The ranging algorithm is commonly used based on received signal strength indicator (RSSI), based on time of arrival (TOA), time difference of arrival (TDA), and AOA based on the signal arrival angle (angle of arrival) positioning method. Īt present, the positioning algorithm can be divided into two categories: based on ranging positioning algorithm and no ranging positioning algorithm. As an important information-processing technology in the field of smart home, indoor positioning technology is the key to improve the comfort, safety, and intelligence of home environment and build an efficient smart home system. With the development of Internet of things and mobile Internet technology, smart home is gradually entering people’s daily life. The simulation results show that the proposed method has strong anti-RSSI perturbation and high positioning accuracy. Finally, according to the actual coordinates of the reference node, the coordinate transformation is performed by the planar four-parameter model, and the position of the node in the actual coordinate system is obtained. Then, based on the RSSI data, the dissimilarity matrix is constructed, and the relative coordinates of the nodes in the low-dimensional space are obtained by NMDS solution. First, Gaussian filtering is performed on the received plurality of sets of RSSI signals to eliminate abnormal fluctuations of the RSSI. Aiming at the problem that the indoor target location algorithm based on received signal strength (RSSI) in the IoT environment is susceptible to interference and large fluctuations, an indoor localization algorithm combining RSSI and nonmetric multidimensional scaling (NMDS) is proposed (RSSI- NMDS).
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