Adaptive coherence estimator (ACE) for explosive hazard detection using wideband electromagnetic induction (WEMI)
This work addresses explosive hazard detection for military or security applications, but it is incremental as it applies an existing estimator to a specific sensor data type.
The paper tackled the problem of detecting buried explosive hazards using wideband electromagnetic induction data by applying the adaptive coherence estimator with target signatures from a DSRF model, resulting in performance summarized via receiver operating characteristic curves compared to other methods.
The adaptive coherence estimator (ACE) estimates the squared cosine of the angle between a known target vector and a sample vector in a whitened coordinate space. The space is whitened according to an estimation of the background statistics, which directly effects the performance of the statistic as a target detector. In this paper, the ACE detection statistic is used to detect buried explosive hazards with data from a Wideband Electromagnetic Induction (WEMI) sensor. Target signatures are based on a dictionary defined using a Discrete Spectrum of Relaxation Frequencies (DSRF) model. Results are summarized as a receiver operator curve (ROC) and compared to other leading methods.