Ground Compatibility Tests for Gravity Measurement of SELENE: Accuracies of Two- and Four-Way Doppler and Range Measurements

The Japanese lunar mission Selenological and Engineering Explorer (SELENE) was launched in September 2007 and continued its mission until June 2009, when the main orbiter impacted with the surface of the Moon. SELENE consisted of three satellites: Main, Rstar, and Vstar. Rstar’s tasks were to forward up-link signals from the Usuada Deep Space Center (UDSC) to Main, and to down-link returning signals from Main to UDSC. We refer to this tracking sub-system as a four-way Doppler measurement. In contrast, conventional tracking systems between Rstar and UDSC as well as between Main and ground stations are referred to as two-way Doppler and range measurements. Using Main and Rstar, we successfully observed the gravity field over the farside of the Moon. Because four-way Doppler measurements via a relay sub-satellite were a fundamental experiment in space for Japanese space agencies, compatibility of radiometric instruments onboard Main and Rstar to UDSC were carefully examined at the UDSC using components manufactured for flight models. These tests not only proved the feasibility of the four-way Doppler measurements but also provided biases and variations of the four-way Doppler and two-way Doppler and range measurements that were later taken into account during the processing of tracking data and the analysis of the lunar global gravity field.     

Hypersonic Re-Entry Optical Transfer Equations And Photographic Techniques

Radiation transfer equations applicable to various types of imaging instruments used against distant sources are presented. Emphasis is placed on measurements against point and line radiators made with instruments yielding image spectra. Framing and streaking cameras are discussed in terms of the overall transfer functions of the instrument and sensor. Calibration techniques used for absolute intensity measurements are shown to yield data within a factor of two of the actual value in most cases. The instruments described are of specific use in optical radiometry against bodies penetrating the earth's atmosphere in the hypervelocity regime, and are equally applicable to measurements in a ballistic range. For the problem of tracking these fast-moving objects, imaging instruments are preferred to point detector devices.     

Sustained data recording system based on disk array

Most sustained data recording systems in many real-time fields are based on tape equipments. We have developed an innovative sustained data recording system based on disk array which consists of Array Controller Module (ACM), String Controller Module (SCM) and Main Controller Module (MCM). This system has a better performance and higher reliability than the traditional tape recorder and can be used conveniently in many areas of data recording, storing, playback, and remote backup. This novel recording system has been used in radar data recorder for spacecraft orbit tracking and satellite remote sensing data recording successfully.     

Detection of obstacles in the flight path of an aircraft

The National Aeronautics and Space Administration (NASA), along with members of the aircraft industry, recently developed technologies for a new supersonic aircraft. One of the technological areas considered for this aircraft is the use of video cameras and image-processing equipment to aid the pilot in detecting other aircraft in the sky. The detection techniques should provide high detection probability for obstacles that can vary from subpixel to a few pixels in size, while maintaining a low false alarm probability in the presence of noise and severe background clutter. Furthermore, the detection algorithms must be able to report such obstacles in a timely fashion, imposing severe constraints on their execution time. Approaches are described here to detect airborne obstacles on collision course and crossing trajectories in video images captured from an airborne aircraft. In both cases the approaches consist of an image-processing stage to identify possible obstacles followed by a tracking stage to distinguish between true obstacles and image clutter, based on their behavior. For collision course object detection, the image-processing stage uses morphological filter to remove large-sized clutter. To remove the remaining small-sized clutter, differences in the behavior of image translation and expansion of the corresponding features is used in the tracking stage. For crossing object detection, the image-processing stage uses low-stop filter and image differencing to separate stationary background clutter. The remaining clutter is removed in the tracking stage by assuming that the genuine object has a large signal strength, as well as a significant and consistent motion over a number of frames. The crossing object detection algorithm was implemented on a pipelined architecture from DataCube and runs in real time. Both algorithms have been successfully tested on flight tests conducted by NASA.     

Aerial Mapping Planetary Bodies

Photographic mapping missions over planetary bodies present a number of interesting hardware, operational, data retrieval, and data analysis techniques. Broadly speaking, such a mapping mission can be conducted with present level state-of-the-art equipment. The space-craft and photographic equipment must perform over long periods of time unattended in the hostile space environment. Operations must support the mission and retrieve the photographic data. Maximum data are limited by photographic capacity, operations capacity, and analysis capacity. Data analysis techniques are under development and computer maps have been developed for RANGER analysis; these techniques can be especially suited to analysis of the video (analog or digital) signal transmitted back to Earth.     

