Two-valued sequences with perfect periodic autocorrelation

Periodic two-valued signals which exhibit two-level autocorrelation can, in many cases, be made to yield an out-of-phase autocorrelation value identically equal to zero. This can be achieved by replacing the two values of the sequence (normally +1 and -1) with the two values +1 and e^iφ, or with +1 and β (β real). Simple expression for φ and β are given, based on the parameters of the difference set to which such signals correspond. Another strategy is to transmit a sequence of +1s and -1s, but of +1s and bs (b real and negative). An expression for b is also obtained     

Difference beam aided target detection in monopulse radar

The classical detection step in a monopulse radar system is based on the sum beam only,the performance of which is not optimal when target is not at the beam center. Target detection aided by the difference beam can improve the performance at this case. However, the existing difference beam aided target detectors have the problem of performance deterioration at the beam center, which has limited their application in real systems. To solve this problem, two detectors are proposed in this paper. Assuming the monopulse ratio is known, a generalized likelihood ratio test(GLRT) detector is derived, which can be used when targeting information on target direction is available. A practical dual-stage detector is proposed for the case that the monopulse ratio is unknown. Simulation results show that performances of the proposed detectors are superior to that of the classical detector.     

Moving target imaging algorithm for SAR data

A digital processing algorithm for fine-resolution imaging of synthetic aperture radar (SAR) moving targets is described. The targets may have any translational and rotational motion components relative to the data collection platform. The algorithm requires the presence of up to three prominent points in the image of the target; the signals from these points provide estimates of the unknown target motion parameters. Phase compensation and data formatting based on these estimates eliminate motion-induced phase errors. This algorithm has been implemented on a VAX computer and used to process both simulated and real SAR data of moving targets. Results obtained using the simulated data are presented     

Square-Wave Correlation Phase Detector with VLF Atmospheric Noise

Correlation phase detectors often include hard limiting of both received and reference signals. The characteristics of such " square-wave" correlation detectors for both Gaussian and impluse noise are derived as functions of both phase and carrier-to-noise ratio. Decoding algorithms and accuracy are discussed.     

The Nonparametric Detection of Signals Embedded in Log-Normal Noise

The nonparametric detection of signals embedded in log-normal noise is discussed. The generalized sign (GS), Mann-Whitney (MW), modified Savage (MS), and modified rank squared (MRS) non-parametic detectors are considered and are compared with the mean and trimmed mean (TM) detectors when envelope detection is used. The detection of both nonfluctuating and Rayleigh fluctuating signals is considered.     

子空间干扰加高斯杂波背景下基于 GLRT的斜对称方向检测器设计

文章研究了背景为子空间干扰加高斯杂波的距离扩展目标方向检测问题。杂波是均值为零协方差矩阵未知但具有斜对称特性的高斯杂波,目标与干扰分别通过具备斜对称特性的目标子空间和干扰子空间描述。针对方向检测问题,利用上述斜对称性,根据广义似然比检验(Generalized Likeli-hood Ratio Test,GLRT)准则的一步与两步设计方法,设计了基于 GLRT的一步法与两步法的距离扩展目标方向检测器。通过理论推导证明了这 2种检测器相对于未知杂波协方差矩阵都具有恒虚警率。对比相同背景下已有检测器,特别是在辅助数据有限的场景下,文章提出的 2个检测器表现出了优越的检测性能。     

基于INS/GNSS紧耦合组合的逐步诱导式欺骗检测算法研究

传统惯性辅助GNSS欺骗信号检测方法对小于纯惯导误差漂移的逐步拉偏不敏感。针对这一问题,提出了一种基于INS/GNSS紧耦合组合的逐步诱导式欺骗信号检测方法。基于短时间内纯惯性导航结果和短时间惯导系统位置误差传播模型,利用惯导提供的位置和速度对伪距和伪距率时间序列进行预测估算,并结合伪距、伪距率实际测量结果,分别构造位置/伪距和速度/伪距率时间序列模型做参数拟合。基于真实信号得到的模型参数都是由惯导系统误差造成的,具有一致性;而基于逐步诱导式欺骗信号得到的模型参数还与欺骗策略的设定、载体飞行轨迹的观测以及干扰源的位置有关,具有不一致性。通过对比模型参数可判别欺骗信号的存在,对于真实信号,采用紧耦合组合导航修正INS输出;对于欺骗信号,继续惯性导航并采取相应措施。最后,根据逐步诱导式欺骗原理进行实验仿真,验证了算法的可行性和有效性。     

