Publication | Closed Access
Evaluation of landmine detection performance applying two different algorithms to GPR field data
11
Citations
4
References
2013
Year
Computational BurdenEnvironmental MonitoringEngineeringLand UseUnderground Target DetectionDetection TechniqueTerrestrial SensingDifferent AlgorithmsGpr Field DataEarth ScienceSocial SciencesImage AnalysisData SciencePattern RecognitionSignal DetectionSonar Signal ProcessingMachine VisionAutomatic Target RecognitionSynthetic Aperture RadarGeographyComputer EngineeringLandmine Detection PerformanceSignal ProcessingRadarMine-like ClutterRemote SensingGround-penetrating RadarRemote Sensing SensorAutomated Mining
This paper evaluates and compares the performance of two algorithms that have previously demonstrated their potential in underground target detection. Field data was obtained on specially prepared test fields, where various mine simulants, reference objects, and mine-like clutter where placed at precise locations in different soil types. The efficiency of both algorithms in terms of detection accuracies (ROC curves) and computational burden is compared, as well as the impact of preprocessing strategies. Based on the results, we discuss the convenience of both methods to be integrated in a real - time signal processing system considering their benefits and drawbacks.
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