Kalman Gain with Observation Matrix

Problem

Compute the Kalman gain for a scalar state observed through z = h * x + v, with prior variance p_prior and observation noise variance r. The gain is K = p_prior * h / (h^2 * p_prior + r).

Return 0.0 when the denominator is zero.

Hint

The observation matrix scales both the prior variance and the numerator.

Test cases

case 1

in: [1,2,1]

expected: 0.4

case 2

in: [4,0.5,1]

expected: 1

case 3

in: [0,1,1]

expected: 0

case 4

in: [2,0,0.5]

expected: 0

Starter codePython

def kalman_gain_observation_matrix(p_prior, h, r):
    # Your code here
    pass

4 test cases · run your code against them in the editor