1D Kalman Predict

Problem

Perform the 1D predict step of a Kalman filter tracking position with constant velocity.

Given state x, velocity v, covariance p and process noise q, return [round(x + v, 4), round(p + q, 4)].

case 1

in: [0,1,1,0.1]

expected: [1,1.1]

case 2

in: [5,0,2,1]

expected: [5,3]

case 3

in: [-1,2,0,0]

expected: [1,0]

case 4

in: [1.5,0.5,2.5,0.5]

expected: [2,3]

Starter codePython

def kalman_predict(x, v, p, q):
    # Your code here
    pass

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