UAV Velocity Measurement for Ground Moving Target

To satisfy the demand of measuring the velocity of ground moving target through unmanned aerial vehicle(UAV)electro-optical platform,two velocity measurement methods are proposed.Firstly,a velocity measurement method based on target localization is derived,using the position difference between two points with the advantages of easy deployment and realization.Then a mathematical model for measuring target velocity is built and described by 15 variables,i.e.UAV velocity,UAV attitude angular rate,camera direction angular rate and so on.Moreover,the causes of velocity measurement error are analyzed and a formula is derived for calculating the measurement error.Finally,the simulation results show that angular rate error has a strong influence on the velocity measurement accuracy,especially the UAV pitch angular rate error,roll angular rate error and the camera angular altitude rate error,thus indicating the direction for improving velocity measurement precision.

Best linear unbiased estimation algorithm with Doppler measurements in spherical coordinates

In an active radar-tracking system,the target-motion model is usually modeled in the Cartesian coordinates,while the radar measurement usually is obtained in polar/spherical coordinates.Therefore the target-tracking problem in the Cartesian coordinates becomes a nonlinear state estimation problem.A number of measurement-conversion techniques,which are based on position measurements,are widely used such that the Kalman filter can be used in the Cartesian coordinates.However,they have fundamental limitations to result in filtering performance degradation.In fact,in addition to position measurements,the Doppler measurement or range rate,containing information of target velocity,has the potential capability to improve the tracking performance.A filter is proposed that can use converted Doppler measurements（i.e.the product of the range measurements and Doppler measurements） in the Cartesian coordinates.The novel filter is theoretically optimal in the rule of the best linear unbiased estimation among all linear unbiased filters in the Cartesian coordinates,and is free of the fundamental limitations of the measurement-conversion approach.Based on simulation experiments,an approximate,recursive implementation of the novel filter is compared with those obtained by four state-of-the-art conversion techniques recently.Simulation results demonstrate the effectiveness of the proposed filter.

On-orbit target tracking and inspection by satellite formation

A new type of estimator is developed for the satellite formation to track and inspect on-orbit targets. The follower satellite in the formation works without relative sensors, and its target pointing commands are derived based on relative orbital dynamics. The centralized estimator based on truth measurement is designed, however, this estimator is proved unstable because of the lack of necessary measurement information. After that, an alternative estimator based on pseudo measurement is designed, and its observability and controllability are analyzed to qualitatively evaluate the convergence performance. Finally, an on-orbit target inspection scenario is numerically simulated to verify the performance of the estimator based on pseudo measurement.

Development of China′ s Auto Parts Industry ——Strategies, Targets and Measures (Abstracts)

Ⅰ. Development Strategy for China’ s Auto Parts Industry Carrying the whole industry forward breaking through in critical areas, achieving simultaneous development and joining the international division of labor.

Coordinated target localization base on pseudo measurement for clustered space robot

This paper presents a coordinated target localization method for clustered space robot.According to the different measuring capabilities of cluster members,the master-slave coordinated relative navigation strategy for target localization with respect to slavery space robots is proposed;then the basic mathematical models,including coordinated relative measurement model and cluster centralized dynamics,are established respectively.By employing the linear Kalman flter theorem,the centralized estimator based on truth measurements is developed and analyzed frstly,and with an intention to inhabit the initial uncertainties related to target localization,the globally stabilized estimator is designed through introduction of pseudo measurements.Furthermore,the observability and controllability of stochastic system are also analyzed to qualitatively evaluate the convergence performance of pseudo measurement estimator.Finally,on-orbit target approaching scenario is simulated by using semi-physical simulation system,which is used to verify the convergence performance of proposed estimator.During the simulation,both the known and unknown maneuvering acceleration cases are considered to demonstrate the robustness of coordinated localization strategy.

Comparative analysis of trade effects of anti-dumping measures targeting China vs.those initiated by China

Using the numbers of anti-dumping cases both in China and around the world, the value of imports and exports from 1995 to 2012, and the anti-dumping index (ADI) proposed by Finger and Murray in 1999, this paper analyzes the characteristics of anti-dumping measures that target China and those imposed by China, and constructs a multiple linear regression model. We try to show the effect of anti-dumping measures in either direction on the total value of China’s trade. This paper finds that both have great impact on export trade value. The intensity of the level of anti-dumping measures to which China is subject is positively correlated with total export value since this intensity, to a certain degree, can promote China’s industrial upgrading and the increase of the export of high value-added products. This paper further analyzes different effects of anti-dumping measures based on the method of technological content classification of Lall (2000). Finally, we put forward policy suggestions on how to enhance China’s export competitiveness by overcoming the effects of antidumping measures to which we are subject and by making proper use of antidumping measures on others.

An agent-based model with antibody dynamics information in COVID-19 epidemic simulation

Accurate prediction of the temporal and spatial characteristics of COVID-19 infection is of paramount importance for effective epidemic prevention and control.In order to accomplish this objective,we incorporated individual antibody dynamics into an agent-based model and devised a methodology that encompasses the dynamic behaviors of each individual,thereby explicitly capturing the count and spatial distribution of infected individuals with varying symptoms at distinct time points.Our model also permits the evaluation of diverse prevention and control measures.Based on our findings,the widespread employment of nucleic acid testing and the implementation of quarantine measures for positive cases and their close contacts in China have yielded remarkable outcomes in curtailing a less transmissible yet more virulent strain;however,they may prove inadequate against highly transmissible and less virulent variants.Additionally,our model excels in its ability to trace back to the initial infected case(patient zero)through early epidemic patterns.Ultimately,our model extends the frontiers of traditional epidemiological simulation methodologies and offers an alternative approach to epidemic modeling.

A portable high precision three dimensional trace measuring system for underwater target with high speed

The paper describes a portable high precision three-dimensional trace measuring system for underwater target with high speed. The mathematical model for location, the main error sources, the calibration method for the underwater array and the way to correct its state are discussed. Problems about the distance ambiguity and multi-path interference are also analyzed. Part of experimental results on lake and at sea are given as well.

Multidimensional poverty and types of impoverished counties in Gansu province of China

Gansu province,considered as one of the poorest provinces in China,faces great challenges in fighting against poverty.This study highlights the importance of studying multidimensional poverty in Gansu province.The Multidimensional Poverty Indices of 75 poverty-stricken counties in Gansu province are measured quantitatively.The main driving factors of poverty are identified through the construction and application of a multidimensional poverty measurement system,classifying the impoverished counties into several categories.This study provides a scientific basis for formulating effective policies to achieve sustainable poverty reduction and highquality development in the region after 2020.The results show that:(1)more than half of the poverty-stricken counties in Gansu province have a degree of multidimensional poverty that is below the median poverty level,with regional variations;(2)the main factors driving poverty in these counties include shortages in water and land resources,educational disruptions,undesirable medical conditions,and the underutilisation of labour,which show spatial variations;and(3)these poverty-stricken counties are categorised into four types:counties with fragile ecological environments and insufficient natural resources,counties with undesirable socio-economic conditions,counties with unfavourable conditions in development,and counties with relatively balanced development conditions.Finally,this paper proposes policy recommendations to achieve stable poverty alleviation based on different types of impoverished counties.