Fusion of acoustic LDV and GPR data

We investigate the potential for improving land mine detection by fusing data from ground penetrating radars (GPRs) and sensors of acoustically induced soil motion. We present a case study involving data from the SRI forward-looking radar and a laser Doppler vibrometer (LDV) system developed by the University of Mississippi. The LDV sensor detects acoustically induced soil vibrations, while the GPR detects scattering from dielectric discontinuities or metal objects in the soil. Since these sensors exploit different target physical properties, it is reasonable to expect a benefit in fusion. Although the sensors are relatively new, the LDV and GPR data exhibit evidence for complementarity, in that the GPR is significantly better at detecting metal mines, while the LDV is somewhat better at detecting plastic mines. Decision-level fusion is shown to improve performance. A simple OR fusion approach is found to perform similarly to an optimum hard decision fusion algorithm.