Broadband passive acoustic technique for target motion parameterestimation

A nonlinear least-squares method is formulated to estimate the motion parameters of a target whose broadband acoustic energy emissions are received by a ground-based array of sensors. This passive technique is applied to real acoustic sensor data recorded during the passage of a variety of ground vehicles past a planar cross array and its effectiveness verified by comparing the results with the actual values of the target motion parameters. The technique cam also be applied to airborne targets     

Observability in passive target motion analysis

The nature of observability of nonlinear systems encountered in passive target motion analysis (TMA) is carefully examined. The approach proposed here is based upon a well-chosen criterion which allows us to answer the major observability questions     

Low observable target motion analysis using amplitude information

In conventional passive and active sonar system, target amplitude information (AI) at the output of the signal processor is used only to declare detections and provide measurements. We show that the AI can be used in passive sonar system, with or without frequency measurements, in the estimation process itself to enhance the performance in the presence of clutter where the target-originated measurements cannot be identified with certainty, i.e., for “low observable” or “dim” (low signal-to-noise ratio (SNR)) targets. A probabilistic data association (PDA) based maximum likelihood (ML) estimator for target motion analysis (TMA) that uses amplitude information is derived. A track formation algorithm and the Cramer-Rao lower bound (CRLB) in the presence of false measurements, which is met by the estimator even under low SNR conditions, are also given. The CRLB is met by the proposed estimator even at 6 dB in a cell (which corresponds to 0 dB for 1 Hz bandwidth in the case of a 0.25 Hz frequency cell) whereas the estimator without AI works only down to 9 dB. Results demonstrate improved accuracy and superior global convergence when compared with the estimator without AI. The same methodology can be used for bistatic radar     

Discrete-time observability and estimability analysis for bearings-only target motion analysis

Observability in the context of bearings-only tracking (BOT) is still the subject of important literature. Different from previous approaches, where continuous-time analysis was considered, our approach relies on discrete-time analysis. It is then shown that this allows us to use directly and efficiently the simple formalisms of linear algebra. Using the direct approach, observability analysis is essentially reduced to basic considerations about subspace dimensions. Even if this approach is conceptually quite direct, it becomes more and more complex as the source-encounter scenario complexity increases. For complex scenarios, the dual approach may present some advantages essentially due to the direct use of multilinear algebra. New results about BOT observability for maneuvering sources are thus obtained. Observability analysis is then extended to unknown instants of source velocity changes. Even if observability analysis provides thorough insights about the algebraic structure of the BOT problem, the optimization of the observer maneuvers is essentially a control problem. Basic algebraic considerations prove that a relevant cost functional for this control problem is the determinant of the Fisher information matrix (FIM). So, a large part of this work is devoted to the analysis of this cost functional. Using multilinear algebra, general approximations of this functional are given. In order to involve only directly estimable parameters, the source bearing-rates are examined. Using these approximations, a general framework for optimizing the observer trajectory is derived which allow us to approximate the optimal sequence of controls. It is worth stressing that our approach does not require the knowledge of the source trajectory parameters and is still valid for a maneuvering source.     

Three-dimensional target motion analysis using angle and frequency measurements

It is well known that passive target tracking by a single observer, commonly referred to as target motion analysis (TMA), can be done using angle and/or frequency measurements. Depending on the measurement set, different passive tracking procedures result: angle-only tracking (AOT), frequency-only tracking (FOT), and angle/frequency tracking (AFT). Whereas the two-dimensional passive tracking problem has been solved for a multitude of scenarios, thus giving a good insight into the parametric dependences, the three-dimensional problem has been discussed only in a few specific cases. To get a deeper insight into the parametric dependences of three-dimensional TMA, this work analyzes AOT and AFT in typical three-dimensional Airborne Warning and Control System (AWACS) scenarios. A Cramer Rao (CR) analysis of the problem reveals the parametric dependences of both methods and gives a clear idea of the increase in estimation accuracy by using AFT instead of AOT. The results obtained in this way are well confirmed by Monte Carlo simulations taking maximum likelihood (ML) as estimation procedure.     

