Prototype system for multi-sensor tracking with sensor bias correction

Fusion tracking using data from multiple, distributed sensors will only be successful if the bias associated with each platform can be estimated and removed before data fusion is attempted. In many cases, the sensors cannot be reliably calibrated in advance and it is necessary to rely upon targets of opportunity. Bias estimation must then become part of an integrated data fusion system. This paper demonstrates the feasibility of such system, using TOTS to provide the multi-model, multi-sensor tracking capability, with additional functionality to support the bias estimation and correction based on whatever common targets are observed. Such a prototype system is shown to be effective, and is valuable in highlighing the main issues that must be addressed before a full system can be fielded.