干扰环境下直扩系统中DMF捕获性能研究

基于数字匹配滤波器(DMF)的捕获电路具有较快的捕获速度,因此它在直扩系统(DSSS)中得到了广泛的应用。为了在干扰环境下进一步提高其捕获性能,本文对影响捕获性能的检测概率和虚警概率进行了分析;并对直扩系统中基于DMF的平均捕获时间进行了计算机仿真,从而找到了在平均捕获时间较小时应该满足的信干比、干噪比和判决门限,为改善直扩系统的捕获性能提供了理论依据。     

遗传算法在微弱GPS信号捕获方法中的应用

 研究了微弱GPS信号的捕获问题，以捕获时较低的虚警概率和较高的检测概率为目标，以累加时的粗捕获(C/A)码周期数和导航数据数，以及捕获门限等参数为决策变量，应用遗传算法(GA)来解决这一多目标优化问题。仿真结果表明，该方法能够有效地解决所提出的问题，所得解能够优化捕获时欲选取的参数，从而提高捕获性能。     

UMVE对数单元平均恒虚警检测器性能分析

利用无偏最小方差估计(UMVE)算法分析了UMVE对数单元平均恒虚警检测器的性能.它的前沿和后沿均采用UMVE算法产生局部估计,再对两者求和得到背景功率水平.在SwerlingⅡ模型下,给出UMVE对数单元平均恒虚警检测器虚警概率和检测概率解析表达式.与对数单元平均恒虚警检测器相比,UMVE对数单元平均恒虚警检测器的性能得到了改善.     

基于先验门限优化准则的探测阈值自适应选择

针对 2维测量和 4 -sigma确认门 ,把先验检测门限优化准则和修正 Riccati方程的解析近似表示相结合 ,得到了在瑞利起伏环境下使跟踪性能优化的信号探测阈值解析表示式 ,从而使在线求解自适应信号探测阈值能比较容易地实现。通过研究和仿真发现 :在滤波稳定阶段 ,本文给出的自适应信号检测门限方法的跟踪性能优于固定虚警率方法的跟踪性能 ;基于先验检测门限优化准则实现检测 -跟踪的联合优化要求信噪比要大于一定的门限 ,在瑞利起伏环境下 ,对 2维测量和 4 -sigma确认门 ,该门限为 1 .57     

一种变信噪比条件下的恒虚警野值检测方法

野值检测又称异常值检测,是模式识别、机器智能和知识发现等领域经常面临的一个问题。当出现环境失配,数据信噪比（SNR）发生变化时,测试样本和训练样本所含噪声会有不同方差,以往的野值检测方法在虚警控制方面将会失效。针对这一问题,提出一种基于归一化残差（NR）的野值检测方法。该方法首先根据所需虚警概率和噪声方差变化情况确定野值检测门限,其次基于训练样本计算待考查模式的NR值,再比较NR值与检测门限的相对大小,从而判断待考查模式是否为野值。这一方法所依赖的检测门限对所需虚警率和噪声方差变化具有适应能力,因此可以在变信噪比条件下实现恒虚警（CFAR）野值检测。仿真实验验证了所提方法在虚警控制和野值检测方面的优越性能。     

空地数据链自适应编码调制方法研究

针对空地数据链高效可靠的传输要求,本文研究了空地数据链自适应编码调制方法。该方法基于码率可变的Turbo码,传输信道模型解算与加栽,最大似然信道估计,自适应判决门限的确定等技术,在微波暗室环境内模拟了空地数据链的通信。仿真结果表明：在误码率为10^-5时,自适应编码调制方法能够根据信道状况自适应调整编码与调制模式,较大...     

数字式自适应双门限检测装置的研究

 数字式自适应双门限检测装置是一种简化的雷达自动目标检测器;在设计得当时。其性能可与理想非相每检测器比美。本文着重分析组成实际的检测系统时必须加以考虑的两个重要问题。即:1.波门的形式及其宽度的选择。指出,在实际系统里,整个波门间隔内单次检测的虚警概率要比波门内某点的虚警概率大数倍;并指出噪声包络多次超跃第一门限这一事实的存在,最后提出采用“跳跃”式波门以降低系统的总虚警概率。2.检测系统的恒虚警。本文提出一种按平均估值方式工作的恒虚警方法;指出,这种估值方式完全能实现恒虚警控制,而其检测性能,当观察次数 n 大于50时,与最佳的均方根估值方式相比,相差不到1分贝。由于这种估值方式大大简化了数学模型,给工程实践,特别是给小型数字式信号处理装置带来不少设计上和技术实现上的便利。本系统正是采用这种方式实现恒虚警,使系统组成大为简化。与某机载雷达的联试结果表明,数字式自适应双门限检测装置能使原雷达发现目标所需之最低信噪比降低4～6分贝,而且雷达显示画面清晰,没有由噪声引起的杂乱背景。     

