Unscented Kalman Filter for Autonomous Warship Attitude Determination

To address a problem of autonomous attitude determination algorithm using gravitational field and geomagnetic field observation, a new recursive optimization autonomous attitude estimation algorithm is proposed. The algorithm is based on unscented Kalman fiher(UKF), and can synchronously provide the attitude rate information. The simulated results show that the measurement precision of the method could be increased by 2 times compared to that of the common methods.     

Detection Algorithm for LFM Echo of Underwater Moving Targets Based on Discrete Fractional Fourier Transform

The mismatch between echo and replica caused by underwater moving target（UMT）＇s radial velocity degrades the detection performance of the matched filter（MF） for the linear frequency modulation（LFM） signal. By using the focusing property of fractional Fourier transform（FRFT） to that signal, a detection algorithm for UMT＇s LFM echo based on the discrete fractional Fourier transform（DFRFT） is proposed. This algorithm is less affected by the target＇s radial velocity compared with the other MF detection algorithm utilizing zero radial velocity replica（ZRVR）, and the mathematical relation between the output peak positions of these two algorithms exists in the case of existence of target echo. The algorithm can also estimate the target distance by using this relation. The simulation and experiment show that this algorithm＇s detection performance is better than or equivalent to that of the other MF algorithm utilizing ZRVR for the LFM echo of UMT with unknown radial velocity under reverberation noise background.     

Collaborative Error Registration Algorithm for Radar System

Affected by common target selection, target motion estimation and time alignment, the radar system error reg- istration algorithm is greatly limited in application. By using communication and time synchronization function of a data link network, a collaborative algorithm is proposed, which makes use of a virtual coordinates constructed by airplane to get high precision measurement source and realize effective estimation of the system error. This algorithm is based on Kalman filter and does not require high capacities in memory and calculation. Simulated results show that the algorithm has better convergence performance and estimation precision, no constrain on sampling period and accords with transfer characteristic of data link and tactical internet perfectly.     

Kalman Filter for Generalized 2-D Roesser Models

The design problem of the state filter for the generalized stochastic 2-D Rocsser models, which appears when both the state and measurement are simultaneously subjected to the interference from white noise, is discussed. The wellknown Kalman filter design is extended to the generalized 2-D Roesser models. Based on the method of ＂scanning line by line＂, the filtering problem of generalized 2-D Roesser models with mode-energy reconstruction is solved. The formula of the optimal filtering, which minimizes the variance of the estimation error of the state vectors, is derived. The validity of the designed filter is verified by the calculation steps and the examples are introduced.     

Rough Sets Probabilistic Data Association Algorithm and its Application in Multi-target Tracking

A rough set probabilisfic data association （RS-PDA） algofitlml is proposed for reducing the complexity and time consumption of data association and enhancing the accuracy of tracking results in multi-target tracking appiication. In this new algorithm, the measurenlents lying in the intersection of two or more validation regions are allocated to the conesponding targets through rough set theory, and the multi-target tracking problem is transformed into a single target tracking after the classification of measurenaents lying in the intersection region. Severed typical multi-target tracking applications are given. The simulation results show that the algorithm can not ouly reduce the complexity and time consumption but also enhance the accuracy and stability of the tracking results.     

A New Single DIFAR Sonobuoy Target Location Algorithm

In order to solve the problem of target location of single direction finding and ranging(DIFAR) sonobuoy, a new target location algorithm is proposed. Based on the new generation of high performance sonobuoy signal processing platform, the new algorithm makes full use of the Doppler information of the targets while using the target location data, and successfully implements the target detection, location and tracking. In the calculation of target parameters, the new algorithm utilizes the repeated measurement data to further improve the calculation accuracy of the target parameters using the principle of Least Square. The simulation results indicate the correctness of the new algorithm. The algorithm is simple, stable and easily implemented in engineering. And besides, it overcomes the weakness of the traditional algorithm which requires at least two DIFAR buoys to locate the targets.     

Cooperative Navigation for Autonomous Underwater Vehicles Based on Estimation of Motion Radius Vectors

A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.     

A Correlation Tracking Algorithm Based on Template Partition Motion Estimation

A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation （BME） algorithm, the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The rela- tion of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70 % time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.     

