Extract a signal that is known to repeat every 4 samples at a known phase i.e. exactly 500 Hz signal in 2000 Hz data
To estimate the amplitude of the 500 Hz signal, a simple moving average filter will give you the best estimate in the presence of white Gaussian noise. This can be easily done by doing a moving average on the result of converting the 500 Hz signal to baseband as described below. This filter will have a Sinc response in frequency, so has high sidelobes which means it would be sensitive to the presence of other stronger signals if present. A very simple work-around is to just window the time domain signal first and then follow the same process (downcovert to baseband and sum  the result over N samples where N is the length of the moving average).   This is essentially a bandpass filter (using the windowing filter design approach) but in any filter used there will be a trade between frequency selectivity and time of convergence. 



A convenience of having a "digital IF" that is exactly $Fs/4$ is you can down-convert to baseband (create the equivalent baseband analytic signal) by just multiplying by +/-1 as follows:

To get I you multiply by

I = 1 0 -1 0 1 0 -1 0

To get Q you multiply by

Q = 0 -1 0 1 0 -1 0 1

As these would be the values for the Local Oscillator $e^{-j\omega t}$ for $\omega = \pi/2$ which is the normalized radian frequency at an LO of $f_s/4$. 

I detail this approach further at this post: 

DAC and ADC architecture in SDRs