Model-based characterization of electromagnetic inductionsignatures obtained with the MTADS electromagnetic array

A sensor response model based on empirically determined orthogonal response coefficients β is presented for the analysis of electromagnetic induction (EMI) sensor data. The model is applied to high-quality survey data from the multi-sensor towed array detection system (MTADS) program. Data from both a prepared test range and a live-site survey are analyzed. At the test field, the authors show that the model successfully reproduces the measured signatures of ordnance, ordnance simulants, flat plates, and clutter. At the live site, fit statistics were collected showing that for the most abundant ordnance target, 81-mm mortars, the three beta response parameters are distributed log-normally. This allows for a simple method of discrimination. A receiver operating characteristic (ROC) analysis based on this discrimination method is performed and the results discussed     

Multi-aspect detection of surface and shallow-buried unexplodedordnance via ultra-wideband synthetic aperture radar

An ultra-wideband (UWB) synthetic aperture radar (SAR) system is investigated for the detection of former bombing ranges, littered by unexploded ordnance (UXO). The objective is detection of a high enough percentage of surface and shallow-buried UXO, with a low enough false-alarm rate, such that a former range can be detected. The physics of UWB SAR scattering is exploited in the context of a hidden Markov model (HMM), which explicitly accounts for the multiple aspects at which a SAR system views a given target. The HMM is trained on computed data, using SAR imagery synthesized via a validated physical-optics solution. The performance of the HMM is demonstrated by performing testing on measured UWB SAR data for many surface and shallow UXO buried in soil in the vicinity of naturally occurring clutter     

Magnetic models of unexploded ordnance

Magnetometry is widely used for the characterization of areas contaminated by unexploded ordnance (UXO). To successfully discriminate hazardous UXO from nonhazardous clutter requires accurate models of the ordnance response. This paper develops an ordnance library with 15 different items using total-field magnetic data collected over a test stand. The induced and remanent magnetizations were obtained by varying the three-dimensional orientation of each item and measuring the magnetic field on a horizontal plane in the dipolar regime. Replicate measurements using multiple specimens of the same ordnance returned very similar induced magnetizations. The fitted moments were used to estimate the detection depths for different sensor noise floors. A prolate spheroid with a 3.5 aspect ratio was used to provide a good approximation to the detection depths for many of the ordnance items. Assuming a 1-nT noise floor, these orientation-dependent detection depths ranged from 10 to 17 times of the object's diameter.     

航空军械仿真系统关键技术研究

一种以工控机和PLC控制技术为基础的航空军械仿真系统,于日常管理中应用该系统可以为航空军械提供所需的训练任务,并对其训练结果进行系统性的分析和评估。为航空军械仿真训练做出了一定的贡献,本文通过对其运行数据的分析来判断其可实施性。     

Simulation of near-surface detection of objects in layered media by the BCGS-FFT method

Near-surface electromagnetic characterization of objects buried in multilayered earth is important for the detection and identification of landmines, unexploded ordnance, and underground structures. However, so far little progress has been made in the development of fast algorithms for inhomogeneous objects in a layered medium. We report an iterative technique, the stabilized biconjugate gradient fast Fourier transform (BCGS-FFT) method, that simulates near-surface detection of three-dimensional, inhomogeneous objects buried in multilayered media. The CPU time and memory cost of the BCGS-FFT method is O(NlogN) and O(N), respectively, where N is the number of unknowns. This method is significantly more efficient than method of moments. It is capable of solving large-scale electromagnetic scattering problems with an arbitrary inhomogeneous object embedded in a layered medium with an arbitrary number of layers. Examples in subsurface detection of large buried objects are shown to demonstrate the efficacy of this method. At present, the object must be located completely within one single layer in this multilayer medium, but efforts are underway to remove this limitation.     

