From: A general cardinalized probability hypothesis density filter
The general partitioning algorithm | |
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1. Identify the potential target measurements | |
2. Obtain the general original partition | |
(1) Calculate the multiple-detection distance \(d({{{\mathbf {z}}}_{i}},{{{\mathbf {z}}}_{j}})\) between any two measurements | |
(2) Obtain the original partition \({{\wp }_{o}}=\left\{ {{O}_{d}} \right\} _{d=1}^{D}\) of measurement set | |
(3) Reserve the target cells and merge the clutter measurements into the clutter cell | |
(4) Obtain the general original partition \({{\wp }_{c}}=\left( \bigcup \nolimits _{d=1:{\hat{D}}}{{{O}_{d}}} \right) \bigcup C\) | |
3. Obtain the general partitions | |
(1) Calculate all partitions of each target cell in the general original partition | |
(2) Obtain the 1st type of partition | |
(3) Obtain the 2nd type of partition | |
(4) Obtain the 3rd type of partition |