Performance limits of track-to-track fusion versus centralized estimation: theory and application [sensor fusion]

Track-to-track fusion is an important part in distributed multisensor-multitarget tracking. The centralized and distributed tracking configurations were studied in (H.Chen et al., Proc. of SPIE Conf. on Signal and Data Processing of Small Targets, vol. 4048, 2000) using simulated air-to-air scenarios, and in (K.C. Chang, et al, IEEE Transact. on Aerospace and Electronic Systems, vol. 33, no. 4, pp. 1271-1276, 1997) with analytical results based on /spl alpha/-/spl beta/ filters. The current work generalizes the results in the latter to the cases with more than 2 sensors. As the number of sensors increases, the performance of the distributed tracker is shown to degrade compared with the centralized estimation even when the optimal track-to-track fusion is used. An approximate track-to-track fusion is presented and compared with the optimal track-to-track fusion with performance curves for various numbers of sensors. These performance curves can be used in designing a fusion system where certain trade-offs need to be considered. Finally, these results are compared with simulation results for a realistic air-to-air encounter scenario.     

基于Jerk输入估计的MCS模型及非线性跟踪算法

针对强机动目标跟踪问题,基于当前统计(CS,Current Statistical)模型、改进输入估计 (MIE,Modified Input Estimation)和无迹强跟踪滤波器,提出了一种新的自适应目标跟踪算法.该算法引入Jerk输入估计改进了当前统计模型的状态方程和机动加速度方差调整方法,利用改进的无迹强跟踪滤波器实现了状态协方差、状态噪声协方差和机动频率的联合自适应.在没有加速度先验知识的情况下,能够实时准确跟踪目标连续强机动、匀加速机动和匀速运动状态.仿真实验表明:相比CS模型无迹滤波算法、CS模型无迹强跟踪算法和交互多模型算法,该算法在对目标强机动的适应性、跟踪精度和对突变状态跟踪的收敛性方面都有更好的性能.     

A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

Prognostics and health management (PHM) significantly improves system availability and reliability, and reduces the cost of system operations. Design for testability (DFT) developed concurrently with system design is an important way to improve PHM capability. Testability modeling and analysis are the foundation of DFT. This paper proposes a novel approach of testability modeling and analysis based on failure evolution mechanisms. At the component level, the fault progression-related information of each unit under test (UUT) in a system is obtained by means of failure modes, evolution mechanisms, effects and criticality analysis (FMEMECA), and then the failure-symptom dependency can be generated. At the system level, the dynamic attributes of UUTs are assigned by using the bond graph methodology, and then the symptom-test dependency can be obtained by means of the functional flow method. Based on the failure-symptom and symptom-test dependencies, testability analysis for PHM systems can be realized. A shunt motor is used to verify the application of the approach proposed in this paper. Experimental results show that this approach is able to be applied to testability modeling and analysis for PHM systems very well, and the analysis results can provide a guide for engineers to design for testability in order to improve PHM performance.     

一种新型水溶性芯模的制备和性能

概述了金属模具不易脱模的形状复杂的复合材料结构件成型中遇到的工艺技术难题,着重对水溶性芯模的制备工艺特点和性能进行了研究,并将所制得的水溶性芯模成功的用于树脂基复合材料结构件的制造中。结果表明,水溶性芯模的各项性能满足复杂异型复合材料结构件制造的要求。     

Multiple model particle flter track-before-detect for range ambiguous radar

The middle pulse repetition frequency（MPRF）and high pulse repetition frequency（HPRF）modes are widely adopted in airborne pulse Doppler（PD）radar systems,which results in the problem that the range measurement of targets is ambiguous.The existing data processing based range ambiguity resolving methods work well on the condition that the signal-to-noise ratio（SNR）is high enough.In this paper,a multiple model particle flter（MMPF）based track-beforedetect（TBD）method is proposed to address the problem of target detection and tracking with range ambiguous radar in low-SNR environment.By introducing a discrete variable that denotes whether a target is present or not and the discrete pulse interval number（PIN）as components of the target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the proposed algorithm converts the problem of range ambiguity resolving into a hybrid state fltering problem.At last,the hybrid fltering problem is implemented by a MMPF-based TBD method in the Bayesian framework.Simulation results demonstrate that the proposed Bayesian approach can estimate target state as well as the PIN simultaneously,and succeeds in detecting and tracking weak targets with the range ambiguous radar.Simulation results also show that the performance of the proposed method is superior to that of the multiple hypothesis（MH）method in low-SNR environment.     

基于分段模型的测速雷达电波折射误差修正方法

针对高精度测速系统在优化设备时取消探空气象测量的要求,提出用统计大气折射率剖面分段模型代替探空测量剖面,并在此基础上建立了基于分段模型的测速雷达电波折射误差修正方法。利用某测站历史气象数据对该方法进行了验证,结果表明精度较高,基本上能够满足测速雷达数据处理电波折射修正的精度要求。     

亚燃燃烧室稳态工作过程数值研究

采用Fluent流场计算软件,对液体亚燃冲压发动机燃烧室的稳态工作过程,包括点火前的冷流场与点火后的两相反应流场进行数值模拟研究。首先,通过二维计算,对比研究两种不同阻塞比燃烧室方案的冷流损失特性与回流区特性,进行方案初选。随后,对选型后方案进行两相反应流场计算,研究燃烧室热态工作过程的温度场、燃油分布与燃烧效率的一般规律,比较并选择适合的燃油供应方案;最后,对燃烧室进行三维详细结构的建模并计算。计算结果很好地揭示了燃烧室内的流动和燃烧过程,与试验数据吻合较好。     

自识别自校准Kalman滤波方法

在导航滤波、故障诊断等许多工程领域中,受环境因素影响、模型和参数的选取不当等原因,系统状态方程中往往含有未知输入(系统误差),传统的Kalman滤波方法无法消除这种未知输入的影响,导致产生较大的滤波误差。为此,提出一种自识别自校准Kalman滤波方法,并分别对线性系统和非线性系统进行了详细讨论,给出了相应的公式和滤波步骤。该方法能够自动识别状态方程中有无未知输入,当有未知输入时,则能自动估计未知输入,并对它进行补偿和修正。大量实例计算和仿真模拟表明,与传统方法相比,本文方法能够有效提高状态估计精度,且计算简单,便于工程应用。     

几种GEOSAR上成像算法比较

地球同步轨道SAR具备着低轨SAR所不具有的优势,然而其具有合成孔径时间长、慢速运动的特点,成像处理远比低轨SAR复杂。针对地球同步轨道＂8＂字形星下点轨迹的特点,结合现有的成像算法,对GEOSAR回波信号进行了建模,对成像算法的选择做了说明,主要分析了BP算法、RD算法、CS算法。最后在对三种算法分别仿真的基础上详细地比较了算法在地球同步轨道上的适应性、成像效果以及计算量。     

火星进入段探测器自校准状态估计

由于大气密度、气动参数、突风和沙尘暴等因素的影响,火星探测器在进入段高速飞行的动力学模型中往往带来未知输入,这些未知输入使传统的滤波方法出现较大的偏差。研究采用一种新的自校准扩展Kalman滤波方法,对火星进入段的探测器进行状态估计,可以成功地消除这些未知输入带来的影响。数值仿真结果表明,该方法能有效提高导航精度。