Ultrawide-band synthetic aperture radar for detection of unexplodedordnance: modeling and measurements

Electromagnetic (EM) scattering from subsurface unexploded ordnance (UXO) is investigated both theoretically and experimentally. Three EM models are considered: the multilevel fast multipole algorithm (MLFMA), the method of moments (MoM), and physical optics (PO). The relative accuracy of these models is compared for several scattering scenarios. Moreover, the model results are compared to data measured by an experimental synthetic aperture radar (SAR) system, SAR images have been generated for subsurface UXO targets, in particular 155-mm shells. We compare SAR images from the measured data with theoretical images produced by the MoM and PO simulations, using a standard back-projection imaging technique. In addition to such comparisons with measurement, we consider additional buried-UXO scattering scenarios to better understand the underlying wave phenomenology     

RFID tags to aid detection of buried unexploded ordnance

The difficulty in reliably and efficiently detecting and locating buried unexploded ordnance (UXO) is a concern for the military. Tagging munitions and ordnance items before they are fired or launched would allow for a significantly more efficient means of locating buried UXO. Munition tagging can be accomplished by employing existing passive radio-frequency identification (RFID) tag technology, such as the Texas Instruments' solenoidal tags. This tagging approach would result in very low falsealarm rates compared to those currently experienced. The tags provide information on the munition's location and identity when the UXO tag interrogation module is brought nearby. This paper summarizes the analytical and experimental efforts Battelle pursued to reach these conclusions. Analytical efforts included modeling of the magnetic field's behavior to understand the requirements to transmit energy from the above-ground interrogator to the tag and from the tag back to the above-ground receiver. Laboratory work validated the modeling results and showed the feasibility of the technique. Field testing of a prototype system indicated the likely success of this approach to detecting buried UXO.     

SAR processing of ground-penetrating radar data for buried UXOdetection: results from a surface-based system

Battelle and The Ohio State University ElectroScience Laboratory have built and demonstrated a ground-penetrating radar (GPR) system for locating buried unexploded ordnance (UXO), the system is ground based and towed by an autonomously controlled vehicle as part of the subsurface ordnance characterization system (SOCS). This paper presents the results of the synthetic aperture radar (SAR) processing of the radar data acquired at Tyndall Air Force Base, FL, and Jefferson Proving Ground (JPG), IN     

Area-based results for mine detection

The cost and the closely related length of time spent in searching for mines or unexploded ordnance (UXO) may well be largely determined by the number of false alarms. False alarms can result in time consuming digging of soil or in additional multisensory tests in the minefield. The authors consider two area-based methods for reducing false alarms. These are: (a) the previously known “declaration” technique and (b) the new δ technique, which they introduce. They first derive expressions and lower bounds for false-alarm probabilities as a function of declaration area and discuss their impact on receiver operation characteristic (ROC) curves. Second, they exploit characteristics of the statistical distribution of sensory energy in the immediate neighborhood of targets and of false alarms from available calibrated data, to propose the δ technique, which significantly improves discrimination between targets and false alarms. The results are abundantly illustrated with statistical data and ROC curves using electromagnetic-induction sensor data made available through DARPA from measurements at various calibrated sites     

CMOS silicon avalanche photodiodes for NIR light detection: a survey

This paper surveys recent research on CMOS silicon avalanche photodiodes (SiAPD) and presents the design of a SiAPD based photoreceiver dedicated to near-infrared spectroscopy (NIRS) application. Near-infrared spectroscopy provides an inexpensive, non-invasive, and portable means to image brain function, and is one of the most efficient diagnostic techniques of different neurological diseases. In NIRS system, brain tissue is penetrated by near-infrared (NIR) radiation and the reflected signal is captured by a photodiode. Since the reflected NIR signal has very low amplitude, SiAPD is a better choice than regular photodiode for NIR signal detection due to SiAPD`s ability to amplify the photo generated signal by avalanche multiplication. Design requirements of using CMOS SiAPDs for NIR light detection are discussed, and the challenges of fabricating SiAPDs using standard CMOS process are addressed. Performances of state-of-the-art CMOS SiAPDs with different device structures are summarized and compared. The efficacy of the proposed SiAPD based photoreceiver is confirmed by post layout simulation. Finally, the SiAPD and its associated circuits has been implemented in one chip using 0.35 μm standard CMOS technology for an integrated NIRS system.     

Discrimination and classification of buried unexploded ordnance using magnetometry

Magnetic surveys are quite successful at locating buried steel objects, including unexploded ordnance (UXO). However, many of the anomalies apparent in a magnetic image of a contaminated area are from metallic debris, shrapnel, and geological variations in ferromagnetic concentration. Observations are usually made in the far-field of the object so that, in most cases, we can only recover the dipole moment of a buried item. Due to self-demagnetization effects, the magnitude and direction of induced magnetism varies significantly with ordnance orientation. This results in an infinite number of ordnance-like objects that can reproduce a given dipole moment. To discriminate, we define a library of ordnance items expected to occur in the area and find how closely each recovered moment matches one of the UXOs in this library. We define the size of this mismatch as the remanent magnetization and produce a prioritized dig-list on the assumption that items with lower remanence are more likely to be UXO. Such a ranking scheme proves to be very effective when implemented at two sites in Montana. The analysis reveals that live-site and emplaced UXO have significantly different remanence and implies that previous tests of magnetic discrimination performance on seeded sites have been overly pessimistic.     