恒虚警下复合载波导航信号联合捕获方法

复合载波导航信号(NSCC)作为一种新型的导航增强信号体制,其独特的多载波结构和灵活的体制参数设计,使之具备良好的导航增强效能。同时,以上典型信号特征也使得传统的导航信号同步算法对其不再适用。针对复合载波导航信号结构特征和体制参数设计特点,提出了一种基于多载波架构的恒虚警联合捕获方法。该方法利用复合载波导航信号各子载波信号功率进行自适应检测门限设置,并利用各子载波频点间隔信息进行并行检测,然后根据联合策略做出判决,提升了捕获性能和捕获效率。理论分析及仿真实验均表明,在低信噪比(SNR)情况下,本文所提出的联合捕获方法的捕获性能明显优于单载波捕获算法,并缩短了平均捕获时长。     

扩频系统中伪码防错锁技术研究

针对扩频系统中出现的伪码错锁问题,分析了产生伪码错锁的原因,根据伪码自相关性和互相关性特点,从伪码捕获策略、错锁自动判决策略等角度研究了伪码防错锁措施：选择自相关性和互相关性尽可能好的码;合理设置捕获门限;减小多普勒捕获范围;采用并行伪码捕获方法,并在捕获过程中防止载波错捕现象发生;单独建立验证通道,进行相关值比较判决等。实践表明,采用文中方法可提高正确捕获概率,缩短捕获时间,从硬件设计上有效解决了伪码错锁问题。     

直扩测控系统抗多址能力分析与验证

为了防止多址干扰造成接收机出现误捕和假锁,改善直接序列扩频测控系统抗多址干扰性能,在Gold码特性和扩频接收机性能分析的基础上,结合最大似然原理,对采用扩频体制测控系统的抗干扰能力进行了分析。为契合工程应用,采用仿真遍历结合理论分析的方式,对Gold码的互相关抑制能力理论值进行了工程修正。在分析捕获阶段的抗干扰捕获门限后,还分析了载噪比估计结果在正常锁定和假锁两种状态下的差异,给出了接收机对假锁状态的判决方法和门限。根据分析和仿真的结果,给出了系统设计约束条件和优化的接收机设计流程,作为测控系统和接收机设计的参考。     

OS-CFAR thresholding in decentralized radar systems

In a decentralized detection scheme, several sensors perform a binary (hard) decision and send the resulting data to a fusion center for the final decision. If each local decision has a constant false alarm rate (CFAR), the final decision is ensured to be CFAR. We consider the case that each local decision is a threshold decision, and the threshold is proportional, through a suitable multiplier, to a linear combination of order statistics (OS) from a reference set (a generalization of the concept of OS thresholding). We address the following problem: given the fusion rule and the relevant system parameters, select each threshold multiplier and the coefficients of each linear combination so as to maximize the overall probability of detection for constrained probability of false alarm. By a Lagrangian maximization approach, we obtain a general solution to this problem and closed-form solutions for the AND and OR fusion logics. A performance assessment is carried on, showing a global superiority of the OR fusion rule in terms of detection probability (for operating conditions matching the design assumptions) and of robustness (when these do not match). We also investigate the effect of the hard quantization performed at the local sensors, by comparing the said performance to those achievable by the same fusion rule in the limiting case of no quantization     

末制导雷达虚警概率检验方法

针对只有10^-8～10^-9量级的末制导雷达虚警概率难以检验的问题,研究虚警概率与发现概率、虚警时间的关系,论证了将虚警概率转化为虚警时间的检验方法,利用定时截尾统计检验理论,研究了不同鉴别比、不同试验时间、不同接收故障数时研制方与使用方的风险,提出了新型末制导雷达虚警概率的检验方法,解决了该项指标检验的难题。     

