盲稀疏度下基于粒子滤波的稀疏信号重构

针对现有贪婪迭代类压缩感知重构算法对非高斯量测噪声抵抗性差的问题,提出一种盲稀疏度下基于粒子滤波的稀疏信号重构算法。该算法首先将鲁棒性更高的Huber损失函数替代常规的二次损失函数,用来增加对非高斯噪声的抵抗能力;并且引入粒子滤波实现对原始信号的最优估计,以削弱量测噪声的影响;最后在信号稀疏度未知的条件下,结合稀疏度自适应匹配追踪算法实现盲稀疏度下的原信号重构。理论分析和仿真结果表明,所提算法可以有效抵抗因非高斯噪声干扰或稀疏度未知导致的重构精度降低,且重构性能优于现有典型贪婪迭代类算法。     

INS辅助的GNSS接收机信号捕获性能分析

针对信号捕获过程中Doppler频移造成的影响,采用INS辅助的GNSS信号捕获方法,分析了INS辅助后卫星信号捕获的性能。利用INS速度误差方程与Doppler误差之间的关系,分析INS辅助后的捕获性能,并通过性能参数的比较,理论上验证了INS辅助后的捕获能力的提升。仿真结果表明,INS辅助能够有效提高信号捕获的检测概率和对弱信号的捕获能力,并大幅减小平均捕获时间。同时,考虑到INS器件参数的关键性作用,采用战术级的INS器件完全满足工程需求。     

自然场景车标数据集的构建及其应用

车标作为车辆身份的关键特征之一,在车辆的监控与辨识中发挥着重要作用。由于自然场景复杂多变,对其中的车标进行准确识别仍具有很大的挑战性。目前公开数据库很少且存在诸多局限,导致研究缺乏可信度和实用性。本文建立了一个面向自然场景的全新数据集,包含多种采集环境下的10 324幅、67类车辆图像。基于此数据集开展应用研究,提出一个目标检测与深度学习相结合的车标识别方法,包括车标区域定位和车标种类预测两大步骤。实验表明,该方法对复杂背景有较强的适应性,在涉及30种车标的分类任务中达到89.0%的总体识别率。     

Bidirectional parallel multi-branch convolution feature pyramid network for target detection in aerial images of swarm UAVs

In this paper, based on a bidirectional parallel multi-branch feature pyramid network (BPMFPN), a novel one-stage object detector called BPMFPN Det is proposed for real-time detection of ground multi-scale targets by swarm unmanned aerial vehicles (UAVs). First, the bidirectional parallel multi-branch convolution modules are used to construct the feature pyramid to enhance the feature expression abilities of different scale feature layers. Next, the feature pyramid is integrated into the single-stage object detection framework to ensure real-time performance. In order to validate the effectiveness of the proposed algorithm, experiments are conducted on four datasets. For the PASCAL VOC dataset, the proposed algorithm achieves the mean average precision (mAP) of 85.4 on the VOC 2007 test set. With regard to the detection in optical remote sensing (DIOR) dataset, the proposed algorithm achieves 73.9 mAP. For vehicle detection in aerial imagery (VEDAI) dataset, the detection accuracy of small land vehicle (slv) targets reaches 97.4 mAP. For unmanned aerial vehicle detection and tracking (UAVDT) dataset, the proposed BPMFPN Det achieves the mAP of 48.75. Compared with the previous state-of-the-art methods, the results obtained by the proposed algorithm are more competitive. The experimental results demonstrate that the proposed algorithm can effectively solve the problem of real-time detection of ground multi-scale targets in aerial images of swarm UAVs.     

Electronic warfare in the optical band: Main features,examples and selected measurement data

The paper presents the possibilities of, and methods for, acquiring, analysing and processing optical signals in order to recognise, identify and counteract threats on the contemporary battleground. The main ways electronic warfare is waged in the optical band of the electromagnetic wave spectrum have been formulated, including the acquisition of optical emitter signatures, as well as ultraviolet (UV) and thermal (IR) signatures. The physical parameters and values describing the emission of laser radiation are discussed, including their importance in terms of creating optical signatures. Moreover, it has been shown that in the transformation of optical signals into signatures, only their spectral and temporal parameters can be applied. This was confirmed in experimental part of the paper, which includes our own measurements of spectral and temporal emission characteristics for three types of binocular laser rangefinders. It has been further shown that through simple registration and quick analysis involving comparison of emission time parameters in the case of UV signatures in “solar-blind” band, various events can be identified quickly and faultlessly. The same is true for IR signatures, where the amplitudes of the recorded signal for several wavelengths are compared. This was confirmed experimentally for UV signatures by registering and then analyzing signals from several events during military exercises at a training ground, namely Rocket Propelled Grenade (RPG) launches and explosions after hitting targets, trinitrotoluene (TNT) explosions, firing armour-piercing, fin-stabilised, discarding sabots (APFSDS) or high explosive (HE) projectiles. The final section describes a proposed model database of emitters, created as a result of analysing and transforming the recorded signals into optical signatures.     

Cooperative interception with fast multiple model adaptive estimation

For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang-bang evasive maneuver with a random switching time. Combined Fast multiple model adaptive estimation (Fast MMAE) algorithm, the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration. Introduced the detection error model related to the line-of-sight (LOS) separation angle of two interceptors, an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance. Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion, Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately. The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.     

多径条件下的空时解相关接收机研究

通过建立了一般的空时CDMA系统模型 ,探讨多址干扰和多径效应的联合抑制问题。首先分析了系统的可辨识条件 ,然后利用多约束最优化准则研究了FIR空时解相关接收机设计和实现 ,并进一步分析了系统性能     

有源消声技术与应用述评

近十几年来 ,有源消声技术成为噪声控制领域一个多学科交叉、渗透、延伸的研究热点 ,它以其体积小、重量轻、低频消声效果好等优点获得普遍的关注。本文简述有源消声的基本原理 ,对有源消声理论研究、实现技术、产品应用三个方面的国内外研究现状、进展和难点进行了详细的阐述和分析 ,较为完整地展示了当前该研究领域的全貌 ,最后进一步分析了有源消声走向工程化过程中存在的一些主要问题 ,提出了有源消声技术的几个重点发展方向     

基于定子反电势E的异步电机速度辨识方法

针对以转子磁通作中间变量 ,利用定子电压电流辨识电机转速的MRAS方法存在的问题 ,提出以反电势作中间变量的改进的MRAS转速辨识方法 .通过对无速度传感器矢量控制系统的仿真 ,表明该方案具有较好的实用性     

Honeypot系统研究与比较

Honeypot系统是构建一个跟实际系统类似的网络陷阱,成为现有网络安全体系的重要补充手段。它可以诱惑攻击者将时间和资源都花费在攻击Honeypot上,从而保护真实工作系统免于攻击。它能监视和跟踪入侵者,收集入侵者的信息,以分析系统所面临的威胁,研究入侵者所用的入侵工具、策略和动机,在网络安全中起着主动防御的作用,是现有安全体系的重要补充。文章分析了构造Honeypot的分类及其优缺点,对Honeypot的实现软件进行比较,并指出了Honeypot系统存在的不足。