Airborne Target State Estimator

A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link in the integrated Flight/Fire Control (IFFC) system. By adopting the Cartesian coordinates and pseudomeasurements ,the result ed TSE has it s advantages in computation.In addition, by employing accurate range and range-rate redundant filter, the range direction estimations obtained in Cartesian filter are greatly improved. The TSE shows its satisfaCtory performance in the Monte Carlo simulation of the IFFC system.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Target reliability index for serviceability limit state of single piles

The objective is to develop an approach for the determination of the target reliability index for serviceability limit state(SLS) of single piles. This contributes to conducting the SLS reliability-based design(RBD) of piles. Based on a two-parameter,hyperbolic curve-fitting equation describing the load-settlement relation of piles, the SLS model factor is defined. Then, taking into account the uncertainties of load-settlement model, load and bearing capacity of piles, the formula for computing the SLS reliability index(βsls) is obtained using the mean value first order second moment(MVFOSM) method. Meanwhile, the limit state function for conducting the SLS reliability analysis by the Monte Carlo simulation(MCS) method is established. These two methods are finally applied to determine the SLS target reliability index. Herein, the limiting tolerable settlement(slt) is treated as a random variable. For illustration, four load test databases from South Africa are compiled again to conduct reliability analysis and present the recommended target reliability indices. The results indicate that the MVFOSM method overestimates βsls compared to that computed by the MCS method. Besides, both factor of safety(FS) and slt are key factors influencing βsls, so the combination of FS and βsls is welcome to be used for the SLS reliability analysis of piles when slt is determined. For smaller slt, pile types and soils conditions have significant influence on the SLS target reliability indices; for larger slt, slt is the major factor having influence on the SLS target reliability indices. This proves that slt is the most key parameter for the determination of the SLS target reliability index.

Optimal observation configuration of UAVs based on angle and range measurements and cooperative target tracking in three-dimensional space

This article investigates the optimal observation configuration of unmanned aerial vehicles(UAVs) based on angle and range measurements, and generalizes predecessors' researches in two dimensions into three dimensions. The relative geometry of the UAVs-target will significantly affect the state estimation performance of the target, the cost function based on the Fisher information matrix(FIM) is used to derive the FIM determinant of UAVs' observation in three-dimensional space, and the optimal observation geometric configuration that maximizes the determinant of the FIM is obtained. It is shown that the optimal observation configuration of the UAVs-target is usually not unique, and the optimal observation configuration is proved for two UAVs and three UAVs in three-dimension. The long-range over-the-horizon target tracking is simulated and analyzed based on the analysis of optimal observation configuration for two UAVs. The simulation results show that the theoretical analysis and control algorithm can effectively improve the positioning accuracy of the target. It can provide a helpful reference for the design of over-the-horizon target localization based on UAVs.

A Method to Obtain the Moving Speed of Uncooperative Target Based on Only Two Measurements

The existing research results show that a fixed single station must conduct three consecutive frequency shift measurements and obtain the target’s moving speed by constructing two frequency difference equations. This article proposes a new method that requires only two consecutive measurements. While using the azimuth measurement to obtain the angular difference between two radial distances, it also conducts two consecutive Doppler frequency shift measurements at the same target azimuth. On the basis of this measurement, a frequency difference equation is first constructed and solved jointly with the Doppler frequency shift equation. By eliminating the velocity variable and using the measured angular difference to obtain the target’s lead angle, the target’s velocity can be solved by using the Doppler frequency shift equation again. The new method avoids the condition that the target must move equidistantly, which not only provides an achievable method for engineering applications but also lays a good foundation for further exploring the use of steady-state signals to achieve passive positioning.

Application of Road Information in Ground Moving Target Tracking

A new algorithm is developed to achieve accurate state estimation in ground moving target tracking by means of using road information. It is an adaptive variable structure interacting multiple model estimator with dynamic models modification （DMM VS-IMM for short）. Firstly, road information is employed to modify the target dynamic models used by filter, including modification of state transition matrix and process noise. Secondly, road information is applied to update the model set of a VS-IMM estimator. Predicted state estimation and road information are used to locate the target in the road network on which the model set is updated and finally IMM filtering is implemented. As compared with traditional methods, the accuracy of state estimation is improved for target moving not only on a single road, but also through an intersection. Monte Carlo simulation demonstrates the efficiency and robustness of the proposed algorithm with moderate computational loads.

Nonlocal multi-target controlled controlled gate using Greenberger–Horne–Zeilinger channel and qutrit catalysis

We present a scheme for implementing locally a nonlocal N-target controlled–controlled gate with unit probability of success by harnessing two（N＋1）-qubit Greenberger–Horne–Zeilinger（GHZ） states as quantum channel and N qutrits as catalyser. The quantum network that implements this nonlocal（N＋2）-body gate is built entirely of local single-body and two-body gates, and has only（3N＋2） two-body gates. This result suggests that both the computational depth of quantum network and the quantum resources required to perform this nonlocal gate might be significantly reduced. This scheme can be generalized straightforwardly to implement a nonlocal N-target and M-control qubits gate.

