# Table 1 The soft information processing of each node in Fig. 3

SI(a,b) Inputs Outputs
SI(Pi,pi) ($$\widehat {p}_{i}$$, 0) $$\left ({m_{{P_{i}},{p_{i}}}},\sigma _{{P_{i}},{p_{i}}}^{2}\right)$$
SI(pi,Dt) $$\left ({m_{{P_{i}},{p_{i}}}},\sigma _{{P_{i}},{p_{i}}}^{2}\right)$$ $$\left ({m_{{p_{i}},{D_{t}}}},\sigma _{{p_{i}},{D_{t}}}^{2}\right)$$
SI(Dt,Rt) $$\left ({m_{{p_{i}},{D_{t}}}},\sigma _{{p_{i}},{D_{t}}}^{2}\right)$$, $$\left ({m_{{p_{j}},{D_{t}}}},\sigma _{{p_{j}},{D_{t}}}^{2}\right)$$ $${m_{{D_{t}},{R_{t}}}} = {m_{{p_{i}},{D_{t}}}} - {m_{{p_{j}},{D_{t}}}}$$, $$\sigma _{{D_{t}},{R_{t}}}^{2} = \sigma _{{p_{i}},{D_{t}}}^{2} + \sigma _{{p_{j}},{D_{t}}}^{2}$$
SI(Rt,At) $$\left ({m_{{D_{t}},{R_{t}}}}, \sigma _{{D_{t}},{R_{t}}}^{2}\right)$$ $${m_{{R_{t}},{A_{t}}}} = {m_{{D_{t}},{R_{t}}}}$$, $$\sigma _{{R_{t}},{A_{t}}}^{2} = \sigma _{{D_{t}},{R_{t}}}^{2}$$
SI(At,x) $$\left ({m_{{R_{t}},{A_{t}}}},\sigma _{{R_{t}},{A_{t}}}^{2}\right)$$, $$({m_{{y},{A_{t}}}},\sigma _{{y},{A_{t}}}^{2})\phantom {\dot {i}\!}$$ $${m_{{A_{t}},x}} = \left (1- k_{y,t}^{'}{m_{y,{A_{t}}}} - k_{z,t}^{'}{m_{z,{A_{t}}}}- k_{r,t}^{'}{m_{{R_{t}},{A_{t}}}}\right)/k_{x,t}^{'}$$,
$$\sigma _{_{{A_{t}},x}}^{2} = \left (k_{y,t}^{'2}\sigma _{y,{A_{t}}}^{2} + k_{z,t}^{'2}\sigma _{z,{A_{t}}}^{2} + k_{r,t}^{'2}\sigma _{{R_{t}},{A_{t}}}^{2}\right)/k_{x,t}^{'2}$$
SI(At,y) $$\left ({m_{{R_{t}},{A_{t}}}},\sigma _{{R_{t}},{A_{t}}}^{2}\right)$$, $$\left ({m_{{x},{A_{t}}}},\sigma _{{x},{A_{t}}}^{2}\right)\phantom {\dot {i}\!}$$ $${m_{{A_{t}},y}} = \left (1- k_{x,t}^{'}{m_{x,{A_{t}}}} - k_{z,t}^{'}{m_{z,{A_{t}}}} - k_{r,t}^{'}{m_{{R_{t}},{A_{t}}}}\right)/k_{y,t}^{'}$$,
$$\sigma _{_{{A_{t}},y}}^{2} = \left (k_{x,t}^{'2}\sigma _{x,{A_{t}}}^{2} + k_{z,t}^{'2}\sigma _{z,{A_{t}}}^{2} + k_{r,t}^{'2}\sigma _{{R_{t}},{A_{t}}}^{2}\right)/k_{y,t}^{'2}$$
SI(At,z) $$\left ({m_{{R_{t}},{A_{t}}}},\sigma _{{R_{t}},{A_{t}}}^{2}\right)$$, $$\left ({m_{{x_{t}},{A_{t}}}},\sigma _{{x_{t}},{A_{t}}}^{2}\right)$$ $${m_{{A_{t}},z}} = \left (1- k_{x,t}^{'}{m_{x,{A_{t}}}} - k_{y,t}^{'}{m_{y,{A_{t}}}}- k_{r,t}^{'}{m_{{R_{t}},{A_{t}}}}\right)/k_{z,t}^{'}$$,
