An Improved Underground Location Algorithm Based on Convex Sets of RSSI

Location algorithm based on fingerprint has been applied to underground tunnel of coal mines. However, obvious and unignorable errors will occur if reference locations are selected sparsely when detecting unknown points, which may make it difficult for locating people in coal mines. Hence, an underground location algorithm based on convex sets of Received Signal Strength Indication (RSSI) is proposed in this paper. Many reference location points are deployed at the experimental tunnel every 5m both 2 sides as depicted in Fig. (5) shows, then a reference location can be randomly selected. Firstly, calculate the Euclidean distance between unknown points and reference locations in a fingerprint database established by using RSSI value that de-noised by the Kalman filter algorithm. Secondly, select several reference locations that mostly match with unknown points, construct a convex. Finally, take the coordinates of centroid of the convex as the coordinates of the unknown points. The simulation experiments indicate that the proposed algorithm locates unknown points with higher accuracy than the traditional one based on fingerprint.