Error in EKF.py predict_update

[Paulkie99]

I believe the Jacobian should be computed after the predict step instead of before.

filterpy/filterpy/kalman/EKF.py

Lines 222 to 242 in 1d2834d

	H = HJacobian(x, *args)
	# predict step
	x = dot(F, x) + dot(B, u)
	P = dot(F, P).dot(F.T) + Q
	# save prior
	self.x_prior = np.copy(self.x)
	self.P_prior = np.copy(self.P)
	# update step
	PHT = dot(P, H.T)
	self.S = dot(H, PHT) + R
	self.SI = linalg.inv(self.S)
	self.K = dot(PHT, self.SI)
	self.y = z - Hx(x, *hx_args)
	self.x = x + dot(self.K, self.y)
	I_KH = self._I - dot(self.K, H)
	self.P = dot(I_KH, P).dot(I_KH.T) + dot(self.K, R).dot(self.K.T)

[jsvacha]

I agree. You want to linearize the system about the current estimate. Once you run the prediction, the estimate changes and so should the measurement Jacobian.