Research on Airborne Electro-Optical Tracking and Sighting System Based on Fuzzy PID and H∞ Control

Airborne electro-optical tracking and sighting system is a three-degree-of-freedom angular position servo system which is influenced by multi-disturbance, and its control system consists of stabilizing and tracking components. Stabilizing control is applied to track angular velocity order and control multi-disturbance under airborne condition, and its robustness should be very good; tracking control is applied to compensate tracking error of angular position. A mathematical model is established by taking the control of yaw loop as example. H∞ stabilizing controller is designed by taking the advantage of H∞ control robustness and combining with Kalman filter. A fuzzy control is introduced in general PID control to design a decoupled fuzzy Smith estimating PID controller for tracking control. Simulation research shows that the control effect of airborne electro-optical tracking and sighting system based on fuzzy PID and H∞ control is good, especially when the model parameters change and the multi-disturbance exists, the system capability has little fall, but this system still can effectively track a target.     

Research on Instantaneous Thrust Measurement for Attitude-control Solid Rocket Motor

In order to measure the instantaneous thrust of a certain attitude-control solid rocket motor, based on the analysis of the measurement principles, the difference between the instantaneous thrust and steady thrust measurements is pointed out. According to the measurement characteristics, a dynamic digital filter compensation method is presented. Combined the identification-modeling, dynamic compensation and simulation, the system＇s dynamic mathematic model is established. And then, a compensation digital filter is also designed. Thus, the dynamic response of the system is improved and the instantaneous thrust measurement can be implemented. The measurement results for the rocket motor show that the digital filter compensation is effective in the instantaneous thrust measurement.     

微波交会对接雷达目标跟踪的卡尔曼滤波器设计

针对空间交会对接应用中追踪航天器对目标航天器的精密跟踪，采用三阶修正卡尔曼滤波器直接在球坐标系下对径向距离和径向速度进行联合跟踪，采用2个结构一致的二阶修正卡尔曼滤波器分别对俯仰角和俯仰角速度、方位角和方位角速度进行联合跟踪。提出一种状态噪声的实时估计算法，有效地解决了卡尔曼滤波应用中状态噪声的参数设计问题。仿真结果表明，本文设计的卡尔曼滤波器能够精确地跟踪目标航天器，同时具有较强的动态适应能力。     

移动机器人的卡尔曼滤波定位算法改进与仿真

针对传统卡尔曼滤波算法和扩展卡尔曼滤波算法应用于移动机器人定位系统时出现的误差值较大和算法发散现象,在定位算法中引入修正因子对状态估计方程进行优化.分析传统卡尔曼滤波和扩展卡尔曼滤波的定位算法原理,研究运动过程中驱动力和摩擦力对移动机器人的影响,引入修正因子改进卡尔曼滤波算法,并对传统卡尔曼滤波算法、扩展卡尔曼滤波算法和改进算法做仿真对比和研究.仿真结果表明:修正因子对传统卡尔曼滤波算法和扩展卡尔曼滤波算法都具有改进效果,能提高定位精度.     

基于纯方位角测量的水下目标被动跟踪技术

水下目标的被动跟踪技术在军事上具有重要的应用价值,为了解决基于纯方位角测量的水下目标被动跟踪技术在实际应用中的问题,研究了几种适合于单、双观测站的水下目标被动跟踪算法.分别对伪线性估计算法、扩展卡尔曼滤波算法、无迹卡尔曼滤波算法在不同参数情况下的性能进行了详细的仿真与分析.仿真结果表明,静止单观测站虽不能获得目标的完全观测,但是在具有一定先验信息的情况下,伪线性估计算法也可以实现对目标轨迹的估计;双观测站可以获得对目标的完全观测,并且在观测方程严重非线性的情况下,无迹卡尔曼滤波方法的性能要优于扩展卡尔曼滤波方法.仿真结果对工程应用具有重要的参考价值.     

