Distributed detection by a large team of sensors in tandem

The problem of decentralized binary hypothesis testing by a team consisting of N decision makers (DMs) in tandem is considered. Each DM receives an observation and transmits a binary message to its successor; the last DM has to decide which hypothesis is true. The necessary and sufficient condition for the probability of error to go asymptotically to zero as N→∞ is that the log-likelihood ratio of the observation of each DM be unbounded. The result is generalized for multiple hypotheses and multiple messages. An easily implementable suboptimal decision scheme is also considered; in this case, the necessary and sufficient condition for the probability of error to asymptotically go to zero is that the log-likelihood ratio of the observation of each DM be unbounded from both above and below. The tradeoff between the complexity of the decision rules and their performance is examined, and numerical results are presented, in order to demonstrate that the performance of both decision schemes is comparable     

柔性决策

提出了柔性决策的思想,并对决策科学的发展进行了回顾。为解决柔性决策问题,提出了极大－极小方法、人机交互方法和集包含方法。     

Optimal Array Processor Performance Trade-offs under Directional Uncertainty

Detection performance in terms of the receiver operating characteristic (ROC) curve is obtained for three specific problems involving either signal or noise source location uncertainty. The array processors are optimum in the sense that they form the likelihood ratio of the outputs of the individual array elements. Performance trade-offs due to signal uncertainty, signal and noise source location uncertainty, and array size are presented.     

Performance of Likelihood Ratio Processors

Summarized by its ROC curve, the performance of a Bayes optimal detector is a function of two joint a priori probability density functions on the uncertain parameters involved. An investigation is made to determine at what point in the generation of an ROC curve for a given pair of priors sufficient information is retained for the calculation of a new ROC based on a different pair of priors.     

Optimum multisensor fusion of correlated local decisions

A distributed detection system consisting of a number of local detectors and a fusion center is considered. Each detector makes a decision for the underlying binary hypothesis testing problem based on its own observation and transmits its decision to the fusion center where the global decision is derived. The local decision rules are assumed to be given, but the local decisions are correlated. The correlation is generally characterized by a finite number of conditional probabilities. The optimum decision fusion rule in the Neyman-Pearson sense is derived and analyzed. The performance of the distributed detection system versus the degree of correlation between the local decisions is analyzed for a correlation structure that can be indexed by a single parameter. System performance as well as the performance advantage of using a larger number of local detectors degrade as the degree of correlation between local decisions increases     

Asynchronous distributed detection

Binary parallel distributed-detection architectures employ a bank of local detectors to observe a common volume of surveillance, and form binary local decisions about the existence or nonexistence of a target in that volume. The local decisions are transmitted to a central detector, the data fusion center (DEC), which integrates them to a global target or no target decision. Most studies of distributed-detection systems assume that the local detectors are synchronized. In practice local decisions are made asynchronously and the DFC has to update its global decision continually. In this study the number of local decisions observed by the central detector within any observation period is Poisson distributed. An optimal fusion rule is developed and the sufficient statistic is shown to be a weighted sum of the local decisions collected by the DFC within the observation interval. The weights are functions of the individual local detector performance probabilities (i.e., probabilities of false alarm and detection). In this respect the decision rule is similar to the one developed by Chair and Varshney for the synchronized system. Unlike the Chair-Varshney rule, however, the DFC's decision threshold in the asynchronous system is time varying. Exact expressions and asymptotic approximations are developed for the detection performance with the optimal rule. These expressions allow performance prediction and assessment of tradeoffs in realistic decision fusion architectures which operate over modern communication networks     

Bayesian Design of Decision Rules for Failure Detection

The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.     

基于深度强化学习的多无人机协同进攻作战智能规划

无人机依靠作战效费比高、灵活自主等优势逐步替代了有生力量作战,多无人机协同作战任务规划成为热点研究问题。针对传统任务规划采用的智能优化算法存在的依赖静态、低维的简单场景、机上计算较慢等不足,提出一种基于深度强化学习（DRL）的端到端的多无人机协同进攻智能规划方法。将压制敌防空作战（SEAD）任务规划过程建模为马尔科夫决策过程,建立基于近端策略优化（PPO）算法的SEAD 智能规划模型,通过两组实验验证智能规划模型的有效性和鲁棒性。结果表明：基于DRL 的智能规划方法可以实现快速、精细规划,适应未知、连续高维的环境态势,智能规划模型具有战术协同规划能力。     