Security applications of computer vision

In an age which bears witness to a proliferation of Closed Circuit Television (CCTV) cameras for security and surveillance monitoring, the use of image processing and computer vision techniques which were provided as top end bespoke solutions can now be realised using desktop PC processing. Commercial Video Motion Detection (VMD) and Intelligent Scene Monitoring (ISM) systems are becoming increasingly sophisticated, aided, in no small way, by a technology transfer from previously exclusively military research sectors. Image processing is traditionally concerned with pre-processing operations such as Fourier filtering, edge detection and morphological operations. Computer vision extends the image processing paradigm to include understanding of scene content, tracking and object classification. Examples of computer vision applications include Automatic Number Plate Recognition (ANPR), people and vehicle tracking, crowd analysis and model based vision. Often image processing and computer vision techniques are developed with highly specific applications in mind and the goal of a more global understanding computer vision system remains, at least for now, outside the bounds of present technology. This paper will review some of the most recent developments in computer vision and image processing for challenging outdoor perimeter security applications. It also describes the efforts of development teams to integrate some of these advanced ideas into coherent prototype development systems     

The visible imaging system (VIS) for the polar spacecraft

The Visible Imaging System (VIS) is a set of three low-light-level cameras to be flown on the POLAR spacecraft of the Global Geospace Science (GGS) program which is an element of the International Solar-Terrestrial Physics (ISTP) campaign. Two of these cameras share primary and some secondary optics and are designed to provide images of the nighttime auroral oval at visible wavelengths. A third camera is used to monitor the directions of the fields-of-view of these sensitive auroral cameras with respect to sunlit Earth. The auroral emissions of interest include those from N ₂ ⁺ at 391.4 nm, Oi at 557.7 and 630.0 nm, Hi at 656.3 nm, and Oii at 732.0 nm. The two auroral cameras have different spatial resolutions. These resolutions are about 10 and 20 km from a spacecraft altitude of 8R _e . The time to acquire and telemeter a 256×256-pixel image is about 12 s. The primary scientific objectives of this imaging instrumentation, together with thein-situ observations from the ensemble of ISTP spacecraft, are (1) quantitative assessment of the dissipation of magnetospheric energy into the auroral ionosphere, (2) an instantaneous reference system for thein-situ measurements, (3) development of a substantial model for energy flow within the magnetosphere, (4) investigation of the topology of the magnetosphere, and (5) delineation of the responses of the magnetosphere to substorms and variable solar wind conditions.     

大型上单翼飞机机翼三维全场变形测量方案

针对大型上单翼飞机在飞行过程中机翼大挠度变形检测难题,提出了大倾角相机视场下机翼的非接触三维全场变形测量方案。根据上单翼飞机结构特点,将预先标定内参数和相机外参数的共轭相机组安装于飞机垂直尾翼上,采集飞行中的机翼变形图像。首先,提出了大倾角弱相关散斑匹配方法,解决了相机在大倾斜角度状态下采集到的机翼变形弱相关图像相关性差,难以相关匹配的问题。其次,由于测量相机安装于垂直尾翼,飞行测量过程中相机会受到气流扰动产生振动,本文提出了一种相机动态校正方法,通过在机背布置预拉伸刚性不动编码标志点,实时解算基准相机的绝对外参数,进而确定共轭相机的绝对外参数,实现所有测量相机外参数的动态校正。最后,开发了机翼变形全场测量软硬件系统,搭建了缩小比例机翼模型试验台并进行了仿真测量,对系统测量精度进行了比对分析。测量结果验证了本方案的有效性、可行性,对实机测量有一定的指导意义。     

Optimization of point target tracking filters

We review a powerful temporal-based algorithm, a triple temporal filter (TTF) with six input parameters, for detecting and tracking point targets in consecutive frame data acquired with staring infrared (IR) cameras. Using an extensive data set of locally acquired real-world data, we used an iterative optimization technique, the Simplex algorithm, to find an optimum set of input parameters for a given data set. Analysis of correlations among the optimum filter parameters based on a representative subset of our database led to two improved versions of the filter: one dedicated to noise-dominated scenes, the other to cloud clutter-dominated scenes. Additional correlations of filter parameters with measures of clutter severity and target velocity as well as simulations of filter responses to idealized targets reveal which features of the data determine the best choice of filter parameters. The performance characteristics of the filter is detailed by a few example scenes and metric plots of signal to clutter gains and signal to noise gains over the total database     

The stellar triangulation with photographic observations

A general method for the adjustment of stellar triangulation using photographic observations of artificial satellites, missiles or rockets with stars in the background is suggested. This approach recognizes the plate readings as basic data and makes use of the astronomical method of dependences in establishing the conditional equations. The method is valid for both stationary and nonstationary camera systems. Its simplicity makes possible the adjustment in a block — as organic unit — of a world-wide triangulation with photographic observations. Since it is intended to establish a working system from this theory, some controversial engineering aspects are discussed while the method is critically compared with the familiar photogrammetric approach. A historical review and a synthesis of the contemporary efforts for the development of a world-wide stellar triangulation are presented.     

