The application of the UD implementation decoupled bias estimation to attitude determination is analyzed here. The advantage of decoupled bias estimation in general is the reduction in the dimensions of the filter and the subsequent reduction in the amount of processing. The purpose of the UD implementation is to mitigate the effects of round-off errors. A unique advantage of the application of decoupled bias estimation to attitude determination is that the bias processing can easily be turned off whenever a reconfiguration to a bias-free estimator mode is necessary. A comparison of the attitude error of the UD decoupled Kalman filter attitude uncertainty is given with respect to the coupled Kalman filter attitude uncertainty during the time periods when the bias processing is turned off. A detailed discussion of the UD implementation is given.

Problems associated with integrating, debugging and validating real time software systems are well known. Closed ioop tracking systems contain functional elements that illustrate the most difficult aspects of integrating, debugging, and ultimately validating the performance of real time software. Among these are severe real time constraints for line of sight control processing, image processing, inter-processor and peripheral communication. In addition, these highly complex algorithms are running on the target processors that are seldom tested end-to-end prior to system integration.The problem is exacerbated by unavailable or intermittently available hardware during the development and the integration phase of a typical program. Even with fully integrated hardware and software, performance validation is difficult because operational conditions of the platform and targets cannot be adequately represented in a laboratory setting without costly equipment to support hardware-inthe-loop simulation. The pressure to reduce cost and algorithm development to real-time software cycle time further aggravates the problem by limiting the time available for gaining confidence in the algorithms and software before they are committed to integration. This paper discusses a simulation approach that has streamlined the real-time software development process for a closed loop image-based tracking system. The MATLAB/SIMULINK simulation consists of elements constructed from common source modules shared with the deliverable system. The simulation has provided a tool to support algorithm development for the fundamental system components, including a system controller, a servo controller, and an image processor. In addition, the simulation has provided a testbed for verification of system performance. The context for this application is the low rate initial production phase of a tactical airborne avionics system that includes an image-based tracking system.

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