A systematic approach to nonlinear rotorcraft model identification

The development of a powerful parameter estimation routine and its integration into the simulation environment HOST is described. With this tool approaches are being made towards new strategies of mathematical modeling, aimed at providing highly accurate and nevertheless run-time efficient simulation models. The identification routine is capable of optimizing parameterized models in both dynamic time domain simulation and static (e.g. trim state variation) conditions. Examples of both cases are presented to emphasize the improvement in the system response prediction and to demonstrate the abilities of the identification techniques in combination with the nonlinear simulation platform. This article reviews the activities and achievements accomplished by the DLR Institute of Flight Research and the ONERA Systems Control and Flight Dynamics Department during the last few years in the research on rotorcraft flight dynamics modeling and model identification. Future activities that require extensive high fidelity modeling are in the scope of the current and coming modeling activities that include the use of the presented methods and software technologies.     

3-D position estimation of isolated target and optimal trajectory choice in parasitic synthetic aperture radar

Bistatic SAR (BSAR) systems have recently been the subject of several studies, but little attention has been given to the potential of the location of targets. In the paper, the performance of the estimation of 3-D position of a target (TPE) in parasitic SAR is obtained analytically and illustrated by computer simulation using ambiguity function analysis, and the maximum likelihood estimate (MLE) approach. It was shown that by using a multi look parasitic BSAR all three coordinates of an isolated point target (IPT) could be evaluated. Analytical closed form equations that characterize the measurement accuracy were derived. In the final these equations will be used to demonstrate various cases of more practical, including optimal trajectories choice under any geometry configuration case, moreover, the conclusion is verified via Matlab.     

小型弹体转动惯量的测定

阐述了对称式三线摆的结构原理及该摆微角与大角摆动周期的计算方法 ,利用此摆可以测量构件的转动惯量。当 RL <130 、φ0 <6 0°时 ,该装置的测量准确度优于 1%。     

基于偏最小二乘回归分析的装备研制费用估算方法及应用

介绍了寿命周期费用的概念以及各阶段分布情况;针对经典回归分析的不足,采用偏最小二乘回归分析对某装备样本数据进行分析建模;建立了研制费用与几个相关指标的回归方程,并将估算结果与经典的回归分析进行对比,验证模型的合理性。该模型能较好地反映了费用与各指标之间的关系,对后续寿命周期费用的分析与控制有一定的意义。     

一般概率测度的核估计

在测度弱收敛的意义下，研究了一般概率测度μ的核估计μn，得到了它的渐近无偏性、强相合性及在给定条件下的收敛速度。     

轻型塔架挠度速算法

本文介绍了轻型塔架的挠度速算法,并以三角形截面的钢塔架为例题作了计算公式推导。这种方法具有计算简单和具有足够精度的优点。     

基于卫星观测数据的弹道导弹初始状态估计

利用卫星探测数据对大气层外飞行的弹道导弹弹道进行估计。在极大似然估计中,由于卫星探测导弹运动的可观测性较差,使初始点估计变得十分病态,传统的Gauss Newton迭代算法不再适用,而采用较为复杂Levenberg Marquardt算法,分别对单颗卫星和两颗卫星的情况进行了Monte Carlo仿真,得到了各自的归一化残差测量误差(代价函数),结果表明该算法有效。     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.     

Orbit determination of BDS-3 satellite based on regional ground tracking station and inter-satellite link observations

The BeiDou global navigation satellite system (BDS-3) has established the Ka-band inter-satellite link (ISL) to realize a two-way ranging function between satellites, which provides a new observation technology for the orbit determination of BDS-3 satellites. Therefore, this study presents a BDS satellite orbit determination model based on ground tracking station (GTS) observations and ISL ranging observations firstly to analyze the impact of the ISL ranging observations on the orbit determination of BDS-3 satellites. Subsequently, considering the data fusion processing, the variance component estimation (VCE) algorithm is applied to the parameter estimation process of the satellite orbit determination. Finally, using the measured data from China’s regional GTS observations and BDS-3 ISL ranging observations, the effects of ISL ranging observations on the orbit determination accuracy of BDS-3 satellites are analyzed. Moreover, the impact of the VCE algorithm on the fusion data processing is evaluated from the aspects of orbit determination accuracy, Ka-band hardware delay parameter stability, and ISL ranging observation residuals. The results show that for China’s regional GTSs, the addition of BDS-3 ISL ranging observations can significantly improve the orbit determination accuracy of BDS-3 satellites. The observed orbit determination accuracy of satellite radial component is improved from 48 cm to 4.1 cm. In addition, when the initial weight ratio between GTS observations and ISL ranging observations is not appropriate, the various indicators which include orbit determination accuracy, ISL hardware delay, and ISL observation residuals were observed to have improved after the adjustment of the VCE algorithm. These results validate the effectiveness of the VCE algorithm for the fusion data processing of the GTS observations and ISL ranging observations.     

Direction finding for two-dimensional incoherently distributed sources with Hadamard shift invariance in non-uniform orthogonal arrays

This paper proposes a novel algorithm for Two-Dimensional (2D) central Direction-of-Arrival (DOA) estimation of incoherently distributed sources. In particular, an orthogonal array structure consisting of two Non-uniform Linear Arrays (NLAs) is considered. Based on first-order Taylor series approximation, the Generalized Array Manifold (GAM) model can first be established to separate the central DOAs from the original array manifold. Then, the Hadamard rotational invariance relationships inside the GAMs of two NLAs are identified. With the aid of such relationships, the central elevation and azimuth DOAs can be estimated through a search-free polynomial rooting method. Additionally, a simple parameter pairing of the estimated 2D angular parameters is also accomplished via the Hadamard rotational invariance relationship inside the GAM of the whole array. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound. The simulation results show that the proposed algorithm can achieve a remarkably higher precision at less complexity increment compared with the existing low-complexity methods, which benefits from the larger array aperture of the NLAs. Moreover, it requires no priori information about the angular distributed function.