04. EKF Tradeoffs 1 - State
Nd787 C4 L04 03 EKF Tradeoffs 1 - State V3
The "Full" State Vector
Often, the full state vector actually has more than 12 variables in it. That's because in addition to estimating the typical 12 variables, we often also want to keep track of the IMU biases. Remember from the lesson on sensors that bias is typically modeled as a random walk, that is:
b_t = b_{t-1} + \mathcal{N}({0, \sigma^2})
Estimating the bias in real-time like this is what's known as "online system identification".