2 research outputs found
A Simple Geometric-Aware Indoor Positioning Interpolation Algorithm Based on Manifold Learning
Interpolation methodologies have been widely used within the domain of indoor
positioning systems. However, existing indoor positioning interpolation
algorithms exhibit several inherent limitations, including reliance on complex
mathematical models, limited flexibility, and relatively low precision. To
enhance the accuracy and efficiency of indoor positioning interpolation
techniques, this paper proposes a simple yet powerful geometric-aware
interpolation algorithm for indoor positioning tasks. The key to our algorithm
is to exploit the geometric attributes of the local topological manifold using
manifold learning principles. Therefore, instead of constructing complicated
mathematical models, the proposed algorithm facilitates the more precise and
efficient estimation of points grounded in the local topological manifold.
Moreover, our proposed method can be effortlessly integrated into any indoor
positioning system, thereby bolstering its adaptability. Through a systematic
array of experiments and comprehensive performance analyses conducted on both
simulated and real-world datasets, we demonstrate that the proposed algorithm
consistently outperforms the most commonly used and representative
interpolation approaches regarding interpolation accuracy and efficiency.
Furthermore, the experimental results also underscore the substantial practical
utility of our method and its potential applicability in real-time indoor
positioning scenarios
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Indoor Localization Using Direction of Arrival Approach
In this paper, a Direction of Arrival (DOA) based system is proposed. This method searches the direction relative to the array to find where the signal source is located. The proposed system can achieve sub-meter level accuracy with a near real-time update rate. Also, we introduced several refinement methods including a compact tracking system that is compatible with small items, a DOA accuracy prediction function, a method based on linear prediction to expand antenna array to create a virtual antenna matrix, and a novel method for multipath effect cancellation. Overall, the proposed system achieved sub-meter level accuracy, and the functionality of the refinement methods has been approved in the simulation