We present a portable 3-D millimeter wave imaging system operating in the K-band (24 GHz). This imaging system consists of a multiple input, multiple output (MIMO) array of 32 transmit elements and 32 receive elements that illuminates a scene with millimeter wave energy and processes the reflected signals to reconstruct a 3-D image. To achieve an acceptable image resolution from this sparse array, the system combines multiple measurements while the sensor is moved relative to the scene being imaged. For ease of portability, the imaging system uses a single Ethernet cable to power the sensor and transfer the captured raw data to a laptop computer. A graphics processing unit (GPU)-optimized image reconstruction algorithm transforms the raw data to a 3-D image with approximately 1 cm voxel resolution, which is rendered in 3-D in a Web browser based user interface. We present measured test images and demonstrate an achieved dimensioning accuracy of ±1 − 3 mm when the system is used to detect and dimension objects hidden behind opaque building materials such as drywall, plywood, ceramic tile, vinyl flooring, and cement.
KEYWORDS: Millimeter wave imaging, 3D image processing, Imaging systems, Packaging, Nondestructive evaluation, Metals, K band, Extremely high frequency
Non-paper inclusions inside paper and plastic document mailing envelopes present both economic loss and security concerns for shipping carriers. Such contraband often goes unnoticed unless an envelope is physically opened by a human, which is infeasible given a global shipping volume in the tens of millions of envelopes per day. Millimeter waves (mmWaves) penetrate most non-metallic packaging materials, enabling the detection of anomalous nonpaper items within a stack of documents. At the same time, the non-ionizing nature of mmWave energy enables the safe use of mmWave imaging in close proximity to human workers without a requirement for shield barriers. We demonstrate a high-throughput K-Band (24 GHz) mmWave imaging system used to scan envelopes and thin packages transiting a conveyor belt. This imaging system is capable of supporting conveyor speeds of up to 3 m/s and enables non-destructive imaging inside sealed envelopes. We also present an automated screening algorithm that uses a logistic regression approach to detect anomalies among the expected paper documents. Automatic anomaly detection removes the human from the equation and allows for high-throughput diversion of suspect envelopes for secondary screening. In this work, we investigate mmWave detection of non-paper inclusions such as metalized plastic and metal items among paper documents in paper, cardboard, and Tyvek envelopes, as well as padded bubble packs. We achieve resolution better than 1 cm in the plane of the envelope, allowing for identification of sub-cm3 anomalies, and demonstrate automated first-pass flagging of suspect envelopes.
KEYWORDS: Video, Millimeter wave imaging, 3D image processing, Motion estimation, Imaging systems, Image quality, Video compression, Sensors, Prototyping, K band
Lens-less millimeter-wave (mmWave) imaging of moving objects using a sparse array relies on knowledge of the relative positions between the moving object and the imaging system to enable coherent image reconstruction. However, accurate object position information is rarely available in commercial applications where the moving object, e.g. a conveyor belt or a robot, is controlled independently of the imaging system, or where the imaged objects move autonomously. This poses a significant hurdle for many commercial mmWave imaging applications. We present a video-based motion extraction approach for active mmWave imaging. The object velocity is extracted in real time from motion vectors obtained from a compressed video. This information is combined with readouts from a distance sensor to infer the position of the object at each time instant. Leveraging video-derived motion vectors enables the offloading of computational complexity of 2-D spatial correlations to highly optimized algorithms operating on camera frames. We show experimentally that the image quality of a commercial high-throughput 3-D mmWave imaging system prototype is improved significantly by this approach when the velocity of the target is unknown and time-varying. We furthermore show that image quality is also improved compared to known average motion profiles of the imaged objects. Using a lab setup with known ground truth, we show that the RMS position error is 2.5 mm over a travel length of 0.52 m. This is better than 1/8 of the wavelength at K-band (24 GHz) along the trajectory and thus sufficient to achieve excellent image quality at K-band and longer wavelengths.
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