Complementary Filter(CF) Often, there are cases where you have two different measurement sources for estimating one variable and the noise properties of the two measurements are such that one source gives good information only in low frequency region while the other is good only in high frequency region You can use a complementary filter Example: Tilt angle estimation using accelerometer and rate gyro accelerometer rate gyro High Pass Filter for example 0≈| (angular rate) dt not good in long term due to integration 0≈sn- accel. output g only good in long term Low Pass Filter not proper during fast motionComplementary Filter (CF) Often, there are cases where you have two different measurement sources for estimating one variable and the noise properties of the two measurements are such that one source gives good information only in low frequency region while the other is good only in high frequency region. Æ You can use a complementary filter ! Example : Tilt angle estimation using accelerometer and rate gyro ≈ ∫(angular rate) dt - not good in long term due to integration outputaccel. ⎞ ⎟ + ⎠ τ τ ⎛ ⎜ ⎝ s 1 examplefor, s = θ est accelerometer rate gyro High Pass Filter ⎛ ⎞ θ θ 1 g - not proper during fast motion ⎞ ⎟ τ ⎠ = ⎛ ⎜ ⎝ 1 s + − sin 1 - only good in long term Low Pass Filter ⎟ ⎟ ⎠ ⎜ ⎜ ⎝ θ ≈