基于LSTM的空间机器人系统惯性张量在轨辨识

在空间机器人抓捕目标的过程中,整个系统的惯性张量会随时间变化且在目标被捕获瞬间发生突变,这会严重影响整体姿态控制的精度。针对以上问题,提出了一种基于长短期记忆（LSTM）的系统惯性张量在轨实时辨识方法。首先,对于目标捕获前后的2个阶段,利用拉格朗日方程建立了空间机器人的动力学模型;然后,基于所建空间机器人模型采用域随机化方法生成足量训练数据,并用其对由LSTM网络与多层全连接网络构建的参数辨识网络进行训练;最后,使用训练好的参数辨识网络对系统惯性张量进行辨识。数值仿真结果表明：所提方法能够精确辨识空间机器人抓捕过程中的系统惯性张量,所研究系统的主惯量平均相对辨识误差小于0.001,惯性积的平均相对辨识误差小于0.01。     

Analysis on Potential Conflict Frequency of Intersected Air Routes in Terminal Airspace Design

In order to obtain accurate conflict risks in terminal airspace design, the concept and calculation model of potential conflict frequency for intersected routes are proposed. Conflict frequency is represented by the product of horizontal conflict frequency and vertical conflict probability. The horizontal conflict frequency is derived from the probability density distribution of conflicts in a period of time. Based on the recorded radar trajectory data, the concept and model of ROUTE distance are proposed, and the probability density function of aircraft height at a specified ROUTE distance is deduced by kernel density estimation. Furthermore, vertical conflict probability and its horizontal distribution are achieved. Examples of three intersected arrival and departure route design schemes are studied. Compared with scheme 1, the conflict frequency values of the other two improved schemes decrease to 53 % and 24%, respectively. The results show that the model can quantify potential conflict frequency of intersec ted routes.     

The impact of orbital errors on the estimation of satellite clock errors and PPP

Precise satellite orbit and clocks are essential for providing high accuracy real-time PPP (Precise Point Positioning) service. However, by treating the predicted orbits as fixed, the orbital errors may be partially assimilated by the estimated satellite clock and hence impact the positioning solutions. This paper presents the impact analysis of errors in radial and tangential orbital components on the estimation of satellite clocks and PPP through theoretical study and experimental evaluation. The relationship between the compensation of the orbital errors by the satellite clocks and the satellite-station geometry is discussed in details. Based on the satellite clocks estimated with regional station networks of different sizes (∼100, ∼300, ∼500 and ∼700 km in radius), results indicated that the orbital errors compensated by the satellite clock estimates reduce as the size of the network increases. An interesting regional PPP mode based on the broadcast ephemeris and the corresponding estimated satellite clocks is proposed and evaluated through the numerical study. The impact of orbital errors in the broadcast ephemeris has shown to be negligible for PPP users in a regional network of a radius of ∼300 km, with positioning RMS of about 1.4, 1.4 and 3.7 cm for east, north and up component in the post-mission kinematic mode, comparable with 1.3, 1.3 and 3.6 cm using the precise orbits and the corresponding estimated clocks. Compared with the DGPS and RTK positioning, only the estimated satellite clocks are needed to be disseminated to PPP users for this approach. It can significantly alleviate the communication burdens and therefore can be beneficial to the real time applications.     

邻信道合并的改进及其测频方法

为了确保高灵敏度,数字信道化接收机的子信道带宽一般较窄。然而,在现代电子战环境中,存在大量的宽带雷达信号,其带宽经常会大于信道宽度,使得多信道都存在信号,将增加信道编码及脉内处理的复杂度。提出了一种邻信道合并方法,直接对信道化的原型低通滤波器进行了解析设计,便于采用带宽相加实现输出子信道的带宽扩展。首先给出了原型低通滤波器的一种解析解;然后,采用相似系数,从仿真角度证明了邻信道合并对宽带信号的适用性;最后,根据信道分布特点,设计了一种窄带测频方法。理论分析和仿真结果证实了方法的有效性。     

Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall

In the present paper, an artificial neural network (ANN) based technique has been developed to estimate instantaneous rainfall by using brightness temperature from the IR sensors of SEVIRI radiometer, onboard Meteosat Second Generation (MSG) satellite. The study is carried out over north of Algeria. For estimation of rainfall, weight matrices of two ANNs namely MLP1 and MLP2 are developed. MLP1 is to identify raining or non-raining pixels. When rainy pixels are identified, then for those pixels, instantaneous rainfall is estimated by using MLP2. For identification of raining and non raining pixels, 7 input parameters from the IR sensors are utilized. Corresponding data of raining/non-raining pixels are taken from radar. For instantaneous rainfall estimation, 14 input parameters are utilized, where 7 parameters are information about raining pixels and 7 parameters are related with cloud features. The results obtained show the neural network performs reasonably well.     

