先验失配条件下的知识辅助检测器稳健性分析

充分利用探测环境的先验信息是提高雷达探测能力的有效途径之一。先验信息必须在雷达检测算法设计阶段确定下来,因此先验信息与当前探测环境之间可能存在不一致性。以复合高斯杂波中的、利用纹理分量先验信息的知识辅助(KA)检测器作为研究对象,首先建立了该检测器检测性能与先验分布参数失配之间的量化关系,然后根据给定的杂波探测环境模型参数,分析了先验模型失配对检测性能的影响。分析结果表明:知识辅助检测器的稳健性与当前探测环境模型参数有关。进一步给出了先验模型失配的容许区间,当先验模型参数在这个区间内,知识辅助检测器性能优于不使用先验信息的检测器性能。     

从探测概率的角度评价飞机的隐身性能

采用雷达散射截面(RCS)均值来衡量飞机的隐身性能并不能给出足够充分的信息,从信号检测概率的角度来衡量飞机的可探测性可以提供更完整的信息。本文从探测概率的角度详细分析了4种典型隐身飞机RCS起伏数据与虚警概率、探测概率、探测距离、信噪比(SNR)等参数间的关系,并给出了完整的推导过程,采用此方法可以对任意飞机目标在给定雷达参数下的可探测性进行准确计算。一般在雷达性能评估中需要用到RCS起伏模型,本文对飞机目标回波信号进行检测分析时采用数值计算方法,信号的概率密度函数(PDF)直接来源于原始回波起伏信号,避免了模型拟合带来的回波特性失真,且不会产生大的计算误差。通过对比分析计算结果发现:单脉冲检测下回波信号均值中值比越大,回波取值范围越小,则信号的检测概率越小,其中均值中值比一般相差3倍以上时可以得到明显不同的检测概率;在快起伏假设下,非相参积累检测的积累脉冲数Nin即便较小,也能得到较大的信噪比增益,此增益可能大于Nin。     

The AWIATOR airborne LIDAR turbulence sensor

The development and first flight tests are described of a short pulse direct measuring UV LIDAR for the measurement of gusts, turbulence and potentially wake vortices. The results of these stage 1 tests confirm that relative wind velocities can be measured with a standard deviation of below 10 m/s even at high altitudes with no appreciable aerosol concentrations. Operating the system under various flight conditions including rain, dense clouds, and clear air up to 24,000 ft was highly successful. Means to push the standard deviation below 1.6 m/s, foremost by increasing the laser output power and the efficiency of the light collecting system, are identified and quantified. Questions of instrument stability are addressed.     

Passive optical detection of submillimeter and millimeter size space debris in low Earth orbit

Understanding of the space debris environment and accuracy of its observation-validated models are essential for optimal design and safe operation of satellite systems. Existing ground-based optical telescopes and radars are not capable of observing debris smaller than several millimeters in size. A new experimental and instrumental approach – the space-based Local Orbital Debris Environment (LODE) detector – aims at in situ measuring of debris with sizes from 0.2–10 mm near the satellite orbit. The LODE concept relies on a passive optical photon-counting time-tagging imaging system detecting solar photons (in the visible spectral range) reflected by debris crossing the sensor field of view. In contrast, prior feasibility studies of space-based optical sensors considered frame detectors in the focal plane. The article describes the new experimental concept, discusses top-level system parameters and design tradeoffs, outlines an approach to identifying and extracting rare debris detection events from the background, and presents an example of performance characteristics of a LODE sensor with a 6-cm diameter aperture. The article concludes with a discussion of possible sensor applications on satellites.     

基于深度学习的ADS-B异常数据检测模型

广播式自动相关监视（ADS-B）是下一代空中交通运输系统的重要组成部分，是新航行系统中非常重要的通信和监视技术，但其协议没有提供相关的信息认证和数据加密，因此极其容易受到欺骗干扰的影响。针对ADS-B报文数据特点，采用深度学习的seq2seq模型对ADS-B报文数据进行重构，通过重构误差来检测异常，并对数据进行特征扩展，使模型能更好的捕捉数据的时间依赖性。实验结果表明，所采用的方法优于传统的机器学习方法，且在数据特征扩展后，模型检测效果提升。相比于现有的欺骗干扰检测方法，该方法不需要改变ADS-B系统的协议，也不需要额外的节点或传感器参与，具有一定的适应性和灵活性。     

一种电能表表号区域的定位方法

电能表表号可以唯一标识一块电能表的身份,针对当前对电能表表号识别研究比较少,研究了一种定位电能表表号区域的方法。由于电能表表面存在字符的区域比较多,定位电能表表号区域相对比较困难,结合了电能表表号数字区域的特征,通过对图片进行Canny边缘检测、数学形态学运算和区域限定,最后成功实现了电能表表号的定位。     

神经网络在火箭容错控制中的应用

利用解析冗余思想和神经网络的非线性映射能力，提出了基于神经网络的故障检测和容错控制框架，以此实现解析冗余，并将其应用于火箭稳定回路容错控制设计，仿真研究表明，该方案设计思想正确．具有一定的实用价值。     

Bayesian edge detector for SAR imagery using discontinuity-adaptive Markov random feld modeling

Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.     

复合高斯杂波中距离扩展目标的迭代近似GLRT检测器

 研究了结构化的复合高斯杂波(CGC)背景中距离扩展目标自适应检测问题。针对异质杂波背景中的近似广义似然比检验(AGLRT-HTG)检测器应用于CGC背景中时存在一定的信杂比损失问题,结构化的复合高斯杂波采用自回归过程建模,结合近似广义似然比检验(AGLRT)方法和迭代估计思想,提出了CGC背景中距离扩展目标的迭代近似广义似然比检测器(RAGLRT-CGC)。从理论上分析了极限情况下RAGLRT-CGC虚警概率与检测门限关系的解析表达式。仿真结果表明,在CGC背景中,RAGLRT-CGC对不同多主散射点目标具有较好的鲁棒性,并且检测性能明显优于AGLRT-HTG。