Direction of Arrival Estimation using MUSIC Algorithm for Antenna Arrays Kartik Erappa Cholachgudda Communication Engineering Dept. VIT University Vellore, India kartikenc@gmail.com Puram Dixith Reddy Communication Engineering Dept. VIT University Vellore, India dixithreddy3216@gmail.com Ashish P. Communication Engineering Dept. VIT University Vellore, India ashish.p@vit.ac.in Abstract — Direction of arrival (DOA) estimation has been a vital area of research since few decades due to its importance in applications like wireless communications, navigation, radar, sonar and soon. The resolution being one of the main challenges in the direction of arrival estimation can be enhanced by using an array antenna system with reliable signal processing. High resolution techniques make use of array antenna structures to efficiently process the incoming signals. This paper simulates a high resolution subspace based DOA algorithm namely; Multiple Signal Classification (MUSIC) on a uniform linear array in the presence of white Gaussian noise. The paper also provides an extensive discussion on importance of Adaptive beam forming algorithm used in mobile communication systems along with the DOA algorithm. The simulation results indicate that MUSIC which is a subspace based method provides high spatial resolution and the resolution improves as the number of array elements, number of snapshots and spacing between the array elements increase. It also showed that increase of separation angle between the two sources also gives better results. Keywords— DOA, MUSIC, Resolution, Uniform linear array, Adaptive beam forming. I. INTRODUCTION In the last few decades, accurate determination of direction of arrival (DOA) from a signal source has received a lot of attention in military communication, radar systems and commercial applications. Wireless communications, radio astronomy, sonar, radar, navigation, tracking of various objects are a few examples of many applications. One example of defence applications it is to identify the direction of a possible threats [1]. In wireless mobile communication, DOA estimation can be used to identify the desired user signal and the interference signal from the received data at the base station sensor array. This DOA estimation results are then used to adjust the weights of adaptive beam former which helps in maximising the power of desired user and radiation nulls in the direction of interference signals. This process of adaptive beam forming provides spatial filtering of multiple users i.e., if one or more mobiles are on the identical frequency band and communicating at the same time with the base station, the base station can still separate them using spatial filtering (DOA) [2]. DOA estimation uses antenna arrays. It is known that antenna radiation main lobe beam width is inversely proportional to the number of elements in antenna. So, if we consider a single antenna then array pattern will be wider and the resolution cannot be good. Instead of using single antenna, an antenna array system is used in DOA estimation which will improve the resolution of the received signals (Resolution in DOA estimation is the ability to distinguish two signals arriving at different angles). An array system has a multiple elements distributed in space. There are various methods to estimate the angle of arrival (DOA) of radio signals on the antenna array. DOA estimation techniques can be broadly divided into three different categories namely; conventional methods, subspace based methods and maximum likelihood methods. Convolutional methods are based on the concepts of beam forming and null steering but it requires a large number of elements to provide high resolution. Examples of this method are delay and sum and Capon’s minimum variance method [3]. One major limitation of this method is poor resolution that is its ability to separate closely spaced signals. Unlike conventional methods, subspace methods exploit the information of the received data resulting in high resolution. Two main subspace based algorithms are Multiple Signal Classification and Estimation of Signal Parameters via Rotational Invariance Techniques. These algorithms give information about number of incident signals and DOA of each signal. Maximum likelihood method is one of the first technique to be investigated for DOA estimation but has the drawback of intensive computational complexity [4]. We present in this paper a DOA estimation procedure for M uncorrelated signals impinged on uniform linear array of N elements by using high resolution MUSIC subspace method and discuss some of the basics of Adaptive beam forming used in smart antennas. We will also observe that the important parameters like number of antenna elements, number of snapshots and spacing between elements to take into consideration for better accuracy. Finally we will conclude with an analysis of performance of MUSIC algorithm.