Dynamic imaging and RCS measurements of aircraft

Results on radar cross section (RCS) measurements and inverse synthetic aperture radar images of a Mooney 231 aircraft using a ground-to-air measurement system (GTAMS) and a KC-135 airplane using an airborne radar are presented. The Mooney 231 flew in a controlled path in both clockwise and counterclockwise orbits, and successively with the gear down, flaps in the take-off position and with the speed brakes up. The data indicates that RCS pattern measurements from both ground-based and airborne radar of flying aircraft are useful and that the inverse synthetic aperture radar (ISAR) images obtained are valuable for signature diagnostics     

Precision large scale air traffic surveillance using IMM/assignmentestimators

We present the development and implementation of a multisensor-multitarget tracking algorithm for large scale air traffic surveillance based on interacting multiple model (IMM) state estimation combined with a 2-dimensional assignment for data association. The algorithm can be used to track a large number of targets from measurements obtained with a large number of radars. The use of the algorithm is illustrated on measurements obtained from 5 FAA radars, which are asynchronous, heterogeneous, and geographically distributed over a large area. Both secondary radar data (beacon returns from cooperative targets) as well as primary radar data (skin returns from noncooperative targets) are used. The target IDs from the beacon returns are not used in the data association. The surveillance region includes about 800 targets that exhibit different types of motion. The performance of an IMM estimator with linear motion models is compared with that of the Kalman filter (KF). A number of performance measures that can be used on real data without knowledge of the ground truth are presented for this purpose. It is shown that the IMM estimator performs better than the KF. The advantage of fusing multisensor data is quantified. It is also shown that the computational requirements in the multisensor case are lower than in single sensor case, Finally, an IMM estimator with a nonlinear motion model (coordinated turn) is shown to further improve the performance during the maneuvering periods over the IMM with linear models     

Efficient approaches to low-cost high-fault coverage VLSI BISTdesigns

This work introduces a built-in self-test (BIST) design methodology that can sequentially test large very large scale integrated (VLSI) circuits with very high fault coverage. The proposed techniques, circular BIST ((BIST) and (BIST with pseudopartial scan (PPSCAN), are modeled after the principles of the circular self-test path (CSTP). The basis of this method is to trade a minimal increase in hardware overhead for a large increase in fault coverage. It is shown that this technique yields a much higher fault coverage with reasonable time and test vector length when compared with existing sequential test methods. The effectiveness of the technique has been demonstrated by applying it to practical VLSI circuits, which include: 1) the system control coprocessor (CP0) of MIPS 3000 central processing unit (CPU) core and 2) the SIMD graphic engine, namely, enhanced memory chip (EMC). The BIST results show that (BIST and its derivative (BIST with pseudopartial scan (PPSCAN) are feasible for practical VLSI designs and generate BIST with high fault coverage and low overhead     

Concatenated Sequences for Spread Spectrum Systems

Concatenated sequences are suggested and developed for use in spread spectrum (SS) systems. Special receiver realization is discussed and it is shown that the concatenated sequences offer great advantage in reducing the size of the matched filter correlators (MFC) in the SS receiver. Experimental systems have been built using concatenated sequences and their performance is reported here. It has been shown that a processing gain of 60 is obtainable with a 15 × 4 concatenated sequence which requires three tapped delay lines (TDL), two of length 15 and one of 4. Thus a total of only 34 delay units (with a nonlinear interface network, only 19 delay units) are required. Teleprinter signals can be transmitted over telephone channels using a bandwidth (BW) expansion of 60 with an input signal-to-noise ratio (SNR) of only -5.1 dB, resulting in a character- error-rate of 1 in 103. Techniques have been developed to reduce the sidelobe levels in the aperiodic autocorrelation functions (ACF) of the pseudonoise (PN) codes. For 15 length and 7 length PN sequences, sidelobes are reduced by 9 dB and 9.4 dB, respectively, using transversal filters. Application of the SS systems to the problem of multiaccessing and antijamming are discussed.     

