I want to implement a formula but I'm having issues understanding some of the components which make it up.
The premise of the equation is to use a modified version of the Kalman filter that estimates the speed of variation and to use it to predict the future possible values.
The formula is as follows. See equations (14) and (15) of the relevant paper:
$ \hat{R}_{est(i)} = \hat{R}_{pred(i)} + a(R_{prev(i)} - \hat{R}_{pred(i)})$
$ \tilde{V}_{est(i)} = \tilde{V}_{pred(i)} + \frac{b}{T_s}(R_{prev(i)} - \hat{R}_{pred(i)}) $
Each of the above parts are detailed as follows:
RSSI=received signal strength indicator
$\hat{R}_{est(i)}$ = estimated value of an RSSI value (which I have a calculation for)
$\hat{R}_{pred(i)}$ = the ith prediceted value of RSSI
$R_{prev(i)}$ = the ith previous value of RSSI
$\tilde{V}_{est(i)}$ & $\tilde{V}_{pred(i)}$ are the ith estimation speed and ith predicted speed
However, the two parts of the equation that I can't understand, or what out what to make them, are the letters $a$ and $b$.
In the paper where I got the above equation (located here) it is stated that they are somehow related to the gain constant.
How would I go about working that out?