基于混合卡尔曼滤波器组故障传感器定位方法

为了在发动机性能蜕化与传感器故障并存的情况下实现故障传感器的定位与部件蜕化情况的估计,并实现故障诊断基准数据的修正,构建了1种包含了机载模型与线性卡尔曼滤波器的组合结构混合卡尔曼滤波器组。该卡尔曼滤波器组能够在之前所描述的故障/蜕化耦合情况下定位故障传感器,并得到较为准确的部件蜕化估计结果。为了验证了混合卡尔曼滤波器组的有效性,进行了相关仿真。仿真结果表明:混合卡尔曼滤波器组能够在发动机动态过程中遭遇传感器故障与部件蜕化并存的情况下完成故障定位与蜕化估计。     

Characterization of Kalman filter residuals in the presence ofmismodeling

The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed. All of the other filters use internal models that mismodel the true system. We compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared with simulation results of flight control failures that correspond to mismodeled input matrices and output matrices     

Comments on "Computationally Efficient Bank of Rectangular Digital Filters"

In [1] a scheme for forming a rectangular FIR filter bank is described using only a few percent of the number of multiplications required by straightforward procedures. The sidelobe level suffers degradation. Attention is drawn to a different scheme published in [2] and [3] which needs even fewer multiplications without degradationvof the sidelobe level.     

Interrelationship of single-filter and multiple-model adaptivealgorithms

An equivalent filter bank structure for multiple model adaptive estimation (MMAE) is developed that uses the residual and state estimates from a single Kalman filter and linear transforms to produce equivalent residuals of a complete Kalman filter bank. The linear transforms, which are a function of the differences between the system models used by the various Kalman filters, are developed for modeling differences in the system input matrix, the output matrix, and the state transition matrix. The computational cost of this new structure is compared with the cost of the standard Kalman filter bank (SKFB) for each of these modeling differences. This structure is quite similar to the generalized likelihood ratio (GLR) structure, where the linear transforms can be used to compute the matched filters used in the GLR approach. This approach produces the best matched filters in the sense that they truly represent the time history of the residuals caused by a physically motivated failure model     

Performance of a Two-Sample Mann-Whitney Nonparametric Detector in a Radar Application

The detection of signals in an unknown, typically non-Gaussian noise environment, while attempting to maintain a constant false-alarm rate, is a common problem in radar and sonar. The raw receiver data is commonly processed initially by a bank of frequency filters. The further processing of the outputs from the filter bank by a two-sample Mann-Whitney detector is considered. When the noise statistics in all filters are identical, the Mann-Whitney detector is distribution free, i. e., the false-alarm probability may be prescribed in advance regardless of the precise form of the noise statistics. The primary purpose of this paper is to demonstrate the potential advantage of nonparametric detectors over conventional detectors. The signal detection performance of the Mann-Whitney detector is compared to that of an ordinary linear envelope detector plus integrator in the presence of Gaussian and several hypothetical forms of non-Gaussian noise. This comparison is made for both uniform and nonuniform distributions of noise power across the filter bank. Besides providing a much more constant false-alarm rate than the conventional detector, the Mann-Whitney detector's signal detection performance is found also to be much less sensitive to the form of the noise statistics. In one case, its detection sensitivity is found to be 11 dB better than that of the conventional detector. Even when the noise power density is made moderately nonuniform across the filter bank, the detection performance of the Mann-Whitney detector is found not to be significantly affected.     

Filters for manufacturability in design optimization of variable stiffness composites

In the design optimization of variable stiffness composites, manufacturing constraints imposed by the automated fiber placement technology must be considered. In the present paper, two filters are proposed to address this issue, and they are incorporated into the Shepard interpolation-based design optimization framework developed in our previous studies. The fiber angle arrangement of a composite is represented by a continuous function that interpolates fiber angles at scattered design points. Two filters are appointed for each design point to deal with two typical manufacturing constraints, i.e., fiber curvature and gap/overlap. At each design point, the sensitivity is first filtered in a rectangular region around this point, and by this means the fiber curvature is controlled; then in another rectangular region around this design point, the filtered sensitivities are averaged, and the result is used to update the corresponding design variable. Several numerical examples are investigated, and the results show that the proposed method is effective.     

