Intelligent Antenna Attitude Parameters Measurement Based on Deep Learning SSD Model

Due to the consideration of safety,non-contact measurement methods are be-coming more acceptable.However,massive measurement will bring high labor-cost and low working efficiency.To address these limitations,this paper introduces a deep learning model for the antenna attitude parameter measurement,which can be divided into an an-tenna location phase and a calculation phase of the attitude parameter.In the first phase,a single shot multibox detector(SSD)is applied to automatically recognize and discover the antenna from pictures taken by drones.In the second phase,the located antennas’fea-ture lines are extracted and their attitude parameters are then calculated mathematically.Experiments show that the proposed algorithms outperform existing related works in effi-ciency and accuracy,and therefore can be effectively used in engineering applications.

3D attitude measurement by means of spread spectrum modulated ultrasonic wave

Local position and attitude measurement methods are necessary for the navigation of autonomous robots and the other applications. In this paper, a 3D attitude measurement method is proposed. This method uses the spread spectrum modulated ultrasonic wave for the measurement of the pseudo-distance of each pathway between transmitter and receiver elements that are arranged in an array. The relative attitude between transmitter and receiver unit could be calculated from the relationship between these pseudo-distances. The use of spread spectrum modulation enables the high accuracy, noise tolerance, and coexistence of multiple transmitter devices by code division multiple access (CDMA) between transmitter and receiver elements. A pair of transmitter and receiver prototype for proposed method was manufactured, and the fundamental performance was examined in experiments. As a result, accuracy of σ=0.78 mm in the pseudo-distance measurement of each pathway between transmitter and receiver elements was confirmed, and about 0.01 rad resolution in the attitude measurement was also confirmed.

ALGORITHM OF SAR SATELLITE ATTITUDE MEASUREMENT USING GPS AIDED BY KINEMATIC VECTOR

In this paper,in order to improve the accuracy of the Synthetic Aperture Radar (SAR) satellite attitude using Global Positioning System (GPS) wide-band carrier phase,the SAR satellite attitude kinematic vector and Kalman filter are introduced.Introducing the state variable function of GPS attitude determination algorithm in SAR satellite by means of kinematic vector and describing the observation function by the GPS wide-band carrier phase,the paper uses the Kalman filter algorithm to obtian the attitude variables of SAR satellite.Compared the simulation results of Kalman filter algorithm with the least square algorithm and explicit solution,it is indicated that the Kalman filter algorithm is the best.

GDOP’s Influence on Observable Degree of Multi-Antenna GPS/SINS Integrated Attitude Measuring System

GDOP’s influence on observable degree is studied by analyzing a multi-antenna GPS/SINS attitude measuring system. Firstly, the mathematical model of the attitude measuring system, whose observations are single-differences, is provided;Secondly, it is proved that the model can be studied by PWCS theory, and GDOP’s influence on observable degree is explained intuitively. Then, the variance of observable degree is studied by simulation while GDOP is different, and the result is analysed. Simulation results show that, the observable degree becomes worse with the increasing GDOP value. Therefore, while designing such kind of Kalman filter, the influence to observable degree which made by GDOP should be considered adequately.

The Role of Attitude Strength in Predicting Organ Donation Behaviour by Implicit and Explicit Attitude Measures

Explicit attitude measures seem to be rather poor predictors of organ donation behaviour. This study examined whether implicit attitude measures acted as better predictors. Special attention was paid to the moderating role played by attitude strength in predicting deliberate donation behaviour. In this study (N = 78), explicit and implicit measures of attitudes towards organ donation, as well as behavioural commitment, were assessed. Implicit associations were measured by an Implicit Association Test;five constructs assessed self-reported—understood as reflected—attitude strength. The explicit attitude measure appeared to be the best single predictor of whether the participant ended up taking an organ donor card. More importantly, test results demonstrated the moderating role of attitude strength. In the case of low attitude strength, the likelihood of taking a donor card increased with an increasing positive implicit association. In contrast, increasing strength was associated with a weaker link between card taking and the implicit attitude measure. The results are discussed in light of the power of implicit associations to predict more deliberate behaviours.

Tracking a maneuvering target in clutter with out-of-sequence measurements for airborne radar

There are many proposed optimal or suboptimal al- gorithms to update out-of-sequence measurement（s） （OoSM（s）） for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clut- ter, an interacting multiple model probabilistic data association （IMMPDA） algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed （ECEF） coordinate system where it considers the effect of the platform＇s attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the perfor- mance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the track- ing performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.

