面向智能空战的它机协同试飞验证方法

为验证无人机自主协同算法在空战环境下的适用性，提出了一种高等效的它机协同试飞验证方法。根据算法功能实现的需求，以成熟的民用固定翼无人机平台为基础进行改装，搭建它机试飞平台，对真实空战环境开展模拟和等效设计。以四机协同编队算法为例，在试飞平台上移植算法程序，开展相关科目试飞验证。当需要验证不同控制算法时，无需针对它机试飞平台开发控制策略，只需修改控制算法即可。试验结果表明：编队综合误差较小，算法能够实现无人机编队的稳定控制；同时，它机协同试飞验证方法因其迭代速度快、安全稳定性高、成本低等特点，可用作中间阶段算法的前置试飞手段，为算法的开发迭代提供有效验证。     

自主多无人机的分散化协同控制

协同前提是无人机(UAV)平台间的通信和信息共享,无人机平台之间信息和计算是高度分布的,无人机平台的运动以及通信拓扑的变化,使得集中式协调控制结构很难实现。以最小通信量为基础的分散协同控制具有可扩展性、异构性和动态可重构性等特点,可靠性和鲁棒性较好。针对多无人机平台分散化协同的特点和要求,建立了集中和分散相结合的多无人机平台协同控制系统结构,集中式任务管理系统主要完成目标分配、通信管理和编队管理功能,分散式协同部分主要实现局部任务规划、协调策略及协调控制等功能。分别以多机协同目标跟踪、多机和多编队一致性协调、多机协同编队控制与重构等多无人机平台分散化协同控制技术为应用对象,探讨了分散化协调机制、策略、控制及其与信息之间关系。给出了部分算法的仿真结果。     

拒止环境下多弹协同导航及编队优化设计

针对拒止环境下的多弹编队协同导航问题,提出了一种基于协同导航的编队位置优化设计算法。建立编队协同导航框架和相对导航信息测量模型,并基于联邦式滤波算法进行协同导航解算;定义单弹和编队导航精度指标,建立编队位置分配优化模型,在给定高精度弹数量的前提下,利用遗传算法进行编队位置优化设计;在此基础上,在给定编队导航精度的前提下,对编队中高精度弹数量进行规划。仿真结果表明,该算法可以有效提高多弹编队的整体导航精度。     

多导弹编队齐射攻击分散化协同制导方法

针对多导弹编队齐射攻击在时间上的协同要求,将攻击时间可控制导律(ITCG)与一致性分散化协调算法相结合,提出一种多导弹编队齐射攻击的分散化协同制导方法.编队内各导弹采用相邻局部通信,编队之间则通过各编队通信拓扑生成树的根节点进行通信.设计了导弹编队内和编队间的分散化协调策略,实现多导弹编队齐射攻击的分散化协调.推导了攻...     

基于Dodgson集结算法的多机协同空战机动决策方法

针对多机编队协同作战空战问题,研究了协同机动决策改进方法.基于Dodgson集结函数,设计了新的协同决策中的机群偏好集结环节,提出了一种基于Dodgson集结算法的多机自主协同空战机动决策方法.典型多机协同空战算例表明,该决策算法能在敌机不机动、初始态势占劣等多种条件下,产生合理有效的机动决策.     

集群编队条件下通导一体高精度时间同步方法

针对集群编队条件下对高精度时间同步的需求，对通导一体高精度时间同步方法进行了研究，将卫星导航系统与数据链系统进行深度融合，提出了动基座条件下基于卫星导航载波差分算法的节点间高精度时间同步算法。该算法通过协同时间驯服的方式来抑制两次定位间隔间受钟漂影响导致的节点间时间同步误差发散以及节点间时钟修正不同步导致的时间同步误差，提升了编队组网条件下节点间的时间同步精度。最后,通过仿真对算法进行了验证。结果表明，时空同步精度可以达到1ns，可有力支撑未来集群编队作战、高精度协同探测、高精度协同制导等典型场景下对节点间高精度时间同步的需求。     

编队无人机的高生存力协同航路规划方法

提出了一种基于多目标遗传算法的编队无人机高生存力协同航路规划方法。方法由备选航路生成和协同规划两个步骤组成。备选航路生成的目的是为编队中的每一个无人机生成多条航路,该步骤采用的算法是多目标遗传算法。协同规划的目的是为各个无人机从备选航路中选择航路,使得各个无人机同时到达目标区域,以增加任务突然性,提高整个编队的生存力。通过仿真算例,把方法与基于Voronoi图的方法作了对比,给出了方法的优缺点分析。     