甲状腺功能亢进症的态靶辨治策略

借鉴现代甲状腺功能亢进症的生理病理等医学认识,结合甲状腺功能亢进症的临床诊疗特征等,基于传统中医思维,以态靶辨治理论为指导,重新认识甲状腺功能亢进症,构建现代中医诊疗体系。根据甲亢(瘿气)的疾病发展演变态势,可概括为郁、火、虚三个阶段,治疗以态靶结合,态下分证,随病机变化施以疏肝散郁,或清泄火热,或益气养阴等,重视靶方靶药与现代药理研究的结合应用,精准用药。

基于状态可观测性和多模态数据PF的移动目标跟踪

为了实现对移动目标的跟踪,提出了一种新颖的基于目标状态可观测性和多模态数据粒子滤波(Particle Filter,PF)的跟踪方案。通过部署在目标移动区域中的传感器获得跟踪目标的距离和到达方向测量值,对接收到的数据进行预处理来计算PF的观测值,以形成一个临时距离图像。通过利用状态更新函数和形成的候选图像模板确定目标状态向量;在PF器中加入额外的加权阶段,使得PF器可自适应地同步多模态数据流,以实现鲁棒的目标跟踪。仿真实验结果验证了所提方案能够有效地跟踪移动目标。

Uncertain IMM Estimator for Multi-Sensor Target Tracking

Interacting Multiple Model (IMM) estimator can provide better performance of target tracking than mono model Kalman filter. In multi-sensor system ordinarily, availability of measurement from different sensors is stochastic, and it is difficult to construct uniform global observation vector and observation matrix appropri-ately in existing method. An IMM estimator for uncertain measurement is presented. By the method invalid measurement is regarded as outlier, and approximation is reconstructed by feedback of system state estima-tion of fusion center. Then nominally generalized certain measurement can be obtained by substituting re-constructed one for invalid one. The generalized certain measurement can be centralized to construct global measurement and provided to IMM estimator, and existing multi-sensor IMM estimation method is general-ized to uncertain environment. Theoretical analysis and simulation results show the effectiveness of the method.

Using approximate dynamic programming for multi-ESM scheduling to track ground moving targets

This paper researches the adaptive scheduling problem of multiple electronic support measures(multi-ESM) in a ground moving radar targets tracking application. It is a sequential decision-making problem in uncertain environment. For adaptive selection of appropriate ESMs, we generalize an approximate dynamic programming(ADP) framework to the dynamic case. We define the environment model and agent model, respectively. To handle the partially observable challenge, we apply the unsented Kalman filter(UKF) algorithm for belief state estimation. To reduce the computational burden, a simulation-based approach rollout with a redesigned base policy is proposed to approximate the long-term cumulative reward. Meanwhile, Monte Carlo sampling is combined into the rollout to estimate the expectation of the rewards. The experiments indicate that our method outperforms other strategies due to its better performance in larger-scale problems.

基于态靶辨治理论诊疗慢性阻塞性肺疾病

慢性阻塞性肺疾病是常见的呼吸系统气道慢性病,严重影响患者的生活质量。传统的中医辨证论治体系存在对疾病的发生发展规律认识不足,对检查化验指标改善欠佳的问题。仝小林院士经过多年的临床实践,提出“态靶辨治”的现代中医诊疗体系,并将其用于慢性疾病临床诊疗过程中。基于此,以“态靶辨治”理论为指导,结合临床经验与现代药理学研究成果,将慢性阻塞性肺疾病发病过程分为“痰、阻、瘀、衰”四态(四期),每态下进行分证,并结合治疗靶点,确定各阶段相应的靶方靶药,构建慢性阻塞性肺疾病的态靶辨治体系,为提高该病的中医治疗效果提供新的路径。

Al/Ta-Nb合金阻抗匹配靶的制备工艺研究

为了获得钽铌合金(Ta-Nb)材料在高压下的状态方程数据,制备了用于激光状态方程实验研究的铝/钽铌合金(Al/Ta-Nb)阻抗匹配靶。研究了Ta-Nb合金箔的精密轧制与飞秒激光切割工艺,获得了厚度13μm,宽度400μm的Ta-Nb合金台阶样品。使用聚乙烯醇(PVA)水溶胶将Ta-Nb合金台阶与铝(Al)标准材料进行复合装配。利用白光干涉仪、电子密度计等仪器对阻抗匹配靶的表面形貌、台阶厚度、样品密度等靶参数进行精密测量,结果表明研制的Al/Ta-Nb合金阻抗匹配靶能够满足激光状态方程物理实验需求。

