民用飞机货舱烟雾探测系统研究

货舱烟雾探测系统作为飞机探测系统的重要组成部分,对货舱的烟雾或火情状况进行探测、监控和告警。介绍了民用飞机货舱烟雾探测系统的组成,对两种常用的货舱烟雾探测器的类型进行了对比分析;对货舱烟雾探测的相关条款进行了分析说明;对货舱烟雾探测系统设备级试验、系统级试验和机上试验进行了详细的介绍;针对烟雾探测系统当前存在的设计难点和适航验证试验,提出了新的研究方法。     

Maximum Likelihood Energy Detection of Mary Orthogonal Signals

The literature on energy detection is extended by applying it to the processing of M'ary orthogonal communication signals of arbitrary time-bandwidth product. Guassian noise channel transition probabilities are derived for maximum likelihood energy detection, modified to the extent of including an erasure threshold. Relations and computational techniques are described for determining the symbol erasure and error probabilities for general signal alphabet sizes (M) and time-bandwidth products. When time of arrival is known exactly and Doppler is negligible, gible, it is determined that energy detection is inferior to noncoherent matched filter detection. For time-bandwidth products of the order of 100 and error probabilities around 10 3, a loss of about 5 dB occurs which is attributable to a lack of knowledge of the detail signal structure. However, for problems where time of arrival and/ or Doppler are unknown, energy detection will perform nearly as well as matched filter detection of, for example, spread spectrum signals, and is also simpler to implement. General energy detection performance curves are given in terms of required signal energy for specific error and erasure probabilities, as a function of M'ary and time-bandwidth product.     

A unified approach to the design of decentralized detection systems

A unified approach to the design of decentralized detection networks with arbitrary topologies is proposed and analyzed. In this approach, a decentralized detection system of arbitrary topology is represented by a communication matrix that specifies the interconnection structure of the detection network. This matrix is used to derive the general decision rule using the person-by-person-optimal (PBPO) solution methodology. It is shown that the PBPO decision rule is a likelihood ratio test for statistically independent observations. The threshold of the test is shown to be a function of the decision input vector of the detector under consideration. This unified approach is used to obtain the PBPO decision rules of decentralized detection systems with various topologies. Various results in the literature are verified. In addition, the PBPO decision rules for a decentralized detection system with peer communication are presented. Numerical examples are presented for illustration     

Sequential track extraction

Sensors like radar or sonar usually produce data on the basis of a single frame of observation: target detections. The detection performance is described by quantities like detection probability Pd and false alarm density f. A different task of detection is formation of tracks of targets unknown in number from data of multiple consecutive frames of observation. This leads to quantities which are of a higher level of abstraction: extracted tracks. This again is a detection process. Under benign conditions (high Pd, low f and well separated targets) conventional methods of track initiation are recommended to solve a simple task. However, under hard conditions the process of track extraction is known to be difficult. We here concentrate on the case of well separated targets and derive an optimal combinatorial method which can be used under hard operating conditions. The method relates to MHT (multiple hypothesis tracking), uses a sequential likelihood ratio test and derives benefit from processing signal strength information. The performance of the track extraction method is described by parameters such as detection probability and false detection rate on track level, while Pd and f are input parameters which relate to the signal-to-noise interference ratio (SNIR), the clutter density, and the threshold set for target detection. In particular the average test lengths are analyzed parametrically as they are relevant for a user to estimate the time delay for track formation under hard conditions     

Optimal polarimetric detection of radar target in a slowlyfluctuating environment of clutter

It is shown that in a situation where a radar target is distant enough from the radar and is included in a natural or artificial clutter environment in such a manner that the conventional detection methods fail, it is possible to improve the radar detection performance by using appropriate signal processing on two orthogonal polarization states. A CFAR (constant false alarm rate) polarimetric detection system based on the study of the polarization difference between clutter and target is proposed. Since the polarization state of the clutter echoes fluctuates slowly from cell to cell, an autoregressive model can be applied to the components of the polarization vector to predict the detection thresholds needed to follow the polarization state variation. The detection thresholds are determined to maintain a false alarm probability equal to 10^-6. The presence of a target registers as a significant variation of the estimation error of the polarization vector. Results obtained from measurements of simple and canonical targets with artificial clutter are presented, and these results validate the principle of polarimetric detection     

A Nominator-Selector Two-Stage Signal Detection Scheme

A two-stage approach to computationally efficient signal detection is to nominate candidate signal vectors using a suboptimal, but computationally cheap, detection scheme, and subsequently perform optimal detection on the candidates. Bounds on the detection performance of this approach are presented along with sufficient conditions for optimality. Examples are presented of an optimal and nearly optimal two-stage detection scheme where computational costs are drastically reduced relative to the singli-stage optimal detector.     

