https://github.com/gitaditee/extended-kalman-filter-algorithms

Kalman filter is an algo for estimating the state of a system for position and the speed of a car using past observation and current un- noising measurement of the system.
https://github.com/gitaditee/extended-kalman-filter-algorithms

algorithms numpy python3

Last synced: about 2 months ago
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Kalman filter is an algo for estimating the state of a system for position and the speed of a car using past observation and current un- noising measurement of the system.

• Host: GitHub
• URL: https://github.com/gitaditee/extended-kalman-filter-algorithms
• Owner: gitaditee
• Created: 2023-10-11T17:21:26.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-10-11T17:29:33.000Z (over 1 year ago)
• Last Synced: 2024-01-28T17:42:02.257Z (12 months ago)
• Topics: algorithms, numpy, python3
• Language: Python
• Homepage:
• Size: 636 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# extended-kalman-filter-algorithms

Kalman filter is an algo for estimating the state of a system for position and the speed of a car using past observation and current un- noising  measurement of the system. 

•	Kalman filter is an algo which takes a series of measurement overtime and then make a prediction off the next measurement and this can be used on so many fields for example-

1.	Sensors 

2.	GPS 

•	For measuring speed of car after every interval you use instrument but it gives noisy measurement of speed noise can be handled by Gaussian variable.

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe.

#Uses/Applications-

The Kalman filter has several applications in technology. Some common applications are: Guidance and navigation of vehicles, particularly aircraft and spacecraft. Robotic motion planning and trajectory adjustment. Position awareness radar sensors for advanced driver assistance systems (ADAS) in autonomous vehicles.