This paper presents a design of a multi-sensor data fusion filter for a Flight Test System. The multi-sensor data consist of positional information of the target from radars and a telemetry system. The data fusion filter has a structure of a federated Kalman filter and is based on the Singer dynamic target model. It consists of dedicated local filter for each sensor, generally operating in parallel, plus a master fusion filter. A fault detection and correction algorithms are included in the local filter for treating bad measurements and sensor faults. The data fusion is carried out in the fusion filter by using maximum likelihood estimation algorithm. The performance of the designed fusion filter is verified by using both simulation data and real data.