两个疲劳分散系数计算公式之间的关系的研究

常见的计算疲劳分散系数的公式有:(1)Antilog和(2)Antilog。国内外有的文献认为公式(1)的缺点是未说明以何种置信度确定母体均值,主张在应用公式(1)之前先对母体均值进行区间估计。本文提出了安全疲劳寿命(或极限)直线的概念,指出两个公式实际上是该直线的两种不同表示形式,并导出了它们之间的等效变换关系,从而说明公式(1)也象(2)一样包含有母体均值置信度的信息。     

耦合多螺旋桨滑流影响的低雷诺数机翼设计

以某型手抛式太阳能无人机(UAV)模型为对象进行考虑多螺旋桨滑流影响的低雷诺数机翼平面形状设计研究。首先,基于升力面理论发展了准定常求解多螺旋桨/机翼相互气动干扰问题的涡格法(VLM)程序,并采用建立参考翼型气动特性数据库的形式发展了相关低雷诺数修正(LRC)方法;然后,通过对翼型、低雷诺数机翼及单螺旋桨/机翼算例的数值模拟及与相关实验结果的对比,验证了本文数值方法具备模拟低雷诺数复杂流动问题的可靠性及准确性;最后,对某型手抛式太阳能无人机简化拉力多螺旋桨/机翼模型进行了直接优化设计及反设计,并通过具有较高精度的CFD准定常求解技术对优化结果进行了验证。结果表明:以CFD方法计算结果为参考,本文涡格法程序及低雷诺数修正方法能够准确高效地计算相关低雷诺数复杂流动问题;传统未考虑多螺旋桨滑流影响的设计机翼在实际螺旋桨工作状态下将偏离设计点,机翼气动特性得不到提高;考虑螺旋桨滑流影响的优化设计方法能够有效改善机翼阻力特性,相对应地,在设计状态下优化机翼总阻力能够降低19.52counts。     

Estimation techniques for GMSK using linear detectors in satellite communications

This paper describes data-aided signal level and noise variance estimators for Gaussian minimum shift keying (GMSK) when the observations are limited to the output of a filter matched to the first pulse-amplitude modulation (PAM) pulse in the equivalent PAM representation. The estimators are based on the maximum likelihood (ML) principle and assume burst-mode transmission with known timing and a block of L₀ known bits. While it is well known that ML estimators are asymptotically unbiased and efficient, the analysis quantifies the rate at which the estimators approach these asymptotic properties. It is shown that the carrier phase, amplitude, and noise variance estimators are unbiased and can achieve their corresponding Cramer-Rao bounds with modest combinations of signal-to-noise ratio and observation length. The estimates are used to estimate the signal-to-noise ratio. It is shown that the mean squared error performance of the ratio increases with signal-to-noise ratio while the mean squared error performance of the ratio in decibels decreases with signal-to-noise ratio. Simulation results are provided to confirm the accuracy of the analytic results.     

Neural and fuzzy reconstructors for the virtual flight datarecorder

The results are presented of a comparative study evaluating the performance of neural network (NN) and fuzzy logic reconstructors (FLRs) for the development of a virtual flight data recorder (VFDK). Typical flight data recorders (FDRS) on commercial airliners do not record the aircraft control surface deflections. These dynamic parameters are critical in the investigation of an accident or an uncommanded maneuver. The results are shown relative to a VFDR based on a neural network simulator (NNS) along with a neural network reconstructor (NNR) or a FLR The NNS is trained off-line, using available flight data for the particular aircraft, for the purpose of simulating any desired dynamic output recorded in current FDRs. The NNS is then interfaced with the NNR or with the FLR. The output of the two reconstructors are the control surface deflections which minimize a performance index based on the differences between the available data from the FDR and the output from the NNS. The study tested with night data from a B737-300 shows that both schemes, the one with the NNR and the one with the FLR, provide accurate reconstructions of the control surface deflections time histories     

Accurate closed-form eigensolutions of three-dimensional panel flutter with arbitrary homogeneous boundary conditions