Adaptive filter for a miniature MEMS based attitude and heading reference system

An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastic model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good estimates of the states. When the system is in the high dynamic mode and the bias has converged to an accurate estimate, the attitude calculation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance.

The Satellite’s On-Orbit Attitude System Error Compensation Technique Based on Stereo Models

According to the problem that the low measurement accuracy of TH-1 satellite star sensor, the low frequency and “slow drift” error which cannot be ignored in the attitude determination system, resulting in obvious random error in the horizontal position and elevation direction, and the change of the error with time and latitude, cannot be calibrated by the ground field of the real problem. In this paper, a low frequency detection model is established by using the principle of relative orientation, and the low frequency error is obtained by parallax elimination. Finally, the satellite attitude is compensated and the more accurate exterior orientation elements are obtained, thus improving the positioning accuracy and stability. The experimental results show that: the proposed methods are feasible, and by using the model to dynamically calibrate the exterior orientation angle elements on orbit, the plane and elevation errors of the ground points can be basically eliminated. The global uncontrollable positioning accuracy and stability of the photogrammetry satellite are improved.

基于双目立体视觉的乘员运动姿态测量方法研究

提出了基于双目立体视觉的汽车乘员运动姿态测量方法。首先使用自主搭建的双目立体视觉系统,按照张正友标定法标定相机并对图像进行立体校正;然后提出基于邻域的SGBM单参数优化算法,并依此建立乘员关键特征点与三维空间坐标间的映射关系,实现了对乘员运动姿态的非接触动态测量。实验结果表明,该方法可以有效地测量乘员运动姿态,且测量精度较高,对汽车乘员非标准坐姿下的保护策略制定具有重要的参考价值。

二维主动位姿引导的单目空间姿态测量方法

针对空间物体姿态快速测量问题,以构建视觉最小系统需求为依据,研究了一种基于二维主动位姿引导的单目视觉空间姿态测量方法,建立了单目相机、二维载台与倾角仪之间的姿态测量模型,实现了空间物体的姿态角的测量。该方法以大地倾角仪坐标系统一测量系统的测量基准,由精密二维载台引导单目相机覆盖地空大视野三维空间,通过前期标定设计完成了单目相机与二维载台之间的工装校准;建立了载台坐标系、摄像机坐标系以及大地倾角仪坐标系之间的姿态测量传递模型,实现了定轴旋转双视角拍照下的空间物体的姿态解算和角度测量。构建了实验验证环境,测角实验结果表明:在系统测量基准坐标系下,其俯仰角的测量误差≤0.82°,测量相对误差≤6.1%;其横滚角的测量误差≤0.43°,测量相对误差≤3.4%。

多矢量姿态测量算法研究综述

将矢量测量转化为姿态测量,该问题在姿态估计中被称为Wahba问题。介绍了最小化Wahba问题的损失函数的不同算法,包括最优四元数估计器(ESOQ)、四元数估计器(QUEST)、快速最优姿态矩阵(FOAM)、矩阵的奇异值分解(SVD)等广泛使用的算法,以及基于快速线性四元数姿态估计器(FLAE)、黎曼流形等近年来提出的算法。给出了简单的计算原理与推导过程,并通过计算机仿真对照,归纳各类算法在计算旋转矩阵时的计算精度、鲁棒性。针对姿态测量算法应对当前应用场景的性能需求,简要介绍其在惯性测量单元(IMU)动态对准、协同集群视觉定姿、图像拼接等方面的适用可能和工作原理,并在此基础上简述了姿态测量算法当前的缺陷与未来的发展趋势。

基于“12345”热线转办的投诉分析及措施探讨

目的归纳总结“12345”热线转办投诉的情况,分析原因,提出处理措施。方法选取2020年1月—2022年12月“12345”热线转办的启东市中医院投诉763件进行分析,分析投诉类型,总结发生投诉的科室分布情况,同时总结引起投诉的相关原因,提出处理措施。结果763件投诉情况中,涉及院感防控方面的总计380件,占比49.80%,其他涉及医院诊疗服务、就医流程、医疗收费等情况。涉及投诉的科室包括门诊医技科室、病区、总务、药房、收费等。分析结果显示,院感防控是3年内引起投诉的主要原因;其次是医患沟通不到位、医疗质量问题、服务态度问题、收费不合理等。结合原因提出相应处理对策。结论通过“12345”热线能够一定程度使医院了解投诉信息,拓宽投诉通道,改进服务机制,提升服务质量,以建立和谐、融洽的医患关系。

