A comprehensive survey on the methods of angle of attack measurement and estimation in UAVs

Angle of Attack (AOA) is a crucial parameter which directly affects the aerodynamic forces of an aircraft. The measurement of AOA is required to ensure a safe flight within its designed flight envelop. This paper intends to summarise a comprehensive survey on the measurement techniques and estimation methods for AOA, specifically in Unmanned Aerial Vehicle (UAV) applications. In the case of UAVs, weight constraint plays a major role as far as sensor suites are concerned. This results in selecting a suitable estimation method to extract AOA using the available data from the autopilot. The most feasible and widely employed AOA measurement technique is by using the Multi-Hole Probes (MHPs). The MHP measures the AOA regarding the pressure variations between the ports. Due to the importance of MHP in AOA measurement, the calibration methods for the MHP are also included in this paper. This paper discusses the AOA measurement using virtual AOA sensors, their importance and the operation.     

Research on navigation of satellite constellation based on an asynchronous observation model using X-ray pulsar

Pulsar navigation is a promising navigation method for high-altitude orbit space tasks or deep space exploration. At present, an important reason for restricting the development of pulsar navigation is that navigation accuracy is not high due to the slow update of the measurements. In order to improve the accuracy of pulsar navigation, an asynchronous observation model which can improve the update rate of the measurements is proposed on the basis of satellite constellation which has a broad space for development because of its visibility and reliability. The simulation results show that the asynchronous observation model improves the positioning accuracy by 31.48% and velocity accuracy by 24.75% than that of the synchronous observation model. With the new Doppler effects compensation method in the asynchronous observation model proposed in this paper, the positioning accuracy is improved by 32.27%, and the velocity accuracy is improved by 34.07% than that of the traditional method. The simulation results show that without considering the clock error will result in a filtering divergence.     

频率及频率变化率的快速最大似然估计

信号参数估计是许多领域 (如雷达、通信、导航和声钠等 )都会遇到的共同问题。文中证明 ,牛顿法是实现频率 (η)和频率变化 (β)最大似然估值器的快速有效算法 ,并且详细分析了牛顿估值器的性能。研究证明 ,对于牛顿法 ,(η,β)是以三次方律收敛于真值 (η,β)的。模拟结果表明 ,当输出信噪比 ( SNR) o≥ 15 d B时 ,估计量的均方误差 ( MSE)达到Cramer- Rao界     

二维通道内湍流边界层分离的实验研究

用激光多普勒技术测量了二维扩压器中不可压湍流边界层分离流动，得到了时均速度和雷诺剪应力分布。实验结果分析表明：以Ｃｏｌｅｓ速度律发展的Ｂａｒｄｉｎａ速度分布可以描述瞬时间歇分离点以前和瞬时间歇再附点以后的时均速度分布，但无法描述分离区的边界层速度型。Ｃｒｏｓｓ速度分布可描述分离区的边界层速度分布。Ｃｅｂｅｃｉ＆Ｓｍｉｔｈ涡粘性代数模型难以正确地描述分离边界层的雷诺剪应力。     

安装和不安装垂直嵌板的鸭式飞机横向稳定性研究

研究了带有和不带有伸出的垂直嵌板的鸭式飞机(Velocity-173)的横向稳定性。众所周知，鸭式飞机(Velocity—173)具有良好的纵向稳定性．但其横向稳定性比较差。为了改善其横向稳定性．设计了两种复合材料夹层板．将其安装在垂直尾翼下面．并进行了一系列的飞行试验来研究安装伸出的垂直嵌板的效果。采用解析法和实时参数估计法从飞行试验数据中提取了横向可控能力／稳定性。本的工作验证了安装垂直嵌板对横向稳定性的效果。     

神经网络在未来超分辨雷达中的应用

最新的技术发展已为研制超分辨雷达创造了条件。它能够突破普通雷达基于匹配滤波原理的分辨能力,而实现超分辨。超分辨雷达的巨大计算量通常来自求解非线性最小二乘问题时的多维搜索。本文针对这一问题,研究了雷达信号处理中的两个典型例子:(1)利用阵列处理检测个数已知而方向未知的雷达目标;(2)对波音727飞机进行超分辨距离多普勒成像。说明Hop-field神经网络通过集体运算能够求解各种困难的最优化问题,因而在未来的超分辨雷达中有广阔的应用前景。     

星载合成孔径雷达回波多普勒频率的计算

从星载合成孔径雷达（ＳＡＲ）与目标的相对运动关系出发，以ＳＡＲ发射信号的波长、卫星的轨道参数和目标的位置（地心经纬度）为已知条件，导出了计算目标回小以的多普勒频率的解析公式，这对于星载ＳＡＲ系统的性能 初步设计具有重要作用。     

自由转子陀螺仪的伺服测试技术研究

自由转子陀螺仪是目前精度最高的一种陀螺仪,没有精密的力矩器,因此,只能采用双轴伺服法来辨识其漂移误差模型。介绍了双轴伺服测试法的基本原理,给出了双轴伺服转台的运动轨迹及重力矢量的变化规律。根据转台的运动特性,建立了自由转子陀螺仪的漂移误差模型,导出双轴伺服转台转角数据估计漂移误差模型系数的算法。从测试结果可以看出自由转子陀螺仪的长时间精度高,表明采用伺服测试法能够获得极高的测试精度,伺服转台可以作为测试自由转子陀螺仪精度的装置。     

Efficacy of Doppler ultrasound [correction of utrasound] for screening symptoms of decompression sickness during simulated extravehicular activities

Doppler ultrasound is frequently used for monitoring circulating microbubbles during decompression to assess the symptoms of Decompression Sickness (DCS). This analysis was carried out to evaluate its effectiveness for screening symptoms of DCS during simulated extravehicular activities (EVA). The information from various hypobaric chamber studies carried out at the NASA Johnson Space Center, Houston, TX was used in this analysis (n = 516). The circulating microbubbles were detected in the precordial area in 42% (218/516), and symptoms were reported in 16% (81/516) of these exposures. The accuracy of Doppler-detectable bubbles (Spencer grades) on all symptoms of DCS was examined by calculating measures of sensitivity and specificity. The efficacy of Doppler as a screening device was examined by calculating their positive predictive value (PPV) and negative predictive value (NPV). The results of these analyses indicated that the sensitivity of Doppler decreased, and the PPV increased with higher Spencer grades. However, the likelihood of detecting true negative cases (NPV) was consistently higher with all bubble grades. Due to the high false-positive rate and low prior probabilities of the risk of DCS, Doppler was found to be more useful to identify those who did not develop DCS, than to detect positive cases of DCS in the simulated EVA exposures.     

卫星成本预测的蒙特卡洛优化模型研究

传统的卫星成本预测模型预测结果单一，未考虑相应的不确定性因素。对此，提出了基于蒙特卡洛方法的卫星成本预测模型。该模型综合考虑了卫星成本技术的不确定性并给出了预测值的区间范围和概率分布。为了降低应用该模型所产生的误差，提出了最优分层抽样的方法，并通过划分分层区间提高了抽样的效率。最后，将收集到的相关数据代人该模型，其结果精度大约提高了10％左右。可见，使用优化的蒙特卡洛方法进行卫星成本预测具有较好的精确度。