Acoustic Landmine Detector
Senior Design Project
Hisham Bedri - Tufts University (2011)
There are 110 million active landmines scattered across 70 countries worldwide. Many of these mines have plastic casings, making them very hard to detect using conventional metal-detectors. For my capstone project at Tufts University, I developed a low-cost prototype acoustic land-mine detector. Here is a summary music video. More project details are below:
Buried landmines can be hard to detect, especially if they have been buried for a long time. When vibrated. however, landmines interact dynamically with the soil around them. The detector works by transmitting two sound tones (two frequencies) and records the sound that bounces back. The detector analyzes the characteristic response of the landmine-dirt system and then determines whether a landmine is buried.
Two frequencies are transmitted into the ground. The detection algorithm detects the non-linear combination of these two frequencies. These non-linear (non-harmonic) peaks in the spectrum of the response is caused by the landmine bouncing against its environment.
On top you can see that when there is no landmine, only the two transmitted frequencies are received. Below you can see the ideal reaction when there is a landmine buried.
Initial setup using an old receiver amplifier, speaker, and microphone. Objects tested were plastic pvc-endcaps (2-4 inches in diameter).
Prototype and testing:
The portable prototype uses 2-9V batteries to run the amplifier and transducer and a laptop running matlab for signal processing. Testing was done at a nearby Airforce National Guard base using inert replica landmines.
The detector was able to discriminate areas with buried objects from those without buried objects with a probability of detection of 70%. The sample size used was too small to truly tell the functionality of the detector, however the initial results show a false alarm rate lower than most metal-based detectors and a probability of detection which is also comparable. Note that there is always a trade-off between probability of detection and false alarm rate.
This was a great project to learn about the concept of signal-detection. In the future I woudl like to validate the portable design by testing further, generating a full Receiver Operating Characterisc (ROC) curve, and implement an smart-phone app to perform the signal processing (so the whole rig will be more portable).