Accurately estimating the direction of arrival (DOA) of wideband signals with a sensorarray is critical in communications, radar, and the internet of Things. This paper proposes two single-source DOA estimation metho...
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Accurately estimating the direction of arrival (DOA) of wideband signals with a sensorarray is critical in communications, radar, and the internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensorinter-elementspacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cram & eacute;r-Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensorarray radar system confirms that our methods are feasible for practical engineering applications.
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