Advances on the detection of Landmines and IEDs in Colombia using UWB GPR and Machine Learning Techniques

Gutiérrez, Sergio Armando; Pantoja, John J.; Ruiz, Eder Fabian; Gonzalez, Nicolas; Vega, Félix; Baer, Christoph; Sachs, J.; Kasmi, Chaouki

doi:10.23919/eucap51087.2021.9411214

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, we assume that the SUT comprises two types of targets: targets with (observation) time-invariant scattering (e.g., scattering from IEDs buried in shallow depths [14]) as Λ α (τ), and targets with (observation) time-variant scattering as Λ β (τ, t ′ ), where •(t ′ ) is the time dimension along which the model H changes (typically referred to as slow time), and is under no circumstances to be confused with the •(t) time domain (also referred to as fast time) that is introduced earlier alongside signal discretizations. Examples of timevariant scenarios include living (i.e.…”

Section: System Modelmentioning

confidence: 99%

Configurable Pseudo Noise Radar Imaging System Enabling Synchronous MIMO Channel Extension

Bräunlich

Wagner

Sachs

et al. 2023

Sensors

View full text Add to dashboard Cite

In this article, we propose an evolved system design approach to ultra-wideband (UWB) radar based on pseudo-random noise (PRN) sequences, the key features of which are its user-adaptability to meet the demands provided by desired microwave imaging applications and its multichannel scalability. In light of providing a fully synchronized multichannel radar imaging system for short-range imaging as mine detection, non-destructive testing (NDT) or medical imaging, the advanced system architecture is presented with a special focus put on the implemented synchronization mechanism and clocking scheme. The core of the targeted adaptivity is provided by means of hardware, such as variable clock generators and dividers as well as programmable PRN generators. In addition to adaptive hardware, the customization of signal processing is feasible within an extensive open-source framework using the Red Pitaya® data acquisition platform. A system benchmark in terms of signal-to-noise ratio (SNR), jitter, and synchronization stability is conducted to determine the achievable performance of the prototype system put into practice. Furthermore, an outlook on the planned future development and performance improvement is provided.

show abstract

Section: System Modelmentioning

confidence: 99%

Configurable Pseudo Noise Radar Imaging System Enabling Synchronous MIMO Channel Extension

Bräunlich

Wagner

Sachs

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The switches are controlled by Raspberry Pi, which also reads the data from the Vector Network Analyzer. The data is sent over a wireless link to a computational platform where a Machine Learning algorithm processes the signal, discriminating the landmine and clutter [2]. The GPR is mounted on a DJI 600 UAV, with the capability of sweeping a 1x1 square meter area in 15 minutes, flying at an altitude of 6 cm above the ground.…”

mentioning

confidence: 99%