Kalman detection of landmines in metal detector array data

摘要

Tens of millions of mines are currently buried in a number of countries around the world. They cause injuries to civilians and economic damage to war-torn countries by restricting the civilian access to huge agricultural lands. Rapid Route and Area Mine Neutralisation System (RRAMNS) is a Capability Technology Demonstrator (CTD) conducted by Defence Science and Technology Organisation (DSTO) in Australia. The detection system consists of three sensors: a metal detector array, an array of ground penetrating radar (GPR), and forward looking infrared and visual imaging systems. The Kalman filter-based detection technique has previously been shown to be a powerful tool for detection of landmines from metal detector data. In this paper scalar Kalman filter-based detection algorithm has been extended to the multi-dimensional case. The new version of the detection technique has been successfully implemented in RRAMNS real-time mine detection system.