Ionospheric TEC （total electron content） time series are derived from GPS measurements at 13 stations around the epicenter of the 2008 Wenchuan earthquake. Defining anomaly bounds for a sliding window by quartile an...Ionospheric TEC （total electron content） time series are derived from GPS measurements at 13 stations around the epicenter of the 2008 Wenchuan earthquake. Defining anomaly bounds for a sliding window by quartile and 2-standard deviation of TEC values, this paper analyzed the characteristics of ionospheric changes before and after the destructive event. The Neyman-Pearson signal detection method is employed to compute the probabilities of TEC abnormalities. Result shows that one week before the Wenchuan earthquake, ionospheric TEC over the epicenter and its vicinities displays obvious abnormal disturbances, most of which are positive anomalies. The largest TEC abnormal changes appeared on May 9, three days prior to the seismic event. Signal detection shows that the largest possibility ofTEC abnormity on May 9 is 50.74%, indicating that ionospheric abnormities three days before the main shock are likely related to the preparation process of the Ms8.0 Wenchuan earthquake.展开更多
A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,t...A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.展开更多
基金supported by the Key Technology Research and Development Program of China (2008BAC35B02)
文摘Ionospheric TEC （total electron content） time series are derived from GPS measurements at 13 stations around the epicenter of the 2008 Wenchuan earthquake. Defining anomaly bounds for a sliding window by quartile and 2-standard deviation of TEC values, this paper analyzed the characteristics of ionospheric changes before and after the destructive event. The Neyman-Pearson signal detection method is employed to compute the probabilities of TEC abnormalities. Result shows that one week before the Wenchuan earthquake, ionospheric TEC over the epicenter and its vicinities displays obvious abnormal disturbances, most of which are positive anomalies. The largest TEC abnormal changes appeared on May 9, three days prior to the seismic event. Signal detection shows that the largest possibility ofTEC abnormity on May 9 is 50.74%, indicating that ionospheric abnormities three days before the main shock are likely related to the preparation process of the Ms8.0 Wenchuan earthquake.
基金Sponsored by the National Natural Science Foundation of China (60773129)the Excellent Youth Science and Technology Foundation of Anhui Province of China ( 08040106808)
文摘A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.
