车载雷达防追尾预警系统中的目标跟踪研究

考虑毫米波雷达测量的误差和噪声的存在,为了提高毫米波雷达汽车防追尾预警系统的可靠性,设计了一个多模型算法实现对机动车辆的准确跟踪。针对汽车在高速公路上最常见的匀速、匀加速及转弯运动模型进行仿真实验,结果表明该算法能够有效地跟踪前方行驶车辆,探知自车与前车之间距离信息、速度信息等,从而降低雷达虚警率。     

钢腐蚀脉冲涡流检测系统的研制与应用

为解决带包覆层钢腐蚀检测的技术难题,根据脉冲涡流检测原理,研制出一套脉冲涡流钢腐蚀检测仪。详细论述了传感器、主机和检测软件等检测系统的组成。实验室和现场试验表明,该系统能够穿透铝和不锈钢等常见管道保护层材料,检测出120 mm包覆层厚度下10%的钢腐蚀变化。钢腐蚀脉冲涡流检测技术为在线检测提供了新的手段。     

Effect of cation substitution on magnetic properties in Mn1−xA’xCr2S4 (A’ = Cd,Zn) thiospinel series

Abstract

Abstract

Colossal magnetoresistance (CMR) materials such as REMnO₃ perovskites and AB₂S₄ thiospinels have been well studied in the past. The authors present thiospinel compounds with A = Mn, since they may be viewed as a link to REMnO₃ CMR perovskites. Ferrimagnetic MnCr₂S₄ is known to present a T _c of 65?K and a magnetic transition towards a non-collinear Yafet-Kittel state. The (Mn_1?xA’_x)Cr₂S₄ series (A = Cd, Zn) was synthesised at 850°C. This series crystallises in the space group Fd3m with a close to 10?Å. When A’ = Cd (T _c ranging from 68?K, x = 0·2, to 79?K, x = 0·6), the ferromagnetic features are enhanced, indicating that antiferromagnetism between Mn spins is progressively lost. For A’ = Zn, two magnetic transitions take place, one at 15?K, which is reminiscent of the antiferromagnetic state of ZnCr₂S₄ and another one at T _c = 115?K. Impurities which could be responsible of these two magnetic states are excluded.     

基于信息复杂度的老年智能图标辅助设计研究

目的 为探究图标语义与信息复杂度的关联,研究按照结构复杂度和资讯复杂度两个维度将图标进行划分,观测两个因素对老年用户辨识正确率与反应时间的表现差异,归纳出老年用户判读的共性,寻找适宜的图标设计原则,使用户有更好的绩效表现。方法 采用实验法和深入访谈法,针对30名老年参与者开展图标识别测试,通过图标与语义配对了解“结构复杂度/资讯复杂度”对辨识效能的影响。结果 相较结构复杂度,资讯复杂度更能决定图标识别率;老年图标设计时尽量采用小于14.5 bit资讯负载量图标;在相同资讯负载条件下,尽量采用“人形”“用具”“自然”作为主要元素,“几何”“字母”“指向”作为辅助元素。结论 构建图标辅助设计系统原型SIID1.0,通过设计方案评估,对前期信息复杂度原则的有效性进行验证。     

改进的交互式多模型粒子滤波跟踪算法

通常的交互多模型卡尔曼滤波(IMMKF)或交互多模型扩展卡尔曼滤波(IMMEKF)对于非高斯问题无能为力;对于非线性问题,其性能不及交互多模型粒子滤波算法(IMMPF)。粒子滤波能够处理非线性/非高斯问题,其与交互式多模型结合用来获得更好的跟踪性能。然而,粒子滤波的主要问题是巨大的计算量,由于粒子滤波通常采用大量的粒子数目,将带来很大的计算负荷。该文提出了一种改进的交互多模型粒子滤波算法,其利用多模型综合使用了卡尔曼滤波和粒子滤波,与常规交互式多模型粒子滤波(IMMPF)相比,大大改善了计算效率。对于非线性/非高斯问题,其性能与IMMPF相当;对于线性问题,其性能与IMMEKF相当,并优于IMMPF的性能。     

