Focusing on the Personal Handy-phone System (PHS) positioning service used in physical distribution logistics, a positioning method for improving positioning accuracy is invented. A disadvantage of PHS positioning is that measurement errors caused by the fluctuation of radio waves due to buildings around the terminal are large, ranging from several tens to several hundreds of meters. Therefore, in this study, a positioning method is developed, which learns radio intensity distribution of each cell station containing errors in advance, and matches them with new data according to the radio propagation map. Then the positioning accuracy is improved to about 1/2 that of the conventional positioning method.

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This paper presents an algorithm to judge moving and staying statuses of distribution equipment from continuous vibration measurement to realize low-cost and power-saving positioning systems. The algorism finds the acceleration threshold of moving and staying statuses with the probabilistically highest accuracy utilizing the characteristic of the vibration that the groups of acceleration data of statuses have little overlap and similar profiles. In the method, first the measured acceleration data are divided into two groups using tentative threshold. Then the threshold is updated repeatedly using Mahalanobis distance of two groups as a new vibration datum is added. Validity of the method is confirmed by the simulation with simply distributed samples and by an experiment with measured acceleration data of an automobile.

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