This report is continuation of the work of (Douglas et al., 1996) and (Douglas et al., 1997) which concerns vehicle fault detection and identification. A vehicle health monitoring approach based on analytical redundancy is described. Fault detection filters and parity equations use the control commands and sensor measurements to generate the residuals which have a unique static pattern in response to each fault. This allows the faults not only to be detected, but also identified. Sensor noise, process disturbances, system parameter variations, unmodeled dynamics and nonlinearities can...