Reconnaissance Platforms Research Articles

Research on single target cognitive electronic reconnaissance strategy for unmanned aerial vehicle

AbstractThe integration of electronic reconnaissance platforms and payloads in the electromagnetic and spatial domains of cognition is necessary for the successful execution of cognitive electronic reconnaissance missions. However, in partially observable environments, platforms and payloads interact in separate operational domains, making it a challenge for the model. The authors create a theoretical model of cognitive electronic reconnaissance, present an analysis method of model elements and derives adequate requirements for optimal radiation source sorting or recognition. Then, a 3D cognitive reconnaissance simulator ‘Scouter’ to simulate the dynamic interaction process of space electronic reconnaissance missions is developed and a deep reinforcement learning framework to optimise the electronic reconnaissance strategies of Unmanned Aerial Vehicle (UAV) is designed. For the first time, a method for judging reconnaissance area coverage using a behavioural angle is proposed. This method enables a deep reinforcement learning‐based UAV with better reconnaissance behaviours and to realise the stable targeting of the target by the receiving antenna beam during reconnaissance. Moreover, the fast convergence of UAV agent training is ensured through the normalisation of partially observable status and reward shaping. Verified by adequate numerical simulations, a trained UAV can complete a 100 reconnaissance cycles mission with a completion rate of 91.9%. Even after the reconnaissance cycles are prolonged to 600, the mission completion rate can still be maintained at 78.5%. The most satisfying aspect is that the UAV comprehends the idea of reconnaissance and behaves in a way that is typical of it, such as by reciprocating or circling the edge of the radar's detecting power.

Advances in Aerial Image Exploitation

The availability of low cost sensors, high bandwidth communication links and the growing popularity of Unmanned Aerial Reconnaissance Platforms like UAVs have resulted in dramatic new opportunities to conduct remote battlefield surveillance and reconnaissance missions from relatively safe Ground Control Stations. The sensors used in UAV explore the visible, infrared and microwave regions of the spectrum and the images are produced optically, electronically or by film. Aerial Image Exploitation is an innovative image utilization program that uses multi sensor, multi resolution and multi spectral imagery obtained from Aerial Reconnaissance Platform for the purpose of Extraction, Exploitation, Dissemination and Interpretation of Imagery Intelligence. Research in aerial image exploitation is focused to provide a total solution of the problem by combining both hardware and software at the system and subsystem level. Major operational goal of image exploitation technology is to extract the vital intelligence from a large storehouse of available imagery by filtering those which are most likely to produce valuable findings, to combine classical image/signal processing techniques with technologies available in other fields and to use specialized hardware wherever required. The first part of the paper describes the Ground Image Exploitation System and Imagery Intelligence Exploitation System being developed in ADE. The second part of the paper describes some of the basic and advanced research work being carried out in ADE, which is the backbone that lead to the development of these systems. Some of the areas discussed in this paper are adaptive preprocessing of imagery, image mosaicing, terrain classification and high-resolution reconstruction of target region.

Review for Region Localization in Large-Scale Optical Remote Sensing Images

For the massive large-scale visible image data obtained by satellite, unmanned aerial vehicles, and other reconnaissance platforms, if only relying on manual visual interpretation, there will be problems such as heavy workload, low efficiency, high repeatability, strong subjectivity, and high cost, which cannot meet the demand of modern society for efficient information. Therefore, in order to improve work efficiency, it is necessary to study the rapid automatic region localization in large-scale remote sensing images. That will play an important role in change detection, temperature retrieval, and other files. The development and present situation of the region localization algorithms are analyzed. This paper summarizes the development, improvement, and deficiency of the traditional algorithm, as well as the difficulties and challenges. And the authors make a comparison to the deep learning-based methods. Finally, a possible development direction is prospected.

Indoor and Outdoor Tests for a Chemi-capacitance Carbon Nanotube Sensor Installed on a Quadrotor Unmanned Aerial Vehicle for Dimethyl Methylphosphonate Detection and Mapping.