风洞试验中模型迎角视觉测量技术研究

 发展了一种基于双相机的风洞试验模型迎角视觉测量技术。即在风洞模型表面绘制或喷涂一些高对比度的标记点,采用两台400万像素的工业相机采集模型的运动图像,然后求解图像的共线方程获得模型表面标记点的三维空间坐标,利用表面标记点坐标最小二乘拟合出一条空间直线,通过不同时刻空间直线单位方向矢量的变化计算出模型的迎角变化。利用精密电子倾斜仪对迎角视觉测量系统进行静态标定,结果表明:迎角视觉测量系统的准确度在0.01°以内。迎角视觉测量系统在2 m超声速风洞中对一尾支撑无主测力天平铰链力矩测量模型的实时迎角进行了测量,结果表明:系统具有很好的响应特性,可以作为风洞试验中迎角测量的一种有效方法,尤其是用于无主测力天平时模型真实迎角和支杆弹性角的测量。     

Video surveillance applications using multiple views of a scene

Automatic video surveillance techniques are used to detect intruders within a scene. This task is mostly reduced to the problem of detecting moving objects evaluating image sequences of a monocular camera. An essential problem of this monocular approach is its inability to measure the 3D-size and 3D-position of objects reliably, as object size and velocity are estimated within the 2D-image plane. To include 3D-information about the scene an approach using a second camera is proposed in this paper which combines the evaluation of the measurement data of the two cameras using an efficient 3D-scene model. Here, two cameras are used with an overlapping field of view, which represents an installation often used in existing video surveillance applications. It is shown that using the combined evaluation of the two cameras, the false detection rate in the case of moving shadows, leaves, birds and insects or blindings can be further reduced compared to a pure monocular evaluation     

Electrooptical navigation for aircraft

Concurrently with the development of guidance laws for low-altitude rotorcraft flight operations, efforts are underway to develop automated systems for locating the terrain and the obstacles using inputs from passive electrooptical sensors such as TV cameras and infrared imagers. A passive obstacle location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given     

一种月球车视觉系统的匹配算法

 对采用双目视觉来实现月球车自主导航提出了一种快速匹配的方法。首先,对相机的内外参数进行精确地标定,通过两相机的外参数对图像进行核线纠正,生成消除上下视差的核线;然后,在核线图像上,采用相关系数法进行由少到多的粗匹配,对匹配结果进行多重的检验,接着用最小二乘方法进行亚像素的精确匹配;最后,在匹配的像点间构建Delaunay三角网,建立两图像重叠区域的匹配关系,实现稠密匹配。对该方法进行了多组实验,实验结果表明:该方法可以快速、可靠地实现稠密的图像匹配。     

N-fold Bernoulli probability based adaptive fast-tracking algorithm and its application to autonomous aerial refuelling

Recently, deep learning has been widely utilized for object tracking tasks. However, deep learning encounters limits in tasks such as Autonomous Aerial Refueling (AAR), where the target object can vary substantially in size, requiring high-precision real-time performance in embedded systems. This paper presents a novel embedded adaptiveness single-object tracking framework based on an improved YOLOv4 detection approach and an n-fold Bernoulli probability theorem. First, an Asymmetric Convolutional Network (ACNet) and dense blocks are combined with the YOLOv4 architecture to detect small objects with high precision when similar objects are in the background. The prior object information, such as its location in the previous frame and its speed, is utilized to adaptively track objects of various sizes. Moreover, based on the n-fold Bernoulli probability theorem, we develop a filter that uses statistical laws to reduce the false positive rate of object tracking. To evaluate the efficiency of our algorithm, a new AAR dataset is collected, and extensive AAR detection and tracking experiments are performed. The results demonstrate that our improved detection algorithm is better than the original YOLOv4 algorithm on small and similar object detection tasks; the object tracking algorithm is better than state-of-the-art object tracking algorithms on refueling drogue tracking tasks.