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"Reconnaissance aircraft"
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The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity
This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.
Journal Article
Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
To achieve cooperative reconnaissance and localization of manned and unmanned aircraft, based on the traditional direction‐finding cross‐localization method, a direction cooperative localization model has been developed based on different baseline criteria. Compared with the traditional methods which require the reconnaissance platforms locating at the same fixed baseline, the proposed model can adapt to different conditions. In this model, the manned electronic reconnaissance aircraft can conduct tasks at a greater distance from the target, while the unmanned electronic reconnaissance aircraft cruises closer to the target. Moreover, the localization error is analyzed by using the circular error probable method, geometric approximation method, and the geometric dilution of precision method. In addition, through simulations, the affecting factors are studied. Simulation results demonstrate that a smaller direction‐finding error leads to a smaller localization error and the closer the unmanned electronic reconnaissance aircraft is to the target, the smaller the localization error. Moreover, simulation results demonstrate the existence of optimal direction‐finding angles that minimize localization error. These optimal angles are determined by the vertical distance between the reconnaissance aircraft′s cruise route and the target, as well as the direction‐finding error. These findings validate that the proposed model can offer better localization accuracy than the traditional method and can be applied in practical cooperative localization tasks.
Journal Article
Above & beyond : John F. Kennedy and America's most dangerous Cold War spy mission
\"From the authors of the bestselling The Finest Hours comes the riveting, deeply human story of President John F. Kennedy and two U-2 pilots, Rudy Anderson and Chuck Maultsby, who risked their lives to save America during the Cuban Missile Crisis. During the ominous two weeks of the Cold War's terrifying peak, two things saved humanity: the strategic wisdom of John F. Kennedy and the U-2 aerial spy program. On October 27, 1962, Kennedy, strained from back pain, sleeplessness, and days of impossible tension, was briefed about a missing spy plane. Its pilot, Chuck Maultsby, was on a surveillance mission over the North Pole, but had become disoriented and steered his plane into Soviet airspace. If detected, its presence there could be considered an act of war. As the president and his advisers wrestled with this information, more bad news came: another U-2 had gone missing, this one belonging to Rudy Anderson. His mission: to photograph missile sites over Cuba. For the president, any wrong move could turn the Cold War nuclear. Above and Beyond is the intimate, gripping account of the lives of these three war heroes, brought together on a day that changed history.\"--provided by publisher.
Book
Design of Effectiveness Evaluation System for Shipborne Unmanned Reconnaissance Aircraft
Gu, T. and Chen, Y., 2018. Design of effectiveness evaluation system for shipborne unmanned reconnaissance aircraft. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 565–570. Coconut Creek (Florida), ISSN 0749-0208. The effectiveness evaluation system of traditional shipborne unmanned reconnaissance aircraft has some disadvantages, such as poor efficiency evaluation, low system connectivity and so on. In order to solve the above problems effectively, it is necessary to designe a new effectiveness evaluation system for the new warship unmanned reconnaissance aircraft on the basis of the original system. It completes the hardware module design of the effectiveness evaluation system for the shipborne unmanned reconnaissance aircraft through the design of system hierarchy, the design of system operation process and the design of system task structure. And it completes the software module design of the effectiveness evaluation system for the shipborne unmanned reconnaissance aircraft through the design of boot development process, the design of the system kernel and the design of the driver. Compared with the traditional system, the experimental results showed that the effectiveness and the efficiency of the system are greatly improved.
Journal Article
Effectiveness evaluation on UAV reconnaissance based on AHP grey-fuzzy comprehensive evaluation model
Regarding the effectiveness evaluation of unmanned aerial vehicle (UAV) reconnaissance, this article constructed an action process for UAV reconnaissance according to the OODA ring theory, analyzed the capability components through top-down approaches, and established a hierarchical index evaluation system for reconnaissance. The analytic hierarchy process (AHP) and grey-fuzzy comprehensive evaluation model were used to establish an effectiveness evaluation model of UAV reconnaissance, to enhance the reliability, credibility, and scientific nature of the evaluation. A certain type of UAV reconnaissance action was taken as an example to verify the practicality and scientific nature of the index evaluation system and evaluation model, which can provide theoretical reference and inspiration for the construction and capability upgrading of UAV reconnaissance equipment.
Journal Article
An Overview of the China Meteorological Administration Tropical Cyclone Database
The China Meteorological Administration (CMA)’s tropical cyclone (TC) database includes not only the best-track dataset but also TC-induced wind and precipitation data. This article summarizes the characteristics and key technical details of the CMA TC database. In addition to the best-track data, other phenomena that occurred with the TCs are also recorded in the dataset, such as the subcenters, extratropical transitions, outer-range severe winds associated with TCs over the South China Sea, and coastal severe winds associated with TCs landfalling in China. These data provide additional information for researchers. The TC-induced wind and precipitation data, which map the distribution of severe wind and rainfall, are also helpful for investigating the impacts of TCs. The study also considers the changing reliability of the various data sources used since the database was created and the potential causes of temporal and spatial inhomogeneities within the datasets. Because of the greater number of observations available for analysis, the CMA TC database is likely to be more accurate and complete over the offshore and land areas of China than over the open ocean. Temporal inhomogeneities were induced primarily by changes to the nature and quality of the input data, such as the development of a weather observation network in China and the use of satellite image analysis to replace the original aircraft reconnaissance data. Furthermore, technical and factitious changes, such as to the wind–pressure relationship and the satellite-derived current intensity (CI) number–intensity conversion, also led to inhomogeneities within the datasets.
Journal Article
Using Deep Learning to Estimate Tropical Cyclone Intensity from Satellite Passive Microwave Imagery
A deep learning convolutional neural network model is used to explore the possibilities of estimating tropical cyclone (TC) intensity from satellite images in the 37- and 85–92-GHz bands. The model, called “DeepMicroNet,” has unique properties such as a probabilistic output, the ability to operate from partial scans, and resiliency to imprecise TC center fixes. The 85–92-GHz band is the more influential data source in the model, with 37 GHz adding a marginal benefit. Training the model on global best track intensities produces model estimates precise enough to replicate known best track intensity biases when compared to aircraft reconnaissance observations. Model root-mean-square error (RMSE) is 14.3 kt (1 kt ≈ 0.5144 m s −1 ) compared to two years of independent best track records, but this improves to an RMSE of 10.6 kt when compared to the higher-standard aircraft reconnaissance-aided best track dataset, and to 9.6 kt compared to the reconnaissance-aided best track when using the higher-resolution TRMM TMI and Aqua AMSR-E microwave observations only. A shortage of training and independent testing data for category 5 TCs leaves the results at this intensity range inconclusive. Based on this initial study, the application of deep learning to TC intensity analysis holds tremendous promise for further development with more advanced methodologies and expanded training datasets.
Journal Article