PDAF with multiple clutter regions and target models

This paper presents the theory of a new multiple model probabilistic data association filter (PDAF). The analysis is generalized for the case of multiple nonuniform clutter regions within the measurement data that updates each model of the filter. To reduce the possibility of clutter measurements forming established tracks, the solution includes a model for a visible target. That is, a target that gives sensor measurements that satisfy one of the target models. Other features included in the algorithm are the selection of a fixed number of nearest measurements and the addition of signal amplitude to the target state vector. The nonuniform clutter model developed here is applicable to tracking signal amplitude. Performance of this algorithm is illustrated using experimentally recorded over-the-horizon radar (OTHR) data.     

Helicopter aeroelastic analysis with spatially uncertain rotor blade properties

This paper investigates the effects of spatially uncertain material properties on the aeroelastic response predictions (e.g., rotating frequencies, vibratory loads, etc.) of composite helicopter rotor. Initially, the spatial uncertainty is modeled as discrete random variables along the blade span and uncertainty analysis is performed with direct Monte Carlo simulations (MCS). Uncertainty effects on the rotating frequencies vary with the higher-order modes in a non-linear way. Each modal frequency is found to be more sensitive to the uncertainty at certain sections of the rotor blade than uncertainty at other sections. Uncertainty effects on the vibratory hub load predictions are studied in the next stage. To reduce the computational expense of stochastic aeroelastic analysis, a high-dimensional model representation (HDMR) method is developed to approximate the aeroelastic response as functions of blade stiffness properties which are modeled as random fields. Karhunen–Loève expansion and a lower-order expansion are used to represent the input and outputs, respectively, in the HDMR formulation which is similar to the spectral stochastic finite element method. The proposed method involves the approximation of the system response with lower-dimensional HDMR, the response surface generation of HDMR component functions, and Monte Carlo simulation. The proposed approach decouples the computationally expensive aeroelastic simulations and uncertainty analysis. MCS, performed with computationally less expensive HDMR models, shows that spatial uncertainty has considerable influence on the vibratory hub load predictions.     

Radar target classification using doppler signatures of human locomotion models

The problem of target classification for ground surveillance Doppler radars is addressed. Two sources of knowledge are presented and incorporated within the classification algorithms: 1) statistical knowledge on radar target echo features, and 2) physical knowledge, represented via the locomotion models for different targets. The statistical knowledge is represented by distribution models whose parameters are estimated using a collected database. The physical knowledge is represented by target locomotion and radar measurements models. Various concepts to incorporate these sources of knowledge are presented. These concepts are tested using real data of radar echo records, which include three target classes: one person, two persons and vehicle. A combined approach, which implements both statistical and physical prior knowledge provides the best classification performance, and it achieves a classification rate of 99% in the three-class problem in high signal-to-noise conditions.     

Survey of maneuvering target tracking. Part I. Dynamic models

This is the first part of a comprehensive and up-to-date survey of the techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. It surveys various mathematical models of target motion/dynamics proposed for maneuvering target tracking, including 2D and 3D maneuver models as well as coordinate-uncoupled generic models for target motion. This survey emphasizes the underlying ideas and assumptions of the models. Interrelationships among models and insight to the pros and cons of models are provided. Some material presented here has not appeared elsewhere.     

Network analysis of Chinese air transport delay propagation

The Chinese air transport system has witnessed an important evolution in the last dec-ade, with a strong increase in the number of flights operated and a consequent reduction of their punctuality. In this contribution, we propose modelling the process of delay propagation by using complex networks, in which nodes are associated to airports, and links between pairs of them are assigned when a delay propagation is detected. Delay time series are analysed through the well-known Granger Causality, which allows detecting if one time series is causing the dynamics observed in a second one. Results indicate that delays are mostly propagated from small and regio-nal airports, and through flights operated by turbo-prop aircraft. These insights can be used to design strategies for delay propagation dampening, as for instance by including small airports into the system's Collaborative Decision Making.     

