Earticle

The long PN code in a Binary Offset Carrier (BOC) modulated signal has a higher rate than the GPS C/A code, which makes the acquisition process in the new global navigation satellite system (GNSS) much more complex. To achieve a fast acquisition of the GNSS signal with a reduced number of correlators and low computational complexity, a two-stage deterministic compressed (DS) GNSS acquisition technique has been proposed. Nevertheless, the ambiguous threat of BOC signal isn’t taken into account in the DS technique. To eliminate the ambiguity threat in the acquisition process of BOC (m, n) signal, an unambiguous deterministic compressed acquisition is proposed in this paper. The main idea of the proposed technique is to introduce a simplified GRASS algorithm in the second stage measurement. Theoretical analysis and simulation results show that, at the expense of some performance degradation the proposed technique can completely remove the undesired positive side peaks of BOC (m, n) signal, and reduce the chance of false peak acquisition compared with the DS technique.

Optical code division multiple access system (OCDMA) has been important with increasing demands of high capacity and speed for communication in optical networks. Due to OCDMA technique high efficiency is achieved, hence fiber bandwidth is fully used .In this paper we will focus on DCS (Dynamic cyclic shift) code with their different detection technique using optiwave system design tool. Due to this codes we will eliminated MAI (multiple access interference) and improve BER (bit error rate) , PIIN( Phase induced intensity noise) and make orthogonality between users in the system .We will use two different detection technique i.e Direct detection technique and AND subtraction detection technique to implement the codes with different parameters. In this paper, the study of different parameters is based on conference a paper that is mainly demonstrated on an experiment to Enhancement a performance of DCS (Dynamic cyclic shift) code with there different parameter of OCDMA using optiwave system design tool.

In view of the problem of particle degradation and tracking accuracy in the standard particle filter tracking target algorithm, a new improved particle filter algorithm called Iterated Cubature Kalman Particle Filter (ICKPF) is proposed in this paper. The new ICKPF algorithm is based on the Markov Chain Monte Carlo (MCMC), and the cubature rule based on numerical integration method is used to calculate the mean and covariance, which generates the proposal distribution for the particle filter. The current measurements are integrated into the proposal distribution. Therefore, degree of approximation to the system posterior density is improved. Simulation results show that the estimation error of the ICKPF-MCMC algorithm is much better than other algorithms.

Vision navigation technology of the autonomous walking robot has been conducted in the research. Based on the characteristics of picking robot working environment, the visual system for the independent walking car is designed, which applies monocular camera to obtain images of marking lines on the surface of road for pre processing. Using the image gray contrast constraints determines the information of the effective area on the surface of road. Then the Hough linear detection combined with constraint will be used for the recognition and detection of the indication line on the surface, and the information of visual examination path will be fed back to the car control system as following. Through the ultrasonic sensors on the head of the walking car, the walking car can detect the obstacle at the same time. According to the real-time feedback data of ultrasonic sensor, fuzzy propulsion and calculation determine the information of the obstacles on the road surface ahead of time in order to achieve the function of real-time obstacle avoidance. The result of visual navigation test shows that maximum deviation of the car walking straight line based on visual navigation system is 1.5cm and the maximum deviation of curve walking is 6cm. The success rate of obstacle avoidance is 96.67%, which can meet the requirement of the vision navigation of picking robot and provide technical support for the autonomous navigation and intelligent operation of picking robot.

In order to make better use of the open and free timing service provided by beidou satellite navigation system, and get rid of the dependence of computer terminal system’s timing on GPS, this paper sets up a timing hardware circuit with the platform using the BDS receiving module UM220 produced by Hexinxingtong company, based on analyzing the BDS’s functional features and timing principles, and presents the implementation of computer terminal timing software and its operating process. Results of system running show that the designed timing device has high reliability and its timing precision could meet the demand of computer terminal system, thus which has a greater practical value.

A novel rectangular microstrip antenna for ultrawideband applications is proposed. The ultrawide frequency response is achieved by determining the dimensions of the radiating patch of antenna .The simulated reflection coefficient is smaller than -10 dB for fractional bandwidth greater than 20%. The fractional bandwidth is further enhanced by providing improvements in the proposed design. Besides a directive radiation pattern, high efficiency and a constant gain is achieved in the operating bandwidth.

In the field of image denoising, nonlocal image denoising algorithm is a nonlinear, space average denoising algorithm, it will not cause boundary blurred, it is an effective denoising algorithm. But its application still has limitations because of it taking much longer time, in this paper, the method was improved, image signal can be divided into high frequency and low frequency part using wavelet decomposition, nonlocal denoising algorithm is used in low-frequency approximate signal, for high frequency detail signals using wavelet filtering method for denoising. The experimental results show that the method improves the speed of image processing and has good practical value.

It is difficult to track, count and separate the moving bars at a high speed on production line for their overlap and accumulation. Therefore, it is necessary to establish a reliable, practical recognition and segmentation mechanism for the adhered bars. A new solution to the problem of bars adhesion is proposed: a support vector machine is constructed to recognize the adhesion type of bars by the feature vectors of training samples. The geometric feature values and moment feature values based on Blob regions in images are extracted, which is the input feature vector of support vector machine. The trained classifier is used for identifying the adhesion type of bars in images. Finally, classification and recognition is carried by support vector machine. The experimental results show that the recognition accuracy based RBF kernel achieves 100%. The method is feasible and effective for the recognition and segmentation of the adhered bars.