The effect of spatial truncation error on variance of gravity anomalies derived from inversion of satellite orbital and gradiometric data

The spatial truncation error (STE) is a significant systematic error in the integral inversion of satellite gradiometric and orbital data to gravity anomalies at sea level. In order to reduce the effect of STE, a larger area than the desired one is considered in the inversion process, but the anomalies located in its central part are selected as the final results. The STE influences the variance of the results as well because the residual vector, which is contaminated with STE, is used for its estimation. The situation is even more complicated in variance component estimation because of its iterative nature. In this paper, we present a strategy to reduce the effect of STE on the a posteriori   variance factor and the variance components for inversion of satellite orbital and gradiometric data to gravity anomalies at sea level. The idea is to define two windowing matrices for reducing this error from the estimated residuals and anomalies. Our simulation studies over Fennoscandia show that the differences between the 0.5°×0.5°$0.5°\times 0.5°$ gravity anomalies obtained from orbital data and an existing gravity model have standard deviation (STD) and root mean squared error (RMSE) of 10.9 and 12.1 mGal, respectively, and those obtained from gradiometric data have 7.9 and 10.1 in the same units. In the case that they are combined using windowed variance components the STD and RMSE become 6.1 and 8.4 mGal. Also, the mean value of the estimated RMSE after using the windowed variances is in agreement with the RMSE of the differences between the estimated anomalies and those obtained from the gravity model.     

多退化变量下基于Copula函数的陀螺仪剩余寿命预测方法

针对惯性导航系统中陀螺仪多退化变量条件下的剩余寿命（RUL）预测问题,提出了一种基于Copula函数的多退化变量剩余寿命预测方法。首先,针对退化变量间不同的退化轨迹,采用不同的方法进行退化建模,并对于陀螺漂移系数样本标准差数据波动性随时间递增的特性,提出了一种方差时变的正态随机过程退化建模方法,得到了陀螺仪剩余寿命的边缘分布函数。然后,通过Copula函数来描述退化变量之间的相关性,将得到的剩余寿命的边缘分布进行融合,得到了陀螺仪剩余寿命的联合分布函数。最后,通过陀螺仪实例分析验证了方法的适用性和可行性。     

简化的混合估计算法及其在GPS／SINS深组合中的应用

为解决GPS/SINS深组合导航系统滤波的非线性和噪声的不确定性的问题,针对深组合模型特点,设计了一种简化的基于U滤波的多模型混合估计滤波器。根据系统模型中状态方程是线性方程、观测方程是非线性方程的特点,提出了一种简化的U滤波算法(Ultra tight coupling unscented Kalman filter,UTCUKF),然后针对噪声变化建立了非线性模型,多模型混合估计滤波器的输出为各滤波器的概率加权融合,因此模型概率是根据噪声变化而调整的,从而也使系统输出对噪声变化具有一定自适应能力。最后进行了仿真,并与基于普通U滤波的多模型混合估计算法进行了比较。结果表明,本文算法的解算时间短,模型切换速度更快,而估计的精确度与同条件下的基于普通U滤波的多模型混合估计算法相当,更符合深组合系统高动态的要求。     

基于低成本陀螺和倾角仪的姿态估计

针对动中通测控系统中低成本陀螺和倾角仪的姿态估计和陀螺误差校正问题,提出一种利用UKF（Uncented Kalman Filter）滤波器对载体姿态角进行估计,然后利用互补滤波器对陀螺漂移进行估计的算法。该算法通过设计三维完全可观测UKF滤波方程和陀螺误差校正模型对姿态角和陀螺漂移分别进行估计,有效避免了利用卡尔曼滤波进行姿态估计和陀螺漂移误差估计时由于误差模型不准确而产生的发散问题,同时降低了滤波器维数。试验中姿态角估计误差在1°以内,x轴陀螺漂移估计误差为0.0148°/s,y轴陀螺漂移估计误差为0.0017°/s,试验结果表明该算法能有效提高姿态角估计和陀螺漂移估计的精度。     

基于自相关及相位差法的高精度频率估计算法

为提高高斯白噪声背景中正弦信号的频率估计精度,对基于自相关运算的频率估计算法的相关长度m进行了推导,得到了m的优化值与信噪比的关系式.当信噪比较高时,m的最优值为N/3(N为信号采样点数);信噪比较低时,m的最优值为N/2.通过对自相关法及分段FFT(Fast Fourier Transforms)相位差法特性的分析,提出了一种性能更优的频率估计综合算法. Monte Carlo仿真实验表明:新算法吸收了两种算法的优点,克服了其不足,在更大的信噪比范围内具有较高的频率估计精度,且计算量也较小.