Position Estimation Based on RSS and DOA Path Loss Model
In complex indoor environment, wireless positioning is mainly affected by non-line-of-sight (NLOS) and multipath problem. In our previous work, we use the ray-tracing model to establish a model of time-of-arrival (TOA) and direction-of-arrival (DOA) based on virtual station (VS) to solve this problem. The advantage of this model is converting NLOS problem into line-of-sight (LOS) problem with VS. It also develops a two-step weighted least squares (TSWLS) positioning estimator using the hybrid TOA and DOA values and have high accuracy. However, it did not take into account the loss of the signal during the propagation process. Based on previous models, developing a Gauss-Markov theorem positioning estimator using the hybrid DOA and Received Signal Strength (RSS) values, taking into account the loss of signal in the propagation process because of transmission, reflection and diffraction, and achieved higher accuracy.
KeywordsRay-tracing model DOA RSS Gauss-Markov theorem Indoor positioning system
This work is supported by the National Natural Science Foundation of China under Grant 61601494.
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