Comparison of Two Target Classification Techniques

It has been shown that radar returns in the resonance region carry information regarding the overall dimensions and shape of targets. Two radar target classification techniques developed to utilize such returns are discussed. Both of these techniques utilize resonance region backscatter measurements of the radar cross section (RCS) and the intrinsic target backscattered phase. A target catalog used for testing the techniques was generated from measurements of the RCS of scale models of modern aircraft and naval ships using a radar range at The Ohio State University. To test the classification technique, targets had their RCS and phase taken from the data base and corrupted by errors to simulate full-scale propagation path and processing distortion. Several classification methods were then used to determine how well the corrupted measurements fit the measurement target signatures in the catalog. The first technique uses nearest neighbor (NN) algorithms on the RCS magnitude and (range corrected) phase at a number (e.g., 2, 4, or 8) of operating frequencies. The second technique uses an inverse Fourier transformation of the complex multifrequency radar returns to the time domain followed by cross correlation. Comparisons are made of the performance of the two techniques as a function of signal-to-error noise power ratio for various processing options.     

Separation of target rigid body and micro-doppler effects in ISAR imaging

Micro-Doppler (m-D) effect is caused by moving parts of the radar target. It can cover rigid parts of a target and degrade the inverse synthetic aperture radar (ISAR) image. Separation of the patterns caused by stationary parts of the target from those caused by moving (rotating or vibrating) parts is the topic of this paper. Two techniques for separation of the rigid part from the rotating parts have been proposed. The first technique is based on time-frequency (TF) representation with sliding window and order statistics techniques. The first step in this technique is recognition of rigid parts in the range/cross-range plane. In the second step, reviewed TF representation and order statistics setup are employed to obtain signals caused by moving parts. The second technique can be applied in the case of very emphatic m-D effect. In the first step the rotating parts are recognized, based on the inverse Radon transform (RT). After masking these patterns, a radar image with the rigid body reflection can be obtained. The proposed methods are illustrated by examples     

基于改进Gappy POD方法的压气机叶栅气动外形反设计方法

针对压气机叶栅气动高效反设计,建立了基于Gappy proper orthogonal demcomposition(Gappy POD)的气动外形反设计框架.通过Kriging代理模型优化获得某型压气机叶栅的气动优化结果,并以此作为反设计目标基础.为进一步提高基本Gappy POD反设计的效率及精度,发展了基于自适应...     

跨声速层流翼型的混合反设计/优化设计方法

跨声速层流翼型设计须兼顾优良的超临界特性和自然层流特性,因而对设计方法提出了更高的要求。针对现有反设计方法和直接优化设计方法的不足,发展了一种适用于跨声速层流翼型的混合反设计/优化设计方法。该方法引入了基于经验的局部流场特征作为反设计目标,翼型性能指标作为直接优化设计目标,然后加权形成了混合反设计/优化设计总目标,并同时考虑了气动和几何约束。优化算法采用基于自适应并行加点技术的代理优化,流动数值模拟采用耦合基于线性稳定性理论的e^N转捩自动判定的雷诺平均Navier-Stokes（RANS）方程求解器。针对现代中短程民用客机需求,以NPU-LSC-72613翼型为基准,开展了层流翼型减阻的混合反设计/优化设计。分别将局部目标压力分布、总阻力作为反设计和直接优化设计目标,得到了较好的优化结果,验证了方法的有效性。经过2轮优化结果显示混合反设计/优化设计总目标显著下降。所设计翼型吸力面局部压力分布与目标压力分布基本一致,总阻力下降15.5%;吸力面和压力面层流范围均大于55%倍弦长,激波强度显著减弱,说明所设计翼型同时具有优良的超临界和层流特性。将所设计翼型配置到机翼上,通过三维数值模拟进行校验,结果显示所设计跨声速层流机翼升阻比提高了6.64%,在一定升力系数范围内,气动性能均有显著提高,验证了所设计跨声速层流翼型在机翼设计中的适用性。     

飞机橡皮囊成形零件毛坯精确预示方法研究

 橡皮囊成形是飞机钣金零件成形的主要方法之一,其初始毛坯形状的预示是橡皮囊成形中的一个难点问题。针对橡皮囊成形的工艺特点,提出了一种基于一步逆成形有限元法的飞机橡皮囊成形钣金零件毛坯快速精确预示方法。首先将设计好的飞机钣金零件作为最终构形,然后采用一步逆成形有限元法进行初始毛坯的快速反向模拟,最后将通过该方法获得的毛坯外形应用到实际飞机钣金橡皮囊成形中,实验结果表明该方法可以快速精确地预示出飞机橡皮囊成形钣金零件的初始毛坯形状。     

