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When searching for land mines using vehicular mounted sensors, it is important that the ground locations of the detected mines be accurately determined. This is useful for data association when one has multiple looks at a mine by a single sensor or if one uses multiple sensors. It is of ultimate importance for the primary mission, which is to neutralize the detected mines or at least to mark them for avoidance. Factors that contribute to errors in geo-location include inaccurate knowledge of the vehicle position and/or attitude, and also incomplete knowledge about the terrain being searched. This paper addresses the problem of incomplete terrain knowledge and presents relationships between terrain unevenness and the resulting geo-location errors. The results of this analysis indicate that there may be significant geo-location errors for situations where the terrain is not so smooth, e.g., off road searches. The problem can be alleviated via better knowledge of the terrain. Such knowledge could be acquired via scanning the field of view with a ranging device, recording range as a function of azimuth and elevation. A variety of uneven surfaces have been simulated. Two types of sensors are considered, Linear-Array Radar and Camera Type Sensors. Geo-location is then computed based on: a) no range measurements, b) four range measurements (to the four vertices of the sensor field of view), and c) nine range measurements (to the four vertices and intermediate points at the top and bottom row, as well as three measurements across the center row). The geo-location errors are much worse for the Camera Type Sensor, but they can be significant for the Linear-Array Radar also. If the field of view is planar or almost planar, even coarse range scanning can improve geo-location accuracy. For more complex surfaces fine scanning may be required. The computed geo-location errors, and the conclusions drawn as to the effectiveness of the different models are presented in the paper.
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