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.
The paper presents a method for the estimation of the bias errors of active and passive sensors used in connection with multisensor multitarget tracking. It is based on comparing the measurements of targets of opportunity, and does not require reference targets or reference sensors. The method handles bias errors that vary with time, and is suitable for on-line processing. The most essential ingredients of the method are: Including of a priori values and uncertainties; minimization of the appropriate function; linearization around nominal points; introduction of process noise; and quasi-recursive processing. Bias estimation is often difficult because of the limited observability of sensor biases, in the sense that there amy not be a unique set of biases that explains the relative errors between measurements. This problem is discussed, and it is illustrated by simulations how the presented method avoids these problems.
A prototype system for tracking tactical ballistic missiles using multiple radars has been developed. The tracking is based on measurement level fusion (`true' multi-radar) tracking. Strobes from passive sensors can also be used. We describe various features of the system with some emphasis on the filtering technique. This is based on the Interacting Multiple Model framework where the states are Free Flight, Drag, Boost, and Auxiliary. Measurement error modeling includes the signal to noise ratio dependence; outliers and miscorrelations are handled in the same way. The launch point is calculated within one minute from the detection of the missile. The impact point, and its uncertainty region, is calculated continually by extrapolating the track state vector using the equations of planetary motion.