Angle/Doppler estimation in heavy-tailed clutter backgrounds

This work describes new methods on the modeling of the amplitude statistics of airborne radar clutter by means of alpha-stable distributions. We develop joint target angle and Doppler, maximum likelihood-based estimation techniques from radar measurements retrieved in the presence of impulsive uncorrelated noise modeled as an alpha-stable random process. We derive the Cramer-Rao bounds (CRBs) for the additive Cauchy interference scenario to assess the best case estimation accuracy which can be achieved. In addition, we introduce a new joint spatial- and Doppler-frequency high-resolution estimation technique based on the fractional lower order statistics of the measurements of a radar array. Simulation results demonstrate that the proposed methods can be of interest in the study of space-time adaptive processing (STAP) for airborne pulse Doppler radar arrays operating in impulsive interference environments     

Application of Recursive Estimation and Kalman Filtering to Doppler Tracking

The techniques of recursive estimation and Kalman filtering are applied to the problem of estimation of space vehicle orbits and trajectories using only measurements of the Doppler shifts in radio signals transmitted by or reflected from the target. Two approaches are described. One is a global fit technique in which the parameters of an assumed trajectory model are estimated. The second is a pointwise mapping technique in which the trajectory estimate is extrapolated as the target tracking data is received. The paper provides a tutorial illustration of the direct application of recursive optimization techniques to a class of engineering problems.     

交互外形设计中的有理插值方法

在CAGD中,构造光滑曲线通过给定的二维或三维点集是非常重要的问题。广泛釆用的方法是Hermite技术,但是依照这种方法,插值曲线的形状过多地依赖于切矢的模长,且形状的修改不能依几何的方式交互完成。本文提出了一种结合交互技术和插值技术于一体的曲线插值方法,插值基函数为有理函数,在此基础上讨论了形状参数在几何修形中的作用,     

Target tracking using infrared measurements and laser illumination

A missile target tracker is designed using a filter/correlator (with adaptive target shape identification) based on forward-looking infrared (FLIR) sensor measurements to track the center-of-intensity of the hardbody/plume combination, and another filter using Doppler and/or speckle information in the return from a low-power laser illuminator to estimate the offset between the intensity centroid and the hardbody center-of-mass. The Doppler information is shown to yield smaller bias and error variance from the tracker than the speckle information. Performance of trackers based on just Doppler or both Doppler and speckle information from the laser return is portrayed as a function of important parameters in the tracking environment     

An inverse design method for supercritical airfoil based on conditional generative models

Inverse design has long been an efficient and powerful design tool in the aircraft industry.In this paper, a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning. A Conditional Variational Auto Encoder(CVAE) and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN), are conducted as generative models. They are used to generate target wall Mach distributions for the inve...     

可应用于民机空气动力设计中的数值优化方法

目前民机成功设计的一个关键要素即在设计中有效地引入计算流体力学（CFD）的模拟方法和软件,特别是具有设计能力的方法和工具。本文概要地叙述了反设计、基于CFD低可信度和高可信度模型等数值优化方法的发展和应用于民机设计的历史和现状;简单地介绍了即将举行的空气动力优化设计计算系列研讨会;重点讨论了对可应用于民机设计的基于Navier-Stokes方程解算器的OPTIMAS的数值优化方法的要求及其构造方法,并以翼身组合体整流外形和翼身融合体（BWB）外形的算例表明其有效性,说明OPTIMAS可以成为民机日常设计的方法和工具之一。     

可应用于民机空气动力设计中的数值优化方法简

 目前民机成功设计的一个关键要素即在设计中有效地引入计算流体力学（CFD）的模拟方法和软件,特别是具有设计能力的方法和工具。本文概要地叙述了反设计、基于CFD低可信度和高可信度模型等数值优化方法的发展和应用于民机设计的历史和现状;简单地介绍了即将举行的空气动力优化设计计算系列研讨会;重点讨论了对可应用于民机设计的基于Navier-Stokes方程解算器的OPTIMAS的数值优化方法的要求及其构造方法,并以翼身组合体整流外形和翼身融合体（BWB）外形的算例表明其有效性,说明OPTIMAS可以成为民机日常设计的方法和工具之一。     