有人/无人机协同编队控制研究综述

有人/无人机协同作战是未来联合作战的重要作战样式之一,开展协同编队控制相关理论和技术研究,将有效促进协同作战能力的提升。针对有人/无人机协同编队控制问题,剖析有人/无人机协同作战的内涵,分析归纳协同作战验证项目的进展情况及发展趋势。在梳理有人/无人机协同编队控制结构的基础上,结合有人/无人机平台使用特点,从编队作战运用流程视角出发,对有人/无人机协同编队控制方法、编队生成与保持、编队重构、编队避障的研究现状进行系统综述,提出了下一步亟待解决的问题及深入探索的方向。相关研究可为有人/无人机协同作战运用提供技术参考和方向指导,具有重要的军事意义。     

基于量子行为鸽群优化的无人机紧密编队控制

随着军事、民用需求的提高和相关领域的技术推动，无人机编队协同作业已成为当今人们逐渐关注的焦点。无人机紧密编队是指无人机间侧向距离在1~2倍翼展内的编队，因其可有效改善编队中无人机的气动性能而备受瞩目。基于无人机紧密编队条件下的气动耦合效应，建立三维空间下的状态空间方程描述双机相对运动，并推导了紧密编队条件下的双机最优编队构型，在此构型下将人工势场法和编队控制相结合作为控制系统中的间接控制环，并针对基本鸽群优化算法的寻优缺陷利用量子行为规则对其进行改进，将改进后的鸽群优化算法和无人机控制量结合作为控制系统中的直接控制环，最后通过仿真对比验证了此控制系统对于紧密编队控制的有效性。     

无人艇集群协同定位算法误差分析

无人艇以集群方式被广泛应用于各个领域.无人艇集群完成任务的前提是获知相对的位置关系.为此,针对无人艇集群协同定位算法误差进行了全面分析.首先,给出了基于数据链协同定位原理.在此基础上,深入剖析了协同定位误差种类、特点及影响.最后,针对协同定位算法中对协同定位精度影响较大的3个因素进行了仿真分析.分析结果表明,伪距测量误...     

Performance improvement for constellation SAR using signal processing techniques

A new concept of spaceborne synthetic aperture radar (SAR) implementation has recently been proposed - the constellation of small spaceborne SAR systems. In this implementation, several formation-flying small satellites cooperate to perform multiple space missions. We investigate the possibility to produce high-resolution wide-area SAR images and fine ground moving-target indicator (GMTI) performance with constellation of small spaceborne SAR systems. In particular, we focus on the problems introduced by this particular SAR system, such as Doppler ambiguities, high sparseness of the satellite array, and array element errors. A space-time adaptive processing (STAP) approach combined with conventional SAR imaging algorithms is proposed which can solve these problems to some extent. The main idea of the approach is to use a STAP-based method to properly overcome the aliasing effect caused by the lower pulse-repetition frequency (PRF) and thereby retrieve the unambiguous azimuth wide (full) spectrum signals from the received echoes. Following this operation, conventional SAR data processing tools can be applied to focus the SAR images fully. The proposed approach can simultaneously achieve both high-resolution SAR mapping of wide ground scenes and GMTI with high efficiency. To obtain array element errors, an array auto-calibration technique is proposed to estimate them based on the angular and Doppler ambiguity analysis of the clutter echo. The optimizing of satellite formations is also analyzed, and a platform velocity/PRF criterion for array configurations is presented. An approach is given to make it possible that almost any given sparse array configuration can satisfy the criterion by slightly adjusting the PRF. Simulated results are presented to verify the effectiveness of the proposed approaches.     

Loopy belief propagation based data association for extended target tracking

The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements. Recently, the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus. Different from the belief propagation based Extended Target tracking based on Belief Propagation (ET-BP) algorithm proposed in our previous work, a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper. The proposed formulation can be solved by the Loopy Belief Propagation (LBP) algorithm. Furthermore, the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy. Finally, experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency. Additionally, the convergence of the proposed algorithm is verified in the simulations.     

Hierarchical adaptive Kalman filtering for interplanetary orbitdetermination

A modular and flexible approach to adaptive Kalman filtering has recently been introduced using the framework of a mixture-of-experts regulated by a gating network. Each expert is a Kalman filter modeled with a different realization of the unknown system parameters. The unknown or uncertain parameters can include elements of the state transition matrix, observation mapping matrix, process noise covariance matrix, and measurement noise covariance matrix. The gating network performs on-line adaptation of the weights given to individual filters based on performance. The mixture-of-experts approach is extended here to a hierarchical architecture which involves multiple levels of gating. The proposed architecture provides a multilevel hypothesis testing capability. The utility of the hierarchical architecture is illustrated via the problem of interplanetary navigation (Mars Pathfinder) using simulated radiometric data. It serves as a useful tool for assisting navigation teams in the process of selecting the parameters of the navigational filter over various operating regimes. It is shown that the scheme has the capability of detecting changes in the system parameters and switching filters appropriately for optimal performance. Furthermore, the expectation-maximization (EM) algorithm is shown to be applicable in the proposed framework     

