In order to improve the positioning ability of mobile Internet of Things sensing terminals and reduce the deviation caused by channel noise, this paper proposes a coordinate sensing algorithm for mobile Internet of Things terminal based on comprehensive weight calibration and mean jump estimation. Firstly, the localization data message is divided into three parts: coordinates, hops and ID of the localization node. The localization node parses the localization data message and obtains the hops and coordinates between the localization nodes. When only the localization node receives multiple localization data messages at the same time, the localization data message is divided into three parts. The coordinates of the positioning nodes are analyzed, and a triangular positioning method is constructed according to the coordinates of the received three positioning nodes. The coordinates are obtained accurately and the coordinate jitter is reduced. Subsequently, according to the mean square error theory, a neighborhood radius prepositioning method based on weight differential correction is designed to accurately obtain the positioning coordinates. Finally, according to the weight difference of different locating nodes in the network, a terminal coordinate correction scheme based on average hop estimation is designed. The equalization mechanism is adopted to enhance the network’s ability to capture nodes, and the inductive processing method is used to optimize the locating equations and modify the node coordinates, so as to improve the terminal sensing accuracy of the Internet of Things. The simulation results show that the proposed algorithm has lower deviation degree of node coordinates and better trajectory prediction ability than the current Internet of things node positioning technology.