$$\sigma _{_{{A_{t}},z}}^{2} = \left (k_{x,t}^{'2}\sigma _{x,{A_{t}}}^{2} + k_{y,t}^{'2}\sigma _{y,{A_{t}}}^{2} + k_{r,t}^{'2}\sigma _{{R_{t}},{A_{t}}}^{2}\right)/k_{z,t}^{'2}$$
SI(x,At) $$\left ({m_{{A_{l}},x}},\sigma _{{A_{l}},x}^{2}\right)$$ $${m_{x,{A_{t}}}} = \sigma _{_{x,{A_{t}}}}^{2}\left (\sum \limits _{l \ne t}^{n} {\frac {{{m_{{A_{l}},x}}}}{{\sigma _{{A_{l}},x}^{2}}}}\right)$$, $$\sigma _{x,{A_{t}}}^{2} = 1/\left (\sum \limits _{l \ne t}^{n} {\frac {1}{{\sigma _{{A_{l}},x}^{2}}}} \right)$$
SI(y,At) $$\left ({m_{{A_{l}},y}},\sigma _{{A_{l}},y}^{2}\right)$$ $${m_{y,{A_{t}}}} = \sigma _{_{y,{A_{t}}}}^{2}\left (\sum \limits _{l \ne t}^{n} {\frac {{{m_{{A_{l}},y}}}}{{\sigma _{{A_{l}},y}^{2}}}}\right)$$, $$\sigma _{y,{A_{t}}}^{2} = 1/\left (\sum \limits _{l \ne t}^{n} {\frac {1}{{\sigma _{{A_{l}},y}^{2}}}}\right)$$
SI(z,At) $$\left ({m_{{A_{l}},z}},\sigma _{{A_{l}},z}^{2}\right)$$ $${m_{z,{A_{t}}}} = \sigma _{_{z,{A_{t}}}}^{2}\left (\sum \limits _{l \ne t}^{n} {\frac {{{m_{{A_{l}},z}}}}{{\sigma _{{A_{l}},z}^{2}}}}\right)$$, $$\sigma _{z,{A_{t}}}^{2} = 1/\left (\sum \limits _{l \ne t}^{n} {\frac {1}{{\sigma _{{A_{l}},z}^{2}}}}\right)$$
SI(x) $$\left ({m_{{A_{t}},x}},\sigma _{{A_{t}},x}^{2}\right)$$ $${m_{x}} = \sigma _{x}^{2} \cdot \left (\sum \limits _{t = 1}^{n} {\frac {{{m_{{A_{t}},x}}}}{{\sigma _{{A_{t}},x}^{2}}}} \right)$$, $$\sigma _{x}^{2} = 1/\left (\sum \limits _{t = 1}^{n} {\frac {1}{{\sigma _{{A_{t}},x}^{2}}}} \right)$$
SI(y) $$\left ({m_{{A_{t}},y}},\sigma _{{A_{t}},y}^{2}\right)$$ $${m_{y}} = \sigma _{y}^{2} \cdot \left (\sum \limits _{t = 1}^{n} {\frac {{{m_{{A_{t}},y}}}}{{\sigma _{{A_{t}},y}^{2}}}} \right)$$, $$\sigma _{y}^{2} = 1/\left (\sum \limits _{t = 1}^{n} {\frac {1}{{\sigma _{{A_{t}},y}^{2}}}} \right)$$
SI(z) $$\left ({m_{{A_{t}},z}},\sigma _{{A_{t}},z}^{2}\right)$$ $${m_{z}} = \sigma _{z}^{2} \cdot \left (\sum \limits _{t = 1}^{n} {\frac {{{m_{{A_{t}},z}}}}{{\sigma _{{A_{t}},z}^{2}}}} \right)$$, $$\sigma _{z}^{2} = 1/\left (\sum \limits _{t = 1}^{n} {\frac {1}{{\sigma _{{A_{t}},z}^{2}}}} \right)$$