Optimal Digital Beam Splitting for Radar Beacon Systems

Beam splitting for a radar beacon system that scans in azimuth is investigated from a theoretical viewpoint. The video output is quantized into two levels corresponding to a detection and no detection. Further, the antenna sensitivity profile is described by sin ?/?. For this system, a digital method of beam splitting that minimizes angular error is developed. Prior information about the probable location of targets can be included. Both Bayesian and minimax approaches are developed. The minimax estimate of the target azimuth is the average of the angles at which beacon signals are detected. The antenna beam can be interpolated by a factor of 10 when the signal power is 3 dB above the noise and without prior azimuth information The interaction of beam splitting and detection is discussed.     

Quickest detection for sequential decentralized decision systems

Quickest detection procedures are techniques used to detect sudden or abrupt changes (also called disorders) in the statistics of a random process. The goal is to determine as soon as possible that the change occurred, while at the same time minimizing the chance of falsely signaling the occurrence of a disorder before the change. In this work the distributed quickest detection problem when the disorder occurs at an unknown time is considered. The distributed local detectors utilize a simple summing device and threshold comparator, with a binary decision at the output. At the fusion center, the optimal maximum likelihood (ML) procedure is analyzed and compared with the more practical Page procedure for quickest detection. It is shown that the two procedures have practically equivalent performance. For the important case of unknown disorder magnitudes, a version of the Hinkley procedure is also examined. Next, a simple method for choosing the thresholds of the local detectors based on an asymptotic performance measure is presented. The problem of selecting the local thresholds usually requires optimizing a constrained set of nonlinear equations; our method admits a separable problem, leading to straightforward calculations. A sensitivity analysis reveals that the resulting threshold settings are optimal for practical purposes. The issue of which sample size to use for the local detectors is investigated, and the tradeoff between decision delay and communication cost is evaluated. For strong signals, it is shown that the relative performance deteriorates as the sample size increases, that is, as the system cost decreases. Surprisingly, for the weak signal case, lowering the system cost (increasing the sample size) does not necessarily result in a degradation of performance     

复杂动态系统实时仿真模型自动生成

提出了一种表示复杂动态系统数学模型的分层结构,探讨了模型变量与参数在实时仿真程序中的引用－赋值关系,提出了一个既包含了模型的数学特征,又包含了模型实时运行所需的信息的实时仿真模型分层结构。在此基础上设计了一个实时仿真模型库及实时仿真模型自动生成系统。     

Adaptive fuzzy terminal sliding mode control for the free-floating space manipulator with free-swinging joint failure

Space manipulator with free-swinging joint failure simultaneously contains kinematic and dynamic coupling relationships, so it belongs to a new underactuated system. To allow the manipulator to carry on tasks, an effective robust underactuated control method for the space manipulator with free-swinging joint failure is studied in this paper. Considering the effect of model uncertainty and joint torque disturbance, a robust underactuated control system based on the Terminal Sliding Mode Controller (TSMC) is designed, but two drawbacks are discussed: (A) Robustness depraves with eliminating chattering. (B) Control parameters are difficult to be determined under unknown uncertainty and disturbance. To improve the TSMC, the adaptive fuzzy controller is introduced to estimate the real effect of unknown uncertainty and disturbance according to deviations of sliding mode and its reaching law. The estimated result is directly compensated into active joints torque. In simulation, the space manipulator with free-swinging joint executes tasks based on the TSMC and the Adaptive Fuzzy Terminal Sliding Mode Controller (AFTSMC) respectively. Same tasks can be finished with smaller joints torque and stronger robustness based on the AFTSMC. Therefore, AFTSMC can serve as an effective robust control method for the space manipulator with free-swinging joint failure under unknown model uncertainty and torque disturbance.     

