# Kalman-Filter
I made tutorial for my studies regarding kalman filtering.
I attach good article related to kalman filtering algorithms.
I ommit that most of my codes are inspired by under atushi.
>https://gist.github.com/AtsushiSakai/5376850
# Algorithm summary
* First, try to understand what is measurement models and kalman filter euqations.
* I was inspired by Kalman filtering - Theory and practice using MATLAB

* We are using constant velocity model for predicting state matrix.

# Samples
* Here, we show you example of radar tracking scenario when human is intruding into sensing area.
* Ture values were compared with motion capture system wich has relatively small measurement error.
# Result of distance filtering

* You can see that data got more smoother than discrete one.
* You can find Q and R for specific numbers in code script data.
# Error of distance filtering

* Error was almost same as raw.
# result of velocity filtering

* The aim of this filter was to estimate velocity when obervation of distance is only avaliable.
* Therefore, we set observation matrix H as [1 0].
# Error of velocity filtering

* Compared to raw data, it can be seen that variance of error got decreased.
# Algorithm explained
1. State matrix model (SSM)
* Firstly, think about car moving and the location of the car can be detected by use of GPS.
* In this scenario, only the location of the car is known.
* Throughout this example, estimating velocity by using discrete kalman filter is shown.


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