| Abstrakt: |
Tracking for multiple extended objects with a complex extension is a challenging radar technology; especially for small back-scattering objects such as extended stealth targets (ESTs). This work provides a new approach for ESTs tracking under the non-linear dynamic system based on track-before-detect (TBD) approach. The sequential Monte Carlo multi-Bernoulli (SMC-MB) filter provides a good framework to cope with TBD approach. Recently, the SMC-MB filter with a random matrix model (RMM) has been applied for tracking extended targets by additional state variables. However, SMC-MB-RMM filter is implemented with known detection probability, which is unsuitable for ESTs-TBD scenario. Therefore, we introduce a new SMC-MB-RMM filter hybrid with TBD algorithm, which is effective method to track ESTs. In ESTs-RMM-TBD scenarios, although the extension ellipsoid is effective, it may not be accurate enough due to lacking the useful parameters, such as shape, size and orientation. Therefore, we propose a ESTs-Sub-RMM-TBD composed of sub-ellipses; each one is applied by RMM. Based on such models, a SMC-Sub-RMM-MB-TBD algorithm is applied to estimate extensions and kinematic states for each sub-objects. The simulation results show that the presented filter has a small OSPA errors and more accurate cardinality calculation than the other algorithms. [ABSTRACT FROM AUTHOR] |
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