Unmanned aerial vehicles (UAVs) have been used as a new chemical reconnaissance platform in chemical, biological, radiological, and nuclear detection and in industrial monitoring and environmental research, owing to their mobility, unconventional accessibility, and safety. Based on the UAV’s payload and operational time considerations, the ultralight chip-sized chemical sensor is the most promising candidate for chemical reconnaissance among various chemical sensors. To optimize the UAV’s chip-sensor performance, realistic outdoor tests of chemical sensors during UAV flights have to be conducted to verify their performances. In this study, indoor and outdoor experiments were conducted with a carbon nanotube (CNT)-based chip sensor installed on the UAV to detect dimethyl methylphosphonates (DMMPs), commonly used as chemical warfare agent simulants. Based on the indoor tests, DMMP concentrations and the position/direction of the CNT sensor were analyzed to optimize the sensing performances during UAV operations. Based on outdoor tests, we confirmed that the chemical sensor mounted on the UAV could detect DMMP gases by moving designated pathways in realistic conditions.

The Effect of a Flow Field on Chemical Detection Performance of Quadrotor Drone.

The determination of a suitable sensor location on quadrotor drones is a very important issue for chemical reconnaissance platforms because the magnitude and direction of air velocity is different for each location. In this study, we investigated a customized chemical reconnaissance system consisting of a quadrotor drone and a chip-sized chemical sensor for detecting dimethyl-methylphosphonate (DMMP; a Sarin simulant) and investigated the chemical detection properties with respect to the sensor position through indoor experiments and particle image velocimetry (PIV) analysis of the system. The PIV results revealed an area free of vortex–vortex interaction between the drone rotors, where there was distinctly stable and uniform chemical detection of DMMP. The proposed chemical reconnaissance system was found to be realistic for practical application.

Near-earth space two-dimension opto-electronic turntable design

Near earth space is a space which has important strategic significance and application value in military, scientific exploration and other industry fields, one of the most practical application is to make a reconnaissance platform that can work normally in the near earth space. In this paper, a two-dimensional photoelectric turntable for video surveillance in near-earth space is designed, which can observe the azimuth angle 360° and pitch angle from −110° to 10°, and the capacity of this photoelectric turntable is 7 kg in a space of ϕ300 mm. The optical imaging load in the photoelectric turntable can output high-definition video in real time and the original image is stored in the memory card simultaneous. What is more, the imaging effect can be adjusted by controlling the magnification and focal length by sending commands through serial communication ports. The two-dimensional photoelectric turntable designed in this paper is mounted on the payload cabin and raised to 32.5 km for surveillance imaging. The experimental results show that the two-dimensional photoelectric turntable can work normally in the harsh near space environment, and the optical imaging load can output and record fluent high-definition video. The photoelectric turntable designed in this paper will be equipped with other optical load and take part in some near space exploration tasks in the future and obtain corresponding result.

车载光电侦察平台视轴稳定技术研究

车载光电侦察平台视轴稳定技术研究

航空光电侦察平台内藏式扫描系统像旋分析及补偿

航空光电侦察平台内藏式扫描系统像旋分析及补偿

Attitude algorithm design for light beam circumrotated on three-axis electro-optical reconnaissance platform

摘要: 为解决某三轴可旋转光电侦查平台上光束旋转的姿态计算问题，分别利用了四元数算法和坐标变换算法对该问题算法进行了推算。经过仿真验证，这两种算法都能够得到正确结果。相比较而言，坐标变换算法形式简单，便于理解和实现。但是，坐标变换计算过程中大量使用的三角函数计算，计算量大，实时性差；四元数算法使用的三角函数计算很少，更易于工程应用。 关键词: 光电侦查平台，姿态算法，四元数，坐标变换

DROP: the Durable Reconnaissance and Observation Platform

PurposeThe Durable Reconnaissance and Observation Platform (DROP) is a prototype robotic platform with the ability to climb vertical cinder block surfaces at a rate of 25 cm/s, make rapid horizontal to vertical transitions, carry an audio/visual reconnaissance payload, and survive impacts from 3 meters.Design/methodology/approachThe platform uses a two‐wheel, two‐motor design that delivers high mobility with low complexity. DROP extends microspine climbing technology from a linear to rotary implementation, providing improved transition ability, increased speeds, and simpler body mechanics while maintaining microspine's ability to opportunistically grip rough surfaces.FindingsThe DROP prototype was able to climb rough, vertical walls at a speed of 25 cm/s. These wheels were also deployed on a commercial platform, the ReconRobotics Scout, and demonstrated additional mobility capabilities such as curb mounting and stair climbing.Originality/valueThis robot is the first wheeled robot to use microspine technology. Various aspects of the prototype robot's design and performance are discussed, including the climbing mechanism, body design, and impact survival.

