Hybrid RSS/AOA Localization using Approximated Weighted Least Square in Wireless Sensor Networks
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Published on: September 8, 2023
SeYoung Kang1, TaeHyun Kim2, WonZoo Chung1
1Division of Computer and Communications Engineering, Korea University, Seoul 02841, Korea.
Abstract:
We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.
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