Distributed CFAR detection in homogeneous and nonhomogeneousbackgrounds

The performance of distributed constant false alarm rate (CFAR) detection with data fusion both in homogeneous and nonhomogeneous Gaussian backgrounds is analyzed. The ordered statistics (OS) CFAR detectors are employed as local detectors. With a Swerling type I target model, in the homogeneous background, the global probability of detection for a given fixed global probability of false alarm is maximized by optimizing both the threshold multipliers and the order numbers of the local OS-CFAR detectors. In the nonhomogeneous background with multiple targets or clutter edges, the performance of the detection system is analyzed and its performance is compared with the performance of the distributed cell-averaging (CA) CFAR detection system     

Adaptive False Alarmrm Regulation in Double Threshold Radar Detection

In practical situations the false alarm probability in double threshold radar detection, sometimes known as binary integration with sliding window detection, is dependent on the nonstationarity and azimuthal correlation of the clutter which is present. Control of the false alarm probability can be achieved, to a certain extent, by the adjustment of the second threshold in the detection process. In this study two adaptive control techniques which are based on the statistical characteristics of the data are compared. Comparing the results for a technique based on first-order statistics with one based on second-order statistics, it is shown that the second-order, or correlation sensitive, technique can give a reduction of 30 to 45 percent in the false alarm probability with no corresponding loss in the detection probability. An interesting aspect of the results is the fact that the effects of the size of the sample area and the bias in the correlation estimator are clearly evident.     

分布式接收宽带多目标信号盲检测迭代处理方法

随着软硬件技术的飞速发展和宽带接收机的广泛使用,频谱检测向着高瞬时带宽的方向发展,传统基于信道化处理的频谱检测方法存在搜索速度慢、处理效率低下的问题。文章提出了 1种新的分布式接收宽带多目标信号盲检测迭代处理方法,在无须预先知道信号数目及信号频谱位置的情况下,能够实现特定虚警概率多信号盲检测,具备较高的灵活性和稳健性。首先,在对信号特征进行分析的基础上,通过构造线性模型,将分布式接收多目标信号检测转化为线性模型求解问题进行处理;然后,基于贝叶斯多参数联合求解模型,在对未知参数先验分布进行合理假设的基础上,推导了各未知参数变分分布及信号检测门限的解析表达式,采用变分分布软信息迭代的方式实现多传感器信号、多参数联合估计,并利用每次迭代参数估计结果,对信号检测门限进行更新,通过置零操作实现预设虚警概率下的多信号盲检测;最后,通过仿真实验对所提方法性能进行了分析,并与相关方法进行了对比。仿真结果表明,所提方法能够有效利用多路接收信号信息,实现宽带未知多目标信号的盲检测,有效提升短数据下的算法处理效能,与现有方法相比,在接收单元数目较多以及信噪比较低时具有明显优势。     

A Method for Setting a Test Signal Level Relative to Noise

A method is described for adjusting the leval of an RF test signal generator relative to the noise level at the receiver output. The method compares a detected output to a threshold and counts the number of times noise and signal plus noise cross the threshold in a given number of tries. By setting the threshold at a given false alarm probability for noise alone and then adding the test signal and adjusting its level to give a specified detection probability, the signal-to-noise ratio can be calibrated to an accuracy that depends on the number of samples used to measure the probabilities. The false alarm and detection probabilities are given for best accuracy as well as the rms error in signal-to-noise ratio as a function of the number of samples used.     

Distributed binary integration

A distributed radar detection system that employs binary integration at each local detector is studied. Local decisions are transmitted to the fusion center where they are combined to yield a global decision. The optimum values of the two thresholds at each local processor are determined so as to maximize the detection probability under a given probability of false alarm constraint. Using an important channel model, performance comparisons are made to determine the integration loss     

Decentralized CFAR signal detection

The authors develop the theory of CA-CFAR (cell-averaging constant false-alarm rate) detection using multiple sensors and data fusion, where detection decisions are transmitted from each CA-CFAR detector to the data fusion center. The overall decision is obtained at the data fusion center based on some k out of n fusion rule. For a Swerling target model I embedded in white Gaussian noise of unknown level, the authors obtain the optimum threshold multipliers of the individual detectors. At the data fusion center, they derive an expression for the overall probability of detection while the overall probability of false alarm is maintained at the desired value for the given fusion rules. An example is presented showing numerical results