper nulls. A novel algorithm is proposed namely Normalized Leaky Variable Step Size-LMS algorithm. The proposed algorithm is applied to a uniform linear array of 8, 12, 16 and 32 elements configurations for different test cases. To demonstrate the efficiency of the proposed algorithm comparison is made with the traditional Least Mean Square, Variable Step Size LMS, and Leaky LMS algorithms. The results show the rate of convergence performance is substantially improved by more than 50% for the proposed algorithm than the existing ones along with providing deeper nulls for interference suppression.


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