Historically, unexploded ordnance (UXO) classification performance has been limited by both the information available from the electromagnetic induction (EMI) sensors and by signal-to-noise limitations. Three of the largest noise terms are inherent sensor noise, motion-induced noise, and sensor location uncertainty.

The most successful demonstrations to date of EMI-based discrimination involved cued detection with gridded collection of EMI data. The success of the gridded data collections was due to the combination of minimal location uncertainty, no motion-induced noise, and sufficient signal-to-noise ratio (SNR). The downside of the implementations previously demonstrated is that they were relatively slow and inefficient, especially on a large site.

The time-domain electromagnetic MTADS (TEMTADS) array was designed to combine the data quality advantages of a gridded survey with the coverage efficiencies of a vehicular system. The design goal of this system was to collect data equal, if not better, in quality to the best gridded surveys (the relative position and orientation of the sensors being known better for gridded data) while prosecuting more targets each field day.


The objective of this demonstration was to validate the performance of the TEMTADS platform through two blind tests that assessed classification performance (e.g., false alarm rejection) and appropriateness for fielding (i.e., production rate, usability, etc.).

Demonstration Results

The first demonstration was conducted at the Aberdeen Proving Ground (APG) Standardized UXO Technology Demonstration Site, Maryland. The second demonstration was conducted as part of the ESTCP Classification Pilot Program at the former Camp San Luis Obispo (SLO), California. At each demonstration, the site had been blind seeded with a significant number of intact, inert UXO types to challenge classification systems and methodologies.

The system was able to consistently interrogate 125 or more cued targets per day. The analysis, which required roughly 15 minutes per target, resulted in a false alarm reduction of more than 50% with 95% correct identification of munitions. The average error in predicted location was less than 10 cm in northing and easting, and the average error in depth estimation was less than 5 cm for non-overlapping targets with reasonable SNR. Qualitatively, the TEMTADS array was found to be easy to use and proved to be a robust and reliable sensor platform.

Implementation Issues

The Defense Science Board has calculated that if the false alarm rate can be reduced from 100:1 to 10:1, the economics of UXO remediation can be inverted from 75% of the cost devoted to digging false alarms to 75% devoted to digging UXO. Achieving this reduction with current analysis methodologies requires the collection of high SNR, precisely located, geophysical data. The TEMTADS array can generate such data with an acceptable productivity measured in targets per day. This approach to cued discrimination can be accomplished with no more visits to the site than currently required.

The TEMTADS is a large, vehicle-towed system that operates best in large, open areas. As seen at the former Camp SLO demonstration, it is possible to operate the system in rocky terrain with grades approaching 20% but at reduced operating capacity and increased system wear. Smaller versions of the system are currently under development as part of ESTCP projects MR-200807 and MR-200909.

For all sensors, there is a limiting anomaly density above which the response of individual targets cannot be separated. The researchers chose relatively small sensors for this array, which helps address this problem, but it cannot be eliminated. Anomaly densities of 300 anomalies/acre or higher would limit the applicability of this system as more than 20% of the anomalies would have another anomaly within a meter.