求解含调整时间排序问题的混合遗传算法

利用仿真工具将启发式方法与遗传算法相结合,提出了一种求解Job Shop排序问题的混合算法框架,利用启发式规则引导遗传搜索过程,以提高遗传算法的求解效率。在求解过程中,遗传算法仅对每台机器的第1道工序搜索寻优,通过仿真过程安排后续工序,在仿真过程中,利用启发式规则确定工件的加工优先级。在以上框架基础上,针对含调整时间的作业排序问题建立了一种混合算法GA-SPTS,通过与已有算法的比较表明,该算法对这类问题具有很好的求解性能。     

Polarization diversity detection in compound-Gaussian clutter

We present the problem of polarization diversity detection in compound-Gaussian clutter with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance structure of the cell under test, is available. Due to the lack of a uniformly most powerful (UMP) detector we resort to a design procedure based upon the Rao and the Wald tests. Specifically we first derive the Rao and the Wald tests assuming that the covariance matrix is known, and then we substitute into the derived decision rules a suitable estimate of the clutter covariance. Interestingly, the newly proposed detectors share the constant false alarm rate (CFAR) property with respect to the texture statistical characterization. Moreover simulation results have shown that the Wald test based detector ensures a performance level higher than the Rao test. We have also conducted a further performance analysis, in the presence of real clutter data and in comparison with the previously proposed generalized likelihood ratio test (GLRT) based receivers, which highlights that, in general, the Wald test receiver outperforms its counterparts. Finally, since the newly proposed decision rules as well as the previously designed GLRTs do not ensure the CFAR property with respect to the clutter covariance matrix, we have developed a sensitivity analysis on the probability of false alarm (P/sub fa/), based on simulated clutter with covariance matrix estimated from real radar data. The results have shown that (P/sub fa/) is only slightly affected by variations in the clutter correlation properties and hence the CFARness is substantially achieved.     

Experimental study of single-row chevron-jet impingement heat transfer on concave surfaces with different curvatures

To address the curvature effect on single-row chevron-nozzle jet impingement heat transfer on concave surface, a series of experiments are conducted in the present investigation.Four concave surfaces including one semi-cylindrical concave surface and three parabolic concave surfaces with different width-to-depth ratios are tested under three typical Reynolds numbers(Re = 5000,10000 and 15000) and several dimensionless nozzle-to-surface distances ranging from 1 to 8.The results show that the concave curvature has a clear impact on chevron-nozzle jet impingement heat transfer, tightly dependent on jet Reynolds number and impinging distance.In general, the semicylindrical concave surface produces the highest longitudinally-averaged Nusselt number at the leading line of concave surface.Under a low jet Reynolds number, the parabolic concave surface with a highly curved curvature produces higher longitudinally-averaged Nusselt number at the leading line and more uniform longitudinally-averaged Nusselt number distribution along the curvilinear direction.However, the longitudinally-averaged Nusselt number at the leading line of concave surface is the lowest for the highly curved surface under a high jet Reynolds number and large impinging distance.In comparison with the round-nozzle, chevron nozzle plays a more significant role on improving jet impingement heat transfer at small impinging distances.     

证据推理冲突问题研究

证据推理是一种重要的人工智能方法,广泛应用于数据融合、数据挖掘和智能决策。但 Dempster组合规则对于高冲突情况的处理不是十分合理的。首先研究了几种组合规则的改进方法和造成其缺陷的机理,给出一类组合规则的改进方法,基于有无先验给出两类算法。仿真结果表明新的证据推理组合规则在处理冲突方面的性能得到了明显的改进。     

On Optimal Minimax Jamming and Detection of Radar Signals

A game between an intelligent jammer J and decision maker DM is considered. DM seeks to detect a coherent slowly fading narrowband signal under a Neyman-Pearson criterion. His observations are corrupted with additive narrowband noise, the source of which is J's jamming with a power constraint, but otherwise almost arbitrary statistics. DM knows J's action but the converse is not true. When the number of samples increases asymptotically, a minimax solution for the game exists where the jamming is Gaussian, independent of the desired signal amplitude level and probability distribution. The same result also holds for detection of a nonrandom baseband signal.     

