**1. Introduction**

Imaging approaches for diagnosis of concealed metallic objects [1], such as on body weapon detection [2, 3] and metallic foreign objects (MFOs) detection in children [4], have received many attentions worldwide in recent years. Concealed weapon detection underneath human subjects' clothing is an active research topic due to rapid screening of human subjects is urgent needed at some security sites, such as airports [1]. In 1995, the United States started the concealed weapon detection program [2] to detect concealed weapons from a standoff distance, especially when it is impossible to arrange the flow of people through a controlled procedure [3].

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Various imaging techniques include infrared imaging [5, 6], passive millimeter-wave (MMW) imaging [7–9], active MMW imaging [10, 11], X-ray imaging [12, 13] and holographic imaging [14–17] have been investigated for concealed metallic object detection. Recent studies have demonstrated that passive MMW imaging has the most potential to become a useful tool to identify concealed MFOs under clothing [18, 19], which has been investigated for various applications include security, military, surveillance and biomedical [20].

**2. Methodology**

image.

**2.1. Imaging measurement system**

recorded data using the HMMW algorithm.

**Figure 1.** Experimental procedure.

**Figure 1** shows the proposed HMMW system for concealed metallic object detection. The system contains a RF generator (vector network analyzer, VNA) to illuminate microwave signals, a data acquisition unit consists of a single transmitter to transmit microwave signals into a target object and an array of receivers to measure scattered electric fields from the target object, a signal and imaging processor to analyze the measured signals which contains phase and amplitude information as well as reconstruct image of the target object using an imaging algorithm, and an image display unit to display the reconstructed

3D Holographic Millimeter-Wave Imaging for Concealed Metallic Forging Objects Detection

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During data collection, port one of the VNA generates millimeter waves to the object of interest and the backscattered electromagnetic fields from the object are recorded at each receiver in the detector array plane that is connected to the second port of VNA. The distance between the target object and the data acquisition unit is in far-field region. The recorded signals include phase and amplitude information, which are used to compute the complex visibility data for each possible pair of receivers. An image of the object can be reconstructed from

Passive MMW imaging sensor techniques offer the best near-term potential for providing a non-invasive method of observing metallic and plastic objects concealed underneath common clothing. However, MMW cameras alone cannot provide useful information about the detail and location of the individual being monitored. The passive MMW system can produce indoor and outdoor images in bad weather, such as smoke and fog [21]. It has been applied to scan human subjects moving in an unconstrained flow, however, the MMW image has poor quality due to low-level signals and system noise [5]. In order to improve the accuracy and specificity of MMW for diagnosing concealed MFOs, many researchers aimed to develop a new MMW approach such as imaging algorithm and implement system.

Holographic technique was first applied in microwave imaging in 1948 [22]. An interference pattern between reference wave and diffracted wave (created by an object) is recorded to produce a hologram that can be digitally stored. The holograms are reconstructed by numerically synthesizing the reference wave, which is well-known wave front reconstruction processing. The target object can be reconstructed from the measured reflections and holograms. Holographic approaches are very different from the conventional synthetic aperture radar imaging method particularly in imaging geometry and no field approximations are required for holographic, which have recently been applied in MMW for MFOs detection [14, 15]. Farhat and Guard [14] applied the holographic approach for concealed weapon detection, and this technique was dramatically improved by Collins et al. [15]. The concealed MFOs detection system aims at extracting features of MFOs and reconstructing the MFOs using the measured data. The image quality is often limited by low signal-to-noise ratio and long scan time. Existing MMW methods are multi-frequency approach, which reconstruct a 3D image from a sequence of 2D images that obtained at different frequencies. However, the multifrequency MMW methods have difficulty in practical implementations and the broadband measurements also cause large noises.

This chapter demonstrates the feasibility of using a single frequency 3D holographic millimeter-wave (HMMW) imaging system and method to detect various small MFOs in inhomogeneous medium. A computer model is developed under MATLAB environment to validate the proposed theory and measurement system setups. The system contains a HMMW measurement model and various realistic models. Simulation and experimental validations are performed to evaluate the accuracy, effectiveness and performance of the proposed theory. The remainder of this chapter is organized as follows. Section 2 introduces the 3D HMMW measure system and imaging processing. Sections 3 and 4 present simulation and experimental performances. Section 5 gives discussion and conclusion of this study.