基于IQPSO-EKF的多传感器融合姿态测量方法研究

为解决自动化竖井掘进设备的定位调姿精度对竖井、孔桩挖掘效率与质量的影响,提出了一种基于改进量子粒子群(IQPSO)-扩展卡尔曼滤波(EKF)的姿态测量算法,以提高微机电系统(MEMS)传感器测量精度。首先,对MEMS传感器数据进行了预处理(除噪、滤波、校准等);然后,参考现有飞行器的坐标系,建立了姿态解算模型,通过姿态角数学模型及运动学分析,构建了EFK状态方程,针对EKF方法参数估计不准确的问题,以分段混沌映射优化初始种群,引入平均位置最优值来避免陷入局部最优的IQPSO-EFK算法,优化EKF的系统、测量噪声的协方差参数;最后,对改进算法和三组姿态误差估计进行了对比实验。研究结果表明:对比三种典型目标函数,IQPSO-EFK相较于普通粒子群算法(QPSO-EFK)具有更强的寻优能力与收敛精度;对比三组旋转速度姿态测量误差,基于IQPSO-EKF算法的姿态测量方法在测量误差时比真实测量误差减少了约86.3%,比扩展卡尔曼滤波减少了约68.7%,比普通粒子群算法减少了约28.2%,证明该算法有效地提高了MEMS传感器测量精度。

Canny边缘检测和轴线矢量靶场目标姿态测量

对于靶场飞行目标的姿态测量问题,提出一种基于Canny边缘检测与Hough直线检测的靶场目标图像轴线提取方法,并利用成像平面交会获得旋转锥形载体的轴线,实现目标轴线的姿态测量的目的。靶场试验一般有多台光学测量设备采集目标图像,对采集到图像首先应用Canny算子检测目标边缘,对边缘图像适用Hough直线检测算法提取到成像平面上的目标轴线,进而可以得到测站和目标轴线所在的空间平面,利用面面相交原理获得目标轴线矢量的姿态角。该测量方法是基于Canny边缘检测和Hough直线检测的轴线提取方法,在仿真试验中对应用不同参数提取的轴线角度误差在0.3°左右,在实际试验中对目标的轴线提取误差在-0.7°~0.6°之间。实验表明该方法提取出的目标轴线的姿态角能够满足试验需求。

可用于狭小空间的单目主动视觉姿态测量方法

在狭小空间智能装配时,需要测量基准面姿态;但现有姿态测量设备尺寸较大或需要附加扫描运动机构,存在装置难以部署等问题,故提出一种适用于狭小空间的基于双线激光的单目主动视觉姿态测量方法。首先提取出线激光中心点进行光平面标定;接着根据中心投影关系,计算出光平面与像平面的转换矩阵;然后提取目标平面线激光中心点像素坐标并转换为相机坐标;最后应用RANSAC算法过滤异常点后使用最小二乘法拟合出物体平面方程,实现目标平面姿态测量。实验结果表明,滚转角测量误差平均值为0.029°,标准差为0.016°;俯仰角测量误差平均值为0.035°,标准差为0.025°。完成了在直径为170 mm、高为520 mm圆柱形腔体内的平面姿态测量,验证了方法的有效性。

一种基于Madgwick-EKF融合算法的卫星姿态测量方法

针对低地球轨道卫星姿态测量时,传感器易受噪声干扰、陀螺仪漂移等问题,提出一种基于Madgwick扩展卡尔曼滤波合算法(EKF)的卫星姿态测量方法。该方法采用陀螺仪、加速度计、磁强计等多传感器数据进行融合,并结合Madgwick算法和EKF算法的优点,实现姿态测量。首先,通过Madgwick算法,利用多个传感器测量数据计算初始姿态。然后,基于初始姿态和实际测量数据,应用EKF算法进行数据融合和噪声滤除,以获得最终准确的姿态估计。实验结果表明:相较Madgwick算法,本算法在测量精度上提升了65.8%,且具有较高的鲁棒性,为低地球轨道卫星姿态测量提供了一种有效的方案。

