It's a one-pole lowpass IIR filter.

But I agree, if a one-pole filter will solve your problem. Kalman filter is an optimal state estimator, useful when you have:

  - multiple input and/or multiple output system
  - non-trivial dynamics (i.e. the system of interest is in motion and you have a state space description of the dynamics)
  - noisy measurements
  - statistical estimates of process and measurement noise are available
  - ideally, iid gaussian noises

Also good if you want to fuse data on different time scales or with different noise properties.

What have I missed?