Highly accurate closed-form eigensolutions for flutter of three-dimensional (3D) panel with arbitrary combinations of simply supported (S), glide (G), clamped (C) and free (F) boundary conditions (BCs), such as cantilever panels, are achieved according to the linear thin plate theory and the first-order piston theory as well as the complex modal analysis, and all solutions are in a simple and explicit form. The iterative Separation-of-Variable (iSOV) method proposed by the present authors is employed to obtain the highly accurate eigensolutions. The flutter mechanism is studied with the benefit of eigenvalue properties from mathematical senses. The effects of boundary conditions, chord-thickness ratios, aerodynamic damping, aspect ratios and in-plane loads on flutter properties are examined. The results are compared with those of Kantorovich method and Galerkin method, and also coincide well with analytical solutions in literature, verifying the accuracy of the present closed-form results. It is revealed that, (A) the flutter characteristics are dominated by the cross section properties of panels in the direction of stream flow; (B) two types of flutter, called coupled-mode flutter and zero-frequency flutter which includes zero-frequency single-mode flutter and buckling, are observed; (C) boundary conditions and in-plane loads can affect both flutter boundary and flutter type; (D) the flutter behavior of 3D panel is similar to that of the two-dimensional (2D) panel if the aspect ratio is up to a certain value; (E) four to six modes should be used in the Galerkin method for accurate eigensolutions, and the results converge to that of Kantorovich method which uses the same mode functions in the direction perpendicular to the stream flow. The present analysis method can be used as a reference for other stability issues characterized by complex eigenvalues, and the highly closed-form solutions are useful in parameter designs and can also be taken as benchmarks for the validation of numerical methods.     

两种亚网格燃烧模型的旋流扩散燃烧大涡模拟

用二阶矩亚网格（SOM—SGS）燃烧模型和文献中的涡旋破碎亚网格（EBU—SGS）燃烧模型，对甲烷一空气旋流扩散燃烧进行了大涡模拟，将二者得到的LES统计平均温度分布和实验结果以及用二阶矩燃烧模型的统观模拟（RANS—SOM）结果比较，表明LES—SOM和RANS—SOM的模拟结果都和实验符合较好，而LES—EBU的模拟结果和实验不符合，在不同区域内高估或者低估了燃烧温度。其原因是由于EBU模型不能有效地考虑有限反应动力学的作用。LES—SOM模拟的瞬态结果显示了旋流扩散火焰的湍流大涡结构不同于射流火焰的特点。     

Maximum likelihood azimuth estimation applied to SSR/IFF systems

A conventional (nonmonopulse) secondary surveillance radar (SSR) is significantly cheaper than a monopulse SSR but exhibits much greater azimuthal error, especially when some of the replies are missing. Estimation techniques and their performance are discussed with special reference to SSR applications, and a novel estimator for conventional SSR is described. The proposed technique is a close approximation of the maximum-likelihood estimator (MLE), taking into account the receiver characteristics as well as the missed replies. Estimator performance obtained by analysis and computer simulation is compared with that of conventional estimators that are based on the leading and trailing edges of binary sequences and shows significantly improved accuracy     

Profiles of Ion and Aerosol Interactions in Planetary Atmospheres

In planetary atmospheres the nature of the aerosols varies, as does the relative importance of different sources of ion production. The nature of the aerosol and ion production is briefly reviewed here for the atmospheres of Venus, Mars, Jupiter and Titan using the concepts established for the terrestrial atmosphere. Interactions between the ions formed and aerosols present cause (1) charge exchange, which can lead to substantial aerosol charge and (2) ion removal. Consequences of (1) are that (a) charged aerosol are more effectively removed by conducting liquid droplets than uncharged aerosol and (b) particle–particle coagulation rates are modified, influencing particle residence times in the relevant atmosphere. Consequences of (2) are that ions are removed in regions with abundant aerosol, which may preclude charge flow in an atmosphere, such as that associated with an atmospheric electrical circuit. In general, charge should be included in microphysical modeling of the properties of planetary aerosols.     

Target detection with synthetic aperture radar

Target detection with synthetic aperture radar (SAR) is considered. We derive generalized likelihood ratio (GLR) detection algorithms that may be used with SAR images that are obtained with coherent subtraction or have Gaussian distributions. We analytically compare the performance of (1) a single pixel detector, (2) a detector using complete knowledge of the target signature information and known orientation information, (3) a detector using incomplete knowledge of the target signature information and known orientation information (4) a detector using unknown target signature information and known orientation information, and (5) a detector using unknown target signature information and unknown orientation information     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

Feedback structure based entropy approach for multiple-model estimation

The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.     

