Acceleration tracking control for a spinning glide guided projectile with multiple disturbances

A novel acceleration tracking controller is proposed in this paper, for a Spinning Glide Guided Projectile (SGGP) subject to cross-coupling dynamics, external disturbances, and parametric uncertainties. The cross-coupled dynamics for the SGGP are formulated with mismatched and matched uncertainties, and then divided into acceleration and angular rate subsystems via the hierarchical principle. By exploiting the structural property of the SGGP, model-assisted Extended State Observers (ESOs) are designed to estimate online the lumped disturbances in the acceleration and angular rate dynamics. To achieve a rapid response and a strong robustness, integral sliding mode control laws and sigmoid-function-based tracking differentiators are integrated into the ESO-based Trajectory Linearization Control (TLC) framework. It is proven that the acceleration tracking controller can guarantee the ultimate boundedness of the signals in the closed-loop system and make the tracking errors arbitrarily small. The superiority and effectiveness of the proposed control scheme in its decoupling ability, accurate acceleration tracking performance and anti-disturbance capability are validated through comparisons and extensive simulations.     

包含乘性噪声自适应修正的非合作目标相对导航算法

无人机（UAV）态势感知的任务是利用机载传感器对未知环境进行目标识别和引导，针对无人机与非合作目标间中远距离的相对导航问题，提出了一种基于角度和距离量测的相对状态估计算法。在现有滤波算法的基础上，为了提高精度和稳定性，本文利用了列文伯格-马夸尔特（LM）优化的思想对迭代卡尔曼滤波（IEKF）算法进行改进，提出了一种LM-IEKF算法，并推导该算法在迭代过程中的状态更新方程及协方差阵的递推公式。在此基础上，考虑到距离传感器由于信号相关特性而引入的乘性噪声，现有的加性噪声模型难以适应，因此，进一步提出了基于量测噪声自适应修正的Modified LM-IEKF方法，通过在线实时更新噪声阵提高滤波的精度，并设置渐消记忆指数平滑估计结果。算法验证结果表明，与现有的EKF、IEKF算法相比，在仅含加性噪声的情况下，LM-IEKF算法具有更好的性能；在包含乘性噪声的情况下，Modified LM-IEKF可以有效地估计量测噪声，与目前广泛使用的EKF算法相比，在综合相对位置和相对速度精度上分别提高了10%和23%。     

Data-driven model-free adaptive attitude control of partially constrained combined spacecraft with external disturbances and input saturation

This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.     

Extending multipath hemispherical model to account for time-varying receiver code biases

Multipath effects on code observables account for one of the major error sources in high-accuracy Global Positioning System (GPS)-based positioning, atmosphere sounding and timing applications. The multipath hemispherical model (MHM) represents one of the most widely used methods of mitigating code multipath effects by taking advantage of their spatial repeatability. The use of MHM usually assumes that the receiver code biases (RCBs) are time-invariant; however, this assumption is not always valid, as RCBs and linear combinations thereof (differential code biases, for instance) have long been found to be time-varying over a period of one day. In this contribution, we propose an extended multipath hemispherical model (EMHM) that is capable of mitigating the code multipath effects in the presence of time-varying RCBs. Consequently, the proposed EMHM has two advantages. First, the EMHM gives rise to code multipath corrections with improved reliability because it addresses the intraday variability of RCBs. Second, more interestingly, the EMHM allows easy and effective calibration of short-term temporal variations, if any, in the RCB on each frequency. These advantages are hopeful to benefit GPS code-related applications.     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.     

基于FPGA的IP over CCSDS设计与实现

首先介绍了TCP/IP(传输控制协议/网际协议)技术和CCSDS(空间数据系统咨询委员会)建议的应用背景,从天地网络一体化和未来空间站与地面交互式通信系统需求的角度出发,提出了一种基于FPGA(现场可编程门阵列)的IP over CCSDS处理方法。详细描述了IP over CCSDS软件的实现方案和技术特点,并对其进行了测试和结果分析。     

基于多敏感器的卫星姿态确定算法

针对多敏感器组成的卫星姿态确定系统,采用四元数方法建立卫星姿态估计器模型,应用扩展卡尔曼滤波EKF算法进行信息融合,通过仿真算例验证此算法具有较高的精度。与此同时,在EKF算法基础上提出一种定常增益的卡尔曼滤波CGKF算法。通过数学仿真对EKF算法和CGKF算法进行比较分析,证明在一定条件下CGKF算法具有与EKF算法相当的滤波精度,并且简化后的CGKF算法在获得与EKF算法相近滤波效果的同时,还能够节约星上资源,减少计算量。     

运动阵列非重叠孔径扩展算法

现有线阵列被动合成阵列算法无法满足非连续信号和非均匀线阵列的处理需要,难以被直接用来提高运动线阵列对时域重叠脉冲信号的空间分辨能力.针对这一问题,本文提出一种能够同时满足对非连续信号和非均匀线阵列处理需求的运动阵列非重叠孔径扩展算法.该算法首先通过二维MUSIC算法估计运动阵列的“相位校正因子”,进而完成阵列孔径扩展实现对多个时域重叠信号的高分辨方向估计.通过仿真研究可知:小孔径运动阵列利用本算法在不牺牲方向估计精度的条件下,可以有效提高对多信号的分辨能力,且具有较好的低信噪比适应能力.     

Autonomous navigation to quasi-periodic orbits near translunar Ubration points

Libration-point missions have been very useful and successful. Due to the unstable natures of most of these orbits, the long-time stationkeeping demands frequent maneuvers and precise orbit determinations. Earth-based tracking will have to undertake much more responsibilities with the increasing number of libration missions. An autonomous navigation system could offer a better way to decrease the need for Earth-based tracking. Nevertheless, when an autonomous navigation system is applied, there are three important factors affecting autonomous navigation accuracy, i.e., the accuracy of initial conditions, the accuracy of measurements, and the accuracy of onboard dynamics for propagation. This paper focuses on analyzing the influence from the third factor and finding an appropriate navigation dynamics, which can satisfy the requirement of estimation accuracy but not cause too much burden for onboard computation. When considering the restricted three-body model and the bicircular restricted four-body model as navigation dynamics, the astrin- gency is not shown during the simulations. Meanwhile, when considering the influences of the Sun＇s direct and indirect perturbations and the eccentricity of the Moon＇s orbit, a new navigation dynamic model with the standard ephemerides is proposed. The simulation shows the feasibility of the proposed model.     

拟合摄动力函数在低轨卫星定轨算法中的应用

为降低卫星定轨中摄动运动方程计算的复杂性，根据低轨卫星动力学模型，在考虑二体作用力和地球非球形引力J2项摄动条件下，以拟合函数表示其余的摄动力，并采用扩展卡尔曼滤波（EKF）算法，提出了一种基于拟合摄动力函数的低轨卫星自主定轨滤波算法。仿真结果表明，该法可明显减少计算量，缩短滤波收敛时间，提高卫星的实时处理能力。定轨精度为：位置方向70．7m（1σ），速度方向0．16m／s（1σ），可满足一般低轨卫星的精度要求。