GLRT Detectors for Aircraft Wake Vortices in Clear Air

 In this article, radar echoes of aircraft wake vortices are modeled as weighted sums of the frequency components of the echoes with a special covariance matrix for the weighted coefficients. With a proposed detection scheme, two generalized likelihood ratio test (GLRT) detectors are derived respectively for aircraft wake vortices with time-varying and time-invariant Doppler spectra. Then the analytical expressions for detection and false alarm probabilities of the detectors are derived and three factors are investigated which mainly influence the detection performance, i.e., the Doppler extension and uncertainty of the aircraft wake vortex, and the number of the detection cells. The results indicate that, the signal-to-noise ratio (SNR) loss induced by Doppler extension is generally several decibels. The SNR loss due to Doppler uncertainty is approximately proportional to the logarithm of the number of spectrum lines in the uncertain Doppler spectrum intervals. For a large number of detection cells, the SNR gain is approximately proportional to the square root of the number of the detection cells.     

液体火箭发动机健康监控──故障检测与诊断

以大型液体火箭发动机故障诊断系统框架为基础，按照发动机不同工作阶段的特点建立了相应的故障检测与诊断算法。利用发动机的高队数学模型，对基于推广的卡尔曼滤波器技术的新息检测算法进行了研究。根据发动机系统工作过程的特点，建立了降阶故障模式响应模型，并发展了相应的故障模式检验方法。为了适应在线实时检测的需要，利用发动机的试验数据，分别研究了基于人工神经元网络辨识模型的发动机启动过程检测算法和基于时间序列分析方法的发动机主机工作过程检测算法。通过试验数据的检测验证，证明了这些实时算法的快速性、准确性和鲁律性。     

星际着陆自主障碍检测与规避技术

 为了在具有科学价值的复杂地形区域实现安全着陆,未来的星际着陆器必须具备自主障碍检测与规避的能力。从星际着陆导航传感器技术、自主障碍检测方法和自主障碍规避技术3个方面出发,对星际着陆自主障碍检测与规避技术进行较全面的分析和总结。首先,对适用于星际着陆自主障碍检测的各种主动式和被动式传感器的工作原理、优缺点进行较深入的阐述;接着,基于不同传感器的测量信息,对各种自主障碍检测方法的障碍检测能力、优缺点进行较详细的对比分析;然后,基于多信息融合的自主障碍检测方法,对安全着陆点选择的原则进行阐述;最后,对星际着陆自主障碍规避流程和适用于星际着陆自主障碍规避的制导控制方法进行较系统的总结。     

Moving target detection via airborne HRR phased array radar

We study moving target detection in the presence of temporally and spatially correlated ground clutter for airborne high range resolution (HRR) phased array radar. We divide the HRR range profiles into large range segments to avoid the range migration problems that occur in the HRR radar data. Since each range segment contains a sequence of HRR range bins, no information is lost due to the division and hence no loss of resolution occurs. We show how to use a vector autoregressive (VAR) filtering technique to suppress the ground clutter. Then a moving target detector based on a generalized likelihood ratio test (GLRT) detection strategy is derived. The detection threshold is determined according to the desired false alarm rate, which is made possible via an asymptotic statistical analysis. After the target Doppler frequency and spatial signature vectors are estimated from the VAR-filtered data as if a target were present, a simple detection variable is computed and compared with the detection threshold to render a decision on the presence of a target. Numerical results are provided to demonstrate the performance of the proposed moving target detection algorithm     

Multiple-Tone Signals and Detection Probabillities

An analysis technique is presented for multiple-tone signals insystems employing noncoherent integration of a square-law detectoroutput. It is shown how the characteristic function for the teststatistic can be found from the easily determined "coherent"characteristic function defined in the two-dimensional signal space.This result is applied to two detection problems, the detection of multiple-tone signals in Gaussian noise and the detection of a Gaussian signal in multiple-tone plus Gaussian noise interference.The detection curves are compared to an approximation that is often used in practice to estimate performance. It is found that detection performance in the presence of multiple-tone interferences can be significantly different from that in the presence of Gaussian noise alone.     