Acoustic detection of buried objects in 3-D fluid saturated porousmedia: numerical modeling

Acoustic waves can be a viable tool for the detection and identification of land mines, unexplored ordnance (UXO), and other buried objects. Design of acoustic instruments and interpretation and processing of acoustic measurements call for accurate numerical models to simulate acoustic wave propagation in a heterogeneous soil with buried objects. Compared with the traditional seismic exploration, high attenuation is unfortunately ubiquitous for shallow surface acoustic measurements because of the loose soil and the fluid in its pore space. To adequately model such acoustic attenuation, we propose a comprehensive multidimensional finite-difference time-domain (FDTD) model to simulate the acoustic wave interactions with land mines and soils based on the Biot theory for poroelastic media. For the truncation of the computational domain, we use the perfectly matched layer (PML). The method is validated by comparison with analytical solutions. Unlike the pure elastic wave model, this efficient PML-FDTD model for poroelastic media incorporates the interactions of waves and the fluid-saturated pore space. Several typical land mine detection measurements are simulated to illustrate the application     

基于分形理论的目标检测

军事目标检测一般是由自然背景和少量的人造目标所组成．现有的图像目标检测方法大多是基于对目标本身特性进行分析，不适用于目标特性未知的军事目标检测．本文根据人造目标和自然背景在分形特征上的固有差异，在利用分形维数提取人造目标边缘特征的基础上，结合小波分析方法提取的目标边缘特征，对自然背景中的人造军事目标进行检测．实验证明该方法具有较好的适应性．     

基于多进制检测的可见光多层成像通信系统

为适应多用户需求,提出了一种基于多进制检测的可见光多层成像通信系统。依不同优先权将发送信息加载在分集程度不同的各层发送单元上。优先权越高,分集程度越高,信息的鲁棒性相对较高但传输速率较低;相反的,优先权越低,复用程度越高,信息的传输速率相对较高但鲁棒性较低。结合系统模型,利用基于最大似然检测的多进制检测算法实现了信息提取。最后,通过仿真实验验证了系统的可行性。在保证系统检测性能和算法复杂度相对较低的同时,实现了多层成像通信系统的稳定传输。     

Intrusion detection in wireless ad hoc networks

Intrusion detection has, over the last few years, assumed paramount importance within the broad realm of network security, more so in the case of wireless ad hoc networks. These are networks that do not have an underlying infrastructure; the network topology is constantly changing. The inherently vulnerable characteristics of wireless ad hoc networks make them susceptible to attacks, and it may be too late before any counter action can take effect. Second, with so much advancement in hacking, if attackers try hard enough they will eventually succeed in infiltrating the system. This makes it important to constantly (or at least periodically) monitor what is taking place on a system and look for suspicious behavior. Intrusion detection systems (IDSs) do just that: monitor audit data, look for intrusions to the system, and initiate a proper response (e.g., email the systems administrator, start an automatic retaliation). As such, there is a need to complement traditional security mechanisms with efficient intrusion detection and response. In this article we present a survey on the work that has been done in the area of intrusion detection in mobile ad hoc networks.     

车联网中基于神经网络的入侵检测方案

车联网的入侵检测（IDS）可用于确认交通事件通知中描述的事件的真实性。当前车联网IDS多采用基于冗余数据的一致性检测方案,为降低IDS对冗余数据的依赖性,提出了一个基于神经网络的入侵检测方案。该方案可描述大量交通事件类型,并综合使用了反向传播（BP）和支持向量机（SVM）2种学习算法。这2种算法分别适用于个人安全驾驶速度快与高效交通系统检测率高的应用。仿真实验和性能分析表明,本方案具有较快的入侵检测速度,且具有较高的检测率和较低的虚警率。     