Incremental maneuver estimation model for target tracking

An incremental model for maneuver detection and estimation for use in target tracking with the Kalman filter is described. The approach is similar to the multiple Kalman filter bank, but with a memory for the maneuver status for the track under consideration. The advantage of this approach is that the target acceleration can be more accurately estimated. The maneuver-detection model has shown good maneuver-following capability. Moreover, it needs only a finite number of Kalman filters to handle all possible maneuver values and it responds quickly as maneuver occurs. When there is an abrupt maneuver change the model can still track the targets in short time     

基于健康蜕化的航空发动机传感器故障诊断(英文)

改进在线故障诊断算法使其能适应发动机健康蜕化是目前故障诊断所面临的困难,如果诊断算法没有自适应能力,在发动机健康蜕化后将失去其诊断功能。为了解决此问题,提出在线故障诊断算法,采用跟踪滤波器估计发动机的健康状况,机载模型根据跟踪滤波器的估计结果进行更新。更新后的机载模型能够与真实的发动机相匹配。这使得当发动机健康蜕化后在线故障诊断仍能保持其有效性。最后采用一组卡尔曼滤波器来对航空发动机传感器故障进行诊断与隔离。通过设计好的一组卡尔曼滤波器,能够诊断并隔离出故障。本文使用非线性发动机模型来验证此方法,仿真结果表明本文提出的在线诊断方法在发动机健康蜕化后仍能保持其有效性。     

Low cost Doppler ratio detection radar with interclutter visibility

A low cost concept, called Doppler ratio detection (DRD), for suppressing the clutter residue of Doppler radars is described. The concept provides a simple way to establish a target detect-clutter reject threshold at each range cell, whether a MTI canceler only or a bank of Doppler filters is used. In its simplest form, the target detect/clutter reject threshold is based on the ratio of the magnitudes of Doppler-processed and non-Doppler processed signals. The experiment showed that clutter was rejected, but the amount of added degradation in detection sensitivity was not determined. This degradation will depend on a number of factors, including the number of pulses per beamwidth     

A hardware-efficient, multirate, digital channelized receiverarchitecture

An approach is presented to realizing a digital channelized receiver for signal intercept applications that provides a hardware efficient implementation of a uniform filter bank in which the number of filters K is greater than the decimation factor M. The proposed architecture allows simple channel arbitration logic to be used and provides reliable instantaneous frequency measurements, even in adjacent channel crossover regions. In the proposed implementation of the filter bank, K is related to M by K=FM where F is an integer. It is shown that the optimum selection of F allows the instantaneous frequency measurement to be made in the channel crossover region and the arbitration function to be based solely on the instantaneous frequency measurement. The development of a filter bank structure which combines the flexibility of the short-time Fourier transform (STFT) with the implementation efficiency of the polyphase filter bank decomposition, meeting these requirements and leading to a hardware-efficient implementation, is presented     

Enhanced motion and sizing of bank in moving-bank MMAE

The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard multiple model adaptive estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. Parameter discretization within the MMAE refers to selection of the parameter values assumed by the elemental Kalman filters, and dynamically redeclaring such discretization yields a moving-bank MMAE. A new online parameter discretization method is developed based on the probabilities associated with the generalized chi-squared random variables formed by residual information from the elemental Kalman filters within the MMAE. This new algorithm is validated through computer simulation of an aircraft navigation system subjected to interference/jamming while attempting a successful precision landing of the aircraft.     

Noncoherent Detection of Split-Phase FSK by Multiple Predetection Filtering

When the cumulative drift in the center frequency of a binary split-phase FSK signal exceeds the peak deviation of the signal, a conventional noncoherent receiver (i.e., one provided with only two IF filters) may be unable to achieve the probability of error per bit which the designer desires. This limitation may be overcome if the receiver is provided with a bank of more than two contiguous filters (each followed by an envelope detector) tospan the total IF band the instantaneous IF signal might occupy. It is shown that the probability of error per bit for such a receiver is a function of 1) the ratio F of peak frequency deviation to peak frequency drift, 2) the number M of IF filter/detectors, and 3) the signal-to-noise ratio ? in the output of the filter containing the signal. It is further shown thatfor a given value of F an increase in M reduces the amount of transmitter power the communication system designer must provide to yield a given probability of error per bit.     

低通滤波器的阶跃响应及其对动态校准的影响

动态测试系统在利用阶跃信号进行动态校准时,系统中的低通滤波器环节所产生的衰减振荡可能会误导测试人员,特别是对于带传压管道的动态压力测试系统。仿真与测试结果表明,各种模拟低通滤波器和IIR数字低通滤波器的阶跃响应都会出现一定的衰减振荡。针对带低通滤波器的系统以及其他系统的阶跃激励校准,通过对简单FFT频响分析方法、矩形单脉冲法、冲激响应法三种方法的比较,发现矩形单脉冲法能更正确地对阶跃校准数据进行频响分析。     

Monopulse Radar Angle Tracking Accuracy with Sum Channel Limiting

The variance of angle tracking error is found for an amplitude-comparison form of monopulse radar when the sum channel contains a limiter prior to the angle error detector. The error expression is valid for any shape of transmitted pulse and any duration of range tracking gate but does assume matched filters in signal processing channels. The procedures used are rigorous and an example of results is worked out for the special case of a rectangular transmitted pulse envelope. It is shown, for rectangular pulses, that achievable angle tracking error variance with sum channel limiting is not more than 2.22 dB larger than the theoretical minimum for any processor and not more than 1.29 dB larger than a similar signal processor that uses a "linear" angle error detector. Results apply for large single-pulse signal-to-noise ratio.     

