1) PLKF
伪线性卡尔曼滤波
1.
A pseudo-linear kulman filter(PLKF)algorithm was presented for tracking a moving target by using DOA and TDOA measurements based on two stations.
建立了两站基于角度(DOA)和时差(TDOA)信息的伪线性观测模型,基于该模型提出了匀速运动目标的伪线性卡尔曼滤波(PLKF)算法。
2.
This method firstly takes full advantage of the spatial and frequency changing information to estimate the velocity vector of the emitter via the Pseudo-Linear Kalman Filter(PLKF) algorithm,which can be used to obtain the position vector,the Kalman filter is to improve the locat.
文中首先利用辐射源信号的空域和频域变化量信息,通过伪线性卡尔曼滤波算法估计出目标的速度矢量;然后利用速度矢量的估计值直接获得目标位置矢量的估计,并将其作为标准卡尔曼滤波算法的观测值进行滤波;最后通过计算机仿真验证了该方法具有较高的定位精度和较快的收敛速度。
2) pseudo-linear Kalman filter
伪线性卡尔曼滤波
1.
Pseudo-linear Kalman Filter in Passive Target Tracking
伪线性卡尔曼滤波在目标被动跟踪中的应用
2.
A PLKF(pseudo-linear Kalman filter) was presented for tracking a moving target by using multi-stations of IRST systems.
建立了目标的多站IRST(红外搜索与跟踪)系统的伪线性观测模型,基于该模型提出了匀速运动目标的伪线性卡尔曼滤波算法。
3.
A PLKF(pseudo-linear Kalman filter) is presented for tracking a moving target using two stations of IRST systems.
建立了目标的两站红外搜索与跟踪系统的伪线性观测模型,基于该模型提出了运动目标的伪线性卡尔曼滤波算法。
3) non-linear extended kalman filtering (EKF)
非线性推广卡尔曼滤波
4) non-linear Kalman filter
非线性卡尔曼滤波
1.
Output probability of speech/non-speech state is calculated sequentially using a Gaussian mixture model,backward estimation and parallel non-linear Kalman filter are used to estimate non-stationary noise.
利用高斯混合模型逐帧计算语音/非语音状态的输出概率,利用后向估计方法和平行非线性卡尔曼滤波器估计非平稳噪声帧。
5) Kalman Filtering
卡尔曼滤波
1.
Study on seam tracking technique based on the Kalman Filtering;
基于卡尔曼滤波的焊缝跟踪技术研究
2.
Simultaneous Determination of Mixed Amino Acids by Kalman Filtering Spectrophotometry;
卡尔曼滤波分光光度法同时测定混合氨基酸
3.
Kalman filtering based traffic information fusion method;
基于卡尔曼滤波的交通信息融合方法
6) Kalman filter
卡尔曼滤波
1.
Simultaneous Determination of Sorbic Acid and Benzoic Acid in Soy and Vinegar by Kalman Filtering UV Spectrophotometry;
卡尔曼滤波紫外光度法同时测定酱油、食醋中的山梨酸和苯甲酸
2.
Simultaneous Determination of Zinc Cadmium and Lead by Kalman Filter-Speetrophotometry;
卡尔曼滤波分光光度法同时测定锌、镉、铅
3.
Kalman Filter Determination of Rare Earth Elements by ICP-AES and Correction of Spectral interferences;
卡尔曼滤波ICP－AES法分析稀土元素及其对光谱干扰的校正
补充资料：卡尔曼滤波
见波形估计。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条