Multi-objective Evolutionary Algorithm Based on Target Space Partitioning Method

Considering the defects of conventional optimization methods, a novel optimization algorithm is introduced in this paper. Target space partitioning method is used in this algorithm to solve multi-objective optimization problem, thus achieve the coherent solution which can meet the requirements of all target functions, and improve the population's overall evolution level. The algorithm which guarantees diversity preservation and fast convergence to the Pareto set is applied to structural optimization problems. The empirical analysis supports the algorithm and gives an example with program.

A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

Research on spatial-variant property of bistatic ISAR imaging plane of space target

The imaging plane of inverse synthetic aperture radar （ISAR） is the projection plane of the target. When taking an image using the range-Doppler theory, the imaging plane may have a spatial-variant property, which causes the change of scatter＇s projection position and results in migration through resolution cells, In this study, we focus on the spatial-variant property of the imaging plane of a three-axis-stabilized space target. The innovative contributions are as follows. 1） The target motion model in orbit is provided based on a two-body model. 2） The instantaneous imaging plane is determined by the method of vector analysis. 3） Three Euler angles are introduced to describe the spatial-variant property of the imaging plane, and the image quality is analyzed. The simulation results confirm the analysis of the spatial-variant property. The research in this study is significant for the selection of the imaging segment, and provides the evidence for the following data processing and compensation algorithm.

Ultra-lightweight CNN design based on neural architecture search and knowledge distillation: A novel method to build the automatic recognition model of space target ISAR images

In this paper,a novel method of ultra-lightweight convolution neural network(CNN)design based on neural architecture search(NAS)and knowledge distillation(KD)is proposed.It can realize the automatic construction of the space target inverse synthetic aperture radar(ISAR)image recognition model with ultra-lightweight and high accuracy.This method introduces the NAS method into the radar image recognition for the first time,which solves the time-consuming and labor-consuming problems in the artificial design of the space target ISAR image automatic recognition model(STIIARM).On this basis,the NAS model’s knowledge is transferred to the student model with lower computational complexity by the flow of the solution procedure(FSP)distillation method.Thus,the decline of recognition accuracy caused by the direct compression of model structural parameters can be effectively avoided,and the ultralightweight STIIARM can be obtained.In the method,the Inverted Linear Bottleneck(ILB)and Inverted Residual Block(IRB)are firstly taken as each block’s basic structure in CNN.And the expansion ratio,output filter size,number of IRBs,and convolution kernel size are set as the search parameters to construct a hierarchical decomposition search space.Then,the recognition accuracy and computational complexity are taken as the objective function and constraint conditions,respectively,and the global optimization model of the CNN architecture search is established.Next,the simulated annealing(SA)algorithm is used as the search strategy to search out the lightweight and high accuracy STIIARM directly.After that,based on the three principles of similar block structure,the same corresponding channel number,and the minimum computational complexity,the more lightweight student model is designed,and the FSP matrix pairing between the NAS model and student model is completed.Finally,by minimizing the loss between the FSP matrix pairs of the NAS model and student model,the student model’s weight adjustment is completed.Thus the ultra-lightweight and high accuracy STIIARM is obtained.The proposed method’s effectiveness is verified by the simulation experiments on the ISAR image dataset of five types of space targets.

Test research on IR radiation characteristics control of space target using cryogenic vacuum multilayer insulation film structure

In order to achieve the objective of controlling IR radiation characteristics of space target,we design multilayer insulation film structure to cover the target.In space environment the structure comes to cryogenic vacuum multilayer insulation film structure.It can quickly lower the surface temperature of space target,approaching to the ultra-low temperature of the space environment.A vacuum simulation verification test was designed and performed.Through the analysis of test results,we can see that the surface temperature of space target covered by the structure changes with the ambient temperature,having no direct relationship with internal temperature of the target.Therefore,the designed cryogenic vacuum multilayer insulation film structure has excellent IR radiation control performance.It can reduce the target’s IR radiation intensity so as to reduce the probability of detection by IR detectors.

