A new system identification technique for harmonic decomposition

An extended and unifying system identification technique is presented for a class of systems that include all main signal models that arise in the harmonic decomposition problem. This technique unifies and extends the previously developed system identification techniques which are improvements on the Pisarenko harmonic decomposition (or, its spatial dual, MUSIC) as they arise in arrays of sensors. The advantages of the technique and some of its specializations include having no assumptions of stationarity on the stochastic processes involved. Another contribution of this technique is that it can also be used without any resort to probability theoretic concepts, thus bypassing the approximation of autocorrelations via time averages, yielding the system parameters exactly. This technique can be utilized to determine the dominant modes of vibrations of flexible structures as well. An analogy is established between arrays of sensors for target signal returns and those that can be used for vibrations in flexible structures. This enables the results developed for each one of these problems to be applied to the other     

一类含动态扰动的随机非线性系统的FNN控制

针对一类非仿射且带有动态扰动的纯反馈随机非线性不确定系统,在随机Lyapunov稳定性理论框架下,利用自适应Backstepping方法并结合模糊神经网络( FNN),设计出保证闭环系统所有信号概率意义下有界的自适应控制器。在控制器设计中,对系统动态扰动进行参数化处理,并对系统不确定性进行FNN逼近,以四层神经网络为基础构架,引入模糊逻辑对网络进行推理,其输出权值可自适应调整,设计方法有效地减少了可调参数的数量,数值仿真结果也表明设计方法的有效性。     

An algorithm for detection of moving optical targets

An algorithm is described for detecting moving optical targets against spatially nonstationary Poisson background and noise. The algorithm has applications in optical detection of objects such as meteors, asteroids, and satellites against a stellar background. A maximum-likelihood approach is used which results in reducing interference from stars. It is shown that by choosing a detection threshold to provide a constant false alarm rate, the resulting algorithm is independent of the signal strength of the target. An analysis of this algorithm is presented, showing the probability of detection for several false-alarm rates     

Tracking in Clutter using IMM-IPDA?Based Algorithms

We describe three single-scan probabilistic data association (PDA) based algorithms for tracking manoeuvering targets in clutter. These algorithms are derived by integrating the interacting multiple model (IMM) estimation algorithm with the PDA approximation. Each IMM model a posteriori state estimate probability density function (pdf) is approximated by a single Gaussian pdf. Each algorithm recursively updates the probability of target existence, in the manner of integrated PDA (IPDA). The probability of target existence is a track quality measure, which can be used for false track discrimination. The first algorithm presented, IMM-IPDA, is a single target tracking algorithm. Two multitarget tracking algorithms are also presented. The IMM-JIPDA algorithm calculates a posteriori probabilities of all measurement to track allocations, in the manner of the joint IPDA (JIPDA). The number of measurement to track allocations grows exponentially with the number of shared measurements and the number of tracks which share the measurements. Therefore, IMM-JIPDA can only be used in situations with a small number of crossing targets and low clutter measurement density. The linear multitarget IMM-IPDA (IMM-LMIPDA) is also a multitarget tracking algorithm, which achieves the multitarget capabilities by integrating linear multitarget (LM) method with IMM-IPDA. When updating one track using the LM method, the other tracks modulate the clutter measurement density and are subsequently ignored. In this fashion, LM achieves multitarget capabilities using the number of operations which are linear in the: number of measurements and the number of tracks, and can be used in complex scenarios, with dense clutter and a large number of targets.     

Detection probabilities for correlated Rayleigh fading signals

Both the method of saddlepoint integration and its associated saddlepoint approximation are applied to calculating the probability of detecting correlated Rayleigh-fading signals in Gaussian noise by means of a detector that integrates M samples of the output of a quadratic rectifier. The quadrature components of the signal samples are modeled as an autoregressive moving-average process, and specific results are exhibited for a first-order Markov process. By these methods the fluctuation loss can be computed for much larger values of M and for larger values of the detection probability than previously. Values calculated by the saddlepoint approximation prove to be close enough to the exact values to be useful over a broad range of signal parameters     

Probability of Anomaly Expressions for Random Waveform Registration

Registration by integral-square error correlation of one-dimensional discrete-time waveforms which are treated as random processes with specified autocorrelation functions is considered. An important design parameter for this class of problems is the probability of anomaly (a false dip in the correlation function) because it gives an indication of system immunity to gross registration errors. Explicit expressions for this parameter are not possible, so bounds and appoximations must be derived. Two upper bounds and an approximation for the probability of anomaly are derived here. The use of these expressions is illustrated by an example. The relative utility of these performance indicators is shown for the example by comparison with actual values of the probability of anomaly obtained by computer simulation.     