Multiple model adaptive estimation with filter spawning

Multiple model adaptive estimation (MMAE) with filter spawning is used to detect and estimate partial actuator failures on the VISTA F-16. The truth model is a full six-degree-of-freedom simulation provided by Calspan and General Dynamics. The design models are chosen as 13-state linearized models, including first order actuator models. Actuator failures are incorporated into the truth model and design model assuming a "failure to free stream." Filter spawning is used to include additional filters with partial actuator failure hypotheses into the MMAE bank. The spawned filters are based on varying degrees of partial failures (in terms of effectiveness) associated with the complete-actuaton-failure hypothesis with the highest conditional probability of correctness at the current time. Thus, a blended estimate of the failure effectiveness is found using the filters' estimates based upon a no-failure hypothesis, a complete actuator failure hypothesis, and the spawned filters' partial-failure hypotheses. This yields substantial precision in effectiveness estimation, compared with what is possible without spawning additional filters, making partial failure adaptation a viable methodology.     

航空发动机双重传感器故障诊断逻辑研究

针对航空发动机控制系统的双重传感器故障,提出了一种采用双路容错设计的卡尔曼滤波器故障检测隔离系统.故障检测隔离系统由一系列卡尔曼滤波器组成,每个滤波器都假定2路传感器故障,而以故障支路外的测量值作为输入量.当双重传感器故障发生时,只有不包含故障传感器信息的滤波器保持较低的估计残差,其他滤波器都会产生较大的估计残差,如此双重传感器故障便可以被隔离.利用滤波器组估计残差的特征,进一步设计合理的运算逻辑,系统就可以同时对传感器单一故障进行检测和隔离.为了验证故障诊断系统的有效性,在发动机慢车状态分别对传感器发生双重故障和单一故障的情况进行仿真.仿真结果表明:故障诊断系统能够准确有效地对传感器双重故障和单一故障进行检测和隔离.      

采用一组卡尔曼滤波器检测发动机传感器故障

在发动机全功能数字电子控制系统中,提高传感器工作的可靠性是十分重要的,除了不断对传感器本身的性能加以改进提高外,现在广泛地采用了余度技术。近二十年来对解析余度(Analyt ical Redundancy)进行了广泛的研究,解析余度(AR)方法是基于各状态变量之间存在的解析关系,在系统可观条件下,利用无故障的输出测量值去估计(构造)已故障传感器正常工作状态时的输出信息,从而实现对故障的检测、隔离与重构,保证控制系统具有预定的控制性能。      

Doppler-Tolerant Classification of Distributed Targets -- A Bionic Sonar

Sonar echo analysis that is not affected by relative motion between target, transmitter, and receiver is discussed. Motion-tolerant measurement and recognition of range-distributed targets involves: 1) a determination of the effects of range rate upon echoes from non-planar reflectors and 2) the derivation of a signal, filter bank, and target parameterization scheme that is insensitive to those effects. The appropriate system is derived, simulated with a computer, and tested with actual echoes from various targets. The system's signals and filters are very similar to those found in biological sonars.     

航空发动机状态监视、故障诊断研究及验证

提出了发动机状态监视、故障诊断的理论方法并搭建了该系统的软硬件平台,为建立机载发动机健康管理系统奠定了坚实的基础。首先,建立并验证了含有健康参数的发动机线性化模型,在模型的基础上设计了用于故障诊断的卡尔曼滤波器;其次,用设计好的滤波器可以准确估计出反应发动机运行状态的不可测参数;随后又用了一组卡尔曼滤波器诊断、隔离了传感器故障;最后,介绍了该部分机载系统原理样机的软硬件配置,并进行了算法平台验证,从操作和实现方式上验证了软硬件平台。该设计满足算法需求且界面人性化、易于操作。     

Clutter suppression using recursive and nonrecursive MTI filters

The author calculates the effectiveness of clutter suppression of a moving-target-indicator (MTI) filter in tandem with a fast-Fourier-transform (FFT) Doppler filter bank, taking into account the transient response of the MTI filter. Both recursive and nonrecursive filters are considered. The analysis is extended to the high-pulse-repetition-frequency (PRF) case with clutter fold over. The results can be used to select key design parameters, including the MTI filter, the window size, and the initial transient segment to be discarded. Numerical examples are included