High resolution inverse synthetic aperture radar imaging of three-axis-stabilized space target by exploiting orbital and sparse priors

The development of inverse synthetic aperture radar （ISAR） imaging techniques is of notable significance for moni- toring, tracking and identifying space targets in orbit. Usually, a well-focused ISAR image of a space target can be obtained in a deliberately selected imaging segment in which the target moves with only uniform planar rotation. However, in some imaging segments, the nonlinear range migration through resolution cells （MTRCs） and time-varying Doppler caused by the three-dimensional rotation of the target would degrade the ISAR imaging performance, and it is troublesome to realize accurate motion compensation with conventional methods. Especially in the case of low signal-to-noise ratio （SNR）, the estimation of motion parameters is more difficult. In this paper, a novel algorithm for high-resolution ISAR imaging of a space target by using its precise ephemeris and orbital motion model is proposed. The innovative contributions are as follows. 1） The change of a scatterer projection position is described with the spatial-variant angles of imaging plane calculated based on the orbital motion model of the three-axis-stabilized space target. 2） A correction method of MTRC in slant- and cross-range dimensions for arbitrarily imaging segment is proposed. 3） Coarse compensation for translational motion using the precise ephemeris and the fine compensation for residual phase errors by using sparsity-driven autofo- cus method are introduced to achieve a high-resolution ISAR image. Simulation results confirm the effectiveness of the proposed method.

A parallel pipeline connected-component labeling method for on-orbit space target monitoring

The paper designs a peripheral maximum gray differ-ence(PMGD)image segmentation method,a connected-compo-nent labeling(CCL)algorithm based on dynamic run length(DRL),and a real-time implementation streaming processor for DRL-CCL.And it verifies the function and performance in space target monitoring scene by the carrying experiment of Tianzhou-3 cargo spacecraft(TZ-3).The PMGD image segmentation method can segment the image into highly discrete and simple point tar-gets quickly,which reduces the generation of equivalences greatly and improves the real-time performance for DRL-CCL.Through parallel pipeline design,the storage of the streaming processor is optimized by 55%with no need for external me-mory,the logic is optimized by 60%,and the energy efficiency ratio is 12 times than that of the graphics processing unit,62 times than that of the digital signal proccessing,and 147 times than that of personal computers.Analyzing the results of 8756 images completed on-orbit,the speed is up to 5.88 FPS and the target detection rate is 100%.Our algorithm and implementation method meet the requirements of lightweight,high real-time,strong robustness,full-time,and stable operation in space irradia-tion environment.

Unified Modeling Approach of Kinematics, Dynamics and Control of a Free-Flying Space Robot Interacting with a Target Satellite

In this paper a unified control-oriented modeling approach is proposed to deal with the kinematics, linear and angular momentum, contact constraints and dynamics of a free-flying space robot interacting with a target satellite. This developed approach combines the dynamics of both systems in one structure along with holonomic and nonholonomic constraints in a single framework. Furthermore, this modeling allows consid-ering the generalized contact forces between the space robot end-effecter and the target satellite as internal forces rather than external forces. As a result of this approach, linear and angular momentum will form holonomic and nonholonomic constraints, respectively. Meanwhile, restricting the motion of the space robot end-effector on the surface of the target satellite will impose geometric constraints. The proposed momentum of the combined system under consideration is a generalization of the momentum model of a free-flying space robot. Based on this unified model, three reduced models are developed. The first reduced dynamics can be considered as a generalization of a free-flying robot without contact with a target satellite. In this re-duced model it is found that the Jacobian and inertia matrices can be considered as an extension of those of a free-flying space robot. Since control of the base attitude rather than its translation is preferred in certain cases, a second reduced model is obtained by eliminating the base linear motion dynamics. For the purpose of the controller development, a third reduced-order dynamical model is then obtained by finding a common solution of all constraints using the concept of orthogonal projection matrices. The objective of this approach is to design a controller to track motion trajectory while regulating the force interaction between the space robot and the target satellite. Many space missions can benefit from such a modeling system, for example, autonomous docking of satellites, rescuing satellites, and satellite servicing, where it is vital to limit the con-tact force during the robotic operation. Moreover, Inverse dynamics and adaptive inverse dynamics control-lers are designed to achieve the control objectives. Both controllers are found to be effective to meet the specifications and to overcome the un-actuation of the target satellite. Finally, simulation is demonstrated by to verify the analytical results.