PHD filters of higher order in target number

The multitarget recursive Bayes nonlinear filter is the theoretically optimal approach to multisensor-multitarget detection, tracking, and identification. For applications in which this filter is appropriate, it is likely to be tractable for only a small number of targets. In earlier papers we derived closed-form equations for an approximation of this filter based on propagation of a first-order multitarget moment called the probability hypothesis density (PHD). In a recent paper, Erdinc, Willett, and Bar-Shalom argued for the need for a PHD-type filter which remains first-order in the states of individual targets, but which is higher-order in target number. In this paper we show that this is indeed possible. We derive a closed-form cardinalized PHD (CPHD) filter, which propagates not only the PHD but also the entire probability distribution on target number.     

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.     

随机集的概率假设密度粒子滤波

多目标跟踪问题中,当目标数已知时,可以用概率数据互联(PDA)或联合概率数据互联(JPDA)算法。而当目标数未知或随时间变化时,需要对不同目标数的跟踪进行比较。可以把目标集看作随机集进行讨论,目标数N是随机变量。随机集的跟踪通过有限集统计(FISST)理论来完成。文中讨论了用粒子滤波实现跟踪随机集的方法。实验表明,在杂波环境下,粒子滤波可以稳健跟踪目标状态和目标数。     

多介质数据库管理系统NAIMDB——模型与方法

采用面向对象的方法构造数据模型,把命名的线性表定义为简单对象。用表可以嵌套的性质构造复杂的多介质对象。对象分为3个层次,即原子对象,简单对象和复杂对象。简单对象在数据库中有实际的物理存贮;复杂对象在数据库中只存贮它的结构描述,即相应嵌套表的结构描述。     

Approximate Evaluation of Detection Probabilities in Radar and Optical Communications

Cumulative probability distributions such as occur in radar detection problems are approximated by a new version of the saddlepoint method of evaluating the inverse Laplace transform of the moment-generating function. When the number of radar pulses integrated is large, the approximation of lowest order yields good accuracy in the tails of the distributions, yet requires much less computation than standard recursive methods. Greater accuracy can be achieved upon summing the residual series by converting it to a continued fraction. The method is applied to evaluating the error-function integral and the Mth-order Q function, and to approximating the inverse of the chi-squared distribution. Cumulative distributions of discrete random variables, needed for determining error probabilities in optical communication receivers that involve counting photoelectrons, can be approximated by a simple modification of the method, which is here applied to the Laguerre distribution.     

Laser Interferometer for High Sensitivity Measurements on Transient Phase Objects

A He-Ne laser beam is sent through a common path differential interferometer and the interference signal is detected by a p-i-n photodiode. Weak phase objects can be examined because optical path changes can be resolved to 0.1 ? with a time resolution of about 20 ns. Examples for different gas-dynamic investigations show good results and demonstrate the wide field of application for this type of laser interferometer.     

Multitarget Bayes filtering via first-order multitarget moments

The theoretically optimal approach to multisensor-multitarget detection, tracking, and identification is a suitable generalization of the recursive Bayes nonlinear filter. Even in single-target problems, this optimal filter is so computationally challenging that it must usually be approximated. Consequently, multitarget Bayes filtering will never be of practical interest without the development of drastic but principled approximation strategies. In single-target problems, the computationally fastest approximate filtering approach is the constant-gain Kalman filter. This filter propagates a first-order statistical moment - the posterior expectation - in the place of the posterior distribution. The purpose of this paper is to propose an analogous strategy for multitarget systems: propagation of a first-order statistical moment of the multitarget posterior. This moment, the probability hypothesis density (PHD), is the function whose integral in any region of state space is the expected number of targets in that region. We derive recursive Bayes filter equations for the PHD that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets. We also show that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.     