基于纯加速度计的弹载GFIMU配置方案研究

为提高火炮弹丸远程精确打击所需姿态测量精度,考虑低成本小型化高过载需求,研究了基于纯加速度计的弹载无陀螺惯性测量单元(GFIMU)方案。针对加速度计偏心产生臂杆效应的机理,分析并选择基于9通道加速度计与12通道加速度计的GFIMU方案;以输出误差为优化目标,利用有约束多目标粒子群算法分别对9/12通道加速度计GFIMU位置配置进行寻优,随后建立了角加速度与角速度二次项的非线性状态空间方程,修正过程方程与量测方程的噪声相关性,设计了噪声相关条件下的角速度扩展卡尔曼滤波(EKF)估计方法。通过建立外弹道模型并加入典型的MEMS加速度传感器噪声进行仿真求解,结果显示建立的GFIMU理论上是有效的,能达到弹丸短时航姿解算所需精度需求。

基于激光雷达的非合作航天器姿态测量

针对目标自遮挡导致姿态解算精度较低的问题,提出了一种基于激光雷达(LiDAR)点云的空间非合作目标姿态估计方法。初始姿态获取阶段,通过RANSAC算法与曲率聚类分割算法对目标特征分割,再与模板特征进行匹配获得粗配准变换矩阵,然后利用迭代最近点(ICP)算法精配准解算初始姿态;姿态跟踪阶段,通过快速点云配准计算相对姿态,通过逐帧点云姿态传递完成目标姿态测量。利用卫星模型搭建实验平台进行姿态测量实验。实验结果表明:所提方法能够稳定完成姿态解算,验证了所提方法的精度与可行性。

基于双PSD的三维测角传感器精度分析

在机载光电转台、多自由度摇摆台等系统中,对于一些运动体与基座间没有确定的回转轴的柔性支撑、并联支撑平台,需要考虑非接触三轴角度测量方法,目前大部分的光电非接触三轴角度测量方案系统复杂,占用空间大,无法适用于如机载、星载等载荷对体积、质量敏感的场景。为此,文中提出了基于双位置敏感探测器(PSD)的非接触三轴角度测量方案,使用准直镜头汇聚、双面反射光楔反射,将光源在两片PSD上汇聚成像,利用PSD上的光斑位置坐标反解出三轴角度。描述了其工作原理以及传感器构成,分析了因两片PSD的相对位置偏移产生的误差,提出了对应补偿方法以减少焊装产生的PSD位置偏移对测量精度的影响。主要对采集的PSD模拟信号值的抖动噪声进行FIR滤波处理,分析了滤波器的相频响应特性,并在MCU中测量相位滞后时间以及滤波器的响应带宽,验证了该数字滤波器在系统内拥有较好的实时传输特性。自准直测量单元总质量为230 g,尺寸为50 mm×50 mm×50 mm。实验结果表明,34阶FIR滤波器将角度测量的误差减小至60%,在±2°测量范围内单轴测量时,方位角、俯仰角、横滚角的误差均方根分别为0.003°、0.007°、0.017°,组合测量时分别为0.006°、0.009°、0.021°,文中所提出的三维测角传感器精度较高,满足机载等场景的使用要求。

面向激光跟踪测量的大范围高精度姿态测量

针对我国高端制造业对高精度空间六自由度测量系统的迫切需求,提出一种面向激光跟踪测量的基于单目视觉的大范围全自动高精度姿态测量方法。阐述了面向激光跟踪测量的姿态测量系统构成、合作靶标硬件设计,并建立了姿态测量数学模型;其次,分析了自适应清晰成像的姿态测量模块特性,基于光学畸变模型与张正友标定法建立了实时相机成像模型,动态校正特征点像素坐标模型,提升了特征点的提取精度;之后,结合合作靶标几何特性、EPnP算法、Soft-POSIT算法提出一种改进的姿态测量方法,建立了姿态测量系统的自动监测纠错机制,实现测量范围内任意动态位姿的自动测量。最后,利用二维精密转台搭载合作靶标对激光跟踪测量的姿态测量系统进行精度测试。实验结果表明:在3~10 m,方位角/俯仰角为±30°、滚动角为±180°内,适配有14个特征点的合作靶标,姿态测量精度优于0.049°;适配有10个特征点的合作靶标,姿态测量精度优于0.065°。此方法普适性强,对合作靶标特征点布局约束较小,可以满足高端制造业激光跟踪测量的精密测量需求。