Table 8 Critical evaluation of the Kalman, OFIR, and OUFIR filters
From: Iterative unbiased FIR state estimation: a review of algorithms
Kalman | Batch OFIR | Iterative OFIR | Batch OUFIR | Iterative OUFIR | |
|---|---|---|---|---|---|
[6] | |||||
Optimality: | Optimal | Optimal | Optimal | Unbiased | Unbiased |
Initial conditions: | A priori | A posteriori | A posteriori | Ignored | A posteriori |
Noise statistics: | Required | Required | Required | Ignored | Ignored |
Noise characteristics: | White | Arbitrary | White | Arbitrary | Arbitrary |
System model: | Stochastic | Arbitrary | Arbitrary | Arbitrary | Arbitrary |
Filter memory (points): | 2 | N opt | N opt | N op | N opt |
Stability: | May diverge | BIBO | BIBO | BIBO | BIBO |
Operation: | Fast | Slow | Medium | Medium | Approximately N opt times slower than |
Kalman; Fast with parallel computing | |||||
Memory consumption: | Small | Large | Medium | Large | Approximately N opt times more than |
Kalman | |||||
Computational complexity: | Low | High | Medium | Medium | Low |