High-Resolution Frequency Measurement by Linear Prediction

The efficacy of linear prediction spectrum analysis (LPSA) (also called autoregressive or maximum entrophy spectrum analysis) for problems concerning narrowband signals in noise is examined by means of Monte Carlo simulation. For the case of pure tones (sinusoids) in white noise, both frequency estimation accuracy and resolution of two closely spaced tones with the linear prediction approach are discussed. In addition, estimation of the carrier frequency of a narrowband random (fading) Gaussian signal in noise is considered. The results are compared with standard fast Fourier transform (FFT) methods. These comparisons indicate that there is no significant advantage to using the linear prediction approach with real (bandpass) data. It is concluded that these experiments should be repeated with complex (baseband) data before a complete assessment of the LPS approach can be made.     

Geometrical entropy approach for variable structure multiple-model estimation

The variable structure multiple-model(VSMM) estimation approach, one of the multiple-model(MM) estimation approaches, is popular in handling state estimation problems with mode uncertainties.In the VSMM algorithms, the model sequence set adaptation(MSA) plays a key role.The MSA methods are challenged in both theory and practice for the target modes and the real observation error distributions are usually uncertain in practice.In this paper, a geometrical entropy(GE) measure is proposed so that the MSA is achieved on the minimum geometrical entropy(MGE) principle.Consequently, the minimum geometrical entropy multiple-model(MGEMM) framework is proposed, and two suboptimal algorithms, the particle filter k-means minimum geometrical entropy multiple-model algorithm(PF-KMGEMM) as well as the particle filter adaptive minimum geometrical entropy multiple-model algorithm(PF-AMGEMM), are established for practical applications.The proposed algorithms are tested in three groups of maneuvering target tracking scenarios with mode and observation error distribution uncertainties.Numerical simulations have demonstrated that compared to several existing algorithms, the MGE-based algorithms can achieve more robust and accurate estimation results when the real observation error is inconsistent with a priori.     

DOA estimation using one-bit quantized measurements

The effects 1-bit quantization of the input samples has on the direction-of-arrival (DOA) estimation accuracy are considered. The signal model assumes a single stochastic Gaussian point source that is embedded in white Gaussian noise (WGN). The inherent limitations governed by the extreme clipping of the input data are analyzed using the Cramer-Rao bound (CRB) that is derived for a two-sensor array. In addition, several estimators for the I-bit estimation are discussed. Numerical and analytical analyses of the estimation error reveal weak dependency on signal-to-noise ratio (SNR) with singular behavior of the estimation error in certain DOA angles.     

Computation of the Noncentral F Distribution (CFAR)Detection

A formula is given that enables accurate values of the cumulative noncentral F distribution to be calculated. Since it does not seem to be generally known that constant false alarm rate (CFAR) detection problems are concerned with evaluating the noncentral F distribution, results using the algorithm are compared with published values obtained using a CFAR algorithm. Both engineers and statisticians are therefore encouraged to consult each other's publications for useful (though maybe disguised) material.     

Capacitive-loaded push-pull parallel-resonant converter

Results of a theoretical and experimental investigation of a capacitive-loaded push-pull parallel-resonant DC-DC converter (CL-PPRC) are presented and discussed. The push-pull parallel-resonant converter (PPRC) is driven by a lower-than-resonance frequency and the secondary voltage is rectified and smoothed by a capacitive filter. The CL-PPRC is shown to operate in the zero voltage switching (ZVS) mode with a boost-like DC transfer ratio that is approximately linear with the period of the switching frequency. Experimental results of a 180 W, high output voltage (1.8 KV) prototype are found to be in good agreement with the analysis, models, and simulation results presented. The basic characteristic of ZVS, the fact that the resonant current is passing through the switches only during a fraction of the period, the high-voltage transfer ratio, and the inherent input/output (I/O) isolation, make the proposed topology a viable design alternative in avionic and aerospace applications