不同检测方式下的维修心理分析

 初步探讨航空维修心理学的概念和航空维修人员应具备的心理品质。当前维修通用直接检测、仪器检测、智能机检测三种方式,分析人-机系统结构特点,论述了维修检测人员心理品质的特征,提出提高检测水平进行心理训练的主要内容。     

Threshold Control for Automatic Detection in Radar Systems

In automatic detection in radar systems an estimate of background clutter power is used to set the detection threshold. Usually detection cells surrounding the cell under test for the presence of a target are used to estimate the clutter power. In the research reported herein, the target location is taken to be uncertain and thus returns from a target could corrupt this clutter power estimate. It is shown how the threshold should be varied to compensate for the resulting degradation in detection performance. The threshold control procedure is based on a priori information about target location that could be supplied by the radar's tracking system. In addition, a simple procedure for calculating detection and false alarm probabilities for Swerling II target models is presented.     

不定线性系统的鲁棒故障检测

 <正> 1.引言 Beard等提出的检测滤波器是一种基于模型的故障检测与识别(FDI)方法,然而,检测滤波器要求精确地已知系统的动力学方程 X=AX+Bu,Y=CX (1) 其中,X∈R~n,Y∈R~m,u∈R~r分别为系统状态输出和控制;A、B、C为具有相应维数已知常阵。由于系统的复杂性以及系统外界干扰的不确定性,获取系统精确的数学模型非常困难。因此要解决的基本问题即考虑下列不定系统的故障检测     

High Resolution Differential Capacitance Detection Scheme for Micro Levitated Rotor Gyroscope

给出了一种用于新型悬浮结构的使用差分电容进行角度检测的电路分析。为了确保电路具有较小的非线性和高分辨率,进行了电路的噪声分析和和输出信号的非线性度仿真。在电容检测接口中,使用了电荷积分放大器作为前置级以消除由于电容接线引起的寄生电容。分析了当存在耦合电容时差分电容桥的输出以及输出信号的非线性误差,分析结果显示该检测电路可以实现高分辨率和低非线性的角度检测。使用 PSpice 仿真并制作了电容检测印刷电路板。实际实验中,该电路可以检测的最小角度分辨率为 0.04o,非线性误差为 2.3%。     

无人机空中对接中的视觉导航方法

无人机空中加油是一种能有效提升巡航里程及续航时长的技术手段,近距相对位置和姿态测量技术是其中需要解决的关键问题之一。针对该问题研究了无人机自主空中对接中的视觉导航方法,完成了近距对接的地面实验。首先,利用移动对接图标和无人机的GPS/INS信息进行无人机的粗略导航,完成会合;再充分利用视觉图标的颜色与形状信息,通过颜色分割选取目标可能区域,在这些区域中进行快速椭圆检测,针对椭圆检测算法存在误检测及边缘不重合的问题,提出了椭圆检测与轮廓检测相结合的方法,能够更准确地描述图标边缘;最后,利用改进的OI算法进行相对位姿的估计,实现近距的精确导航。实验结果表明,无人机在较高速度下的跟踪效果良好,采用的视觉导航方法能够满足空中对接中精度与实时性的要求。     

Exact Detection Performance for Broadband Correlators

The detection of a broadband plane wave in an isotropic noise field is considered. The detection statistic used is the cross correlation of the sampled output from two sensors where the sampling rate equals the Nyquist rate and the time delay is an integer multiple of the sampling period. By restricting the number of points in the cross correlation to be even, the detection and false-alarm probbilities are obtained in closed form. Numerical results are presented for several special cases.     

Robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels

The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective- ness of the orooosed aooroach.     

惯性技术在光电探测技术中的应用

惯性技术是通过惯性传感器敏感载体运动信息,自主建立运动载体姿态基准的手段。随着现代光电探测技术的不断发展,光电武器装备在侦察、监视、定位、导航和通信等场合的应用越来越广泛,惯性技术在光电探测技术与光电设备中的作用也越来越重要。本文介绍了光电探测技术和典型机载光电系统、惯性技术的发展历程,详细介绍了惯性技术在光电探测技术中的应用情况,分析了其对作战方式和作战效能所带来的变化和提升,阐述了惯性技术在光电探测技术应用的未来发展需求和趋势。     

Peformance of dynamic programming techniques forTrack-Before-Detect

“Track-Before-Detect” (TBD) is a target tracking technique where no threshold is applied at each measurement frame. Instead, data are processed over a number of frames before decisions on target existence are made. The track is returned simultaneously with the detection. A simple algorithm is presented and demonstrated via simulations. A detailed analysis enables detection and tracking performance to be predicted for particular algorithm parameters. Good performance is observed at low signal-to-noise ratio (SNR), with rapid degradation as SNR is reduced further. For some cases the detection performance does not improve regardless of how many frames of data are processed. Tracking performance may also be poor even though detection performance is good