航空发动机健康管理系统的快速原型设计

针对航空发动机健康管理系统传统设计方法周期长、成本高等问题,提出了面向健康管理系统的快速原型设计方法,构建了基于虚拟仪器语言和快速原型技术的航空发动机健康管理系统快速原型仿真平台。以CompactRIO平台为核心,在实时响应最高的现场可编程门阵列(FPGA)环境下设计了信号接口单元,模拟发动机真实传感器值,并提供了基于Windows平台的健康管理软件实时开发环境,可以将健康管理算法快速部署下载至硬件平台。结果表明:此健康管理系统的快速原型设计方法是切实有效的,为扩展成为完全的硬件在回路(HIL)仿真的平台奠定了基础,有较好的工程实用价值。     

Wavelet de-noising for IMU alignment

Inertial navigation system (INS) is presently used in several applications related to aerospace systems and land vehicle navigation. An INS determines the position, velocity, and attitude of a moving platform by processing the accelerations and angular velocity measurements of an inertial measurement unit (IMU). Accurate estimation of the initial attitude angles of an IMU is essential to ensure precise determination of the position and attitude of the moving platform. These initial attitude angles are usually estimated using alignment techniques. Due to the relatively low signal-to-noise ratio of the sensor measurement (especially for the gyroscopes), the initial attitude angles may not be computed accurately enough. In addition, the estimated initial attitude angles may have relatively large uncertainties that may affect the accuracy of other navigation parameters. This article suggests processing the gyro and accelerometer measurements with multiple levels of wavelet decomposition to remove the high frequency noise components. The proposed wavelet de-noising method was applied on a navigational grade inertial measurement unit (LTN90-100). The results showed that accurate alignment procedure and fast convergence of the estimation algorithm, in addition to reducing the estimation covariance of the three attitude angles, could be obtained.     

Flexible spacestructure control via moving-bank multiple modelalgorithms

The development and performance of moving-bank multiple model adaptive control (MMAC) algorithms for quelling vibrations induced in the SPICE 2 space structure are presented. The structure consists of a large platform and a smaller platform connected by three legs in a tripod fashion. Deviations of the line-of-sight (LOS) vector from the center of the large platform to the center of the smaller platform are used for LQG controller performance evaluation. The parameter estimator implements the maximum entropy with identity covariance (ME/I) algorithm; the moving-bank logic employs parameter position monitoring; the controller uses the modified MMAC method. Whereas parameter variations of two percent caused instabilities in the single filter/controller design, the MMAC algorithm provides an excellent method to estimate a wide range of parameter variations and to quell oscillations in the structure     

基于信度规则库的惯性平台健康状态参数在线估计

 实时准确的健康状态预测是规划惯性平台系统及时、经济的维修策略的关键技术。由于平台系统的健康状态是不能够直接观测的,假设平台系统的特征参数监测数据是可以获取到的,而且平台系统的健康状态与特征量是相关的。基于信度规则库(BRB),以平台系统的状态监测特征参数作为BRB系统的输入,以平台的健康状态作为输出结果,组建了惯性平台健康状态预测系统。为了克服现有BRB参数优化方法的不足,实现实时状态预测,基于期望最大化(EM)算法,研究了健康状态预测系统的参数在线估计算法。该算法在获取系统新的输入输出信息后,就对参数进行更新。利用本文提出的方法对惯性平台系统的健康状态实时预测问题进行了实验分析,实验结果表明：该方法可以有效地实现惯性平台系统健康状态预测模型参数实时估计;与参数离线优化方法相比,该方法不仅在预测精度上,而且在运行时间上都具有明显的优势;在工程实际中有良好的应用潜力。     

Control of a large space structure using MMAE/MMAC techniques

The application of moving-bank multiple model adaptive estimation and control (MMAE/MMAC) algorithms to an actual spade structure (Space Integrated Controls Experiment (SPICE)) being examined at Phillips Laboratory at Kirtland AFB, NM, is presented. The structure consists of a large platform and a smaller platform connected by three legs in a tripod fashion. Kalman filtering and LQG (linear system, quadratic cost, Gaussian noise) control techniques are utilized as the primary design tools for the components of the MMAE/MMAC. Implementing a bank of filters or controllers increases the robustness of the algorithms when uncertainties exist in the system model, whereas the moving bank is utilized to reduce the computational load. Several reduced-order models are developed from the truth model using modal analysis and modal cost analysis. The MMAE/MMAC design with a substantially reduced-order filter model provides an excellent method to estimate a wide range of parameter variations and to quell oscillations in the structure.     

FrFT-CSWSF:Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.     

确定相干机器多噪声源位置的方法研究

提出利用均匀线阵接收的数据构造一种矩阵进行奇异值（SVD）分解,以实现对相干噪声源的方位估计。利用这种方法,通过改变阵列中心位置便可确定机器多噪声源位置。计算机模拟和声学实验证实了这种方法的可行性。