The growing demand for indoor positioning services has made high-precision positioning methods a key area of research. This paper presents a positioning method that addresses the limited accuracy of Single received signal strength (RSS) positioning methods by combining RSS and angle of arrival (AOA) measurements. Taylor expansion is employed to transform the nonlinear maximum likelihood (ML) optimization model, resulting in a linear matrix equation. We propose two indoor target position estimation methods: linear least squares (LLS) and distance-weighted least squares (D-WLLS). Lastly, an experimental platform is constructed in a real indoor environment to validate the effectiveness of the proposed method.
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Wang et al. (2024) studied this question.
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