基于无迹卡尔曼滤波的单站混合定位跟踪算法

针对移动台的单站跟踪问题,以"到达时间和与到达时间差(TSOA/TDOA)"新型混合定位技术作为基础,提出一种基于"到达时间和与到达时间差"混合被动单站定位模型的无迹卡尔曼滤波跟踪算法。该算法以观测到的有噪信息为基础,引入"到达时间和与到达时间差"观测模式,使用受随机加速影响的匀速运动状态作为跟踪算法的状态模型,将无迹卡尔曼滤波(UKF)算法应用在移动台的定位跟踪上,实现了对移动台的位移和速度的同步跟踪。仿真结果表明:无迹卡尔曼滤波算法应用移动台跟踪系统是有效的;与扩展卡尔曼滤波相比,其跟踪算法的滤波精度、稳定性更优。     

弹丸三维速度实时处理方法研究

为了解决常规靶场测控系统中弹丸三维速度实时高精度处理的难题,提出了基于多元异类实时数据融合处理弹丸三维速度的方法。该方法通过联立弹丸位置和径向速度这两类测元的误差方程,建立了基于径向速度测元的测控系统实时数据融合模型,实现了弹丸三维速度的实时解算。将该方法应用于常规靶场典型试验的实例仿真中,与纯粹的三维速度IMM卡尔曼滤波和增加径向速度观测量后的IMM卡尔曼滤波进行对比分析,验证了模型的正确性和方法的有效性。研究结果表明,该文提出的方法能够高精度处理弹丸的三维速度,并且实时性强,易于工程实践。     

固定指数加权模糊自适应EKF研究及其应用

为了改善扩展卡尔曼滤波（EKF）算法在机动目标跟踪中的跟踪性能，文中研究了一种固定指数加权模糊自适应扩展卡尔曼滤波技术，通过监视理论残差和实际残差的协方差一致程度。应用模糊推理系统不断调整滤波协方差，对扩展卡尔曼滤波器（EKF）进行在线自适应控制．最终实现最优估计。仿真结果表明，改进的算法稳定性高，精度得到明显改善．用于弱机动目标跟踪效果较好。     

基于滤波器组的船舶静电场跟踪

针对船舶静电场跟踪中先验信息缺失的问题,引入滤波器组方法,提出了一种新的船舶静电场跟踪算法。建立船舶静电场跟踪的状态空间模型,用水平电偶极子对船舶静电场进行建模;以渐进更新扩展卡尔曼滤波为基本滤波单元,采用一组滤波器对目标进行跟踪;根据电场计算公式设计滤波初值,并利用最大似然法确定可靠的跟踪轨迹。仿真和海上电偶极子跟踪实验表明,滤波器组方法能够有效地解决先验信息缺失条件下的船舶静电场跟踪问题,最大似然选择法能够筛选出正确的跟踪轨迹,在跟踪过程中滤波算法对方位信息更加敏感。     

低重频脉冲多普勒雷达解速度模糊新方法研究

分析了使用距离微分法解速度模糊存在的精度不高,且不能实时得到目标速度的问题,在此基础上,将Kalman滤波解算的速度值应用到其中,在进行目标距离滤波的同时,将实时的距离变化率作为真实的目标速度进行计算,求出目标的无模糊速度。将此方法与相对距离跟踪的微分方法进行比较,计算结果表明,此方法提高了解速度模糊的准确性,且方法相对简单,易于工程实现。     

基于MIMU/GPS组合导航定位系统的一种新型卡尔曼滤波算法的研究

文中提出了基于MIMU/GPS组合导航定位系统的一种新型卡尔曼滤波算法。系统以MEMSIMU为传感器核心,采用位置和速度组合,运用该算法对系统模型误差和量测噪声协方差误差具有良好的自适应性。     

基于距离跟踪的矢量脱靶量测量方法

提出了一种基于纯距离跟踪的空间目标运动轨迹提取的矢量脱靶量参数估计新方法.该方法利用脉间频率步进体制的脱靶量测量系统获得较为精确的瞬时距离信息.通过建立目标运动模型,采用纯距离目标跟踪定位的有限差分扩展卡尔曼滤波算法,获得目标运动的精确轨迹.利用跟踪得到的空间位置点,时矢量脱靶量参数进行估计.仿真结果表明该方法可以得到满意的矢量脱靶量估计结果.