搜索资源列表
vanderMerwe_GNC2004
- Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion - Applications to Integrated Navigation -
kaerman
- 卡尔曼的原理，以及加速度计，陀螺仪，卡尔曼的融合资料，及卡尔曼融合的实例文档。-Kalman s principle, and accelerometer and gyroscope, kalman fusion material, and kalman fusion instance document.
12234445
- 采用卡尔曼滤波器对系统的俯仰角、 滚转角和航向角的误差进行最优估计；设计数据融合的判别准则，并根据判据的判断结果调整卡尔曼 滤波器中的量测信息，使系统可用于小型无人机的定高自主飞行-Kalman filter system pitch angle, roll angle and yaw angle error optimal estimation design data fusion criterion, and adjust according to the criterion of
An-Integrated-DGPS_IMUh
- 研究GPS与INS数据融合编程卡尔曼滤波算法-Study of GPS and INS data fusion programming Kalman filter algorithm
Attitude-estimation-
- 研究GPS与INS数据融合编程卡尔曼滤波算法-Study of GPS and INS data fusion programming Kalman filter algorithm
An-Integration-of-GPS-
- 研究GPS与INS数据融合编程卡尔曼滤波算法-Study of GPS and INS data fusion programming Kalman filter algorithm
GPS_INS-integration
- 研究GPS与INS数据融合编程卡尔曼滤波算法-Study of GPS and INS data fusion programming Kalman filter algorithm
N_sensors-12-13212-v2
- This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance
Data-Fusion-Approach-for-Altitude-Location-Error.
- Altitude location for UAV by using federated filter is discussed, the fourth structure is selected, because its two sub-filters involving altitude sensor and the difference Global Positioning System (d-GPS) respectively are fully isolated from
data-fusion2
- 自校正加权观测融合KALMAN估计器及其应用方面的一篇硕士论文-Self-tuning weighted measurement fusion KALMAN ESTIMATION and its applications in a master' s thesis
Kalman--HF-radar-
- 一种基于卡尔曼加权融合算法的双基高频地波雷达选频方法-Weighted fusion algorithm based on Kalman bistatic HF radar frequency selection method
IMM_UKF
- 在主/被动雷达双传感器目标跟踪背景下, 提出一种基于IMM- UKF 滤波的加权数据融合算法。-A data fusion algorithm using IMM-UKF is presented based on active/ passive radar target tracking. The algorithm is established in terms of IMM( interact ing mult iple model) and UKF( unscented Kalman f
MEKF
- 该论文提出了一种改进的扩展卡尔曼滤波方法，实现对红外，雷达传感器的信息融合跟踪算法。性能优于传统EKF-This paper presents an improved extended Kalman filter method, to achieve the infrared, radar sensor information fusion tracking algorithm. Better performance than traditional EKF
KALMAN
- 卡尔曼滤波源代码，姿态算法融合，很有参考意义-Kalman filter source code, the attitude algorithm fusion, is of great reference significance
estimation-extended-Kalman-filter
- 针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended K
optical-flow-navigation
- 针对小型无人机在无卫星导航信号条件下的导航问题, 结合光流及地标定位设计了使用摄像头、惯性测量器件、超声测距仪等传感器融合的无人机室内导航方法. 文章使用补偿角速率的光流微分法计算帧间像素点小位移, 并用前后误差算法提取精度较高的点, 避免像素点跟踪错误, 提高了光流测速的精度 对得到的光流场用均值漂移算法进行寻优, 得到光流场直方图峰值, 以此计算光流速度. 本文提出了无累积误差的连续地标定位算法, 实时测量无人机位置. 通过多速率卡尔曼滤波器对观测周期不一致的位置、速度信息进行最优估计. 在