Estimation of the tire slip angle under various road conditions without tire–road information for vehicle stability control

This paper presents a tire slip angle estimator based on an Interacting Multiple Model (IMM) algorithm for vehicle stability control. The proposed algorithm is capable of estimating the tire slip angles under various road conditions without the prior knowledge of tire and road condition by only using on-board vehicle sensors. Instead of employing tire and road information, the proposed algorithm utilizes multiple numbers of model candidates to represent all aspects of vehicle motions under various road conditions. Each model candidate is a combination of lateral vehicle dynamics and transient/steady state tire dynamics. The proposed algorithm evaluates the fidelity of each model candidate to the current vehicle dynamics with probability. Moreover, in the proposed algorithm, multiple numbers of Kalman filters are embedded with these model candidates as process models. The final estimate of the proposed algorithm in each time step is a linear sum of the posteriori states from multiple embedded filters with the calculated probability as coefficients. The proposed estimation algorithm has been evaluated via vehicle tests. The tests have been conducted on dry asphalt and wet asphalt using a luxury passenger car equipped with a high-performance GPS for reference and data logging computer. The results have shown that the proposed estimator can successfully estimate tire slip angles with satisfactory accuracy under various road conditions     

Target tracking using Interactive Multiple Model for Wireless Sensor Network

Target tracking in a Wireless Sensor Network (WSN) environment is a challenging research problem. Interactive Multiple Model (IMM) is a popular scheme for accurate target tracking. The existing target tracking scheme used in WSN employs Kalman Filter (KF) which fails to track the target accurately due to non availability of target data at regular intervals and missing of packets. Though existing KF based tracking in WSN scheme detects the target, it fails to identify the target. To overcome these problems, this paper proposes a IMM based Target Tracking in WSN named ITTWSN that uses multiple models (velocity and acceleration) to handle both maneuvering and non maneuvering targets and multiple sensors to detect and identify the targets. The performance of the proposed ITTWSN is compared with the KF scheme and it is found that the accuracy of the proposed ITTWSN is better than the existing KF based approach.     

机动再入目标跟踪仿真研究

在弹道目标跟踪精度优化的研究中,机动再入目标高速的运动特性与复杂的受力环境,使得单一的运动模型与标准的交互式多模型算法不能真实反映其运动状况,而导致跟踪误差较大.为了提高跟踪精度,引入强跟踪滤波器的交互式多模型(IMM)算法,并将“当前”统计模型(CS)引入到交互式多模型算法中,提出CS_STF_IMM算法.通过“当前”统计模型对强机动的适应性与强跟踪滤波器关于模型失配的鲁棒性提高跟踪的精度与稳定度.仿真结果表明,改进算法在对机动再入弹道目标跟踪时具有良好的跟踪效果,并且稳定性高.     

非线性交互粒子滤波算法

在非线性非高斯系统状态估计问题中,后验概率密度函数的解析形式难以获得,标准粒子滤波算法采用状态转移概率函数代替后验概率作为重要性采样概率密度函数,而未考虑当前观测数据的影响．针对该问题,首先提出了非线性交互多模型算法;然后应用该算法产生重要性采样概率密度函数,设计了新的非线性交互粒子滤波器．新的概率密度函数融入最新观测数据,更接近系统状态后验概率．比较实验表明了所提出算法的有效性．     

Extensions of the SMC-PHD filters for jump Markov systems

The probability hypothesis density (PHD) filter is a promising algorithm for multitarget tracking, which can be extended for jump Markov systems (JMS). Since the existing multiple model sequential Monte Carlo PHD (MM SMC-PHD) filter is not interacting, two extensions of the SMC-PHD filters are developed in this paper. The interacting multiple-model (IMM) SMC-PHD filter approximates the model conditional PHD of target states by particles, and performs the interaction by resampling without any a priori assumption of the noise. The IMM Rao-Blackwellized particle (RBP) PHD filter uses the idea of Rao-Blackwellized to further enhance the performance of target state estimation for JMS with mixed linear/nonlinear state space models. The simulation results show that the proposed algorithms have better performances than the existing MM SMC-PHD filter in terms of state filtering and target number estimation.