Range/Doppler tracking with the Kalman filter and its relatives — A comparative study

2017 ◽  
Author(s):  
Dietrich Franken ◽  
Sebastian Woischneck
Keyword(s):  
Kalman Filter ◽  
Comparative Study ◽  
Doppler Tracking

Comparative Study on Autonomous Robot Trajectory Determination in an Unknown Indoor Environment

2014 ◽  
Vol 555 ◽  
pp. 327-333
Author(s):  
Teodora Gîrbacia
Keyword(s):  
Kalman Filter ◽  
Comparative Study ◽  
Mobile Robot ◽  
Particle Filter ◽  
Measurement Errors ◽  
Indoor Environment ◽  
Autonomous Mobile Robot ◽  
Robot Trajectory ◽  
Slam Algorithm ◽  
Closed Environment

In this paper is presented a comparative study between using extended Kalman filter and particle filter applied on SLAM algorithm for an autonomous mobile robot. The robot navigates through an unknown indoor environment in which are placed 80 landmarks and it creates the map of the environment. Because the sensors placed on the robots produce measurement errors it is necessary to use Bayesian filters as the Kalman filter or the particle filter. An application was implemented that shows the estimated measurement errors produced while using both filters in order to create the estimated map of the closed environment in which the autonomous mobile robot is navigating.

scholarly journals Comparative Study between the Discrete-Frequency Kalman Filtering and the Discrete-Time Kalman Filtering with Application in Noise Reduction in Speech Signals

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Leandro Aureliano da Silva ◽  
Gilberto Arantes Carrijo ◽  
Eduardo Silva Vasconcelos ◽  
Roberto Duarte Campos ◽  
Cleiton Silvano Goulart ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Comparative Study ◽  
Noise Reduction ◽  
Discrete Time ◽  
Kalman Filtering ◽  
Signal To Noise Ratio ◽  
Spectral Distortion ◽  
Signal To Noise ◽  
Discrete Frequency ◽  
Speech Reconstruction

This article aims to carry out a comparative study between discrete-time and discrete-frequency Kalman filters. In order to assess the performance of both methods for speech reconstruction, we measured the output segmental signal-to-noise ratio and the Itakura-Saito distance provided by each algorithm over 25 different voice signals. The results show that although the two algorithms performed very similarly regarding noise reduction, the discrete-time Kalman filter produced smaller spectral distortion on the estimated signals when compared with the discrete-frequency Kalman filter.

Comparative Study of Kalman Filter and H infinity Filter for Current Sensorless Battery Health Analysis

2021 ◽  
Author(s):  
Wahyu Sukestyastama Putra ◽  
Jeki Kuswanto ◽  
Wahid Miftahul Ashari ◽  
Muhammad Koprawi
Keyword(s):  
Kalman Filter ◽  
Comparative Study ◽  
H Infinity ◽  
Current Sensorless
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