肺癌态靶辨治体系的构建

“态靶辨证”是仝小林院士提出的中医临床辨治新方略,其内涵是在现代诊断基础上强调疾病的“分类-分期-分证”及“宏观调态与微观打靶相结合”的辨治模式。肺癌态靶辨治体系的构建,以态靶辨证理论为指导,从肺癌发生发展的时序性演进轨迹和宏微观变化特征出发,将肺癌发病过程分为“郁、痰、瘀、损”四态,并态下分证,结合临床经验与现代药理学研究成果,确定相应的靶方靶药,态靶同调,为肺癌的中医临床诊疗提供新思路。

针对性干预对肺癌化疗伴癌因性疲乏患者的影响

目的:探讨针对性干预对肺癌化疗伴癌因性疲乏患者的影响。方法:选择2021年3月—2023年3月江西省肿瘤医院胸内一病区接收的肺癌化疗伴癌因性疲乏患者80例作为研究对象,按随机数字表法将其分为对照组与观察组,各40例。对照组给予常规干预措施,观察组在对照组的基础上给予针对性干预,比较两组癌因性疲乏程度、心理状态、社会适应性、希望水平、睡眠质量、生存质量。结果:干预后观察组癌因性疲乏程度轻于对照组,差异有统计学意义(P<0.05)。干预后观察组焦虑自评量表(SAS)、抑郁自评量表(SDS)评分均低于对照组,差异均有统计学意义(P<0.05)。干预后观察组社会适应性量表的心理弹性、心理能量、人际适应性、控制倾向维度评分均高于对照组,差异均有统计学意义(P<0.05)。干预后,观察组希望水平、生存质量评分均高于对照组,睡眠质量评分低于对照组,差异均有统计学意义(P<0.05)。结论:对肺癌化疗伴癌因性疲乏患者实施针对性干预可进一步疏解负面情绪,改善癌因性疲乏症状,并增强患者的社会适应性,提高希望水平,恢复良好的睡眠质量和生存质量。

Application of Union of Fuzzy Automata on Target Tracking

For better applications of fuzzy automata on target tracking, this paper presents an associated method of fuzzy automata by discussing the relation between fuzzy automata. The equivalence is mainly discussed regarding these fuzzy automata. The target tracking based on the associated method of fuzzy automata is given. Moreover, the simulation result shows that the associated method is better than single fuzzy automaton relatively. The development of these researches in this paper in turn can quicken the applications of the fuzzy automata in various fields.

基于态靶辨治代谢疾病智能辅助诊疗系统的研究与设计

目的:基于“态靶辨证”中医诊疗思维,利用人工智能技术为代谢病中医辅助诊疗提供智能化支持。方法:通过自然语言处理技术,对医学文献和专家经验进行信息抽取和实体识别,构建包含疾病状态、治疗靶点及相关辨证规则的术语知识库。在此基础上,利用图数据库和深度学习算法,构建态靶辨证知识图谱,表达不同疾病状态与治疗靶点之间的复杂关系。结果:通过模型训练和知识推理,结合病例的具体症状和体质,推荐相应的中医治疗方案,提高了代谢病辅助诊疗的准确性和效率。结论:本研究为中医辨证施治提供了新的方法和思路,不断迭代优化算法,拓展临床应用,推动中医药辅助诊疗的发展和完善,为中医药传承创新奠定良好的技术基础。

从“态靶结合”探讨中风病的辨治策略

“态靶结合”辨治是将中医传统宏观理念与现代研究的微观标靶相结合的辨治模式,为中风病的临床治疗提供了新思路。中风病分为缺血中风和出血中风两大类型,根据病程发展的先后顺序,缺血中风可分为“郁”-“闭”-“虚”三个阶段,出血中风可分为“亢”-“火”-“虚”三个阶段。在明确各阶段的“态”后可结合临床证候、中医证型、药理学研究成果找到“态靶同调”的方药,实现精准化治疗。

Passive target tracking using marginalized particle filter

A marginalized particle filtering （MPF） approach is proposed for target tracking under the background of passive measurement. Essentially, the MPF is a combination of particle filtering technique and Kalman filter. By making full use of marginalization, the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter, and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter. Simulation studies are performed on an illustrative example, and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation. Real data test results also validate the effectiveness of the presented method.

自适应观测识别的多目标分类跟踪算法

在现实多目标跟踪任务中,概率假设密度滤波器性能受杂波干扰明显,较大程度地制约目标跟踪的精度和效率。针对这一问题,在概率假设密度滤波框架下提出一种自适应观测识别的多目标分类跟踪算法。首先,依据各个目标的重要程度,自适应观测识别策略采用自适应门限从各时间步观测中识别源于已存在目标的观测、新出现目标的观测和杂波。然后,目标分类更新策略使用不同目标观测分类更新已存在目标的预测强度和新出现目标的先验强度,消弱了不同类目标观测混用对目标后验强度精度的干扰。仿真目标场景验证了该算法的有效性和稳健性。