Abstract
In this paper, an automatic sensor-fusion based detection algorithm of an anti-personnel land mine is presented. A "feature in-decision out" fuzzy sensor fusion algorithm for a ground penetrating radar (GPR), and a metal detector (MD), for anti-personnel land-mine detection is introduced. The inputs to the fuzzy fusion system are features extracted from both GPR and MD measurements. The output from the fuzzy fusion system is a decision if there is a land mine and at what depth it would be. Fuzzy fusion rules are extracted from training data through a fuzzy learning algorithm. Experimental test results are presented to demonstrate the validity of the proposed fuzzy fusion algorithm and hence its influence in minimizing the false alarm rate for humanitarian demining.