Array signal processing for maximum likelihood direction-of-arrival estimation

Emitter Direction-of-Arrival (DOA) estimation is a fundamental problem in a variety of applications including radar, sonar, and wireless communications. The research has received considerable attention in literature and numerous methods have been proposed. Maximum Likelihood (ML) is a nearly optimal technique producing superior estimates compared to other methods especially in unfavourable conditions, and thus is of significant practical interest. This paper discusses in details the techniques for ML DOA estimation in either white Gaussian noise or unknown noise environment. Their performances are analysed and compared, and evaluated against the theoretical lower bounds

Performance Analysis for Direction of Arrival Estimating Algorithms

Smart antennas have emerged as one of the most promising directions in supporting maximum communication link throughput. In this paper, we have investigated the impact of smart antennas on a complex mobile network such as a railroad wireless communications system. The objective is to analyze the selection of a Direction-Of-Arrival (DOA) estimation algorithm which provides the maximum efficiency when deployed in our railroad testbeds for wireless vehicular communication. Our findings are discussed to provide an indepth understanding of how different algorithms should be selected to support efficient network operations

Advanced array processing techniques and systems

Research and development on smart antennas, which are recognized as a promising technique to improve the performance of mobile communications, have been extensive in the recent years. Smart antennas combine multiple antenna elements with a signal processing capability in both space and time to optimize its radiation and reception pattern automatically in response to the signal environment. This paper concentrates on the signal processing aspects of smart antenna systems. Smart antennas are often classified as either switched-beam or adaptive-array systems, for which a variety of algorithms have been developed to enhance the signal of interest and reject the interference. The antenna systems need to differentiate the desired signal from the interference, and normally requires either a priori knowledge or the signal direction to achieve its goal. There exists a variety of methods for direction of arrival (DOA) estimation with conflicting demands of accuracy and computation. Similarly, there are many algorithms to compute array weights to direct the maximum radiation of the array pattern toward the signal and place nulls toward the interference, each with its convergence property and computational complexity. This paper discusses some of the typical algorithms for DOA estimation and beamforming. The concept and details of each algorithm are provided. Smart antennas can significantly help in improving the performance of communication systems by increasing channel capacity and spectrum efficiency, extending range coverage, multiplexing channels with spatial division multiple access (SDMA), and compensating electronically for aperture distortion. They also reduce delay spread, multipath fading, co-channel interference, system complexity, bit error rates, and outage probability. In addition, smart antennas can locate mobile units or assist the location determination through DOA and range estimation. This capability can support and benefit many location-based services including emergency assistance, tracking services, safety services, billing services, and information services such as navigation, weather, traffic, and directory assistance

Performance Comparison Between Music And Esprit Algorithms For Direction Estimation Of Arrival Signals

This thesis examines and compares the performance of Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) for the estimation of Direction of Arrival (DOA) of incoming signals to the smart antenna. The comparison of these two algorithms was done on the basis of parameters like number of array elements, number of incoming signals, angle difference between the incoming signals, number of the samples taken of signal, processing time and SNR ratio. These two algorithms were implemented with MATLAB and SIMULINK for the experimental purpose. After all the experiments performed, it was analyzed that results obtained from both of the software were almost same. Comparing MUSIC\u27s results with ESPRIT, it was found that MUSIC is less prone to error than ESPRIT for almost all parametric tests. This superiority of MUSIC made it desirable to recommend it for DOA estimation in smart antenna system

Comparative and analysis of evaluation of several direction of arrival estimation methods

Modern-day, global, and clever array systems have several distinguished approaches with regard to a wireless device.  In this paper, a comparative analysis has been carried out amongst nine (DOA) algorithms: Capon, MUSIC, Bartlett, Pisarenko, Linear prediction, Maximum entropies, and Min-norm, Root-MUSIC, and ESPRIT. in this paper reduces the number of antennas and snaps necessary to observe six targets without interference for several DOA estimation methods. After comparing and analyzing all the algorithms, it has been shown that the music algorithm is the best algorithm that reduces interference and detects the desired sources. MATLAB [R2019b] was used in the simulation process

Detect and Pointing Algorithms Performance for a 2D Adaptive Antenna Array

In recent decades, we have witnessed a great progress in wireless communications. The huge amount of data that users expect to access has required an effort to increase the capacity of wireless networks. The main limitation of these communication systems is the increasing interference between channels and multipath fading. Smart antennas technology has emerged, solving some of these problems and improving the performance of wireless networks. This chapter addresses a group of algorithms, directions of arrival (DOA) and beamforming, applied to planar antenna arrays. The algorithms are simulated, and their performance is evaluated in terms of runtime, accuracy and dependence with signal-to-noise ratio (SNR), applied to a smart antenna system