Train speed detection and positioning are key technologies for improving the safety and efficiency of train operation. According to the domestic and foreign research in this field, a train detection and positioning system is designed based on embedded processor and multi-sensor information fusion. An axle speed sensor, a Doppler radar speed sensor, an acceleration sensor and query bails are employed to collect train status information. Federal Kalman filtering and the multi-sensor information fusion method are used to process these information in an embedded system. Problem of errors caused by train wheel diameter wearing, idling, sliding and other factors in tradition system is solved. Simulation results in Matlab show that the system can effectively improve the precision of train speed detection and positioning.
In order to handle the path breakage in the routing of mobile Wireless Sensor Network(WSN), a node-disjoint multipath routing algorithm based on the HSV color space is proposed. The algorithm creates a numeric (h, s, v) tuple for each link in the network and distributes these tuples into six basic planes in the color space, then it can find multiple node-disjoint paths within different basic color planes. It designs disjoint multipath routing maintenance mechanism based on variable intervals for mobile nodes link Received Signal Strength Indicator(RSSI) value detection, which is without any geographic location information. Experimental results show that when using three paths to transmit, the data transfer success rate of the proposed algorithm can achieve 80% above, and other contrastive classic algorithms are all less than 70%. In addition, it also has good performance on the network throughput and energy consumption .