光电稳定平台框架结构探讨

The multi-structures of gimbals for the electro-optical reconnaissance platform are introduced. Their respective merits and flaws are studied from the stabilization principle. At last, the four-gimbal-two-axis electro-optical stabilization platform is pointed out as the best choice in this paper, along with the development of electro-optical reconnaissance techniques and equipments.

English

A wide variety of image processing applications require segmentation and classification ofimages. The problem becomes complex when the images are obtained in an uncontrolledenvironment with a non-uniform illumination. The selection of suitable features is a critical partof an image segmentation and classification process, where the basic objective is to identify theimage regions that are homogeneous but dissimilar to all spatially adjacent regions. This paperproposes an automatic method for the classification of a terrain using image features such asintensity, texture, and edge. The textural features are calculated using statistics of geometricalattributes of connected regions in a sequence of binary images obtained from a texture image.A pixel-wise image segmentation scheme using a multi-resolution pyramid is used to correct thesegmentation process so as to get homogeneous image regions. Localisation of texture boundariesis done using a refined-edge map obtained by convolution, thinning, thresholding, and linking.The individual regions are classified using a database generated from the features extracted fromknown samples of the actual terrain. The algorithm is used to classify airborne images of a terrainobtained from the sensor mounted on an aerial reconnaissance platform and the results arepresented.

English

The aerial imagery obtained from reconnaissance platform is voluminous and the defenceforces rely on image information to perform intelligent tasks. The application of a welldesigned automatic image classifier would enhance the end results of different high levelapplications thereby abridging the effort of a human analyst. Automatic image classifierscould be designed using a training data set for supervised learning or using an unsupervisedlearning. In this paper, a method, which combines both unsupervised and supervised methodsof learning is proposed.

Development of an Autonomous Tactical Reconnaissance Platform

&In this paper, an application of Fuzzy Logic in the control of an autonomous parafoil surveillance platform is described. A unique methodology (Combs’ method) was employed to reduce the common problem of ‘exponential rule expansion’ encountered in Fuzzy Control Systems. The use of this method also simplified the tuning process of the fuzzy system by requiring the optimization of only the membership functions and not the rule base. Modularity and simplicity of design were further enhanced by adopting a layered fuzzy logic architecture. The fuzzy system was optimized over a wide range of simulated flight conditions, providing a simple yet robust means of controlling the vehicle. Hardware limitations in terms of memory, computational speed and cost were critical factors driving the need for a simple yet robust control algorithm. This autonomous parafoil, developed under a grant from the Office of Naval Research, was designed to follow a predetermined flight pattern from altitudes of 350 meters or more down to the ground. Flight tests of a rocket-launched prototype device and simulation in the Matlab/Simulink software environment have verified that this fuzzy logic control method performs to the required specifications.

“Space superiority”: Wernher von Braun's campaign for a nuclear-armed space station, 1946–1956

Abstract The literature on the history of spaceflight has depicted the early 1950s Collier’s articles mostly as a forerunner to the peaceful and scientific exploration of space. Yet the centerpiece of Wernher von Braun's plan was a manned space station that would serve as reconnaissance platform and orbiting battle station for achieving “space superiority” over the USSR. One its roles could be the launching of nuclear missiles. When challenged as to the station's defensibility, von Braun even posited pre-emptive atomic strikes from space as a response to the development of a hostile anti-satellite capability.

Phantom Fracas: The 1968 American Sale of F-4 Aircraft to Israel

In a late November 1968 exchange of letters between Assistant Secretary of Defence for International Security Affairs Paul Warnke and Israeli Ambassador to the United States Yitzhak Rabin, the Johnson administration formally agreed to supply Israel with 50 F-4 Phantom aircraft.' Under the terms of the sale, the Israel Air Force (IAF) would also receive associated ordnance, spare parts, maintenance equipment and training. Six of the Phantoms would be specially configured to serve as reconnaissance platforms, though they would be capable of fulfilling standard combat missions as well. The first batch of aircraft would reach Israel in September 1969, according to an accelerated delivery schedule one that would not, however, interfere with Phantom production for American military forces.2 On both military and diplomatic grounds, the Phantom sale held great significance for Israel. Militarily speaking, the addition of this state-of-the-art aircraft to the Israeli order of battle massively upgraded the IAF's fighting power. Diplomatically speaking, the deal signalled an enhanced American commitment to Israel's security. Likewise, the sale had very important implications for American foreign policy. It meant that the United States had now chosen, in effect, to become Israel's principal arms supplier, a role that it had strenuously sought to avoid before the 1967 Six-Day War. Furthermore, at least insofar as concerned airpower, the United States had now also reconciled itself to providing Israel with better arms than those in the hands of its Arab opponents, another departure from past policy. Not every Johnson administration official necessarily viewed the Phantom sale as quite so consequential at the time, but they all nevertheless recognized that it could seriously affect America's standing in the Middle East by infuriating the Soviet Union and the Arab world. For this reason, the administration thought long and hard about its decision to sell the Phantom to Israel, meticulously weighing the potential benefits and potential costs of such a deal. Indeed, it took almost all of 1968 to make up its mind on the sale. Moreover, the administration's most senior foreign policy officials -

