Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

Phugoid oscillations in optimal reentry trajectories

A major problem with operations of lifting reentry vehicle having an aft center-of-gravity location due to large engine mass at the rear is the required hypersonic trim to fight the desired trajectory. This condition is most severe for lifting maneuvers. As a first step toward analyzing this problem, this paper considers the lift requirement for some basic maneuvers in the plane of a great circle. Considerations are given to optimal lift control for achieving the maximization of either the final altitude, speed or range. For the maximum-range problem, phugoid oscillation along an optimal trajectory is less severe as compared to a glide with maximum lift-to-drag ratio. An explicit formula for the number of oscillations for an entry from orbital speed is proposed.     

测控站点电磁兼容分析与预测技术研究

本文介绍了对测控站点内各测控设备的电磁干扰进行分析和预测的方法。系统采用干扰源与接收机逐对考虑的方式，极大简化了计算。并采用分阶段预测的方法，即分成：快速筛选、幅度筛选、频率筛选和详细预测四个阶段进行逐阶段分析和预测。     

月球探测器姿态大角度机动的反作用轮控制

研究了月球探测器转速与控制力矩受限的姿态大角度机动问题。根据时间变尺度思想，提出了双回路反馈的姿态大角度机动控制方法。以某型月球控测器为例，对该方法进行了仿真验证。结果表明，利用该控制方法，可使探测器以期望的角速度转动，从而完成探测器的姿态大角度机动。     

软着陆小行星的制导与控制规律研究

提出了一种微小探测器软着陆小行星的制导与控制策略，将软着陆小行星控制分解为速度方向控制和减速控制，为了控制速度方向，给出了一种带有终端控制项的比例导引规律，可以按闭环模式将探测器引向着陆点，并满足垂直下落的终端条件，为了实现无碰撞着陆，给出了一种减速控制规律，通过对理想速度曲线的跟踪，实现软着陆，仿具结果表明，提出的制导与控制策略可以实现探测器在小行星表面垂直软着陆。     

A recursive multiple model approach to noise identification

Correct knowledge of noise statistics is essential for an estimator or controller to have reliable performance. In practice, however, the noise statistics are unknown or not known perfectly and thus need to be identified. Previous work on noise identification is limited to stationary noise and noise with slowly varying statistics only. An approach is presented here that is valid for nonstationary noise with rapidly or slowly varying statistics as well as stationary noise. This approach is based on the estimation with multiple hybrid system models. As one of the most cost-effective estimation schemes for hybrid system, the interacting multiple model (IMM) algorithm is used in this approach. The IMM algorithm has two desirable properties: it is recursive and has fixed computational requirements per cycle. The proposed approach is evaluated via a number of representative examples by both Monte Carlo simulations and a nonsimulation technique of performance prediction developed by the authors recently. The application of the proposed approach to failure detection is also illustrated     

Multistage integration model for human egomotion perception

Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.     

Tracking in clutter with nearest neighbor filters: analysis andperformance

The measurement that is “closest” to the predicted target measurement is known as the “nearest neighbor” (NN) measurement in tracking. A common method currently in wide use for tracking in clutter is the so-called NN filter, which uses only the NN measurement as if it were the true one. The purpose of this work is two fold. First, the following theoretical results are derived: the a priori probabilities of all three data association events (updates with correct measurement, with incorrect measurement, and no update), the probability density functions (pdfs) of the NN measurement conditioned on the association events, and the one-step-ahead prediction of the matrix mean square error (MSE) conditioned on the association events. Secondly, a technique for prediction without recourse to expensive Monte Carlo simulations of the performance of tracking in clutter with the NN filter is presented. It can quantify the dynamic process of tracking divergence as well as the steady-state performance. The technique is a new development along the line of the recently developed general approach to the performance prediction of algorithm with both continuous and discrete uncertainties     

Genetic differentiation induced by spaceflight treatment of Cistanche deserticola and identification of inter-simple sequence repeat markers associated with its medicinal constituent contents

The dried, fleshy stems of Cistanche deserticola (Orobanchaceae) are popular tonics in Traditional Chinese Medicine (TCM) to treat the inability of kidney in expelling extra fluid in the body, causing fluid retention, and reform reproductive system. However, the wild plants of C. deserticola have become endangered due to habitat downsizing and over-harvesting for its medicinal usages. The present research was carried out for the following purposes: (1) promoting the space-breeding research; (2) providing molecular evidence for agricultural selective breeding; and (3) protecting this endangered herbal medicine and conserving its genetic resources.