Detection of Target Maneuver Onset

A classical maneuvering target tracking (MTT) problem (detection of the onset of a target maneuver) is presented in two parts. The first part reviews most traditional maneuver onset detectors and presents results from a comprehensive simulation study and comparison of their performance. Six algorithms for maneuver onset detection are examined: measurement residual chi-square, input estimate chi-square, input estimate significance test, generalized likelihood ratio (GLR), cumulative sum, and marginalized likelihood ratio (MLR) detectors. The second part proposes two novel maneuver onset detectors based on sequential statistical tests. Cumulative sums (CUSUM) type and Shiryayev sequential probability ratio (SSPRT) maneuver onset detectors are developed by using a likelihood marginalization technique to cope with the difficulty that the target maneuver accelerations are unknown. The proposed technique gives explicit solutions for Gaussian-mixture prior distributions, and can be applied to arbitrary prior distributions through Gaussian-mixture approximations. The approach essentially utilizes a~priori information about the maneuver accelerations in typical tracking engagements and thus allows to improve detection performance as compared with traditional maneuver detectors. Simulation results demonstrating the improved capabilities of the proposed onset maneuver detectors are presented.     

The Detection Performance of the Siebert and Dicke-Fix CFAR Radar Detectors

The Siebert and the Dicke-fix CFAR radar detectors, used to maintain a constant false alarm rate (CFAR) in radar receivers under very similar circumstances, are considered. The Siebert detector represents the maximum-likelihood detection procedure for a signal in Gaussian noise of unknown power level, whereas the Dicke-fix makes use of a bandpass limiter to normalize the input and thus ensure a constant false alarm rate. The detection performance of the two detectors is determined and a comparison shows that over a wide range of parameters, the Dicke-fix introduces a loss which is approximately 1 B larger than for the Siebert detector.     

基于软件无线电的机会信号实时盲分离系统

在复杂的电磁环境中,往往存在多种频率交叠的机会信号,为利用机会信号进行定位增加了难度。针对这个问题,提出了一种基于软件无线电的机会信号实时盲分离系统。系统的硬件部分是在FPGA中实现等变自适应盲分离算法的,实现了AD采集后的复数域混合信号的分离。分离后的信号通过USB3.0数据线上传到上位机中进行存储、识别和实时显示。算法的FPGA实现采用流水线架构和浮点运算设计来提高信号的实时处理能力和数据计算精度。实测结果表明,该系统能够实时分离多路复数域混合机会信号。     

Family of constrained signal detectors for hyperspectral imagery

Generalized likelihood ratio tests (GLRTs) are derived for the problem of detecting targets in hyperspectral images. These detectors are derived under the assumptions that the signals from the materials in the image mix linearly and that the noise in the system is Gaussian. It is also assumed that the abundances of the signals from the various materials in a pixel must sum to one. This constraint models the fact that the material abundances in a pixel are just the fraction of the pixel that they occupy. Under these assumptions, detectors are derived which outperform the detectors derived without the sum-to-one constraint.     

超机动飞行的非线性反推自适应控制

为解决对象参数未知时的超机动飞行控制问题,设计了一种非线性反推自适应控制器。针对超机动飞行的非线性模型,适当选取Lyapunov函数和中间虚拟控制信号,同时通过自适应控制律的设计来调节未知参数并得到了最终的控制信号。仿真结果表明,即使模型参数未知,所设计的控制律也能在过失速机动条件下控制飞机跟踪指令飞行,同时保证了闭环系统的稳定性。     

基于神经网络的自适应状态观测器

利用ＢＰ神经网络动态系统对一类非线性时变系统的状态进行了估计。利用神经网络的“学习－遗忘”特性,提出了非线性时变系统的自适应状态观测器,对其结构及特性进行了讨论。仿真结果表明这种自适应状态观测器能跟踪系统参数及状态的变化。     

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。     

三种两样本非参量CFAR检测算法分析

介绍了3种两样本非参量CFAR检测算法的基本工作原理,利用实测未知统计概率分布海杂波数据对它们的检测性能进行了研究,并与参量CA-CFAR检测器进行了对比.研究表明:在强海杂波条件下,GS-CFAR检测器的检测性能最优;在弱海杂波条件下,Savage-CFAR检测器的检测性能最优;相比于CA-CFAR检测器,3种两样本...