A non-contact lie detector using radar vital signs monitor (RVSM)technology

Traditional lie detector testing requires the subject to be physically attached to a variety of sensors. This is impractical for scenarios such as checkpoints where a large number of individuals are entering at a high rate, necessitating the employment of other methods. Currently, checkpoint officers must make a quick decision to determine if an individual is being deceptive, and if, in turn, they should be searched. The remote detection of deception (RDD) concept uses a non-contact sensor to obtain physiological information that can be used to aid the checkpoint officer's decision. Such a device must be able to sense physiological signals from the body that may indicate deception in an unobtrusive and non-contact manner     

冲击凹柱面靶板的流场结构实验

采用烟线法研究了冲击凹柱面靶板的流场结构。研究中改变冲击雷诺数Re,冲击距-冲击孔直径比H/d以及冲击靶面相对曲率d/D等参数,利用数码摄像机拍摄流场结构随这些参数的变化规律。研究结果表明:上述参数均影响了冲击凹柱面靶板的流场结构,而且影响规律表现出较强的关联性。实验中,随冲击雷诺数Re的增加或冲击距-冲击孔直径比H/d的减小,在冲击滞止区域两侧形成的稳定旋流结构与冲击靶板分离处的圆心角增大,分离推迟;同时在实验中发现冲击靶板的曲率半径和冲击导管直径之间存在一定的匹配关系(d/D)使流体沿壁面运动的距离最长。     

结合跳点引导的无人机随机搜索避撞决策方法

针对无人机在城市空域环境和密集交通流下的避撞决策问题，提出马尔科夫决策过程（MDP）和蒙特卡洛树搜索（MCTS）算法对该问题进行建模求解。蒙特卡洛树搜索算法在求解过程中为保证实时性而使其搜索深度受限，容易陷入局部最优，导致在含有静态障碍的场景中无法实现避撞的同时保证全局航迹最优。因此结合跳点搜索算法在全局规划上的优势，建立离散路径点引导无人机并改进奖励函数来权衡飞行路线，在进行动态避撞的同时实现对静态障碍的全局避撞。经过多个实验场景仿真，其结果表明改进后的算法均能在不同场景中获得更好的性能表现。特别是在凹形限飞区空域仿真模型中，改进后的算法相对于原始的蒙特卡洛树搜索算法，其冲突概率降低了36%并且飞行时间缩短47.8%。     

Decision fusion rules in multi-hop wireless sensor networks

The decision fusion problem for a wireless sensor network (WSN) operating in a fading environment is considered. In particular, we develop channel-aware decision fusion rules for resource-constrained WSNs where binary decisions from local sensors may need to be relayed through multi-hop transmission in order to reach a fusion center. Each relay node employs a binary relay scheme whereby the relay output is inferred from the channel impaired observation received from its source node. This estimated binary decision is subsequently transmitted to the next node until it reaches the fusion center. Under a flat fading channel model, we derive the optimum fusion rules at the fusion center for two cases. In the first case, we assume that the fusion center has knowledge of the fading channel gains at all hops. In the second case, we assume a Rayleigh fading model, and derive fusion rules utilizing only the fading channel statistics. We show that likelihood ratio (LR) based optimum decision fusion statistics for both cases reduce to respective simple linear test statistics in the low channel signal-to-noise ratio (SNR) regime. These suboptimum detectors are easy to implement and require little a priori information. Performance evaluation, including a study of the robustness of the fusion statistics with respect to unknown system parameters, is conducted through simulations.     

A unified approach to the design of decentralized detection systems

A unified approach to the design of decentralized detection networks with arbitrary topologies is proposed and analyzed. In this approach, a decentralized detection system of arbitrary topology is represented by a communication matrix that specifies the interconnection structure of the detection network. This matrix is used to derive the general decision rule using the person-by-person-optimal (PBPO) solution methodology. It is shown that the PBPO decision rule is a likelihood ratio test for statistically independent observations. The threshold of the test is shown to be a function of the decision input vector of the detector under consideration. This unified approach is used to obtain the PBPO decision rules of decentralized detection systems with various topologies. Various results in the literature are verified. In addition, the PBPO decision rules for a decentralized detection system with peer communication are presented. Numerical examples are presented for illustration     

Analysis of single-platform passive emitter location with terraindata

Frequency measurements made at a moving platform can be used to locate an emitter. An error ellipsoid analysis is used to compare the performance under three levels of a priori information on the emitter's altitude: (1) no knowledge, (2) terrain data, and (3) complete knowledge of the emitter's altitude. The analysis is performed for two simple platform paths that provide frequency measurements that are approximately time reversed versions of one another. When no a priori knowledge is available there is little difference between the performance when the platform maneuvers on a concave circular path or on a convex circular path and the performance depends very Little on the platform altitude. However, when some a priori altitude information is available the performance is markedly different on the two paths and is highly dependent on the platform altitude. Thus, this analysis provides the unexpected result that for seemingly similar platform paths, the performance can vary markedly when the emitter altitude is assumed known. Also, an interesting result is that for some cases it is possible to achieve better x-y accuracy when using terrain data than when the emitter's z location is known, because the terrain data provides terrain slope information. These cases are characterized in terms of the terrain slope at the emitter