Performance analysis of bearing-only target location algorithms

The performance of two well-known bearing-only location techniques, the maximum likelihood (ML) and the Stansfield estimators, is examined. Analytical expressions are obtained for the bias and the covariance matrix of the estimation error, which permit performance comparison for any case of interest. It is shown that the Stansfield algorithm provides biased estimates even for large numbers of measurements, in contrast with the ML method. The RMS error of the Stansfield technique is not necessarily larger than the RMS of the ML technique. However, it is shown that the ML technique is superior to the Stansfield method when the number of measurements is large enough. Simulation results verify the predicted theoretical performance     

Impact of acoustic wave propagation characteristics on aerodynamic damping of rotor blades in a transonic axial compressor

The aeroelastic stability associated with the acoustic wave propagation characteristics of transonic rotor blades was numerically investigated in this study.The influence of the vibration fre-quency on the aerodynamic damping of the first bending mode was primarily considered at different speeds,including both work and stall points.We found that the state of acoustic wave propagation associated with aeroelastic instability is closely related to rotational speed.At low speeds near stall points,the risk of aeroelastic instability is confined to the upstream cut-off state.However,at high speeds near stall points,aeroelastic instability may occur in both the downstream cut-off state and the acoustic wave propagation state of the upstream cut-off frequency,further expanding the range of the acoustic wave propagation state in which aeroelastic instability can arise.The research find-ings show that for suction surfaces,aerodynamic work is affected not only by acoustic wave prop-agation characteristics,but also by shock waves,radial flow,and reflux in the flow field.However,for pressure surfaces,the acoustic wave propagation characteristics play a significant role.When aeroelastic instability occurs,negative damping predominantly arises from the pressure surface.To investigate why lower-order modes are more prone to aeroelastic instability,specific simulations were conducted for the first bending and twisting modes under different operating conditions in the downstream cut-on state.When the vibration frequency significantly exceeds the downstream cut-off frequency,the blade phase is minimally influenced by acoustic wave propagation characteristics,and the rotor is aeroelastically stable in these phases.Simultaneously,there is an approximately linear increase in the unsteady pressure amplitude with increasing vibration frequency,and the aerodynamic work is predominantly influenced by the unsteady pressure amplitude.     

Performance analysis of a radar target discrimination technique

The performance of a radar target discrimination technique using multiple-frequency scattering amplitude without phase data is investigated. Based on the concept of natural resonance frequencies, the technique is aspect independent so that a priori information of the aspect angle is not necessary. The radar cross sections (RCSs) of spheroids are calculated numerically to simulate the received radar returns for distinguishing different spheroids and wires in the resonance frequency range by the proposed technique. By Monte Carlo simulation, the discrimination error rate is estimated as a function of the standard deviation of added noise. The numerical results show that the discrimination algorithm works well under moderately noisy situations and can be applied even in a high-resonance frequency range     

Friction moment analysis of space gyroscope bearing with ribbon cage under ultra-low oscillatory motion

This paper presents the model of calculating the total friction moment of space gyroscope ball bearings which usually work under ultra-low oscillatory motion and are very sensitive to the friction moment. The aim is to know the proportion of the friction moment caused by each frictional source in the bearing＇s total friction moment, which is helpful to optimize the bearing design to deduce the friction moment. In the model, the cage dynamic equations considering six degree-of-freedom and the balls dynamic equations considering two degree-of-freedom were solved.The good trends with different loads between the measured friction moments and computational results prove that the model under constant rate was validated. The computational results show that when the speed was set at 5 r/min, the bearing＇s maximum total friction moment when oscillation occurred was obviously larger than that occurred at a constant rate. At the onset of each oscillatory motion, the proportion of the friction moment caused by cage in the bearing＇s total friction moment was very high, and it increased with the increasing speed. The analyses of different cage thicknesses and different clearances between cage pocket and ball show that smaller thickness and clearance were preferred.     

