Concealed Object Detection and Recognition System Based on Millimeter Wave FMCW Radar

Abstract

At present, millimeter wave radar imaging technology has become a recognized human security solution in the field. The millimeter wave radar imaging system can be used to detect a concealed object; multiple-input multiple-output radar antennas and synthetic aperture radar techniques are used to obtain the raw data. The analytical Fourier transform algorithm is used for image reconstruction. When imaging a target at 90 mm from radar, which belongs to the near field imaging scene, the image resolution can reach 1.90 mm in X-direction and 1.73 mm in Y-direction. Since the error caused by the distance between radar and target will lead to noise, the original reconstruction image is processed by gamma transform, which eliminates image noise, then the image is enhanced by linearly stretched transform to improve visual recognition, which lays a good foundation for supervised learning. In order to flexibly deploy the machine learning algorithm in various application scenarios, ShuffleNetV2, MobileNetV3 and GhostNet representative of lightweight convolutional neural networks with redefined convolution, branch structure and optimized network layer structure are used to distinguish multi-category SAR images. Through the fusion of squeeze-and-excitation and the selective kernel attention mechanism, more precise features are extracted for classification, the proposed GhostNet_SEResNet56 can realize the best classification accuracy of SAR images within limited resources, which prediction accuracy is 98.18% and the number of parameters is 0.45 M.

Simulation and Implementation of Signal Processing for LFM Radar Using DSK 6713

“…Defense systems: LFMCW radar is used for target detection and tracking in military and defense applications, such as target identification, missile defense, and surveillance systems [16][17][18][19][20]; 4. Industrial applications: LFMCW radar can be used for distance measurement, displacement detection, object identification, and motion tracking in industrial settings for automation control and robotics applications [21][22][23][24].…”

High-gain UWB elliptical and circular slotted antipodal Vivaldi antenna for through wall detection

“…Using signal processing techniques, the reflected energy is analyzed to generate an image of the target behind the walls. These systems are particularly useful for detecting metal-based explosive substances in busy public spaces [10].…”

mmSight: A Robust Millimeter-Wave Near-Field SAR Imaging Algorithm

“…There have been many studies based on millimeter-wave SAR imaging technology. Various millimeter-wave SAR near-field imaging systems developed in the literature [5][6][7][8][9][10] were successfully used for security screening. The authors of [11] developed a simple 77 GHz millimeter wave SAR near-field imaging system using a commercial millimeter-wave radar and rails.…”