Improved Study on Position Measurement System for Linear Motor Applied in Electromagnetic Launch System

The linear motor applied in electromagnetic emission system uses a closed loop position control strategy,which needs a set of position measurement system with high reliability,high resolution and integration to achieve real-time acquisition and analysis of position signals.The existing position controller is based on the simple logic chip design without memory function,and does not have the storage analysis and preprocessing function to position signals.Therefore,the system has insufficient scalability,low integration and reliability.Aiming at the improvement of the existing position measurement system,an intelligent position measurement system integrating the functions of position signals acquisition,processing and uploading,data storage and analysis is proposed in this paper,and its working principle and system composition are discussed in detail.The position,speed and acceleration obtained on the electromagnetic emission platform are in good agreement with the expected value of the system.As results,the feasibility and accuracy of the improved integrated intelligent position measurement system are verified,and the control performance of the system is also satisfied well,which can be good guidance and reference for subsequent engineering practice.

Hierarchical and probabilistic quantum information splitting of an arbitrary two-qubit state via two cluster states

Based on non-maximally entangled four-particle cluster states, we propose a new hierarchical information splitting protocol to probabilistically realize the quantum state sharing of an arbitrary unknown two-qubit state. In this scheme, the sender transmits the two-qubit secret state to three agents who are divided into two grades with two Bell-state measurements,and broadcasts the measurement results via a classical channel. One agent is in the upper grade and two agents are in the lower grade. The agent in the upper grade only needs to cooperate with one of the other two agents to recover the secret state but both of the agents in the lower grade need help from all of the agents. Every agent who wants to recover the secret state needs to introduce two ancillary qubits and performs a positive operator-valued measurement(POVM) instead of the usual projective measurement. Moreover, due to the symmetry of the cluster state, we extend this protocol to multiparty agents.

Probabilistic Teleportation of an Arbitrary Two-Qubit State via Positive Operator-Valued Measurement with Multi Parties

We propose a novel scheme to probabilistically transmit an arbitrary unknown two-qubit quantum state via Positive Operator-Valued Measurement with the help of two partially entangled states. In this scheme, the teleportation with two senders and two receives can be realized when the information of non-maximally entangled states is only available for the senders. Furthermore, the concrete implementation processes of this proposal are presented, meanwhile the classical communication cost and the successful probability of our scheme are calculated.

Precise vehicle ego-localization using feature matching of pavement images

Purpose–Precise vehicle localization is a basic and critical technique for various intelligent transportation system(ITS)applications.It also needs to adapt to the complex road environments in real-time.The global positioning system and the strap-down inertial navigation system are two common techniques in thefield of vehicle localization.However,the localization accuracy,reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding,vision enhancement and automatic parking.Aiming at the problems above,this paper aims to propose a precise vehicle ego-localization method based on image matching.Design/methodology/approach–This study included three steps,Step 1,extraction of feature points.After getting the image,the local features in the pavement images were extracted using an improved speeded up robust features algorithm.Step 2,eliminate mismatch points.Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust.Step 3,matching of feature points and trajectory generation.Findings–Through the matching and validation of the extracted local feature points,the relative translation and rotation offsets between two consecutive pavement images were calculated,eventually,the trajectory of the vehicle was generated.Originality/value–The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.