Evaluation of Trajectory Error Effects in BP Based Space Target ISAR Imaging

The space target imaging is important in the development of space technology.Due to the availability of trajectory information of the space targets and the arising of rapid parallel processing hardware,the back projection (BP) method has been applied to synthetic aperture radar (SAR) imaging and shows a number of advantages as compared with conventional Fourier-domain imaging algorithms.However,the practical processing shows that the insufficient accuracy of the trajectory information results in the degrading of the imaging results.On the other hand,the autofocusing algorithms for BP imaging are not well developed,which is a bottleneck for the application of BP imaging.Here,an analysis of the effect of trajectory errors on the space target imaging using microlocal technology is presented.Our analysis provides an explicit quantitative relationship between the trajectory errors of the space target and the positioning errors in the reconstructed images.The explicit form of the position errors for some typical trajectory errors is also presented.Numerical simulations demonstrate our theoretical findings.The measured position errors obtained from the reconstructed images are consistent with the analytic errors calculated by using the derived formulas.Our results will be used in the development of effective autofocusing methods for BP imaging.

土地出让市场化对城市碳排放绩效的影响研究--基于城市面板数据的检验分析

文章基于2011—2022年中国地级市的面板数据,测算地级市土地出让市场化水平与地级市碳排放绩效,采用空间面板模型、工具变量法及调节效应模型等实证方法,检验了土地出让市场化对城市碳排放绩效的影响及其内在机制。研究发现:土地出让市场化与城市碳排放绩效之间呈显著的“U”型非线性关系,且通过系列稳健性检验与内生性处理后,该结论依然成立;作用机制检验表明,资源配置与产业结构升级在土地出让市场化对城市碳排放绩效的作用机制中发挥中介作用;调节效应检验表明,双重目标约束在土地出让市场化与碳排放绩效关系中发挥显著调节作用。研究结论有助于深入理解土地出让市场化对城市碳排放绩效的影响效果和内在机理,为推进土地出让市场化发展、提升城市碳排放绩效和优化目标约束提供有益借鉴。

A Novel Generalized Nonholonomy Criteria and Physical Interpretation of Holonomic/Nonholonomic Constraints of a Free-Flying Space Robot with/without Interaction with a Flying Target Satellite

This paper presents a new nonholonomy criteria and reveals the physical interpretation of holonomoic and nonholonomic constraints acting on a free-flying space robot with or without interaction with a free Flying/Floating target object. The analysis in this paper interprets the physical interpretation behind such constraints, and clarifies geometric and kinematic conditions that generate such constraints. Moreover, a new criterion of finding the holonomy/nonholonomy of constraints impose on a free-flying space robot with or without interaction with a floating object is presented as well. The proposed criteria are applicable in case of zero or non-zero initial momentum conditions. Such nonholonomy criteria are proposed by utilizing the concept of orthogonal projection matrices and singular value decomposition (SVD). Using this methodology will also enable us to verify online whether the constraints are violated in case of real-time applications and to take a correction action or switch the controllers. This criterion is still yet valid even the interaction with floating object is lost. Applications of the proposed criteria can be dedicated to in-orbit servicing robotic satellite to capture malfunctioned spacecrafts and satellites, docking space of NASA and Russian shuttles with International Space Station (ISA), building in-orbit stations, space rescue missions and asteroids dust sampling. Finally, simulation results are presented to demonstrate the effectiveness of the proposed criterion.

基于高分辨一维距离像及其特征的空间目标识别效果分析

目标高分辨一维距离像(High Resolution Range Profile,HRRP)中包含了丰富的目标尺寸、结构等目标特征,是进行空间目标身份识别的有效途径。但由于卫星宽带雷达实测数据获取难度大,前期相关研究多集中于基于HRRP的目标识别算法,结论也多是基于仿真数据和少量类别(几类)的前提下得到的,与工程应用实际情况有较大差距,工程指导意义有限。为解决这一问题,基于地基雷达获取的30类卫星目标的大量一维距离像实测数据,从识别正确率的角度对目标HRRP及其特征(组合)的可分性和在空间目标个体识别中的应用效果进行了量化分析,分析结果可为后续基于HRRP的空间目标个体识别技术研究和工程应用提供可靠依据。

