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Table 2 Pseudo-codes for MD-JITS and MD-JIPDA

From: Joint integrated track splitting for multi-path multi-target tracking using OTHR detections

MD-JITS track update process

for each track

1. Probability of target existence prediction, \({P\left ({\chi _{k}^{t}|{Z^{k - 1}}} \right)}\), (17)

2. Track component state prediction, \(p\left ({{\textbf {x}^{t}}\left (k \right)|\chi _{k}^{t},{\kappa ^{t,k - 1}},{Z^{k - 1}}} \right)\), (8)

3. Measurement selection based on track components

4. Measurement cells generation using measurement partition method

5. Data association event probabilities,

\(\beta _{k}^{t}\left ({\left \langle {0|0} \right \rangle } \right)\) and \(\beta _{k}^{t}\left ({\left \langle {{z_{{\Phi _{t}},{n_{{\Phi _{t}}}}}}\left (k \right)|M_{{j_{k}}}^{t}\left ({{z_{{\Phi _{t}},{n_{{\Phi _{t}}}}}}\left (k \right)} \right)} \right \rangle } \right)\), (25) and (26)

6. Track component probability, P(κt,k|χk,Zk), (28) and (29)

7. Component state generation using nonlinear filter,

\(p\left ({{\textbf {x}^{t}}\left (k \right)|\chi _{k}^{t},{\kappa ^{t,k}},{Z^{k}}} \right)\)

8. Track state at scan k, \(p\left ({{\textbf {x}^{t}}\left (k \right)|\chi _{k}^{t},{Z^{k}}} \right)\), (30)

9. The probability of target existence at scan k, \(P\left ({\chi _{k}^{t}|{Z^{k}}} \right)\), (24)

end for

MD-JIPDA track update process

for each track

1. Probability of target existence prediction, \({P\left ({\chi _{k}^{t}|{Z^{k - 1}}} \right)}\), (17)

2. Track state prediction, \(p\left ({{\textbf {x}^{t}}\left (k \right)|\chi _{k}^{t},{Z^{k - 1}}} \right)\), (8)

3. Measurement selection based on track

4. Measurement cells generation using measurement partition method

5. Data association event probabilities,

\(\beta _{k}^{t}\left ({\left \langle {0|0} \right \rangle } \right)\) and \(\beta _{k}^{t}\left ({\left \langle {{z_{{\Phi _{t}},{n_{{\Phi _{t}}}}}}\left (k \right)|M_{{j_{k}}}^{t}\left ({{z_{{\Phi _{t}},{n_{{\Phi _{t}}}}}}\left (k \right)} \right)} \right \rangle } \right)\), (25) and (26)

6. Track state generated by each data association event using

existing nonlinear filter

7. Track state at scan k, \(p\left ({{\textbf {x}^{t}}\left (k \right)|\chi _{k}^{t},{Z^{k}}} \right)\), (27)

8. The probability of target existence at scan k, \(P\left ({\chi _{k}^{t}|{Z^{k}}} \right)\), (24)

end for