Navigation Aided Image Processing in UAV Surveillance: Preliminary Results and Design of an Airborne Experimental System

AbstractThis paper describes an airborne reconfigurable measurement system being developed at Swedish Defence Research Agency (FOI), Sensor Technology, Sweden. An image processing oriented sensor management architecture for UAV (unmanned aerial vehicles) IR/EO‐surveillance is presented. Some preliminary results of navigation aided image processing in UAV applications are demonstrated, such as SLAM (simultaneous localization and mapping), structure from motion and geolocation, target tracking, and detection of moving objects. The design goal of the measurement system is to emulate a UAV‐mounted sensor gimbal using a stand‐alone system. The minimal configuration of the system consists of a gyro‐stabilized gimbal with IR and CCD sensors and an integrated high‐performance navigation system. The navigation system combines dGPS real‐time kinematics (RTK) data with data from an inertial measurement unit (IMU) mounted with reference to the optical sensors. The gimbal is to be used as an experimental georeferenced sensor platform, using a choice of carriers, to produce military relevant image sequences for studies of image processing and sensor control on moving surveillance and reconnaissance platforms. Furthermore, a high resolution synthetic environment, developed for sensor simulations in the visual and infrared wavelengths, is presented. © 2004 Wiley Periodicals, Inc.

A portable, autonomous, urban reconnaissance robot

Portable mobile robots, in the size class of 20 kg or less, could be extremely valuable as autonomous reconnaissance platforms in urban hostage situations and disaster relief. We have developed a prototype urban robot on a novel chassis with articulated tracks that enable stair climbing and scrambling over rubble. Autonomous navigation capabilities of the robot include stereo vision-based obstacle avoidance, visual servoing to user-designated goals, and autonomous vision-guided stair climbing. The system was demonstrated in an urban reconnaissance mission scenario at Fort Sam Houston in October 1999. A two-axis scanning laser rangefinder has been developed and integrated into the robot for indoor mapping and position estimation. This paper describes the robot, its performance in field trials, and some of the technical challenges that remain to enable fieldable urban reconnaissance robots.

Implementation of Image Registration Algorithms for Real-time Target Tracking Through Video Sequences

Automatic detection and tracking of interesting targets from a sequence of images obtained from a reconnaissance platform is an interesting area of research for defence-related applications. Image registration is the basic step used in target tracking application. The paper briefly reviews some of the image registration algorithms, analyse their performance using a suitable image processing hardware, and selects the most suitable algorithm for a real-time target tracking application using cubic-spline model and spline model Kalman filter for the prediction of an occluded target. The algorithms developed are implemented in a ground-based image exploitation system (GIES) developed at the Aeronautical Development Establishment for unmanned aerial vehicle application, and the results presented for the images obtained during actual flight trial.

Image Exploitation-A Forefront Area for UAV Application

Image exploitation, an innovative image utilisation program uses high revisit multisensor, multiresolution imagery from unmanned air vehicle or other reconnaissance platform for intelligent information gathering. This paper describes the imagc exploitation system developed at the Aeronautical Dcvclopment Establishment, Bangalore, for the remotely piloted vehicle (RPV) Nishonr and highlights two major areas (i) In-flight imagc exploitation, and (ii) post-flight imagc cxploitatlon. In-flight imagc study includes real-timeenhancement of images frames during RPV flight. target acquisition. calculation of geo-location of targets, distance and area computation, and image-to-map correspondence. Post-flight image exploitation study includes image restoration, classtfication of terrain, 3-D depth computation using stereo vision and shape from shading techniques. The paper shows results obtained in each of these areas from actual flight trials.