Upon inspection of this model, we can see see a few more assumptions that we missed last time, namely
• The bias of the accelerometer is known
• The noise on the accelerometer output is known (View Highlight)
White light is composed of equal power in all frequencies in the visual portion of the electromagnetic spectrum and analogously white noise has equal power in all frequencies. (View Highlight)
Let’s start with the white noise term ηN(t). This term, when integrated, induces a random walk. (View Highlight)
Sometimes ARW and VRW are not given in datasheets and the datasheets instead give a value for noise density measured at a specific frequency. The noise density is typically measured at a frequency of around 50Hz in a bandlimited fashion.
(View Highlight)
However, we think the best way to intuitively reason about these units is to simply state that the noise density (the power spectral density) scales with the square root of time. (View Highlight)
Now, let’s look at the brown noise term ηK(t). This term, when integrated, induces a random walk on the biases of the angular velocity or specific force measurement. As such, this term is called the rate random walk (RRW) and the same terminology is used for both gyroscope and accelerometer. (View Highlight)
Lastly, let’s take a look at the pink noise term ηB(t). This term is called the bias instability or the in-run bias stability. This is the most important specification to review when selecting an IMU for your application. In the literature, it’s described as the drift of the bias at a constant temperature in ideal operating conditions and it represents the noise floor for an IMU. (View Highlight)
