高倍率脉冲放电锂电池的功率输出特性

由于电池内阻和极化现象的存在,锂电池在放电的瞬间会出现较大的电压跌落,高倍率脉冲放电锂电池更是如此。为了研究高倍率脉冲放电锂电池的功率输出特性,探讨温度、荷电状态和老化等因素对电池功率性能的影响规律,定义了锂电池的功率特性曲线,搭建了高倍率电池测试平台,并从温度、荷电状态和老化3个阻抗敏感因素开展实验研究。研究方法和结论对后期开展锂电池系统的峰值功率评估和功率曲线预测有一定的指导意义。     

GNSS/INS超紧组合导航综述

卫星/惯性超紧组合导航系统以其定位精度高、动态性能优良、抗干扰能力强等特性成为组合导航领域的研究热点。介绍了卫星/惯性超紧组合的定位原理,基于对技术原理的分析,比较超紧组合模式相对于其他组合模式的优势特点;以高动态下超紧组合技术及卫星/微惯性单元超紧组合为代表介绍国内外研究现状;总结了亟待研究的容错控制技术、神经网络辅助、多传感器辅助超紧组合等关键技术,并对卫星/惯性超紧组合向着低成本、高精度、强稳定趋势发展的前景进行展望。     

GNSS信号功率增强对调零抗干扰接收机的性能影响

由于卫星端信号发射功率小、信号传播损耗大,到达接收机的卫星导航信号极其微弱,容易被干扰。为有效应对电磁干扰的威胁,在系统层面和用户层面同时采取抗干扰措施将是一种很好的选择。建立调零抗干扰接收机抗干扰能力分析模型,并定量分析信号功率增强对调零抗干扰接收机抗干扰性能的提升效果。结果表明：信号功率每增强10 dB,接收机抗干扰能力可提升3～4 dB,但从提高接收机非极限条件下的接收性能(载噪比、测距定位精度等)的角度,信号功率增强15～20 dB时,接收性能最优。研究成果可为卫星功率增强量的优化设计以及终端抗干扰设计提供参考。     

被动全向声纳浮标跟踪潜艇的优化布放方法

反潜飞机利用被动全向声纳浮标可以隐蔽地跟踪潜艇,但浮标消耗量大。在满足定位精度的条件下,如何优化布放浮标以便有效增加跟踪时间是一个亟待解决的问题。首先分析了浮标探测性能和浮标群相对位置对定位精度的影响,得到浮标布放的五种基本原则;然后结合水下目标跟踪技术提出了两种用被动全向声纳浮标跟踪潜艇的优化布放方法:一种是利用遗传算法来优化每一枚浮标的布放位置,另一种是将一批次投放2-4枚浮标的多维优化问题简单转换成一维优化问题来确定浮标的布放位置。最后仿真计算了这两种方法的跟踪性能及浮标消耗量。仿真结果表明,两种优化布放方法均能满足跟踪要求,前者的浮标消耗量比后者略少,但后者的投放批次少很多,有利于减少人员的工作量。     

一种有效的红外弱小目标DBT算法研究

作为红外自寻的制导、搜索跟踪和预警等领域的一项关键技术,红外弱小目标检测与跟踪成了红外图像处理领域中的一项重要研究课题。本文采用了"先检测后跟踪(DBT)"的思想对红外小目标进行检测与跟踪,首先采用基于各向异性偏微分方程的背景抑制技术对单帧图像进行抑制,再用最大绝对对比度阈值对红外图像进行分割,最后采用形心跟踪法对小目标点坐标定位。试验证明本文算法应用于目标检测的可行性和有效性。     

基于最小模型集切换的变结构IMMPF算法

为提高对机动目标的跟踪精度,提出了一种新的基于最小模型集切换的变结构IMMPF跟踪算法,其中以"当前"统计模型为基础的不同最小模型集在不同时刻之间的切换实现了多模型的结构变换。当目标机动方式发生改变时,通过最小模型集的切换实现算法的滤波模型与目标实际机动方式的快速匹配,减小了目标机动的响应时间。通过仿真实验,与通用的IMM估计进行了比较,证明了算法的优越性。     

