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Detection of mines is an important problem to the Army. A stand-off detection radar has been developed to detect mines in real time mode at stand-off distances ranging from 5 to 30 m. This active radar consists of three horn antennas, one transmitter and two receivers, carried by a moving vehicle. The transmit horn generates 36 sinusoidal carrier signals which have frequencies ranging from 0.5 to 4 GHz, in 100 MHz steps. At each frequency, the carrier signals are modulated by a train of 16 pulses having a 10 ns pulse width and a repetition rate of 3.9 MHz. These signals resonate targets including non-metallic and metallic mines and other objects. The mines and objects' return signals will be detected by the two receive antennas. The detection algorithm is used to identify an anomaly if it exists above background. Then, the discrimination algorithm is used to distinguish between mines and other objects. Finally, the location algorithm and the differential global positioning satellite system are used to mark the position of the detected mines. Test results from last year showed that some of the mines were not detected and the positions of some of the detected mines were not marked precisely enough. This resulted in missed detections and in increasing false alarm rate. Therefore, we propose to investigate Kalman filtering to improve the performance of the radar system. A preliminary study on the use of Kalman filtering algorithm for a single target tracking is provided in this paper. We believe that accurate tracking will result in accurate locating the detected target. Kalman filtering algorithm is selected for target tracking because we consider the fact that the source as well as the receivers are moving relative to the mine. This causes the delay to be also varying with time. Therefore, a dynamic algorithm such as Kalman filtering is a good technique to track the target by estimating the variable time delay.
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