Time series identification and Kalman filtering techniques for Doppler lidar velocity estimation

<p>Detailed observation of small scale perturbation in the atmospheric boundary layer during the first generated cumulus cloud are conducted. Our target is to study this small scale perturbation, especially related to the thermal activity at the first generated cumulus cloud. The observation is performed during the daytime on August 17, 2018, and September 03, 2018. Location is focused in the urban area of Kobe, Japan. High-resolution instruments such as Boundary Layer Radar, Doppler Lidar, and Time Lapse camera are used in this observation. Boundary Layer Radar, and Doppler Lidar are used for clear air observation. Meanwhile Time Lapse Camera are used for cloud existence observation. The atmospheric boundary layer structure is analyzed based on vertical velocity profile, variance, skewness, and estimated atmospheric boundary layer height. Wavelet are used to observe more of the period of the thermal activity. Furthermore, time correlation between vertical velocity time series from height 0.3 to 2 km and image pixel of generated cloud time series are also discussed in this study.</p>

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The Estimation of the Heath-Jarrow-Morton Model by Use of Kalman Filtering Techniques

SSRN Electronic Journal ◽

10.2139/ssrn.882664 ◽

1995 ◽

Cited By ~ 3

Author(s):

Ramaprasad Bhar ◽

Carl Chiarella

Keyword(s):

Kalman Filtering ◽

Filtering Techniques

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Dynamic force sensing for high-speed robot manipulation using Kalman filtering techniques

10.1109/cdc.1989.70547 ◽

2003 ◽

Cited By ~ 11

Author(s):

M. Uchiyama ◽

K. Kitagaki

Keyword(s):

Kalman Filtering ◽

High Speed ◽

Force Sensing ◽

Dynamic Force ◽

Robot Manipulation ◽

Filtering Techniques

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On the Ideality of Filtering Techniques in the Business Cycle Analysis Under Conditions of European Economy

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun201563030915 ◽

2015 ◽

Vol 63 (3) ◽

pp. 915-926 ◽

Cited By ~ 1

Author(s):

Ladislava Issever Grochová ◽

Petr Rozmahel

Keyword(s):

Time Series ◽

Business Cycles ◽

Gain Function ◽

Monthly Data ◽

Band Pass ◽

Ideal Filter ◽

Production Indices ◽

The Business Cycle ◽

High Pass ◽

Filtering Techniques

The paper deals with the applications and comparison of various filtering techniques, which is an integral part of the business cycles identification and their further analysis. In particular, the paper examines four high-pass and band-pass filters and compares them to an ideal filter. The gain function is estimated and shown by the periodogram to assess the filters’ efficiency in the extraction of undesired periods in the time series. The monthly data of industrial production indices of chosen EU countries are used to analyse the filtering techniques. The results show the Butterworth filter as a high pass and the Christiano-Fitzgerald filter as a band-pass to be closer to an ideal filter than the Hodrick-Prescott and Baxter-King filters.

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