现代化的GPS军用M码综述

M码是现代化的GPS军用码,是美国"导航战"的重要内容。从M码信号的设计要求出发,介绍了M码信号的调制原理及其功率谱和自相关特性;然后根据相关损失、均方根带宽、频谱隔离系数和等效矩形带宽等参数对M码、C/A码和P(Y)码性能进行了分析比较;最后总结了M码的几种捕获和跟踪方案,并对其各自的优缺点进行了分析。     

基于SNR的烟幕干扰效果仿真

烟幕对红外等电磁波具有吸收、反射和散射特性,可导致导引头上接收的能量大大衰减,从而降低导弹的命中概率.针对外场烟幕性能测试受气象条件和环境因素的影响较大,对准确评估抗红外烟幕遮蔽性能存在较大困难的情况,结合气象条件从烟幕透过率的变化引起导引头信噪比变化的角度,建立了烟幕干扰效果的评估模型,通过计算机仿真,得出了烟幕对红外制导导弹的干扰效果.通过试验对其中的一些结论进行了实验验证,结果表明计算结果能够与实验数据较好吻合.     

ESM量测间歇下雷达/ESM协同跟踪与辐射控制

为减少作战飞机目标跟踪过程中的雷达辐射,提出了一种ESM间歇量测情况下的机载雷达/ESM协同跟踪与辐射控制方法.采用基于IMM-EKF的雷达/ESM序贯滤波算法对目标进行滤波跟踪,利用跟踪过程中的预测协方差与预定门限进行比较控制雷达辐射,并给出了不同ESM间歇时间、控制门限与雷达辐射时间的关系.研究结论有助于提升作战飞机的隐蔽性和生存能力.     

Signal‐to‐interference‐plus‐noise ratio estimation for wireless communication systems: Methods and analysis

The Signal‐to‐Interference‐plus‐Noise Ratio (SINR) is an important metric of wireless communication link quality. SINR estimates have several important applications. These include optimizing the transmit power level for a target quality of service, assisting with handoff decisions and dynamically adapting the data rate for wireless Internet applications. Accurate SINR estimation provides for both a more efficient system and a higher user‐perceived quality of service. In this paper, we develop new SINR estimators and compare their mean squared error (MSE) performance. We show that our new estimators dominate estimators that have previously appeared in the literature with respect to MSE. The sequence of transmitted bits in wireless communication systems consists of both pilot bits (which are known both to the transmitter and receiver) and user bits (which are known only by the transmitter). The SINR estimators we consider alternatively depend exclusively on pilot bits, exclusively on user bits, or simultaneously use both pilot and user bits. In addition, we consider estimators that utilize smoothing and feedback mechanisms. Smoothed estimators are motivated by the fact that the interference component of the SINR changes relatively slowly with time, typically with the addition or departure of a user to the system. Feedback estimators are motivated by the fact that receivers typically decode bits correctly with a very high probability, and therefore user bits can be thought of as quasipilot bits. For each estimator discussed, we derive an exact or approximate formula for its MSE. Satterthwaite approximations, noncentral F distributions (singly and doubly) and distribution theory of quadratic forms are the key statistical tools used in developing the MSE formulas. In the case of approximate MSE formulas, we validate their accuracy using simulation techniques. The approximate MSE formulas, of interest in their own right for comparing the quality of the estimators, are also used for optimally combining estimators. In particular, we derive optimal weights for linearly combining an estimator based on pilot bits with an estimator based on user bits. The optimal weights depend on the MSE of the two estimators being combined, and thus the accurate approximate MSE formulas can conveniently be used. The optimal weights also depend on the unknown SINR, and therefore need to be estimated in order to construct a useable combined estimator. The impact on the MSE of the combined estimator due to estimating the weights is examined. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004