A novel SVM for Ground Penetrating Synthetic Aperture Radar landmine detection

The use of vehicle-or air-borne Ground Penetrating Synthetic Aperture Radar （GPSAR） to quickly detect landmines over large areas is becoming a trend. However, producing too many false alarms in GPSAR landmine detection is a major challenge in practical applications of GPSAR. Support Vector Machine （SVM）, employing structural risk minimization theory, does not need large amounts of training data, which makes it suitable for solving the landmine detection problem. In this paper, a novel SVM with a hypersphere instead of a hyperplane classification boundary is proposed for landmine detection in GPSAR. The HyperSphere-SVM （HS-SVM） can be trained with both landmine and clutter data, or with landmine data only, which are called the two-class HS-SVM and the one-class HS-SVM, respectively. The HS-SVM has better generalization capability than the traditional HyperPlane-SVM （HP-SVM） with respect to varying operating conditions. Quantitative comparisons have been made using real data collected with the rail-GPSAR landmine detection system, which show that both the two-class and the one-class HS-SVMs have better detection performance than the HP-SVM.     

基于HMM核超球面支持向量机的 超宽带SAR未爆物检测

 利用机载超宽带合成孔径雷达(UWB SAR)探测地下未爆物(UXO)具有安全和高效的优点.UXO检测分为预筛选和鉴别.预筛选从大面积SAR图像中提取若干怀疑目标,而鉴别则将这些怀疑目标分成UXO和杂波从而降低虚警.本文提出隐马尔可夫模型(HMM)核的超球面支持向量机(HS-SVM)UXO鉴别器.HS-SVM基于结构风险最小原理并利用核特征空间中的超球面区分UXO和杂波能够解决小训练样本集和无典型杂波样本两个问题.此外将描述UXO多方位特征的HMM作为HS-SVM核函数进一步提高了UXO的鉴别性能.实测数据处理结果表明,HMM核HS-SVM优于HMM和高斯核HS-SVM等UXO鉴别器.     

An attack invariant scheme for content-based video copy detection

Due to the advancement in the field of multimedia technology and communication, it has become easier to access, store, and edit video data. Easy manipulation of video data and its rapid distribution have made content-based video copy detection (CBVCD) an active area of research. In a CBVCD system, reference video sequence and query sequence are compared to detect whether the query video sequence is a copy of reference video sequence. Thus, the generation of fingerprint of a video sequence and sequence matching technique are the core tasks of such system. In order to evade such detection process, a copied version may undergo different kinds of transformations like photometric and post-production attack. So the detection system must be robust enough against such attacks. In this work, fingerprint is generated from the sub-bands of wavelet decomposed intensity image and localized intensity gradient histograms of low sub-band. The fingerprint thus obtained reflects considerable discriminating capability and robustness against the attacks. Furthermore, to cope up with the attacks, we have adopted simple pre-processing technique, which enhances the robustness of the system further. A robust sequence matching technique based on multivariate Wald–Wolfowitz test is proposed here. An experiment has been carried out with a database consisting of distinct 642 shots and 1,485 query sequences representing different attacks. Proposed methodology achieves high copy detection rate (99.39 %) and very low false alarm rate (0.14 %) and performs better than other spatio-temporal measure based systems.     

一种嵌入式中红外甲烷检测系统的研制

为了实现检测系统的便携化、小型化和较强的数 据处理能力,结合ARM 11嵌入式处理器和 LabVIEW数据处理平台,设计并实现了一种嵌入式中红外差分甲烷检测系统。在软件方面, 选用S3C6410 作为主处理器、WinCE作为嵌入式操作系统,采用Platform Builder工具对该系统的内核文 件进行裁剪定 制以及移植安装;采用具有较强数据处理能力的LabVIEW作为数据处理平台,通过Touch Pan el模块编写 并生成可直接运行于WinCE系统的应用程序来处理传感信号。在硬件方面,选用双通道集成 传感器IR12GJ, 其输出的两路传感信号经前端电路放大和滤波处理后,由数据采集卡对其进行采集并传输给 LabVIEW软 件程序,经数据处理后获得甲烷浓度。基于所集成的系统,开展了气体标定、误差测量以及 系统稳定性实 验。实验结果显示,本系统对甲烷气体浓度的检测范围为0~6.5%,对 12种气体样品的相对检测误差小于 10%。对浓度为0.5%的气体样品进行了长达4小 时的稳定性检测,除个别突变点外,最大误差为8.3%。本 文所设计的检测系统结合了嵌入式系统体积小以及LabVIEW数据处理能力强的优点,从而具 有较好的应用前景。