4.5 Article

Analysis and Design of a MuSiC-Based Angle of Arrival Positioning System

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ASSOC COMPUTING MACHINERY
DOI: 10.1145/3577927

关键词

Positioning; localization; angle of arrival; AoA; incident angle; direction of arrival; DoA; secondary RADAR; Fast Fourier Transform; FFT; multiple signal classification; MuSiC; phase difference; spectrum; weighting; relevance; quality; area ratio

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In this research article, a concept for a secondary RADAR angle of arrival based system with cooperative targets is investigated. The system uses Multiple Signal Classification (MuSiC) to determine the angles of incidence and is evaluated through simulations and by developing hardware, firmware, and software. Novel methods for obtaining incident angles from the spectrum are proposed, along with algorithms for computing the final position. Experimental results show improved positioning accuracy compared to classical MuSiC estimation in both outdoor and indoor environments.
In this research article, a concept for a secondary RAdio Direction And Ranging (RADAR) angle of arrival based system with cooperative targets transmitting at 2.4 GHz and using Multiple Signal Classification (MuSiC) to determine the angles of incidence is investigated. In addition to introducing common algorithms and presenting thorough derivations, the system is first examined through simulations. To prove the concept, hardware, firmware, and software are developed. For MuSiC, we propose three novel methods to obtain the correct incident angle from the spectrum, especially in strong multipath environments. These methods work either for a single spectrum or for a combination recorded at multiple times. Together with the estimated angles of incidence, our methods determine measures on the respective likelihoods. Based on this, we additionally propose two algorithms for computing the final position. Our system is characterized in both a simple 20 m x 15 m outdoor and a 17 m x 13 m multipath indoor environment, where we achieve a mean angular error of 3 degrees and a mean positioning error of 0.67 m for the former using only four base stations with four antennas each. Our novel approach shows position accuracy improvements of 15% outdoors and 25% indoors compared to classical MuSiC estimation.

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