Egils Sviestins

Mixed Labelling in Multitarget Particle Filtering

The so-called mixed labelling problem inherent to a joint state multitarget particle filter implementation is treated. The mixed labelling problem would be prohibitive for track extraction from a joint state multitarget particle filter. It is shown, using the theory of Markov chains, that the mixed labelling problem in a particle filter is inherently self-resolving. It is also shown that the factors influencing this capability are the number of particles and the number of resampling steps. Extensive quantitative analyses of these influencing factors are provided.

Rule-based situation assessment for sea surveillance

In order to achieve greater situation awareness it is necessary to identify relations between individual entities and their immediate surroundings, neighboring entities and important landmarks. The idea is that long-term intentions and situations can be identified by patterns of more rudimentary behavior, in essence situations formed by combinations of different basic relationships. In this paper we present a rule based situation assessment system that utilizes both COTS and in-house software. It is built upon an agent framework that speeds up development times, since it takes care of many of the infrastructural issues of such a communication intense application as this is, and a rule based reasoner that can reason about situations that develop over time. The situation assessment system is developed to be simple, but structurally close to an operational system, with connections to outside data sources and graphical editors and data displays. It is developed with a specific simple Sea-surveillance scenario in mind, which we also present, but the ideas behind the system are general and are valid for other areas as well.

Particle filters for tracking closely spaced targets

In this paper we will consider several algorithms for tracking closely spaced objects. In particular we will concentrate on various particle filter implementations. One particular problem when using a joint multi target particle filter is the so-called mixed labelling problem. This problem amounts to the fact that different particles will have a different labelling w.r.t. target identity. The combination of the mixed labelling problem and naive or straightforward track extraction leads to performance degradation. This will be illustrated and alternative methods to alleviate this effect will be presented.