| This thesis considers the emitter location estimation problem in multiple platforms as well as single platform scenario. When multiple platforms are available, we design an algorithm finding the "optimal next states" for platforms such that platforms could keep optimal positioning towards the emitter in order to maximize the overall location estimation accuracy. While in the single platform case, we propose an entropy-based diversity measure to evaluate the ability of getting accurate location estimate of any given platform trajectory. Based on the proposed diversity measure, we show that a spiral shaped trajectory is optimal for achieving most accurate estimate regardless of where the emitter truly resides. In general, this thesis presents research efforts that attack the emitter location estimation problem from a different angle which it to seek the platform-emitter geometry optimality. |