自由漂浮空间机器人捕获翻滚目标的力-位-型融合控制方法

翻滚目标捕获过程中,空间机器人的运动会对基座产生扰动、接触过程的冲击碰撞容易产生安全风险。因此,为了在捕获翻滚目标的同时抑制空间机械臂对基座的扰动和对目标的碰撞冲击,提出一种自由漂浮空间机器人力-位-型融合控制方法。首先将自由漂浮空间机器人的非完整冗余性、运动冗余性表征为型空间,构建由末端位姿、型状态组合的广义状态空间并建立系统的运动学和动力学模型;通过优化基座与机械臂的位-型及零空间运动,减小机械臂抓捕运动在基座产生的扰动;通过优化基座、机械臂与翻滚目标的相对位-型,减小碰撞冲击力在基座产生的姿态扰动。给定最优位-型及末端操作力,基于阻抗控制原理及零空间投影策略,实现多优先级力-位-型融合控制。最后,开展了空间机器人捕获翻滚目标的典型任务仿真,结果表明通过力-位-型融合优化与控制方法可以有效减小空间机器人捕获过程产生的基座扰动。

A Space-Time Reverberation Model for Moving Target Detection

In recent years,moving target detection methods based on low-rank and sparse matrix decomposition have been developed,and they have achieved good results.However,there is not enough interpretation to support the assumption that there is a high correlation among the reverberations after each transmitting pulse.In order to explain the correlation of reverberations,a new reverberation model is proposed from the perspective of scattering cells in this paper.The scattering cells are the subarea divided from the detection area.The energy fluctuation of a scattering cell with time and the influence of the neighboring cells are considered.Key parameters of the model were analyzed by numerical analysis,and the applicability of the model was verified by experimental analysis.The results showed that the model can be used for several simulations to evaluate the performance of moving target detection methods.

基于改进Faster RCNN的微操作空间目标检测算法

将Faster RCNN引入微操作系统的目标检测之中。针对微操作空间下待检测目标存在尺度变化和在显微镜放大倍数较小时,待检测目标尺度过小、特征不明显的问题,提出了一种基于改进Faster RCNN的微操作空间目标检测算法。使用在图像分类任务中性能优越的深度残差网络提取图像的特征。引入递归特征金字塔网络,对特征进行融合。改进区域建议网络的采样策略,对损失函数进行优化。实验结果表明:这种改进的Faster RCNN算法能有效解决由于目标尺度变化和目标尺度过小带来的问题。相比通用的目标检测算法,该算法的准确度更高,速度更快,具有实际应用价值。

基于空间目标定向观测的飞行器导航方法研究

本文主要研究基于定向观测星相机和惯性测量单元(inertial measurement unit, IMU)信息融合的飞行器高精度导航方法.在已有导航方式中,惯性导航系统(inertial navigation system, INS)/全球导航卫星系统(global navigation satellite system, GNSS)组合导航在无线电信号拒止环境中存在性能下降的风险,传统INS/天文导航系统(celestial navigation system, CNS)组合导航能够抑制惯性测量单元中的陀螺漂移,但不能有效消除加速度计零偏的影响.针对上述问题,提出一种基于空间目标定向观测的飞行器自主导航新方法,在飞行器上配置星相机对星历已知的空间目标和背景恒星的视线方向(line-of-sight, LOS)进行观测,利用IMU进行状态预测,通过扩展卡尔曼滤波器(extended Kalman filter, EKF)获得载体位置、速度和姿态的估计值,同时,对惯性器件测量偏差进行校准.设计了基于克拉美劳下界(Cramer-Rao lower bound, CRLB)的观测目标优化选取策略,通过空间目标可见性分析、导航系统可观度分析以及导航滤波器数学仿真验证了所提方法的有效性.

