3D laser scanning strategy based on cascaded deep neural network

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s.The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.

SF^2HDL： A Computational Tool of State Transition Diagram Translation

The lack of standard to electronic circuits modeling made possible the development of many tools and modeling languages for electronic circuits. In this way, several tools to be used on different descriptions stage of the designs are necessary. This paper presents a tool called SF^2HDL （Stateflow to Hardware Description Language or State Transition Table） that translates a finite state machine on state transition diagram representation, described by Stateflow tool, into an input file standard for TABELA program or into a file behavioral VHDL （Very High Speed Integrated Circuits Hardware Description Language） directly. The TABELA program was used to optimization this finite state machine. After that, the TAB2VHDL program was used to generate the VHDL code on register transfer level, what permits comparisons with results obtained by synthesis. The finite state machine must be described by Mealy model and the user can describe the machine on high level abstraction using all Simulink supports. The tool was very efficient on computational cost and it made translation of several cases, for the two VHDL description models. Every state machine translated was simulated and implemented on device EP2C20F484C7 using Quartus II environment.

Particle Filter and Its Application in the Integrated Train Speed Measurement

Particle filter(PF) can solve the problem of state estimation under strong non-linear non-Gaussian noise condition with respect to traditional Kalman filter(KF) and those improved KFs such as extended KF(EKF) and unscented KF(UKF). However, problems such as particle depletion and particle degradation affect the performance of PF. Optimizing the particle set to high likelihood region with intelligent optimization algorithm results in a more reasonable distribution of the sampling particles and more accurate state estimation. In this paper, a novel bird swarm algorithm based PF(BSAPF) is presented. Firstly, different behavior models are established by emulating the predation, flight, vigilance and follower behavior of the birds. Then, the observation information is introduced into the optimization process of the proposal distribution with the design of fitness function. In order to prevent particles from getting premature(being stuck into local optimum) and increase the diversity of particles, Lévy flight is designed to increase the randomness of particle's movement. Finally,the proposed algorithm is applied to estimate the speed of the train under the condition that the measurement noise of the wheel sensor is non-Gaussian distribution. Simulation study and experimental results both show that BSAPF is more accurate and has more effective particle number as compared with PF and UKF, demonstrating the promising performance of the method.

Realization of Communication Protocols of RFID R/W Device Based on CPLD

The function of the communication module of Radio FrequencyIdentification(RFID)system is de- scribed. Based on Electronic DesignAutomation(EDA), the implementation of digital module of RFID usingXIL- INX XC9500 series Complex Programmable Logic Device(CPLD)isintroduced modularized and layering methods In communicationprotocols of RFID systems are employed to enhance the systemperformance and facilitate the de- Sign. To ensure the security andreliability of data transmission, a new method of combing encryptionand error cor- Rection is employed and described in detail.