A clutter independent novel method for target detection

This paper presents a novel, clutter-independent method for target detection, addressing the critical need for high probability of detection and low false alarm rates in challenging environments such as humanitarian demining. Data is acquired using a programmable microwave CW signal generator (Analog Devices “Adalm Pluto”) and a 3D-printed monostatic antenna, moved on a plane a few centimeters above the ground by a three axial scanning system (FESTO EXCM-30) mounted on a robotic platform. Traditional microwave imaging techniques, being reliant on strict Nyquist sampling and susceptible to distortions from clutter, uneven terrain, and imprecise data point positioning, often fall short in these scenarios. Instead, the presented method provides a positive number at each output location, effectively mapping the likelihood of a scatterer’s presence. Notably, the input and output data points are independent in both number and location. The output data is visualized as a color mapped image, enabling clear identification of potential targets. The method’s performance is shown through seven diverse use cases that showcase the algorithm’s robustness, demonstrating its ability to accurately pinpoint target locations with undersampled and positionally imprecise input data. The proposed method offers significant potential for various applications, including airborne, manual, and terrestrial linear scanning for target detection in cluttered environments.

Publication Details

Journal
Florence Research (University of Florence)
Published
2025-01-01
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

A clutter independent novel method for target detection

Florence Research (University of Florence)
Geochemistry and Geologic Mapping
article

A clutter independent novel method for target detection

article en

Abstract

This paper presents a novel, clutter-independent method for target detection, addressing the critical need for high probability of detection and low false alarm rates in challenging environments such as humanitarian demining. Data is acquired using a programmable microwave CW signal generator (Analog Devices “Adalm Pluto”) and a 3D-printed monostatic antenna, moved on a plane a few centimeters above the ground by a three axial scanning system (FESTO EXCM-30) mounted on a robotic platform. Traditional microwave imaging techniques, being reliant on strict Nyquist sampling and susceptible to distortions from clutter, uneven terrain, and imprecise data point positioning, often fall short in these scenarios. Instead, the presented method provides a positive number at each output location, effectively mapping the likelihood of a scatterer’s presence. Notably, the input and output data points are independent in both number and location. The output data is visualized as a color mapped image, enabling clear identification of potential targets. The method’s performance is shown through seven diverse use cases that showcase the algorithm’s robustness, demonstrating its ability to accurately pinpoint target locations with undersampled and positionally imprecise input data. The proposed method offers significant potential for various applications, including airborne, manual, and terrestrial linear scanning for target detection in cluttered environments.

Florence Research (University of Florence)
Openalex Percentile: Top 64%
Geochemistry and Geologic Mapping
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