Three-dimensional analysis of relationship between relative orientation and motion modes

Target motion modes have a close relationship with the relative orientation of missile-totarget in three-dimensional highly maneuvering target interception. From the perspective of relationship between the sensor coordinate system and the target body coordinate system, a basic model of sensor is stated and the definition of relative angular velocity between the two coordinate systems is introduced firstly. Then, the three-dimensional analytic expressions of relative angular velocity for different motion modes are derived and simplified by analyzing the influences of target centroid motion, rotation around centroid and relative motion. Finally, the relationships of the relative angular velocity directions and values with motion modes are discussed. Simulation results validate the rationality of the theoretical analysis. It is demonstrated that there are significant differences of the relative orientation in different motion modes which include luxuriant information about motion modes. The conclusions are significant for the research of motion mode identification,maneuver detection, maneuvering target tracking and interception using target signatures.     

Performance of multiple-model filters and parameter-sensitivity analysis for likelihood evaluation with shock variance models

The performance of multiple-model filtering algorithms is examined for shock-variance models, which are a form of linear Gaussian switching models. The primary aim is to determine whether existing multiple-model filters are suitable for evaluating measurement likelihoods in classification applications, and under what conditions such classification models are viable. Simulation experiments are used to empirically examine the likelihood-evaluation performance of suboptimal merging and pruning algorithms as the number of state hypotheses per time step (i.e., algorithm order) increases. The second-order generalized pseudo-Bayes or (GPB(2)) algorithm is found to provide excellent performance relative to higher order GPB algorithms through order five. Likelihoods from fixed-size pruning (FSP) algorithms with increasing numbers of state hypotheses are used to validate the GPB likelihoods, and convergence of the FSP likelihoods to the GPB values is observed. These results suggest that GPB(2) is a reasonable approximation to the unrealizable optimal algorithm for classification. In all cases except very-low-noise situations, the interacting multiple model (IMM) algorithm is found to provide an adequate approximation to GPB(2). Sensitivity of likelihood estimates to certain model parameters is also investigated via a mismatch analysis. As a classification tool, the discrimination capabilities of the measurement likelihoods are tested using an idealized forced-choice experiment, both with ideal and with mismatched models     

薄壁板结构随机声激励振动响应计算与分析

针对航空发动机压气机转子叶片结构声振动问题,建立了薄壁板有限元简化模型,基于耦合有限元/边界元法对薄壁板在行波加载下随机声激励振动响应进行了仿真计算,得到了在不同声压级下的应力响应结果.改变声载荷激励方向,分别对薄壁板施加单音噪声激励和宽频随机噪声激励,通过仿真计算得到了不同角度随机声激励下薄壁板振动响应频响曲线.对比分析发现,薄壁板模态振型与噪声加载方向是引起薄壁板共振的重要因素.     

M-correlated sweeps performance analysis of mean-level CFARprocessors in multiple target environments

This paper is devoted to the detection performance evaluation of the mean-level (ML) constant false-alarm rate (CFAR) detectors processing M-correlated sweeps in the presence of interfering targets. The consecutive pulses are assumed to be fluctuating according to the Swerling I model. Exact expressions are derived for the detection probability of the conventional mean-level detector (MLD) and its modified versions under Rayleigh fluctuating target model. Performance for independent sweeps can be easily obtained by setting the sweep-to-sweep correlation coefficient equal to zero. Results are obtained for both homogeneous and nonhomogeneous background environments. It is shown that for fixed M, the relative improvement over the single sweep case increases as the correlation between sweeps decreases. For the same parameter values, the minimum MLD has the best performance in the presence of extraneous target returns among the reference noise samples     

动力翼伞多体非线性动力学建模与相对运动分析

动力翼伞的监测与控制设备通常安装在负载上,而主要的气动力结构为翼伞,因此为了实现动力翼伞的精确控制,有必要对其两体相对运动进行分析。考虑动力翼伞的附加质量以及两点柔性连接的特殊结构,采用机理法建立了系统非线性八自由度(8-DOF)相对运动模型,包括翼伞六自由度与负载两体相对运动自由度。通过仿真,分析了动力翼伞在动力变化、转弯和雀降3种操纵下以及遇侧风干扰时的两体相对运动情况。结果表明,动力变化和雀降操纵会引起两体相对俯仰运动,而转弯与遇侧风时具有明显的相对偏航运动。研究结果表明,所建模型可用于解释与分析动力翼伞的两体相对运动问题。