Abstract
Out-of-sequence measurements (OOSMs) frequently arise in a multi-platform central tracking system due to delays in communication networks and varying pre-processing times at the sensor platforms. During the last few years, multiple-lag OOSM filtering algorithms have received a great deal of attention. However, a comparative analysis of these algorithms for multiple OOSMs is lacking. This paper analyzes a number of multiple-lag OOSM filtering algorithms in terms of optimality, accuracy, statistical consistency, and computational speed. These factors are important for realistic multi-target multi-sensor tracking systems. We examine the performance of these algorithms using a number of examples with Monte Carlo simulations. We present numerical results using simulated data, which includes two-dimensional position and velocity measurements.
| Original language | English |
|---|---|
| Pages (from-to) | 175-187 |
| Number of pages | 13 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 5204 |
| State | Published - 2004 |
| Externally published | Yes |
| Event | Signal and Data Processing of Small Targets 2003 - San Diego, CA, United States Duration: 5 Aug 2003 → 7 Aug 2003 |
Keywords
- Multi-sensor Centralized Tracking
- Multiple-lag OOSM
- OOSM Filtering Algorithms
- Out-of-sequence Measurement (OOSM)