Skip to main content
. 2019 May 8;19(9):2134. doi: 10.3390/s19092134
Algorithm 1. DHIWCF implemented by node i at time instant k.
1. Obtain the local measurement zi, k with covariance matrix Ri,k.
2. Compute the measurement contribution vector and contribution matrix.
{ui=Hi,kTRi,k1zi,kUi=Hi,kTRi,k1Hi,k (35)
3. Broadcast state message {yi,k|k1,Yi,k|k1,ui,Ui} to its neighboring nodes jNi.
4. Receive state message {yj,k|k1,Yj,k|k1,uj,Uj} from its neighboring nodes jNi.
5. Compute the initial values.
{y^i,k|k0=11+dijJiy^j,k|k1+jJi(Hj, k)TRj,k1zj, kYi,k|k0=11+dijJiYj,k|k1+jJi(Hj, k)TRj,k1Hj, k (36)
6. Perform consensus.
  for l=1:L do
  • (1)

    Send y^i, k|k1l1 and Yi, k|k1l1 to its neighbors jNi;

  • (2)

    Receive y^j,k|k1l1 and Yj,k|k1l1 from its neighbors jNi;

  • (3)
    Update its consensus state.
    {y^i, k|kl=y^i, k|kl1+jNiπi,j(y^j, k|kl1y^i, k|kl1)Yi, k|kl=Yi, k|kl1+jNiπi,j(Yj, k|kl1Yi, k|kl1) (37)

  end for
7. Compute the posterior estimate.
x^i,k|k=(Yi, k|kL)1y^i, k|kL, Yi,k|k=Yi,k|kL, y^i, k|k=y^i, k|kL
8. Prediction at time instant k+1
x^i,k+1|k=Fkx^i,k|k, Yi,k+1|k=Ψk(Yi, k|k), y^i,k+1|k=Yi,k+1|kx^i,k+1|k