Accurate estimation of signal direction of arrival (DOA) has many applications in communication and radar systems. For example, in defense application, it is important to identify the direction of possible threat. One example of commercial application is to identify the direction of emergency cell phone call such that the rescue team can be dispatched to the proper location. DOA estimation using a fixed antenna has many limitations. Its resolution is limited by the mainlobe beamwidth of the antenna. Antenna mainlobe beamwidth is inversely proportional to its physical size. Improving the accuracy of angle measurement by increasing the physical aperture of the receiving antenna is not always a good option. Certain systems such as a missile seeker or aircraft antenna have physical size limitations; therefore, they have relatively wide mainlobe beamwidth. Consequently, the resolution is quite poor. Also, if there are multiple signals falling in the antenna mainlobe, it will be difficult to distinguish them. Instead of using a filxed antenna, an array antenna system with innovative signal processing would enhance the resolution of signal DOA. It also has the ability to identify multiple targets. Two types of signal processing methods, model based and eigen-analysis estimation techniques, are presented in this paper. The model based approach models the observed data as the output of a linear shift invariant system driven by zero mean white noise. The signal's DOA can be estimated by evaluating the model parameters. This approach has properties similar to the maximum entropy spectrum estimation [1].


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    Titel :

    Direction of Arrival Estimation using Advanced Signal Processing


    Beteiligte:
    Grice, Marshall (Autor:in) / Rodenkirch, Jeff (Autor:in) / Yakovlev, Anatoly (Autor:in) / Hwang, H. K. (Autor:in) / Aliyazicioglu, Zekeriya (Autor:in) / Lee, Anne (Autor:in)


    Erscheinungsdatum :

    01.06.2007


    Format / Umfang :

    8380021 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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