基于灵敏度的可靠性优化解耦方法

针对航空结构可靠性优化设计问题,提出了一种基于灵敏度的可靠性优化(RBO)解耦方法。首先将高效求解的可靠性灵敏度用于失效概率函数(FPF)的快速构建,其优点在于仅需要一次可靠性分析即可得到失效概率函数的局部近似,克服了常规求解方法中需要多次可靠性分析的缺点;然后将得出的FPF近似代入RBO模型中,将原问题解耦成确定性优化子问题,可用常规优化方法来求解。另外,采用了序列近似优化策略来保证可靠性优化解的正确性。文中给出了复合材料梁和机翼三盒段结构的优化求解算例来说明本文方法的可行性和正确性。     

Effectiveness of the likelihood function in logic-based trackformation

A logic-based track formation procedure was presented by C.B. Chang et al. (1984). In addition to the conventional gating logic, it utilized the negative log-likelihood function (goodness of fit or sum of residuals) to further reduce the false track acceptance probability. An analytical technique for the evaluation of the effectiveness of this reduction is presented. The exact solution in closed form and a Gaussian approximation are given and compared. It is shown that the goodness of fit provides an additional reduction of the false track acceptance probability by a factor of two to three     

Reachable set estimation for spacecraft relative motion based on bang-bang principle

For spacecraft formation flight, the information of relative motion reachable set is very important, which can be used to predict the operating boundary of adjacent spacecraft and thus to ensure the safety of spacecraft operation. In this paper, we aim at developing a numerical method to approximate the reachable set for spacecraft relative motion. In particular, we focus on the quality of the approximation and the computational cost. Based on the bang-bang control principle, a polyhedral approximation algorithm is proposed to compute the reachable set of a relative motion spacecraft system. An inner approximation and an outer approximation of the reachable set for the system can be obtained. We prove that the approximation quality measured in Hausdorff distance can be guaranteed. The method is easy to implement and has low computational cost. Finally, the effectiveness of the algorithm is demonstrated by experimental simulation.     

多目标跟踪的概率假设密度粒子滤波

在多目标跟踪中,当目标数很大时,目标状态的联合分布的计算量会非常大。如果目标独立运动,可用各目标分别滤波来代替,但这要求考虑数据互联问题。文章介绍一种可以解决计算量问题的方法,只需计算联合分布的一阶矩——概率假设密度(PHD),PHD在任意区域S上的积分是S内目标数的期望值。因未记录目标身份,避免了数据互联问题。仿真中,传感器为被动雷达,目标观测值为距离、角度及速度时,对上述的PHD滤波进行了粒子实现,并对观测值是否相关的不同情况进行比较。PHD粒子滤波应用在非线性模型的多目标跟踪,实验结果表明,滤波可以稳健跟踪目标数为变数的情况,得到了接近真实情况的结果。     

ESM对2D雷达引导性能分析

 对于由 ESM和雷达组成的多传感器系统,分析和推导了用 ESM对 2 D雷达成功引导的概率解析表示式,为求解成功引导概率提供了依据;研究了 ESM对 2 D雷达成功引导概率随一些特征参数的变化规律,并得出了 4个特性;在多种情况下进行了成功引导概率的数值计算,验证了成功引导概率的一些变化规律,并得出了一些有意义的结论,从而对研究和设计同地配置的 ESM对雷达引导系统具有一定的参考价值。     

Explanation of the “May Swarm” signature in the LDEF IDE impact data

The Interplanetary Dust Experiment (IDE) carried by the Long Duration Exposure Facility (LDEF) satellite detected a large number of small particle impacts. The dataset shows impact events recurring for a number of LDEF orbits. Such events show signatures of particle clouds that intersect the orbit of LDEF. In an effort to identify the impact of particles released during solid rocket motor burns, a new look at the IDE impact records was taken. The generation of dust particles due to solid rocket burns and a close encounter analysis of the released objects with LDEF's orbital path was simulated. An agreement of a specific IDE impact feature occurring in May 1984 with the firing of the apogee kick motors of the satellites WESTAR 6 and PALAPA B2 could be derived.