地表异常即时探测星座设计思考

地表异常具有分布广泛、频率高、演化速度快、影响范围大等特点,现有的天基遥感系统存在着协同弱、响应慢、链路长等问题,无法满足异常即时探测的应用需求.通过对地表异常分类及特点的分析,总结了地表异常天基遥感需求,结合现有天基遥感能力与特点,提出了天基地表异常即时遥感卫星的能力目标表.总结了大规模地表异常即时探测星座的设计思路,分析了地表异常即时探测星座的组成方式、工作模式和应用场景,星座可以实现对地表异常的即时发现、即时识别和即时传输,并根据即时探测需求进行了仿真分析.仿真结果表明,星座具备数据获取到数据服务优于15min的能力,为未来天基地表异常即时探测星座的建立提供了参考.

中国式现代化视域下中国财政收入目标制演变研究

财政收入目标作为财政预算收入编制的基础,是财政政策相机调控的政策工具,亦是有为政府动员部署和调配资源的重要途径。中国财政收入目标制的发展阶段可划分为新中国成立初期财政收入目标考核确立前阶段(1949—1977年)、改革开放后财政收入目标考核萌发阶段(1978—1993年)、分税制后财政收入目标考核发展阶段(1994—1999年)、新世纪财政收入目标与预算绩效融合阶段(2000—2012年)及新时代财政融入国家治理体系阶段(2013年以来)等五个阶段,具有历史演进特征。根据1998—2020年相关数据,全国、省级和地市级三个层面的财政收入目标具有时空格局演变特征:就整体而言,中国财政收入目标具有很强的引导作用,体现了财政的主动性和目标意识;从区域来看,东部发达地区因为自身较大的经济体量,财政收入增速呈现正常的趋缓现象,财政收入目标总体上小于其他欠发达省份;而在区域内部,城市间财政收入目标差异分化较大,中部和西部地区城市所制定目标的水平会更高,目标的增长压力也更大,大部分城市的财政收入目标小于其实际经济增速,目标存在留有余地的空间;各省份和城市之间的收入目标差距均存在收敛效应。

空间目标天基光学定位方法综述

近年来空间目标定位领域不断结合网络协同、多模融合等探测技术,发展迅速。其中,基于天基光学探测的定位方法以隐蔽性好、测量精度高的独特优势在民用和国防领域应用广泛。为了分析不同情景下适用于不同类型目标的定位方法,针对基于天基光学探测的空间小目标定位进行综述。首先介绍天基光学探测技术的发展、空间目标的分类和特点以及空间目标定位的概念。然后着重分析适用于空间“小、弱”目标的单星和多星定位方法,并对近年提出的异质传感器联合定位展开说明。最后,依据成像过程建立空间目标定位误差分析模型,分析定位精度的影响因素占比并根据现存问题做出总结和展望。

天空地一体化多目标跟踪算法研究综述

为实现全时全域“泛在连接”,构建天空地一体化网络已成为国家重大需求,而基于天空地一体化网络下跨域协同系统进行多目标跟踪是其中一个重要的发展方向,其在军民用领域都极具应用价值。本文详细阐述了天空地一体化网络背景下多目标跟踪方法研究进展。首先,介绍了天空地一体化跨域协同多目标跟踪的研究背景与意义。其次,从基于视觉的多目标跟踪、基于模型的多目标跟踪和基于多模态融合的多目标跟踪三个方面概述了当前的代表性研究方法:在基于视觉的多目标跟踪算法方面,介绍了单摄像头和多摄像头融合的多目标跟踪方法;对于基于模型的多目标跟踪,先介绍了单传感器多目标跟踪方法,以及在多种复杂场景下的改进,然后介绍了多传感器融合方法;在基于多模态信息融合的目标跟踪方面,在对多传感器时空配准方法和有代表性的多模态信息融合方法介绍的基础上,概括了基于多模态融合的多目标跟踪算法。最后探讨了当前存在的问题和未来发展方向:无论基于视觉的还是基于模型的多目标跟踪方法都有不少问题有待解决,特别是两种方法的结合值得深入研究;在面临复杂干扰时,基于多传感器信息融合的多目标跟踪由于能实现信息的互补,成为未来的主流发展方向;此外,跨域协同系统,由于能利用更多的资源和信息,其多目标跟踪问题研究极具价值,不过其中通信安全问题和多目标跟踪模型轻量化问题值得探讨。本文对从事目标跟踪及空天地一体化协同控制相关理论与技术研究的科研工作者具有重要参考价值。