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I meet a problem with designing a filter. I have two different instruments that could measure the same AC signal (usually ~200hz, always <1kHz), A and B. A can carry out signal measurement during the normal operation of the instrument. B can only be used during instrument calibration, and A can also be used at this time. B can accurately measure the signal. The measurement accuracy of A is lower than that of B.

I want to design a real-time filter for A to filter out the interference noise. The parameters of the filter are adjustable. When the instrument is calibrated, both A and B are used to measure the signal. The measurement result of B is taken as the standard result to calculate the parameters of the filter adaptively. After setting the parameters of the filter, A is used to measure the signal without B.

I have investigated a variety of filters and found that the adaptive filter is quite suitable for my needs. However, the adaptive filter needs to input two signals, while I can only provide the measurement result of A during the operation of the instrument. So the adaptive filter is not completely suitable for my needs.

I don't know how to solve this problem. Is there any method that suits my needs? Thank you very much!

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If you can use a higher precision instrument to measure the signal, then, if the signal maintains it's characteristics, you can build a system's model and use a Kalman filter for the "not so good" input channel.

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  • $\begingroup$ My signal to be tested is a pulse signal of 200Hz, with a duty cycle of 20%. It's like a square wave signal. I have learned the information on the Kalman filter. Is Kalman filter applicable to impulse signal? What I've found is a general use of Kalman filters for filtering continuous signals. $\endgroup$ – Marcus May 22 at 15:18
  • $\begingroup$ You can model square waves and PWM (variable duty cycle) syle behaviour by intercepting a horizontal line with a triangular wave. Moving the horizontal line up and down will change the square wave duty cycle. What are your error sources? Frequency? Duty cycle? What are you calibrating? $\endgroup$ – Filipe Pinto May 22 at 21:51

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