A covariance matrix reconstruction approach for single snapshot direction of arrival estimation

Achieving accurate single snapshot direction of arrival (DOA) information significantly improves communication performance. This paper investigates an accurate and high-resolution DOA estimation technique by enabling single snapshot data collection and enhancing DOA estimation results compared to multiple snapshot methods. This is carried out by manipulating the incoming signal covariance matrix while suppressing undesired additive white Gaussian noise (AWGN) by actively updating and estimating the antenna array manifold vector. We demonstrated the estimation performance in simulation that our proposed technique supersedes the estimation performance of existing state-of-the-art techniques in various signal-to-noise ratio (SNR) scenarios and single snapshot sampling environments. Our proposed covariance-based single snapshot (CbSS) technique yields the lowest root-mean-squared error (RMSE) against the true DOA compared to root-MUSIC and the partial relaxation (PR) approach for multiple snapshots and a single signal source environment. In addition, our proposed technique presents the lowest DOA estimation performance degradation in a multiple uncorrelated and coherent signal source environment by up to 25.5% with nearly negligible bias. Lastly, our proposed CbSS technique presents the best DOA estimation results for a single snapshot and single-source scenario with an RMSE of 0.05° against the true DOA compared to root-MUSIC and the PR approach with nearly negligible bias as well. A potential application for CbSS would be in a scenario where accurate DOA estimation with a small antenna array form factor is a limitation, such as in the intelligent transportation system industry and wireless communication

An Improvement Of Doa Estimation On Rfid Systems

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2011Bu tez çalışmasında, pasif RFID etiketlerinin 2-boyutta yerlerinin tespit edilmesi için geliştirilmiş sistemle yapılan çalışmalara yer verilmektedir. Bu sistem anten dizisi, okuyucu ve veri toplama cihazlarından oluşmaktadır. Sistem ve etiketin haberleşmesi, çalışmada kullanılan etiket pasif olduğundan okuyucuya bağlı bir dipol antenden yayılan işaretle gönderilen sorgu paketine, etiketin kendisine gelen dalgadan aldığı güçle cevap hazırlayıp göndermesi şeklinde olur. Cevap işareti anten dizisiyle alınıp veri toplama cihazından geçtikten sonra bilgisayara ulaşır. Bilgisayarda MATLAB program diliyle yazılmış algoritmayla işlenir ve etiketin yeri tespit edilir. Tez kapsamında yapılan çalışmalar anten dizisinin kolay ve ucuz bir şekilde tekrar kalibre edilmesi, yansımalı ortamda pasif etiketlerinin doğru bir şekilde yerlerinin belirlenmesi ve son olarak radyoastronomik görüntülemede kullanılan CLEAN algoritmasının uygulanmasının yer tespit etme algoritmasında karşılaşılan bazı problemlerin çözümü olarak sunulması olarak sıralanabilir.In this thesis, a set of studies related to 2-D direction finding system which is designed for localizing passive RFID tags is included. This system consists of antenna array, reader and data collector devices. Because of the tag’s being passive, it uses the power of the incoming request signal which is transmitted by the dipole antenna connected to the reader to prepare a response and communicate with the system. This response is collected by the data collector device and sent to the personal computer. It is processed with Direction of Arrival estimation algorithm written in MATLAB and the localization of the tag in 2-D is found. The context of the thesis can be listed as follows: recalibration of the array cheaply and easily, localization of passive tags in multipath environment and proposition of applying a post-processing algorithm which is commonly used in radio astronomy imaging to the direction finding system.Yüksek LisansM.Sc

High-resolution Direction-of-Arrival estimation

Direction of Arrival (DOA) estimation is considered one of the most crucial problems in array signal processing, with considerable research efforts for developing efficient and effective direction-finding algorithms, especially in the transportation industry, where the demand for an effective, real-time, and accurate DOA algorithm is increasing. However, challenges must be addressed before real-world deployment can be realised. Firstly, there is the requirement for fast computational time for real-time detection. Secondly, there is a demand for high-resolution and accurate DOA estimation. In this thesis, two state-of-the-art DOA estimation algorithms are proposed and evaluated to address the challenges. Firstly, a novel covariance matrix reconstruction approach for single snapshot DOA estimation (CbSS) was proposed. CbSS was developed by exploiting the relationship between the theoretical and sample covariance matrices to reduce estimation error for a single snapshot scenario. CbSS can resolve accurate DOAs without requiring lengthy peak searching computational time by computationally changing the received sample covariance matrix. Simulation results have verified that the CbSS technique yields the highest DOA estimation accuracy by up to 25.5% compared to existing methods such as root-MUSIC and the Partial Relaxation approach. Furthermore, CbSS presents negligible bias when compared to the existing techniques in a wide range of scenarios, such as in multiple uncorrelated and coherent signal source environments. Secondly, an adaptive diagonal-loading technique was proposed to improve DOA estimation accuracy without requiring a high computational load by integrating a modified novel and adaptive diagonal-loading method (DLT-DOA) to further improve estimation accuracy. An in-depth simulation performance analysis was conducted to address the challenges, with a comparison against existing state-of-the-art DOA estimation techniques such as EPUMA and MODEX. Simulation results verify that the DLT-DOA technique performs up to 8.5% higher DOA estimation performance in terms of estimation accuracy compared to existing methods with significantly lower computational time. On this basis, the two novel DOA estimation techniques are recommended for usage in real-world scenarios where fast computational time and high estimation accuracy are expected. Further research is needed to identify other factors that could further optimize the algorithms to meet different demands