飞翼气动优化中参数化和网格变形技术

几何参数化和网格变形是飞行器气动外形数值优化迭代过程中的两个关键技术。基于非均匀有理B样条(NURBS)的自由型面变形(NFFD)技术对几何表示形式具有普适性,距离权函数(DWF)网格变形技术具有计算快速和网格拓扑无关性,两者广泛应用于曲面优化。基于NFFD技术改进了反求参数的Newton迭代算法,并通过提高物面附近网格刚度改进的距离权函数(IDWF)技术使其适用于更大程度的网格变形。还提出了改进后的参数化和网格变形两种技术并行计算的具体实现算法。结合离散伴随方法,使用参数化和网格变形技术,实现了由NACA0012初始翼型到飞翼标准翼型EH1590的反设计;针对某飞翼标模完成了单点全机升阻比优化,升阻比提高约18%。数值结果表明,建立的NFFD和IDWF动网格技术可满足飞翼气动外形优化参数化和快速网格变形的需求。     

Use of map information for tracking targets on airport surface

A generic and novel approach for integrating airport map information with sensor measurements in the track estimation process is proposed and evaluated. The surface restrictions imposed by the network of roads, taxiways, and runways, represented by a simplified geometric model, are included in both the target observation and the dynamic models, to derive the target state estimates. The performance of the methods proposed is illustrated in representative airport surface scenarios, taking as a reference for comparison other tracking alternatives such as VS-IMM (variable structure interacting multiple model estimator) ground target tracking, or standard ones that do not make use of ground information.     

Automatic Target Recognition: Some Considerations

Machine analysis of aerial reconnaissance data is desirable. New acquisition techniques, equipment, and sensors, plus a growing demand for rapidly obtained, accurate information necessitate machine performance of tasks presently accomplished by observers and interpreters. Many of these tasks can be described as pattern recognition or information processing functions. This paper discusses significant problems encountered when attempting to identify objects or regions automatically from aerial photography. Problems include sensor distortions, variations in target environment, and concepts of design and ?teaching? of an actual device. Operational requirements such as processing speed and flexibility restrict the types of solutions available. Approaches to target recognition with relative merits and shortcomings are presented; these include shape correlation, feature extraction, and image quantization. The effect of mission requirements on system parameters is discussed. A bibliography is included.     

Pulse Doppler signature of a rotary-wing aircraft

Field measurements of a modified Sikorsky S-55 helicopter target were carried out to investigate rotary-wing aircraft Doppler radar signature phenomenology. The results of the data analysis with regard to classification and identification of the aircraft based on its signature are presented. It was found that using the Doppler radar return and appropriate feature extraction techniques, the helicopter's design features can be estimated. Target backscatter from the main rotor blades, tail rotor blades, or hub can be used for target detection, acquisition, and classification as a rotary-wing aircraft. The extraction of configuration and blade count features can further define the helicopter for identification     

Multi-EAP:Extended EAP for multi-estimate extraction for SMC-PHD filter

The ability to extract state-estimates for each target of a multi-target posterior, referred to as multi-estimate extraction (MEE), is an essential requirement for a multi-target filter, whose key performance assessments are based on accuracy, computational efficiency and reliability. The probability hypothesis density (PHD) filter, implemented by the sequential Monte Carlo approach, affords a computationally efficient solution to general multi-target filtering for a time-varying num-ber of targets, but leaves no clue for optimal MEE. In this paper, new data association techniques are proposed to distinguish real measurements of targets from clutter, as well as to associate par-ticles with measurements. The MEE problem is then formulated as a family of parallel single-estimate extraction problems, facilitating the use of the classic expected a posteriori (EAP) estima-tor, namely the multi-EAP (MEAP) estimator. The resulting MEAP estimator is free of iterative clustering computation, computes quickly and yields accurate and reliable estimates. Typical sim-ulation scenarios are employed to demonstrate the superiority of the MEAP estimator over existing methods in terms of faster processing speed and better estimation accuracy.     

Application of neural networks for synthesizing flight control algorithms. I neural network inverse dynamics method for aircraft flight control

The application of artificial neural networks for aircraft motion control, in particular, for creation of nonlinear algorithms of the aircraft remote control system (RCS) is considered. Aircraft as a control object is represented as a multidimensional nonlinear dynamic system and nonlinear control methods are used to operate this system. The control loop is constructed using the method of inverse dynamics based on the feedback linearization principle. The nonlinear control law is represented as a neural network being learned (adjusted) by recorded or incoming measurements of motion parameters. Synthesis and testing of neural network control algorithms is performed with the fully nonlinear mathematical model of a maneuverable aircraft for three control channels. Simulation results of the closed system are presented.