Novel model based EMI processing framework

Hayes, Charles Ethan; McClellan, J.H.; Scott, Waymond R.

doi:10.1117/12.2262884

Cited by 2 publications

(5 citation statements)

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“…As described by Hayes, application of these projections creates a data measurement matrix which can be defined in subsets demonstrating highly unique attributes. 10 This decomposition is shown in Figure 4.…”

Section: Soil Interference Removalmentioning

confidence: 98%

“…Following the notation outlined by Hayes, et al, the WEMI measurement data can be written as M (ω, p), where ω describes the operating frequency at which a measurement was taken, and p is the corresponding spatial location at the time of measurement. 10,11 A measurement matrix can be created by combining a series of frequency samples through position such that…”

Section: Measurement Matrixmentioning

confidence: 99%

“…12 In this work, however, the method described by Scott and Hayes is adopted which uses an orthonormal discrete cosine transform (DCT) basis matrix to remove both the DC and high-frequency spatial noise from the measurement matrix. 10,12 The DCT method operates on real cosines and extends the signal with mirroring before filtering. These qualities are desirable as sinusoidal shapes are ideal for downtrack filtering and mirroring the signal before filtering avoids generation of potentially harmful edge effects.…”

Section: Down-track Filteringmentioning

confidence: 99%

“…While it has been assumed that WEMI sensors should only be effective at discovering targets demonstrating highly-conductive attributes, a recent work by Hayes, et al showed that the empirical soil model may be further exploited for removing soil-response interference. 10,11 Given appropriate conditions, this method may even be able to detect targets supplying a small conductive response or even lacking metal completely. The method uses a projection matrix P G to transform the data into a space which is void of soil interference.…”

Section: Soil Interference Removalmentioning

confidence: 99%

“…and the left singular vectors U S (corresponding to frequency) were scaled by the square root of the ratio between the corresponding and first singular values. 10,11 The scaled representations were concatenated to create feature vectors.…”

Section: Soil Interference Removalmentioning

confidence: 99%

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Comparison of hand-held WEMI target detection algorithms

McCurley

Bocinsky

Zare

2019

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV

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Wide-band Electromagnetic Induction Sensors (WEMI) have been used for a number of years in subsurface detection of explosive hazards. While WEMI sensors have proven effective at localizing objects exhibiting large magnetic responses, detecting objects lacking or containing very low amounts of conductive materials can be challenging. In this paper, we compare a number of target detection algorithms in the literature in terms of detection performance. In the comparison, methods are tested on two real-world data sets: one containing relatively low amounts of ground noise pollution, and the other demonstrating highly-magnetic soil interference. Results are quantitatively evaluated through receiver-operator characteristic (ROC) curves and are used to highlight the strengths and weaknesses of the compared approaches in hand-held explosive hazard detection.rely on observing high-magnitude responses to flag potential threats, 6 Scott, et al. proposed that the relaxation energy emitted by conductive objects can be modeled as a function of operating frequency and used to created a dictionary of expected target responses. 7-9 Elaboration on the discrete spectrum of relaxation frequencies (DSRF) target dictionary and its exploitation for use in WEMI hazard detection is provided in Section 3.1.While there have been many successes in algorithm development for detection of high-metal targets, EHD is certainly not a solved problem. The first obstacle making EHD difficult is that there exists a wide assortment of targets to be detected, ranging from small anti-personal to large anti-tank. Additionally, metal content can range from high to low, or even even be absent in the case of plastic targets. While it has long been assumed that the inherent properties exhibited by metal detectors make discovery of lowly and non-conductive objects difficult to achieve, recent work has shown that the utilization of a novel WEMI processing procedure may provide discriminative information for unmasking difficult targets. Further description of this processing as well an initial investigation to the use of its generated features for hazard discovery is presented in Sections 3.6 and 4.4.3, respectively. In addition to the range of targets, non-target objects (clutter) and natural variations in the soil's electromagnetic properties can bring rise to false alarms (FA) where nontarget objects are labeled as potential threats. A principal challenge in EHD is mitigating false alarms while not masking true detections, or true positives (TP).In this paper, the authors compare an assortment of WEMI prescreeners which have shown considerable success as subsurface object detectors on alternative WEMI hazard discovery systems. Experiments were conducted to 1.) gauge the performance of target detectors across a variety of WEMI sensors, 2.) compare prescreeners utilizing pre-defined versus learned target concepts, and 3.) evaluate two pre-processing methods for interference removal. Quantitative evaluation of performance is given by receiver-operating characte...

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Section: Soil Interference Removalmentioning

confidence: 98%

Section: Measurement Matrixmentioning

confidence: 99%