RWR/ESM系统中对于诸如"虚警"、"漏警"等概念,经常从理论上和应用上混淆。结合RWR/ESM系统实际信号处理流程和功能,从信号统计检测理论出发,对比雷达/通信相关概念,发现传统意义上的"虚警"、"漏警"已不足以描述RWR/ESM对威胁的检测识别错误,为此基于多元假设检验理论,结合信号威胁等级,重新梳理RWR/ESM系统中信号检测类型的概念,将RWR/ESM的"虚警"、"漏警"拓展为带威胁级差的"虚警"、"漏警",增加"同级差错"概念,并初步探讨其概率、代价因子等相关特性。

For RWR/ESM suites/systems, such concepts as“False Alarm”,“Miss Alarm” are often con-fused in engineering operations and theoretic analysis. According to the theory of signalˊs statistical detec-tion/classification, in combination with RWR/ESM’ s signal processing flow and functions, and through comparing corresponding concepts of radar and communication, it is found that the traditional concepts of“False Alarm” and “Miss Alarm” can not cover the error detection kinds in RWR/ESM system. So signalˊs detection kinds in RWR/ESM are re-teased combined with threating levels and based on multiple hypotheses testing.“False Alarm” and “Miss Alarm” of RWR/ESM are developed with threating level-differs, and “same threating level error” is superadded, the characters of related probability, cost genes and so on are discussed preliminarily.

确的位置信息在维护VANETs的正常运行扮演着重要的角色，恶意节点的位置欺骗将严重影响VANETs诸多应用。通过对节，董的位置验证以检测节点的位置欺骗是VANETs重要的研究领域。针对、硝NETs中车辆移动的相对速度较高，网络拓扑结构频繁变化，传统wsN和MANET中的位置验证方案不再适用于VANETs，提出基于车辆的运动轨迹位置验证方案，采用最小二乘法对车辆进行连续定位跟踪，并绘制其行驶路线，与邻居车辆的行驶路线、速度相比较，计算其吻合度，检测位置欺骗。仿真结果表明，该方案有较低的漏警率和虚警率，当恶意节点的欺骗距离达到30m时，漏警率和虚警率接近于0。

The correct location information of vehicles plays an important role in the maintenance of the normal operation of vehicle Ad-hoc networks (VANETs) and the position spoofing from malicious node will seriously affect many applications of VANETs. Therefore, the detection of the position spoofing by location verification is an important issue. The traditional location algorithm in WSN and MANET no longer applies to VANETs. In this paper, a vehicle trajectory-based location verification scheme is proposed to locate and track continuously the vehicle and draw the trajectory. The inosculation is calculated and the position spoofing is detected by comparing with the trajectory and speed of the neighbor vehicle. The simulation results show that false negative rate and false positive rate are low. When the cheating distance of malicious node is 30 m, false negative and false positive rate are close to 0.

为提高定时捕获的正确捕获概率并降低漏检概率,提出一种基于分布式天线协同感知的定时捕获方法。该方法针对线形小区的平坦瑞利衰落信道场景,利用两根分布式接收天线接收来自单天线移动台的发射信号;根据中心处理器处的协同感知,确保各分布式接收天线的预定虚警概率,并为门限检测推导协同处理门限;各天线根据门限检测进行分布式天线系统的最大似然定时捕获。仿真结果表明,无论移动台处于线形小区的哪个位置,提出方法在不增加预定虚警概率的情况下,均能改善各分布式天线的正确捕获概率和漏检概率。

To increase the probability of correct acquisition and decrease the missed detection probability, a timing acquisition method with the cooperative sensing of distributed receive antennas is proposed. In the flat Rayleigh channels of linear cell, two distributed receive antennas are employed to receive the signal transmitted from the Mobile Station(MS)with a single antenna. This paper exploits the false alarm probability at the central processor to guarantee the false alarm probability at each distributed antenna. Based on the exploited probability of false alarm at the central processor, a cooperative detection threshold of each antenna is derived for threshold detection. According to the threshold detection, a Maximum-Likelihood(ML)-based timing acquisition method is proposed for Distributed Antenna Systems(DAS). Without increasing the pre-defined probability of false alarm, the analysis and simulation results show that the correct acquisition probability and the missed detection prob

概率假设密度（PHD）滤波器是解决虚警、漏检和目标数未知情况下多目标跟踪问题的新方法.然而在该滤波器中已存在的目标一旦在某个时刻不能被传感器检测到,漏检目标的大量信息会被滤波器丢弃.为解决漏检目标的信息丢失问题,对PHD滤波器的预测和更新方程进行了修正,提出了一种具有信息保持能力的PHD滤波器.在此基础上提出了适用于线性高斯模型的修正PHD滤波器高斯混合（GM）实现算法.仿真实验结果表明,与现有的PHD滤波器相比,在存在漏检的情况下所提出的GM-PHD滤波器能够提供更好的多目标跟踪能力.

The probability hypothesis density (PHD)filter has been proved to be an efficient method for the multi-target tracking in the presence of false alarms ,missed detections and an unknown number of targets .However ,in the original PHD filter , a large amount of information of the existing targets will be immediately discarded by the PHD filter once they cannot be detected by a sensor at a given time .To resolve the information loss problem of missed true targets ,we modify the predication and update e-quations of the PHD filter and propose a modified PHD filter with the capability of information hold .A Gaussian mixture implemen-tation of the modified PHD filter for linear Gaussian models is also presented .The simulation results demonstrate that the proposed filter can achieve better tracking performance of multiple targets than the original PHD filter in the presence of missed detections .

基于信号包络线相似性，本文提出了特定场地地下爆炸的识别方法，并将其用于一个特定场地地震事件分析，以评估该方法对特定场地爆炸事件的识别效果．结果表明，在误警率约为6．3％的情况下，事件间距小于15 km 的爆炸事件漏检率约为0．5％，事件间距在15—30 km 范围内的爆炸事件漏检率约为5．0％．与波形互相关方法相比，本文方法大幅扩大了有效识别特定场地爆炸事件的空间范围．

This paper presented a discriminant algorithm based on the similarity of wave envelopes to discriminate seismic events in the same site.The events in a fixed site were analyzed to evaluate the discriminating performance for under-ground explosions.The result shows good performance.When the false alarm rate is about 6.3%,the misclassification rate for explosions with inter-distance smaller than 15 km is only 0.5%,and that for explosions with inter-distance of 15—30 km is about 5.0%.Comparison with the result from the algorithm based on waveform cross-correlation indicates that the method in this paper can discriminate explosions with much larger inter-distance.